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The anaerobic acetogenic bacterium Acetobacterium woodii employs a novel type of Na+-motive anaerobic respiration, caffeate respiration. However, this respiration is at the thermodynamic limit of energy conservation, and even worse, in the first step, caffeate is activated by caffeyl-CoA synthetase, which hydrolyzes ATP to AMP and pyrophosphate. Here, we have addressed whether or not the energy stored in the anhydride bond of pyrophosphate is conserved by A. woodii. Inverted membrane vesicles of A. woodii have a membrane-bound pyrophosphatase that catalyzes pyrophosphate hydrolysis at a rate of 70–120 milliunits/mg of protein. Pyrophosphatase activity was dependent on the divalent cation Mg2+. In addition, activity was strictly dependent on Na+ with a Km of 1.1 mm. Hydrolysis of pyrophosphate was accompanied by 22Na+ transport into the lumen of the inverted membrane vesicles. Inhibitor studies revealed that 22Na+ transport was primary and electrogenic. Next to the Na+-motive ferredoxin:NAD+ oxidoreductase (Fno or Rnf), the Na+-pyrophosphatase is the second primary Na+-translocating enzyme in A. woodii.
A1AO ATP synthases with a V-type c subunit have only been found in hyperthermophilic archaea which makes bioenergetic analyses impossible due to the instability of liposomes at high temperatures. A search for a potential archaeal A1AO ATP synthase with a V-type c subunit in a mesophilic organism revealed an A1AO ATP synthase cluster in the anaerobic, acetogenic bacterium Eubacterium limosum KIST612. The enzyme was purified to apparent homogeneity from cells grown on methanol to a specific activity of 1.2 U·mg−1 with a yield of 12%. The enzyme contained subunits A, B, C, D, E, F, H, a, and c. Subunit c is predicted to be a typical V-type c subunit with only one ion (Na+)-binding site. Indeed, ATP hydrolysis was strictly Na+-dependent. N,N′-dicyclohexylcarbodiimide (DCCD) inhibited ATP hydrolysis, but inhibition was relieved by addition of Na+. Na+ was shown directly to abolish binding of the fluorescence DCCD derivative, NCD-4, to subunit c, demonstrating a competition of Na+ and DCCD/NCD-4 for a common binding site. After incorporation of the A1AO ATP synthase into liposomes, ATP-dependent primary transport of 22Na+ as well as ΔµNa+-driven ATP synthesis could be demonstrated. The Na+ A1AO ATP synthase from E. limosum is the first ATP synthase with a V-type c subunit from a mesophilic organism. This will enable future bioenergetic analysis of these unique ATP synthases.
Unresolved inflammation maintained by release of danger‐associated molecular patterns, particularly high‐mobility group box‐1 (HMGB1), is crucial for hepatocellular carcinoma (HCC) pathogenesis. To further characterize interactions between leucocytes and necrotic cancerous tissue, a cellular model of necroinflammation was studied in which murine Raw 264.7 macrophages or primary splenocytes were exposed to necrotic lysates (N‐lys) of murine hepatoma cells or primary hepatocytes. In comparison to those derived from primary hepatocytes, N‐lys from hepatoma cells were highly active—inducing in macrophages efficient expression of inflammatory cytokines like C‐X‐C motif ligand‐2 , tumor necrosis factor‐α, interleukin (IL)‐6 and IL‐23‐p19. This activity associated with higher levels of HMGB1 in hepatoma cells and was curbed by pharmacological blockage of the receptor for advanced glycation end product (RAGE)/HMGB1 axis or the mitogen‐activated protein kinases ERK1/2 pathway. Analysis of murine splenocytes furthermore demonstrated that N‐lys did not comprise of functionally relevant amounts of TLR4 agonists. Finally, N‐lys derived from hepatoma cells supported inflammatory splenic Th17 and Th1 polarization as detected by IL‐17, IL‐22 or interferon‐γ production. Altogether, a straightforward applicable model was established which allows for biochemical characterization of immunoregulation by HCC necrosis in cell culture. Data presented indicate a remarkably inflammatory capacity of necrotic hepatoma cells that, at least partly, depends on the RAGE/HMGB1 axis and may shape immunological properties of the HCC microenvironment.
The Earth’s surface condition we find today is a result of long exposure to metabolism of life forms. Particularly, molecular oxygen in the atmosphere is a feature which developed over time. The first substantial and lasting rise of atmospheric oxygen level happened ≈ 2.5 Ga ago, but localities are reported where transiently elevated oxygen levels appeared before this time-point. To trace the timing and circumstances of the earliest availability of free oxygen in the atmosphere is important to understand the habitats of early microbial life forms on Earth.
This thesis focuses to obtain information of oxygen levels and the related atmospheric cycling of metals in sediments of the 3.5 to 3.2 Ga Barberton Greenstone Belt. First, as iron was a ubiquitous constituent of Archean seawater, I investigated its isotopic composition in minerals of chemical sediments. Hereby, I tried to resolve the changes within the water basin on small scale sedimentary sequence cycles. Second, I focused on the minor constituents of Archean seawater. The Re-Os geochronologic system and the abundance patterns of the platinum-group elements were chosen to integrate information of oxygen promoted weathering of a large source area. To integrate information of a large time interval, the isotopes of uranium were investigated over a large stratigraphic section.
The two key findings of this thesis are:
• Quantitative oxidation of ferrous iron in surface layers of Paleoarchean seawater occurred during the onset and termination of hydrothermal FeIIaq delivery into shallow waters.
• Paleoarchean sedimentary successions of the Barberton Greenstone Belt lack any evidence of transient basin-scale oxygenation.
The Manzimnyama Iron Formation (IF, Fig Tree Group, Barberton Greenstone Belt, South Africa) has been deciphered to exist of cyclic stacks of lithostratigraphic units with varying amounts of iron oxide and carbonate minerals. In-situ femtosecond-Laser-Ablation ICP-MS iron isotope measurements showed that the majority of siderite (γ56Fe ≈ −0.5 ‰) precipitated directly from seawater of γ56Fe ≈ 0 ‰. Ferric iron from the surface layers is preserved in ≤ 1μ m hematite and in magnetite that has been grown within the consolidated sediment. During FeIIaq events, fine-grained hematite (γ56Fe ≈ 2.2 ‰) and magnetite (γ56Fe 0.5 to 0.8 ‰) indicate oxygen levels in surface waters of lower than 0.0002 μM. Upon onset and termination of iron oxide abundance, magnetite with γ56Fe ≈ 0 ‰ indicates that low concentrations of FeIIaq in surface waters were oxidized quantitatively. These observations demonstrate the existence of iron oxidation in Paleoarchean surface waters independent of FeIIaq concentration. This is the first investigation of Paleoarchean IF showing that lithostratigraphic cyclicity can be traced in iron isotopic composition of oxide minerals.
ID-ICP-MS measurement of Re, Ir, Ru, Pt and Pd, trace element (SF-ICP-MS) and ID-MCICP- MS uranium isotope determination have been applied to carbonaceous shale of the Mapepe Fm. (Fig Tree Group) after inverse Aqua Regia leaching and bulk digestion. The sediments reveal a silicified fraction which exhibits a seawater REE signature and a mixture of detrital and meteoritic PGE. Neither enrichment of the redox-sensitive elements Re or Mo nor fractionated uranium isotopes have been found on a stratigraphic interval of several hundred meters. The non-silica fraction shows no depletion of Re which indicates that the detrital material had no contact to oxidizing fluids. ID-TIMS measurements of Re and Os after the CrO3-SO4 Carius Tube method of two sample intervals showed that the Re-Os isotopic systems of the non-silica fractions are identical to two komatiite occurrences. Weltevreden Fm. and Komati Fm. rocks were uplifted, eroded and transported to the deep part of the sedimentary basin without any change to the Re-Os system. Negative fractionated uranium isotopes (γ238U = −0.41 ± 0.01 ‰) associated with detrital Ba-Cr-U occurrences suggest the existence of distal redox-processes that involve uranium species. This study demonstrates that over the time of exposure and deposition of the Mapepe Fm. sedimentation, free oxygen was not available for weathering in the catchment area.
A multiple filter test for the detection of rate changes in renewal processes with varying variance
(2014)
The thesis provides novel procedures in the statistical field of change point detection in time series.
Motivated by a variety of neuronal spike train patterns, a broad stochastic point process model is introduced. This model features points in time (change points), where the associated event rate changes. For purposes of change point detection, filtered derivative processes (MOSUM) are studied. Functional limit theorems for the filtered derivative processes are derived. These results are used to support novel procedures for change point detection; in particular, multiple filters (bandwidths) are applied simultaneously in oder to detect change points in different time scales.
Highlights
• BaP exposure increases the mutation rate of C. riparius.
• BaP exposure is detrimental for the fitness and the population dynamics of C. riparius.
• Multi-generational studies are essential to assess evolutionary implications of anthropogenic substances on biodiversity.
Abstract
The release of polycyclic aromatic hydrocarbons (PAHs) into the environment is posing a threat to ecosystems and human health. Benzo(a)pyrene (BaP) is considered a biomarker of PAH exposure and is classified as a Group 1 carcinogen. However, it was not known whether BaP is mutagenic, i.e. induces inherited germline mutations. In this study, we used a recently established method, which combines short-term mutation accumulation lines (MAL) with whole genome sequencing (WGS) to assess mutagenicity in the non-biting midge Chironomus riparius. The mutagenicity analysis was supplemented by an evaluation of the development of population fitness in three successive generations in the case of chronic exposure to BaP at a high concentration (100 μg/L). In addition, the level of ROS-induced oxidative stress was examined in vivo. Exposure to the higher BaP concentration led to an increase in germline mutations relative to the control, while the lower concentration showed no mentionable effect. Against expectations, BaP exposure decreased ROS-level compared to the control and is thus probably not responsible for the increased mutation rate. Likewise, the higher BaP concentration decreased fitness measured as population growth rate per day (PGR) significantly over all generations, without signs of rapid evolutionary adaptations. Our results thus highlighted that high BaP exposure may influence the evolutionary trajectory of organisms.
Aim: To evaluate preclinical education in Endodontology at Austrian, German and Swiss dental schools using an online survey. Methodology: An online survey divided into nine categories was sent using SurveyMonkey software to 37 dental schools, before the spread of the COVID-19 pandemic. The questionnaire included 50 questions to evaluate preclinical endodontic education, such as faculty-to-student ratios, topics taught and materials used, in preclinical phantom head courses. Seven and 14 days after the first e-mail contact, dental schools received a reminder e-mail. After four and six weeks, the dental schools were contacted by telephone and asked to participate in the online survey. The processing time was eight weeks in total. Results: The response rate was 89%. Preclinical endodontic education at the participating dental schools differs considerably. Theory classes ranged from 1 to 70 h (15 h mean), and practical classes ranged from 3 to 78 h (39 h mean). The faculty-to-student ratio varied between 1:4 and 1:38 (1:15 mean). Forty-five per cent of the dental schools had a specialist in endodontics teaching theory. Several dental microscopes were available for preclinical teaching purposes at 82% of the dental schools. The majority (82%) taught root canal preparation with rotary or reciprocating NiTi instruments. Overall, 85% of the dental schools taught lateral compaction, amongst other methods, for canal filling. Conclusion: A substantial divergence amongst the dental schools regarding the time dedicated to theory and practical instruction in Endodontology was reported. However, convergence in the use of root canal treatment techniques and materials was reported.
Variants resistant to compounds specifically targeting HCV are observed in clinical trials. A multi-variant viral dynamic model was developed to quantify the evolution and in vivo fitness of variants in subjects dosed with monotherapy of an HCV protease inhibitor, telaprevir. Variant fitness was estimated using a model in which variants were selected by competition for shared limited replication space. Fitness was represented in the absence of telaprevir by different variant production rate constants and in the presence of telaprevir by additional antiviral blockage by telaprevir. Model parameters, including rate constants for viral production, clearance, and effective telaprevir concentration, were estimated from 1) plasma HCV RNA levels of subjects before, during, and after dosing, 2) post-dosing prevalence of plasma variants from subjects, and 3) sensitivity of variants to telaprevir in the HCV replicon. The model provided a good fit to plasma HCV RNA levels observed both during and after telaprevir dosing, as well as to variant prevalence observed after telaprevir dosing. After an initial sharp decline in HCV RNA levels during dosing with telaprevir, HCV RNA levels increased in some subjects. The model predicted this increase to be caused by pre-existing variants with sufficient fitness to expand once available replication space increased due to rapid clearance of wild-type (WT) virus. The average replicative fitness estimates in the absence of telaprevir ranged from 1% to 68% of WT fitness. Compared to the relative fitness method, the in vivo estimates from the viral dynamic model corresponded more closely to in vitro replicon data, as well as to qualitative behaviors observed in both on-dosing and long-term post-dosing clinical data. The modeling fitness estimates were robust in sensitivity analyses in which the restoration dynamics of replication space and assumptions of HCV mutation rates were varied.
Highlights
• 153 chemicals of emerging concern detected in complex multi-component mixtures.
• 108 possible mixture risk assessment scenarios were investigated.
• Non-detects, QSARs, and experimental ecotoxicological data were integrated for risk assessment.
• 8 chemicals were the main risk drivers in at least one site across the River Aconcagua basin.
Abstract
Environmental risk assessments strategies that account for the complexity of exposures are needed in order to evaluate the toxic pressure of emerging chemicals, which also provide suggestions for risk mitigation and management, if necessary. Currently, most studies on the co-occurrence and environmental impacts of chemicals of emerging concern (CECs) are conducted in countries of the Global North, leaving massive knowledge gaps in countries of the Global South.
In this study, we implement a multi-scenario risk assessment strategy to improve the assessment of both the exposure and hazard components in the chemical risk assessment process. Our strategy incorporates a systematic consideration and weighting of CECs that were not detected, as well as an evaluation of the uncertainties associated with Quantitative Structure-Activity Relationships (QSARs) predictions for chronic ecotoxicity. Furthermore, we present a novel approach to identifying mixture risk drivers. To expand our knowledge beyond well-studied aquatic ecosystems, we applied this multi-scenario strategy to the River Aconcagua basin of Central Chile. The analysis revealed that the concentrations of CECs exceeded acceptable risk thresholds for selected organism groups and the most vulnerable taxonomic groups. Streams flowing through agricultural areas and sites near the river mouth exhibited the highest risks. Notably, the eight risk drivers among the 153 co-occurring chemicals accounted for 66–92 % of the observed risks in the river basin. Six of them are pesticides and pharmaceuticals, chemical classes known for their high biological activity in specific target organisms.
Streams and rivers are characterised by the presence of various chemicals of emerging concern (CECs), including pesticides, pharmaceuticals, personal care products, and industrial chemicals. While these chemicals are found usually only in low (ng/L) concentrations, they might still harm aquatic life and disrupt the ecological balance of aquatic ecosystems due to their high ecotoxicological potency. Environmental risk assessments that account for the complexity of exposures are needed in order to evaluate the toxic pressure of these chemicals, which also provide suggestions for risk mitigation and management, if necessary. Currently, most studies on the co-occurrence and environmental impacts of CECs are conducted in countries of the Global North, leaving massive knowledge gaps in countries of the Global South.
In this study, we implement a multi-scenario risk assessment strategy to improve the assessment of both the exposure and hazard components in the chemical risk assessment process. Our strategy incorporates a systematic consideration and weighting of CECs that were not detected, as well as an evaluation of the uncertainties associated with Quantitative Structure-Activity Relationships (QSARs) predictions for chronic ecotoxicity. Furthermore, we present a novel approach to identifying mixture risk drivers. To expand our knowledge beyond well-studied aquatic ecosystems, we applied this multi-scenario strategy to the River Aconcagua basin of Central Chile. The analysis revealed that the concentrations of CECs exceeded acceptable risk thresholds for selected organism groups and the most vulnerable taxonomic groups. Streams flowing through agricultural areas and sites near the river mouth exhibited the highest risks. Notably, the eight risk drivers among the 153 co-occurring chemicals accounted for 66-92% of the observed risks in the river basin. Six of them are pesticides and pharmaceuticals, chemical classes known for their high biological activity in specific target organisms.
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different cell types in motor cortex due to transcranial magnetic stimulation. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict detailed neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to predict activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also predicts differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of corctial pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.
Neurons of the mammalian neocortex are produced by proliferating cells located in the ventricular zone (VZ) lining the lateral ventricles. This is a complex and sequential process, requiring precise control of cell cycle progression, fate commitment and differentiation. We have analyzed publicly available databases from mouse and human to identify candidate genes that are potentially involved in regulating early neocortical development and neurogenesis. We used a mouse in situ hybridization dataset (The Allen Institute for Brain Science) to identify 13 genes (Cdon, Celsr1, Dbi, E2f5, Eomes, Hmgn2, Neurog2, Notch1, Pcnt, Sox3, Ssrp1, Tead2, Tgif2) with high correlation of expression in the proliferating cells of the VZ of the neocortex at early stages of development (E15.5). We generated a similar human brain network using microarray and RNA-seq data (BrainSpan Atlas) and identified 407 genes with high expression in the developing human VZ and subventricular zone (SVZ) at 8–9 post-conception weeks. Seven of the human genes were also present in the mouse VZ network. The human and mouse networks were extended using available genetic and proteomic datasets through GeneMANIA. A gene ontology search of the mouse and human networks indicated that many of the genes are involved in the cell cycle, DNA replication, mitosis and transcriptional regulation. The reported involvement of Cdon, Celsr1, Dbi, Eomes, Neurog2, Notch1, Pcnt, Sox3, Tead2, and Tgif2 in neural development or diseases resulting from the disruption of neurogenesis validates these candidate genes. Taken together, our knowledge-based discovery method has validated the involvement of many genes already known to be involved in neocortical development and extended the potential number of genes by 100's, many of which are involved in functions related to cell proliferation but others of which are potential candidates for involvement in the regulation of neocortical development.
The calcareous substrate of spring-fed fens makes them unique islands of biodiversity, hosting endangered, vulnerable, and protected vascular plants. Hence, spring-fed fens ecosystems require special conservation attention because many of them are destroyed (e.g. drained, forested) and it is extremely difficult or even impossible to restore the unique hydrogeological and geochemical conditions enabling their function. The long-term perspective of paleoecological studies allows indication of former wetland ecosystem states and provides understanding of their development over millennia. To examine the late Holocene dynamics of a calcareous spring-fed fen (Raganu Mire) ecosystem on the Baltic Sea coast (Latvia) in relation to environmental changes, substrate and human activity, we have undertaken high-resolution analyses of plant macrofossils, pollen, mollusc, stable carbon (δ13C) and oxygen (δ18O) isotopes combined with radiocarbon dating (AMS) in three coring locations. Our study revealed that peat deposits began accumulating ca. 7000 cal. yr BP and calcareous deposits (tufa) from 1450 cal. yr BP, coinciding with regional hydrological changes. Several fire events occurred between 4000 and 1600 cal. yr BP, which appeared to have had a limited effect on local vegetation. The most significant changes in the forest and peatland ecosystems were at 3200 cal. yr BP associated with a dry climate stage and high fire activity, and then between 1400 and 500 cal. yr BP potentially associated with temperature changes during the Medieval Climate Anomaly (MCA) and Little Ice Age. Hydrological disturbances in the peatland catchment from 1400 cal. yr BP were most likely strengthened by human activity (deforestation) in this region. The relationship between the development of this peatland and changes in its catchment area, such as land cover changes or fluctuations in groundwater levels, suggest that protection and restoration of spring-fed fen ecosystems should also include the surrounding catchment. The presence of calcareous sediments, as well as appropriate temperature and local hydrological conditions appear to be the most crucial factors controlling Cladium marisus populations in our site - currently at the eastern limit of its distribution in Europe.
In light of the global sea-level rise and climate change of the 21th century, it is important to look back into the recent past in order to understand what the future might hold. A multi-proxy data set was compiled to evaluate the influence of geomorphological and environmental factors, such as antecedent topography, subsidence, sea level and climate, on reef, sand apron and lagoon development in modern carbonate platforms through the Holocene. Therefore, a combination of remote sensing and morphological data from 122 modern carbonate platforms and atolls in the Atlantic, Indian and Pacific Oceans were conducted, along with a case study from the oceanic (Darwinian) barrier-reef system of Bora Bora, French Polynesia, South Pacific.
The influence of antecedent topography and platform size as factors controlling Holocene sand apron development and extension in modern atolls and carbonate platforms is hypothesized. Antecedent topography describes the elevation and relief of the underlying Pleistocene topography (karst) and determines the distance from the sea floor to the rising postglacial sea level. Maximum lagoon depth and marginal reef thickness, when available in literature, were used as proxies for antecedent topography. Sand apron proportions of 122 atolls and carbonate platforms from the Atlantic, Indian and Pacific Oceans were quantified and correlated to maximum lagoon depth, total platform area and marginal reef thickness. This study shows that sand apron proportions increase with decreasing lagoon depths. Sand apron proportions also increase with decreasing platform area. The interaction of antecedent topography and Holocene sea-level rise is responsible for variations in accommodation space and at least determines the extension of the lateral expansion of sand aprons. In general, sand apron formation started when marginal reefs approached relative sea level. Spatial and regional variations in sea-level history let sand apron formation start earlier in the Indo-Pacific region (transgressive-regressive) than in the Western Atlantic Ocean (transgressive).
The influence of sea level, antecedent topography and subsidence of a volcanic island on late Quaternary reef development was evaluated based on six rotary core transects on the barrier and fringing reefs of Bora Bora. This study was designed to revalue the Darwinian model, the subsidence theory of reef development, which genetically connects fringing reef, barrier reef and atoll development by continuous subsidence of the volcanic basement. Postglacial sea-level rise, and to a minor degree subsidence, were identified as major factors controlling Holocene reef development in that they have created accommodation space and controlled reef architecture. Antecedent topography was also an important factor because the Holocene barrier reef is located on a Pleistocene barrier reef forming a topographic high. Pleistocene soil and basalt formed the pedestal of the fringing reef. Uranium-Thorium dating shows that barrier and fringing reefs developed contemporaneously during the Holocene.
In the barrier–reef lagoon of Bora Bora, the influence of environmental factors, such as sea level and climate, tsunamis and tropical cyclones controlling Holocene sediment dynamics was evaluated based on sedimentological, paleontological, geochronological and geochemical data. The lagoonal succession comprises mixed carbonate-siliciclastic sediments overlying peat and Pleistocene soil. The multi-proxy data set shows variations in grain-size, total organic carbon (proxy for primary productivity), Ca and Cl element intensities (proxies for carbonate availability and lagoonal salinity) during the mid-late Holocene. These patterns could result from event sedimentation during storms and correlate to event deposits found in nearby Tahaa, probably induced by elevated cyclone activity. Accordingly, elevated erosion and runoff from the volcanic island and lower lagoonal salinity would be a result of rainfall during repeated cyclone landfall. However, Ti/Ca and Fe/Ca ratios as proxies for terrigenous sediment delivery peaked out in the early Holocene and declined since the mid-Holocene. Benthic foraminifera assemblages do not indicate reef-to-lagoon transport. Alternatively, higher and sustained hydrodynamic energy is probably induced by stronger trade winds and a higher-than-present sea level during the mid-late Holocene. The increase in mid-late Holocene sediment dynamics within the back-reef lagoon is supposed to display sediment-load shedding of sand aprons due to the oversteepening of slopes at sand apron/lagoon edges during their progradation rather than an increase in tropical storm activity during that time.
The influence of sea-level and climate changes on sediment import, composition and distribution in the Bora Bora lagoon during the Holocene is validated. Lagoonal facies succession comprises siderite-rich marly wackestones, foraminifera-siderite wackestones, mollusk-foraminifera marly packstones and mollusk-rich wackestones during the early-mid Holocene, and mudstones since the mid-late Holocene. During the early Holocene, enhanced weathering and iron input from the volcanic island due to wetter climate conditions led to the formation of siderite within the lagoonal sediments. The geochemical composition of these siderites shows that precipitation was driven by microbial activity and iron reduction in the presence of dissolved bicarbonate. Chemical substitutions at grain margins illustrate changes in the oxidation state and probably reflect changes in pore water chemistry due to sea-level rise and climate change (rainfall). In the late Holocene, sediment transport into the lagoon is hampered by motus on the windward side of the lagoon, which led to early submarine lithification within the lagoon.
The first concerted multi-model intercomparison of halogenated very short-lived substances (VSLS) has been performed, within the framework of the ongoing Atmospheric Tracer Transport Model Intercomparison Project (TransCom). Eleven global models or model variants participated (nine chemical transport models and two chemistry–climate models) by simulating the major natural bromine VSLS, bromoform (CHBr3) and dibromomethane (CH2Br2), over a 20-year period (1993–2012). Except for three model simulations, all others were driven offline by (or nudged to) reanalysed meteorology. The overarching goal of TransCom-VSLS was to provide a reconciled model estimate of the stratospheric source gas injection (SGI) of bromine from these gases, to constrain the current measurement-derived range, and to investigate inter-model differences due to emissions and transport processes. Models ran with standardised idealised chemistry, to isolate differences due to transport, and we investigated the sensitivity of results to a range of VSLS emission inventories. Models were tested in their ability to reproduce the observed seasonal and spatial distribution of VSLS at the surface, using measurements from NOAA's long-term global monitoring network, and in the tropical troposphere, using recent aircraft measurements – including high-altitude observations from the NASA Global Hawk platform.
The models generally capture the observed seasonal cycle of surface CHBr3 and CH2Br2 well, with a strong model–measurement correlation (r ≥ 0.7) at most sites. In a given model, the absolute model–measurement agreement at the surface is highly sensitive to the choice of emissions. Large inter-model differences are apparent when using the same emission inventory, highlighting the challenges faced in evaluating such inventories at the global scale. Across the ensemble, most consistency is found within the tropics where most of the models (8 out of 11) achieve best agreement to surface CHBr3 observations using the lowest of the three CHBr3 emission inventories tested (similarly, 8 out of 11 models for CH2Br2). In general, the models reproduce observations of CHBr3 and CH2Br2 obtained in the tropical tropopause layer (TTL) at various locations throughout the Pacific well. Zonal variability in VSLS loading in the TTL is generally consistent among models, with CHBr3 (and to a lesser extent CH2Br2) most elevated over the tropical western Pacific during boreal winter. The models also indicate the Asian monsoon during boreal summer to be an important pathway for VSLS reaching the stratosphere, though the strength of this signal varies considerably among models.
We derive an ensemble climatological mean estimate of the stratospheric bromine SGI from CHBr3 and CH2Br2 of 2.0 (1.2–2.5) ppt, ∼ 57 % larger than the best estimate from the most recent World Meteorological Organization (WMO) Ozone Assessment Report. We find no evidence for a long-term, transport-driven trend in the stratospheric SGI of bromine over the simulation period. The transport-driven interannual variability in the annual mean bromine SGI is of the order of ±5 %, with SGI exhibiting a strong positive correlation with the El Niño–Southern Oscillation (ENSO) in the eastern Pacific. Overall, our results do not show systematic differences between models specific to the choice of reanalysis meteorology, rather clear differences are seen related to differences in the implementation of transport processes in the models.
The first concerted multi-model intercomparison of halogenated very short-lived substances (VSLS) has been performed, within the framework of the ongoing Atmospheric Tracer Transport Model Intercomparison Project (TransCom). Eleven global models or model variants participated, simulating the major natural bromine VSLS, bromoform (CHBr3) and dibromomethane (CH2Br2), over a 20-year period (1993-2012). The overarching goal of TransCom-VSLS was to provide a reconciled model estimate of the stratospheric source gas injection (SGI) of bromine from these gases, to constrain the current measurement-derived range, and to investigate inter-model differences
due to emissions and transport processes. Models ran with standardised idealised chemistry, to isolate differences due to transport, and we investigated the sensitivity of results to a range of VSLS emission inventories. Models were tested in their ability to reproduce the observed seasonal and spatial distribution of VSLS at the surface, using measurements from NOAA’s long-term global monitoring network, and in the tropical troposphere, using recent aircraft measurements - including high altitude observations from the NASA Global Hawk platform.
The models generally capture the seasonal cycle of surface CHBr3 and CH2Br2 well, with a strong model measurement correlation (r ≥0.7) and a low sensitivity to the choice of emission inventory, at most sites. In a given model, the absolute model-measurement agreement is highly sensitive to the choice of emissions and inter-model differences are also apparent, even when using the same inventory, highlighting the challenges faced in evaluating such inventories at the global scale. Across the ensemble, most consistency is found within the tropics where most of the models (8 out of 11) achieve optimal agreement to surface CHBr3 observations using the lowest of the three CHBr3 emission inventories tested (similarly, 8 out of 11 models for CH2Br2). In general, the models are able to reproduce well observations of CHBr3 and CH2Br2 obtained in the tropical tropopause layer (TTL) at various locations throughout the Pacific. Zonal variability in VSLS loading in the TTL is generally consistent among models, with CHBr3 (and to a lesser extent CH2Br2) most elevated over the tropical West Pacific during boreal winter. The models also indicate the Asian Monsoon during boreal summer to be an important pathway for VSLS reaching the stratosphere, though the strength of this signal varies considerably among models.
We derive an ensemble climatological mean estimate of the stratospheric bromine SGI from CHBr3 and CH2Br2 of 2.0 (1.2-2.5) ppt, ∼57% larger than the best estimate from the most re- cent World Meteorological Organization (WMO) Ozone Assessment Report. We find no evidence for a long-term, transport-driven trend in the stratospheric SGI of bromine over the simulation period. However, transport-driven inter-annual variability in the annual mean bromine SGI is of the order of a ±5%, with SGI exhibiting a strong positive correlation with ENSO in the East Pacific
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
DEAD-box proteins are enzymes endowed with nucleic acid-dependent ATPase, RNA translocase and unwinding activities. The human DEAD-box protein DDX3 has been shown to play important roles in tumor proliferation and viral infections. In particular, DDX3 has been identified as an essential cofactor for HIV-1 replication. Here we characterized a set of DDX3 mutants biochemically with respect to nucleic acid binding, ATPase and helicase activity. In particular, we addressed the functional role of a unique insertion between motifs I and Ia of DDX3 and provide evidence for its implication in nucleic acid binding and HIV-1 replication. We show that human DDX3 lacking this domain binds HIV-1 RNA with lower affinity. Furthermore, a specific peptide ligand for this insertion selected by phage display interferes with HIV-1 replication after transduction into HelaP4 cells. Besides broadening our understanding of the structure-function relationships of this important protein, our results identify a specific domain of DDX3 which may be suited as target for antiviral drugs designed to inhibit cellular cofactors for HIV-1 replication.
We developed a Monte Carlo event generator for production of nucleon configurations in complex nuclei consistently including effects of nucleon–nucleon (NN) correlations. Our approach is based on the Metropolis search for configurations satisfying essential constraints imposed by short- and long-range NN correlations, guided by the findings of realistic calculations of one- and two-body densities for medium-heavy nuclei. The produced event generator can be used for Monte Carlo (MC) studies of pA and AA collisions. We perform several tests of consistency of the code and comparison with previous models, in the case of high energy proton–nucleus scattering on an event-by-event basis, using nucleus configurations produced by our code and Glauber multiple scattering theory both for the uncorrelated and the correlated configurations; fluctuations of the average number of collisions are shown to be affected considerably by the introduction of NN correlations in the target nucleus. We also use the generator to estimate maximal possible gluon nuclear shadowing in a simple geometric model.
In the title compound, C15H14N2O4, (I), the molecule lies on a twofold rotation axis which passes through the central C atom of the aliphatic chain, giving one half-molecule per asymmetric unit. The structure is a monoclinic polymorph of the triclinic structure previously reported [Brito, Vallejos, Bolte & López-Rodríguez (2010). Acta Cryst. E66, o792], (II). The most obvious difference between them is the O/C/C/C—O/C/C/C torsion angle [58.2 (7)° in (I) and 173.4 (3)/70.2 (3)° in (II) for GG and TG conformations, respectively]. Another important difference is observed in the dihedral angle between the planes of the aromatic rings [86.49 (7)° for (I) and 76.4 (3)° for (II)]. The crystal structure features a weak pi–pi interaction [centroid–centroid distance = 4.1397 (10)Å]; this latter kind of interaction is not evident in the triclinic polymorph.
The bluebottle blow fly Calliphora vicina is a common species distributed throughout Europe that can play an important role as forensic evidence in crime investigations. Developmental rates of C. vicina from distinct populations from Germany and England were compared under different temperature regimes to explore the use of growth data from different geographical regions for local case work. Wing morphometrics and molecular analysis between these populations were also studied as indicators for biological differences. One colony each of German and English C. vicina were cultured at the Institute of Legal Medicine in Frankfurt, Germany. Three different temperature regimes were applied, two constant (16°C & 25°C) and one variable (17–26°C, room temperature = RT). At seven time points (600, 850, 1200, 1450, 1800, 2050, and 2400 accumulated degree hours), larval lengths were measured; additionally, the durations of the post feeding stage and intrapuparial metamorphosis were recorded. For the morphometric and molecular study, 184 females and 133 males from each C. vicina population (Germany n = 3, England n = 4) were sampled. Right wings were measured based on 19 landmarks and analyzed using canonical variates analysis and discriminant function analysis. DNA was isolated from three legs per specimen (n = 61) using 5% chelex. A 784 bp long fragment of the mitochondrial cytochrome b gene was sequenced; sequences were aligned and phylogenetically analyzed. Similar larval growth rates of C. vicina were found from different geographic populations at different temperatures during the major part of development. Nevertheless, because minor differences were found a wider range of temperatures and sampling more time points should be analyzed to obtain more information relevant for forensic case work. Wing shape variation showed a difference between the German and English populations (P<0.0001). However, separation between the seven German and English populations at the smaller geographic scale remained ambiguous. Molecular phylogenetic analysis by maximum likelihood method could not unambiguously separate the different geographic populations at a national (Germany vs England) or local level.
How the brain evolved remains a mystery. The goal of this thesis is to understand the fundamental processes that are behind the evolutionary history of the brain. Amniotes appeared 320 million years ago with the transition from water to land. This early group bifurcated into sauropsids (reptiles and birds) and synapsids (mammals). Amniote brains evolved separately and display obvious structural and functional differences. Although those differences reflect brain diversification, all amniote brains share a common ancestor and their brains show multiple derived similarities: equivalent structures, networks, circuits and cell types have been preserved during millions of years. Finding these differences and similarities will help us understand brain historical evolution and function. Studying brain evolution can be approached from various levels, including brain structure, circuits, cell types, and genes. We propose a focus on cell types for a more comprehensive understanding of brain evolution. Neurons are the basic building blocks and the most diverse cell types in the brain. Their evolution reflects changes in the developmental processes that produce them, which in turn may shape the neural circuits they belong to. However, there is currently a lack of a unified criteria for studying the homology of connectivity and development between neurons. A neuron’s transcriptome is a molecular representation of its identity, connectivity, and developmental/evolutionary history. Hence the comparison of neuronal transcriptomes within and across species is a new and transformative development in the study of brain evolution. As an alternative, comparing neuronal transcriptomes across different species can provide insights into the evolution of the brain. We propose that comparing transcriptomes can be a way to fill this gap and unify these criteria. In previous studies, published in Science (Tosches et al., 2018) and Nature (Norimoto et al., 2020), we leveraged scRNAseq in reptiles to re-evaluate the origins and evolution of the mammalian cerebral cortex and claustrum. Motivated by the success of this approach, in this thesis we have now expanded single-cell profiling to the entire brain of a lizard species, the Australian dragon Pogona vitticeps, with a special focus in thalamus and prethalamus of. This approach allowed us to study the evolution of neuron types in amniotes. Therefore, we aimed to build a multilevel atlas of the lizard brain based on histology and transcriptomic and compare it to an equal mouse dataset (Zeisel et al., 2018).
Our atlas reveals a general structure that is consistent with that for other amniote brains, allowing us to make a direct comparison between lizard and mouse, despite their evolutionary divergence 320 million years ago. Through our analysis of the transcriptomes present in various neuron types, we have uncovered a core of conserved classes and discovered a fascinating dichotomy of new and conserved neuron types throughout the brain. This research challenges the traditional notion that certain brain regions are more conserved than others.
Our research also has uncovered the evolutionary history of the lizard thalamus and prethalamus by comparing them to homologous brain regions of the mouse. This pioneering research sheds new light on our understanding of the evolutionary history of the lizard brain. We propose a new classification of the lizard thalamic nuclei based on
transcriptomics. Our research revealed that the thalamic neuron types in lizards can be grouped into two large, conserved categories from the medial to lateral thalamus. These categories are encoded by a common set of effector genes, linking theories based on connectivity and molecular studies of these areas. In our data we have seen that there is a conservation of the medial-lateral transcriptomic axis in mouse and lizard, this conservation was most likely already present in the common ancestor. Although there is a shared medial-lateral axis, a deeper study of the thalamic cell types has allowed us to see the existence of a partial diversification of the thalamic population, specifically in the sensory-related lateral thalamus; in opposition, the medial thalamic nuclei neuron-types have been preserved.
On the other hand, the comparison with the mammalian prethalamus allowed us to confirm that the lizard ventromedial thalamic neuron types are homologous to mouse reticular thalamic neuron types (Díaz et al., 1994), even if they do not express the classical Reticular thalamic nucleus (RTn) marker PV/pvalb. We also discovered that there has been a simplification in the mammalian prethalamic neuron types in favor of an increase in the number of Interneurons (IN) types within their thalamus. We suggest that the loss of GABAergic neuronal types in the mammalian prethalamus is linked to the need for a more efficient control of the thalamo-pallial communication in mammals, while in lizards, where thalamo-pallial communication is probably simpler, the diversity prethalamus presents a higher diversity.
We contribute to the foundations of tropical geometry with a view toward formulating tropical moduli problems, and with the moduli space of curves as our main example. We propose a moduli functor for the moduli space of curves and show that it is representable by a geometric stack over the category of rational polyhedral cones. In this framework, the natural forgetful morphisms between moduli spaces of curves with marked points function as universal curves.
Our approach to tropical geometry permits tropical moduli problems—moduli of curves or otherwise—to be extended to logarithmic schemes. We use this to construct a smooth tropicalization morphism from the moduli space of algebraic curves to the moduli space of tropical curves, and we show that this morphism commutes with all of the tautological morphisms.
Background: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma.
Methods: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics.
Results: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on "double-hit" MYC and BCL2 transformed lymphomas.
Conclusions: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.
We consider a linear ill-posed equation in the Hilbert space setting. Multiple independent unbiased measurements of the right-hand side are available. A natural approach is to take the average of the measurements as an approximation of the right-hand side and to estimate the data error as the inverse of the square root of the number of measurements. We calculate the optimal convergence rate (as the number of measurements tends to infinity) under classical source conditions and introduce a modified discrepancy principle, which asymptotically attains this rate.
Recently, new soil data maps were developed, which include vertical soil properties like soil type. Implementing those into a multilayer Soil-Vegetation-Atmosphere-Transfer (SVAT) scheme, discontinuities in the water content occur at the interface between dissimilar soils. Therefore, care must be taken in solving the Richards equation for calculating vertical soil water fluxes. We solve a modified form of the mixed (soil water and soil matric potential based) Richards equation by subtracting the equilibrium state of soil matrix potential ψE from the hydraulic potential ψh. The sensitivity of the modified equation is tested under idealized conditions. The paper will show that the modified equation can handle with discontinuities in soil water content at the interface of layered soils.
We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of the United States, Donald J. Trump. We analyze around 1,400 of his tweets related to the US economy and classify them by topic and textual sentiment using machine learning algorithms. We investigate whether the tweets contain relevant information for financial markets, i.e. whether they affect market returns, volatility, and trading volumes. Using high-frequency data, we find that Trump’s tweets are most often a reaction to pre-existing market trends and therefore do not provide material new information that would influence prices or trading. We show that past market information can help predict Trump’s decision to tweet about the economy.
We propose a model of the dynamics of organizational communication. Our model specifies the mechanics by which communication impact is fed back to communication inputs and closes the gap between sender and receiver of messages. We draw on language critique, a branch of language philosophy, and derive joint linguistic actions of interlocutors to explain the emergence and adaptation of communication on the group level. The model is framed by Te'eni's cognitive-affective model of organizational communication.
This paper solves a dynamic model of households' mortgage decisions incorporating labor income, house price, inflation, and interest rate risk. It uses a zero-profit condition for mortgage lenders to solve for equilibrium mortgage rates given borrower characteristics and optimal decisions. The model quantifies the effects of adjustable vs. fixed mortgage rates, loan-to-value ratios, and mortgage affordability measures on mortgage premia and default. Heterogeneity in borrowers' labor income risk is important for explaining the higher default rates on adjustable-rate mortgages during the recent US housing downturn, and the variation in mortgage premia with the level of interest rates.
The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network’s changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network’s sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.
The aim of this work is to develop an effective equation of state for QCD, having the correct asymptotic degrees of freedom, to be used as input for dynamical studies of heavy ion collisions. We present an approach for modeling an EoS that respects the symmetries underlying QCD, and includes the correct asymptotic degrees of freedom, i.e. quarks and gluons at high temperature and hadrons in the low-temperature limit. We achieve this by including quarks degrees of freedom and the thermal contribution of the Polyakov loop in a hadronic chiral sigma-omega model. The hadronic part of the model is a nonlinear realization of an sigma-omega model. As the fundamental symmetries of QCD should also be present in its hadronic states such an approach is widely used to describe hadron properties below and around Tc. The quarks are introduced as thermal quasi particles, coupling to the Polyakov loop, while the dynamics of the Polyakov loop are controlled by a potential term which is fitted to reproduce pure gauge lattice data. In this model the sigma field serves a the order parameter for chiral restoration and the Polyakov loop as order parameter for deconfinement. The hadrons are suppressed at high densities by excluded volume corrections. As a next step, we introduce our new HQ model equation of state in a microscopic+macroscopic hybrid approach to heavy ion collisions. This hybrid approach is based on the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) transport approach with an intermediate hydrodynamical evolution for the hot and dense stage of the collision. The present implementation allows to compare pure microscopic transport calculations with hydrodynamic calculations using exactly the same initial conditions and freeze-out procedure. The effects of the change in the underlying dynamics - ideal fluid dynamics vs. non-equilibrium transport theory - are explored. The final pion and proton multiplicities are lower in the hybrid model calculation due to the isentropic hydrodynamic expansion while the yields for strange particles are enhanced due to the local equilibrium in the hydrodynamic evolution. The elliptic and directed flow are shown to be not sensitive to changes in the EoS while the smaller mean free path in the hydrodynamic evolution reflects directly in higher flow results which are consistent with the experimental data. This finding indicates qualitatively that physical mechanisms like viscosity and other non equilibrium effects play an essentially more important role than the EoS when bulk observables like flow are investigated. In the last chapter, results for the thermal production of MEMOs in nucleus-nucleus collisions from a combined micro+macro approach are presented. Multiplicities, rapidity and transverse momentum spectra are predicted for Pb+Pb interaction at different beam energies. The presented excitation functions for various MEMO multiplicities show a clear maximum at the upper FAIR energy regime making this facility the ideal place to study the production of these exotic forms of multistrange objects.
Fire is the primary disturbance factor in many terrestrial ecosystems. Wildfire alters vegetation structure and composition, affects carbon storage and biogeochemical cycling, and results in the release of climatically relevant trace gases including CO2, CO, CH4, NOx, and aerosols. One way of assessing the impacts of global wildfire on centennial to multi-millennial timescales is to use process-based fire models linked to dynamic global vegetation models (DGVMs). Here we present an update to the LPJ-DGVM and a new fire module based on SPITFIRE that includes several improvements to the way in which fire occurrence, behaviour, and the effects of fire on vegetation are simulated. The new LPJ-LMfire model includes explicit calculation of natural ignitions, the representation of multi-day burning and coalescence of fires, and the calculation of rates of spread in different vegetation types. We describe a new representation of anthropogenic biomass burning under preindustrial conditions that distinguishes the different relationships between humans and fire among hunter-gatherers, pastoralists, and farmers. We evaluate our model simulations against remote-sensing-based estimates of burned area at regional and global scale. While wildfire in much of the modern world is largely influenced by anthropogenic suppression and ignitions, in those parts of the world where natural fire is still the dominant process (e.g. in remote areas of the boreal forest and subarctic), our results demonstrate a significant improvement in simulated burned area over the original SPITFIRE. The new fire model we present here is particularly suited for the investigation of climate–human–fire relationships on multi-millennial timescales prior to the Industrial Revolution.
Fusion of mitochondrial outer membranes is crucial for proper organelle function and involves large GTPases called mitofusins. The discrete steps that allow mitochondria to attach to one another and merge their outer membranes are unknown. By combining an in vitro mitochondrial fusion assay with electron cryo-tomography (cryo-ET), we visualize the junction between attached mitochondria isolated from Saccharomyces cerevisiae and observe complexes that mediate this attachment. We find that cycles of GTP hydrolysis induce progressive formation of a docking ring structure around extended areas of contact. Further GTP hydrolysis triggers local outer membrane fusion at the periphery of the contact region. These findings unravel key features of mitofusin-dependent fusion of outer membranes and constitute an important advance in our understanding of how mitochondria connect and merge.
Epigenetic silencing of transgene expression represents a major obstacle for the efficient genetic modification of multipotent and pluripotent stem cells. We and others have demonstrated that a 1.5 kb methylation-free CpG island from the human HNRPA2B1-CBX3 housekeeping genes (A2UCOE) effectively prevents transgene silencing and variegation in cell lines, multipotent and pluripotent stem cells, and their differentiated progeny. However, the bidirectional promoter activity of this element may disturb expression of neighboring genes. Furthermore, the epigenetic basis underlying the anti-silencing effect of the UCOE on juxtaposed promoters has been only partially explored. In this study we removed the HNRPA2B1 moiety from the A2UCOE and demonstrate efficient anti-silencing properties also for a minimal 0.7 kb element containing merely the CBX3 promoter. This DNA element largely prevents silencing of viral and tissue-specific promoters in multipotent and pluripotent stem cells. The protective activity of CBX3 was associated with reduced promoter CpG-methylation, decreased levels of repressive and increased levels of active histone marks. Moreover, the anti-silencing effect of CBX3 was locally restricted and when linked to tissue-specific promoters did not activate transcription in off target cells. Thus, CBX3 is a highly attractive element for sustained, tissue-specific and copy-number dependent transgene expression in vitro and in vivo.
In this Letter we study the radiation measured by an accelerated detector, coupled to a scalar field, in the presence of a fundamental minimal length. The latter is implemented by means of a modified momentum space Green's function. After calibrating the detector, we find that the net flux of field quanta is negligible, and that there is no Planckian spectrum. We discuss possible interpretations of this result, and we comment on experimental implications in heavy ion collisions and atomic systems.
Explaining humans as rational creatures—capable of deductive reasoning—remains challenging for evolutionary naturalism. Schechter (Philosophical Perspectives, 24(1)437–464, 2011, 2013) proposes to link the evolution of this kind of reasoning with the ability to plan. His proposal, however, does neither include any elaborated theory on how logical abilities came into being within the hominin lineage nor is it sufficiently supported by empirical evidence. I present such a theory in broad outline and substantiate it with archeological findings. It is argued that the cognitive makeup of any animal is constituted by being embedded in a certain way of life. Changing ways of life thus foster appearances of new cognitive abilities. Finally, a new way of life of coordinated group behavior emerged within the hominins: anticipatory group planning involved in activities like making sophisticated spears for hunting. This gave rise to human logical cognition. It turned hominins into domain-general reasoner and adherents of intersubjective norms for reasoning. However, as I argue, it did not—and most likely could not—give rise to reason by deductive logic. More likely, deductive reasoning entered our world only a few thousand years ago: exclusively as a cultural artifact.
For experiments on fission-fragment induced desorption the detection of significant correlations between desorbed ions has been reported [1]. In this paper the method for the detection and quantitative description of these correlations will be described. The statistics of the desorption-process leads to equations for mass-line intensities of ion spectra. Using a time-to-amplitude-converter for flight-time measurements these intensities depend on interdependences of different ions desorbed by the same fission-fragment. The equations allow the computation of correlationcoefficients whose interdependence with desorption probabilities of the respective ions can be shown in Venn-diagrams. Results are given and an interpretation is suggested for fission-fragment desorbed thiamine molecular and fragment ions.
Background: Compound flaps offer the advantage of one stage defect reconstruction respecting all relevant tissues and early functional recovery by optimal vascularity of all components. Due to its specific vascular anatomy and the three-dimensional donor site, compound flaps with bone components may result in higher complication rates compared to soft tissue compound flaps. The meta-analysis summarizes the available evidence and evaluates whether bone components are a risk factor for periprocedural complications in upper extremity multidimensional defect reconstruction. Method: PubMed and Embase were searched for all publications addressing compound free flaps for upper extremity defect reconstruction with bone or soft tissue components published between January 1988 and May 2018. The methodological quality was assessed with the American Society of Plastic Surgeons Evidence Rating Scale for Therapeutic Studies. Flap loss, thrombosis rate, early infection, hematoma, seroma, as well as donor site complications were extracted and analyzed. Results: Twelve out of 1157 potentially eligible studies (evidence-III) comprising 159 patients were finally included with publication bias for all summarized complication rates. Complication rates for flaps with/ without bone components were: total flap loss 5%, 95% CI = 3%–10% (6%/5%); partial flap loss 8%, 95% CI = 5%–15%, (9%/8%); arterial/venous thrombosis 7%, 95% CI = 4%–12%, (8%/5%)/14%, 95% CI = 9%–21% (16%/6%, P < .05) with higher risk for flaps with bone components; infection 6%, 95% CI = 3%–12% (6%/6%); hematoma 6%, 95% CI = 3%–11% (6%/5%); seroma 5%, 95% CI = 3%–10% (5%/5%); dehiscence 10%, 95% CI = 6%–17% (11%/9%). Conclusion: Compound flaps for upper extremity defect reconstruction including bone components have a higher venous thrombosis rate compared to compound soft-tissue flaps.
Volatile organic compounds are secondary metabolites emitted by all organisms, especially by plants and microbes. Their role as aboveground signals has been established for decades. Recent evidence suggests that they might have a non-negligible role belowground and might be involved in root–root and root–microbial/pest interactions. Our aim here was to make a comprehensive review of belowground volatile diversity using a meta-analysis approach. At first we synthesized current literature knowledge on plant root volatiles and classified them in terms of chemical diversity. In a second step, relying on the mVOC database of microbial volatiles, we classified volatiles based on their emitters (bacteria vs. fungi) and their specific ecological niche (i.e., rhizosphere, soil). Our results highlight similarities and differences among root and microbial volatiles and also suggest that some might be niche specific. We further explored the possibility that volatiles might be involved in intra- and inter-specific root–root communication and discuss the ecological implications of such scenario. Overall this work synthesizes current knowledge on the belowground volatilome and the potential signaling role of its constituents. It also highlights that the total diversity of belowground volatiles might be orders of magnitude larger that the few hundreds of compounds described to date.
A message from the human placenta: structural and immunomodulatory defense against SARS-CoV-2
(2020)
The outbreak of the coronavirus disease 2019 (COVID-19) pandemic has caused a global public health crisis. Viral infections may predispose pregnant women to a higher rate of pregnancy complications, including preterm births, miscarriage and stillbirth. Despite reports of neonatal COVID-19, definitive proof of vertical transmission is still lacking. In this review, we summarize studies regarding the potential evidence for transplacental transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), characterize the expression of its receptors and proteases, describe the placental pathology and analyze virus-host interactions at the maternal-fetal interface. We focus on the syncytium, the barrier between mother and fetus, and describe in detail its physical andstructuraldefenseagainstviralinfections. Wefurtherdiscussthepotentialmolecularmechanisms, whereby the placenta serves as a defense front against pathogens by regulating the interferon type III signaling, microRNA-triggered autophagy and the nuclear factor-κB pathway. Based on these data, we conclude that vertical transmission may occur but rare, ascribed to the potent physical barrier, the fine-regulatedplacentalimmunedefenseandmodulationstrategies. Particularly,immunomodulatory mechanismsemployedbytheplacentamaymitigateviolentimmuneresponse,maybesoftencytokine storm tightly associated with severely ill COVID-19 patients, possibly minimizing cell and tissue damages, and potentially reducing SARS-CoV-2 transmission.
Background: Cognitive dysfunctions represent a core feature of schizophrenia and a predictor for clinical outcomes. One possible mechanism for cognitive impairments could involve an impairment in the experience-dependent modifications of cortical networks.
Methods: To address this issue, we employed magnetoencephalography (MEG) during a visual priming paradigm in a sample of chronic patients with schizophrenia (n = 14), and in a group of healthy controls (n = 14). We obtained MEG-recordings during the presentation of visual stimuli that were presented three times either consecutively or with intervening stimuli. MEG-data were analyzed for event-related fields as well as spectral power in the 1–200 Hz range to examine repetition suppression and repetition enhancement. We defined regions of interest in occipital and thalamic regions and obtained virtual-channel data.
Results: Behavioral priming did not differ between groups. However, patients with schizophrenia showed prominently reduced oscillatory response to novel stimuli in the gamma-frequency band as well as significantly reduced repetition suppression of gamma-band activity and reduced repetition enhancement of beta-band power in occipital cortex to both consecutive repetitions as well as repetitions with intervening stimuli. Moreover, schizophrenia patients were characterized by a significant deficit in suppression of the C1m component in occipital cortex and thalamus as well as of the late positive component (LPC) in occipital cortex.
Conclusions: These data provide novel evidence for impaired repetition suppression in cortical and subcortical circuits in schizophrenia. Although behavioral priming was preserved, patients with schizophrenia showed deficits in repetition suppression as well as repetition enhancement in thalamic and occipital regions, suggesting that experience-dependent modification of neural circuits is impaired in the disorder.
The development of epilepsy (epileptogenesis) involves a complex interplay of neuronal and immune processes. Here, we present a first-of-its-kind mathematical model to better understand the relationships among these processes. Our model describes the interaction between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model reproduces the available data from three animal models. The model successfully describes characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries or the existence of qualitatively different outcomes for varying injury intensity. In line with the concept of degeneracy, our simulations reveal multiple routes toward epilepsy with neuronal loss as a sufficient but non-necessary component. Finally, we show that our model allows for in silico predictions of therapeutic strategies, revealing injury-specific therapeutic targets and optimal time windows for intervention.
Selfish genetic elements that act as post-segregation distorters cause lethality in non-carrier individuals after fertilization. Two post-segregation distorters have been previously identified in Caenorhabditis elegans, the peel-1/zeel-1 and the sup-35/pha-1 elements. These elements seem to act as modification-rescue systems, also called toxin/antidote pairs. Here we show that the maternal-effect toxin/zygotic antidote pair sup-35/pha-1 is required for proper expression of apical junction (AJ) components in epithelia and that sup-35 toxicity increases when pathways that establish and maintain basal epithelial characteristics, die-1, elt-1, lin-26, and vab-10, are compromised. We demonstrate that pha-1(e2123) embryos, which lack the antidote, are defective in epidermal morphogenesis and frequently fail to elongate. Moreover, seam cells are frequently misshaped and mispositioned and cell bond tension is reduced in pha-1(e2123) embryos, suggesting altered tissue material properties in the epidermis. Several aspects of this phenotype can also be induced in wild-type embryos by exerting mechanical stress through uniaxial loading. Seam cell shape, tissue mechanics, and elongation can be restored in pha-1(e2123) embryos if expression of the AJ molecule DLG-1/Discs large is reduced. Thus, our experiments suggest that maternal-effect toxicity disrupts proper development of the epidermis which involves distinct transcriptional regulators and AJ components.
Background: Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine‐learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain.
Methods: Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine‐learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analysed by means of computational functional genomics in the Gene Ontology knowledgebase.
Results: Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signalling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research.
Conclusions: The present computational functional genomics‐based approach provided a computational systems‐biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine‐learned methods provide innovative approaches to knowledge discovery from previous evidence.
Significance: We show that knowledge discovery in genetic databases and contemporary machine‐learned techniques can identify relevant biological processes involved in Persitent pain.
A machine-learned analysis suggests non-redundant diagnostic information in olfactory subtests
(2019)
Background: The functional performance of the human sense of smell can be approached via assessment of the olfactory threshold, the ability to discriminate odors or the ability to identify odors. Contemporary clinical test batteries include all or a selection of these components, with some dissent about the required number and choice.
Methods: Olfactory thresholds, odor discrimination and odor identification scores were available from 10,714 subjects (3662 with anomia, 4299 with hyposmia, and 2752 with normal olfactory function). To assess, whether the olfactory subtests confer the same information or each subtest confers at least partly non-redundant information relevant to the olfactory diagnosis, we compared the diagnostic accuracy of supervised machine learning algorithms trained with the complete information from all three subtests with that obtained when performing the training with the information of only two or one subtests.
Results: The training of machine-learned algorithms with the full information about olfactory thresholds, odor discrimination and odor identification from 2/3 of the cases, resulted in a balanced olfactory diagnostic accuracy of 98% or better in the 1/3 remaining cases. The most pronounced decrease in the balanced accuracy, to approximately 85%, was observed when omitting olfactory thresholds from the training, whereas omitting odor discrimination or identification was associated with smaller decreases (balanced accuracies approximately 90%).
Conclusions: Results support partly non-redundant contributions of each olfactory subtest to the clinical olfactory diagnosis. Olfactory thresholds provided the largest amount of non-redundant information to the olfactory diagnosis.
Bacteria that are capable of organizing themselves as biofilms are an important public health issue. Knowledge discovery focusing on the ability to swarm and conquer the surroundings to form persistent colonies is therefore very important for microbiological research communities that focus on a clinical perspective. Here, we demonstrate how a machine learning workflow can be used to create useful models that are capable of discriminating distinct associated growth behaviors along distinct phenotypes. Based on basic gray-scale images, we provide a processing pipeline for binary image generation, making the workflow accessible for imaging data from a wide range of devices and conditions. The workflow includes a locally estimated regression model that easily applies to growth-related data and a shape analysis using identified principal components. Finally, we apply a density-based clustering application with noise (DBSCAN) to extract and analyze characteristic, general features explained by colony shapes and areas to discriminate distinct Bacillus subtilis phenotypes. Our results suggest that the differences regarding their ability to swarm and subsequently conquer the medium that surrounds them result in characteristic features. The differences along the time scales of the distinct latency for the colony formation give insights into the ability to invade the surroundings and therefore could serve as a useful monitoring tool.
The coordinate and momentum space configurations of the net baryon number in heavy ion collisions that undergo spinodal decomposition, due to a first-order phase transition, are investigated using state-of-the-art machine-learning methods. Coordinate space clumping, which appears in the spinodal decomposition, leaves strong characteristic imprints on the spatial net density distribution in nearly every event which can be detected by modern machine learning techniques. On the other hand, the corresponding features in the momentum distributions cannot clearly be detected, by the same machine learning methods, in individual events. Only a small subset of events can be systematically differ- entiated if only the momentum space information is available. This is due to the strong similarity of the two event classes, with and without spinodal decomposition. In such sce- narios, conventional event-averaged observables like the baryon number cumulants signal a spinodal non-equilibrium phase transition. Indeed the third-order cumulant, the skewness, does exhibit a peak at the beam energy (Elab = 3–4 A GeV), where the transient hot and dense system created in the heavy ion collision reaches the first-order phase transition.
Meat adulteration is a global problem which undermines market fairness and harms people with allergies or certain religious beliefs. In this study, a novel framework in which a one-dimensional convolutional neural network (1DCNN) serves as a backbone and a random forest regressor (RFR) serves as a regressor, named 1DCNN-RFR, is proposed for the quantitative detection of beef adulterated with pork using electronic nose (E-nose) data. The 1DCNN backbone extracted a sufficient number of features from a multichannel input matrix converted from the raw E-nose data. The RFR improved the regression performance due to its strong prediction ability. The effectiveness of the 1DCNN-RFR framework was verified by comparing it with four other models (support vector regression model (SVR), RFR, backpropagation neural network (BPNN), and 1DCNN). The proposed 1DCNN-RFR framework performed best in the quantitative detection of beef adulterated with pork. This study indicated that the proposed 1DCNN-RFR framework could be used as an effective tool for the quantitative detection of meat adulteration.
Recently, a 15-valent (PCV15) and a 20-valent pneumococcal conjugate vaccine (PCV20) have been licensed by the US Food and Drug Administration and are under evaluation by the European Medicines Agency. PCV15 contains all serotypes of the 13-valent conjugate vaccine (PCV13) plus serotype 22F and 33F and PCV20 includes PCV13 serotypes plus serotypes 8, 10A, 11A, 12F, 15B, 22F, 33F. We investigated pneumococcal serotype distribution, secular trends and proportion of pneumonia caused by serotypes included in PCV13, PCV15, PCV20, and the 23-valent pneumococcal polysaccharide vaccine (PPV23) among adult patients with all-cause community-acquired pneumonia (CAP) between 2013 and 2019. We applied logistic mixed regression modelling to assess annual trends. Urine samples from adult patients with CAP treated in the community or hospital in Germany and included in the CAPNETZ study, a prospective multi-centre cohort study, were analysed by two serotype-specific multiplex urinary antigen detection assays (UAD1/UAD2) at Pfizer’s Vaccines Research and Development Laboratory. UAD1 detects serotypes in PCV13, UAD2 detects additional serotypes in PCV20 plus serotypes 2, 9N, 17F and 20. Out of 1,831 patients screened, urine samples with a valid UAD test result were available for 1,343 patients (73.3%). Among those patients, 829 patients (61.7%) were male, 792 patients (59.0%) were aged ≥60 years, 1038 patients (77.3%) had at least one comorbidity and 1,204 patients (89.7%) were treated in the hospital. The overall proportion of vaccine-type pneumonia among all-cause CAP for PCV13, PCV15, PCV20 and PPV23 was 7.7% (n=103), 9.1% (n=122), 12.3% (n=165) and 13.3% (n=178). Over the entire observation period, we did not observe evidence for significant annual trends in pneumococcal vaccine serotype coverage against pneumonia in adults (PCV13: OR 0.94, 95% CI 0.83-1.05; PCV15: OR 0.93, 95% CI 0.84-1.03; PCV20: OR 0.95, 95% CI 0.86-1.04; PPV23: OR 0.99, 95% CI 0.90-1.08). In conclusion, our data show that i) the infant vaccination program of PCV13, which started in Germany 2010 did not result in a relevant and sustained decrease of PCV13 serotypes in pneumonia in adults and ii) that the gap in the coverage between PCV20 and PPV23 was small and did not increase over the entire observation time.
Recently, a 15-valent (PCV15) and a 20-valent pneumococcal conjugate vaccine (PCV20) have been licensed by the US Food and Drug Administration and are under evaluation by the European Medicines Agency. PCV15 contains all serotypes of the 13-valent conjugate vaccine (PCV13) plus serotype 22F and 33F and PCV20 includes PCV13 serotypes plus serotypes 8, 10A, 11A, 12F, 15B, 22F, 33F. We investigated pneumococcal serotype distribution, secular trends and proportion of pneumonia caused by serotypes included in PCV13, PCV15, PCV20, and the 23-valent pneumococcal polysaccharide vaccine (PPV23) among adult patients with all-cause community-acquired pneumonia (CAP) between 2013 and 2019. We applied logistic mixed regression modelling to assess annual trends. Urine samples from adult patients with CAP treated in the community or hospital in Germany and included in the CAPNETZ study, a prospective multi-centre cohort study, were analysed by two serotype-specific multiplex urinary antigen detection assays (UAD1/UAD2) at Pfizer’s Vaccines Research and Development Laboratory. UAD1 detects serotypes in PCV13, UAD2 detects additional serotypes in PCV20 plus serotypes 2, 9N, 17F and 20. Out of 1,831 patients screened, urine samples with a valid UAD test result were available for 1,343 patients (73.3%). Among those patients, 829 patients (61.7%) were male, 792 patients (59.0%) were aged ≥60 years, 1038 patients (77.3%) had at least one comorbidity and 1,204 patients (89.7%) were treated in the hospital. The overall proportion of vaccine-type pneumonia among all-cause CAP for PCV13, PCV15, PCV20 and PPV23 was 7.7% (n=103), 9.1% (n=122), 12.3% (n=165) and 13.3% (n=178). Over the entire observation period, we did not observe evidence for significant annual trends in pneumococcal vaccine serotype coverage against pneumonia in adults (PCV13: OR 0.94, 95% CI 0.83-1.05; PCV15: OR 0.93, 95% CI 0.84-1.03; PCV20: OR 0.95, 95% CI 0.86-1.04; PPV23: OR 0.99, 95% CI 0.90-1.08). In conclusion, our data show i) no decline of PCV13 serotypes in all-cause CAP between 2013-2019 mainly due to a persistently high proportion of serotype 3 suggesting no meaningful effect of childhood PCV13 vaccination on PCV13 coverage in pneumonia in adults during this time period and ii) that the gap in the coverage between PCV20 and PPV23 was small and did not increase over the entire observation time.
Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signaling pathways. Achieving a detailed understanding of intracellular GSH trafficking and regulation depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Herein, we present a new GSH sensing platform, TRaQ-G, for live-cell imaging. This small-molecule/protein hybrid sensor possesses a unique reactivity turn-on mechanism that ensures that the small molecule is only sensitive to GSH in the desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein of choice to give a ratiometric response. Using TRaQ-G-mGold, we demonstrated that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. We also used this sensor, in combination with roGFP, to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.
On average, "young" people underestimate whereas "old" people overestimate their chances to survive into the future. We adopt a Bayesian learning model of ambiguous survival beliefs which replicates these patterns. The model is embedded within a non-expected utility model of life-cycle consumption and saving. Our analysis shows that agents with ambiguous survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival probabilities. Our ambiguity-driven model therefore simultaneously accounts for three important empirical findings on household saving behavior.
Based on a cognitive notion of neo-additive capacities reflecting likelihood insensitivity with respect to survival chances, we construct a Choquet Bayesian learning model over the life-cycle that generates a motivational notion of neo-additive survival beliefs expressing ambiguity attitudes. We embed these neo-additive survival beliefs as decision weights in a Choquet expected utility life-cycle consumption model and calibrate it with data on subjective survival beliefs from the Health and Retirement Study. Our quantitative analysis shows that agents with calibrated neo-additive survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival chances. Our neo-additive life-cycle model can therefore simultaneously accommodate three important empirical findings on household saving behavior.
Tumor progression and pregnancy share many common features, such as immune tolerance and invasion. The invasion of trophoblasts in the placenta into the uterine wall is essential for fetal development, and is thus precisely regulated. Its deregulation has been implicated in preeclampsia, a leading cause for maternal and perinatal mortality and morbidity. Pathogenesis of preeclampsia remains to be defined. Microarray-based gene profiling has been widely used for identifying genes responsible for preeclampsia. In this review, we have summarized the recent data from the microarray studies with preeclamptic placentas. Despite the complex of gene signatures, suggestive of the heterogeneity of preeclampsia, these studies identified a number of differentially expressed genes associated with preeclampsia. Interestingly, most of them have been reported to be tightly involved in tumor progression. We have discussed these interesting genes and analyzed their potential molecular functions in preeclampsia, compared with their roles in malignancy development. Further investigations are warranted to explore the involvement in molecular network of each identified gene, which may provide not only novel strategies for prevention and therapy for preeclampsia but also a better understanding of cancer cells. The trophoblastic cells, with their capacity for proliferation and differentiation, apoptosis and survival, migration, angiogenesis and immune modulation by exploiting similar molecular pathways, make them a compelling model for cancer research.
The ability to respond appropriately to employees' work-related well-being requires leaders to pay attention to their employees' well-being in the first place. We propose that leaders' stress mindset, that is, the belief that stress is enhancing versus debilitating, may bias their perception of employees' well-being. We further propose that this judgment then influences leaders' intention to engage in or refrain from health-oriented leadership behavior, to express higher performance expectations, or to promote their employees. We expect this process to be stronger if leaders strongly identify with their team, increasing their perceived similarity with their employees. In three experiments (N1 = 198, N2 = 292, N3 = 250), we tested the effect of participants' stress mindset on their intention to show certain leadership behaviors, mediated by their perception of employee well-being (emotional exhaustion, somatic symptoms, work engagement) and moderated by their team identification. Our findings largely support the association between stress mindset and the perception of well-being. The results for the proposed mediation and the moderating function of identification were mixed. Overall, the results emphasize the critical role of leaders' stress mindset and may, thus, improve health promotion in organizations by helping leaders to adequately recognize employees' well-being and respond appropriately.
In the nineteenth century, two Neolithic axe-heads were reported from the Michelsberg enclosure system at Kapellenberg. The recent identification of an unusually large tumulus, from which the axe-heads were almost certainly once recovered, reveals that socio-political hierarchisation, linked to the emergence of high-ranking elites in Brittany and the Paris Basin during the fifth millennium cal BC, may have extended into Central Europe.
The human brain achieves visual object recognition through multiple stages of nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output M/EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
The human brain achieves visual object recognition through multiple stages of linear and nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models’ prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
Spin waves in yttrium-iron garnet has been the subject of research for decades. Recently the report of Bose-Einstein condensation at room temperature has brought these experiments back into focus. Due to the small mass of quasiparticles compared to atoms for example, the condensation temperature can be much higher. With spin-wave quasiparticles, so-called magnons, even room temperature can be reached by externally injecting magnons. But also possible applications in information technologies are of interest. Using excitations as carriers for information instead of charges delivers a much more efficient way of processing data. Basic logical operations have already been realized. Finally the wavelength of spin waves which can be decreased to nanoscale, gives the opportunity to further miniaturize devices for receiving signals for example in smartphones.
For all of these purposes the magnon system is driven far out of equilibrium. In order to get a better fundamental understanding, we concentrate in the main part of this thesis on the nonequilibrium aspect of magnon experiments and investigate their thermalization process. In this context we develop formalisms which are of general interest and which can be adopted to many different kinds of systems.
A milestone in describing gases out of equilibrium was the Boltzmann equation discovered by Ludwig Boltzmann in 1872. In this thesis extensions to the Boltzmann equation with improved approximations are derived. For the application to yttrium-iron garnet we describe the thermalization process after magnons were excited by an external microwave field.
First we consider the Bose-Einstein condensation phenomena. A special property of thin films of yttrium-iron garnet is that the dispersion of magnons has its minimum at finite wave vectors which leads to an interesting behavior of the condensate. We investigate the spatial structure of the condensate using the Gross-Pitaevskii equation and find that the magnons can not condensate only at the energy minimum but that also higher Fourier modes have to be occupied macroscopically. In principle this can lead to a localization on a lattice in real space.
Next we use functional renormalization group methods to go beyond the perturbation theory expressions in the Boltzmann equation. It is a difficult task to find a suitable cutoff scheme which fits to the constraints of nonequilibrium, namely causality and the fluctuation-dissipation theorem when approaching equilibrium. Therefore the cutoff scheme we developed for bosons in the context of our considerations is of general interest for the functional renormalization group. In certain approximations we obtain a system of differential equations which have a similar transition rate structure to the Boltzmann equation. We consider a model of two kinds of free bosons of which one type of boson acts as a thermal bath to the other one. Taking a suitable initial state we can use our formalism to describe the dynamics of magnons such that an enhanced occupation of the ground state is achieved. Numerical results are in good agreement with experimental data.
Finally we extend our model to consider also the pumping process and the decrease of the magnon particle number till thermal equilibrium is reached again. Additional terms which explicitly break the U(1)-symmetry make it necessary to also extend the theory from which a kinetic equation can be deduced. These extensions are complicated and we therefore restrict ourselves to perturbation theory only. Because of the weak interactions in yttrium-iron garnet this provides already good results.
Background: The aim of this pilot study was to analyze postures during the work of neurologists with respect to their occupational activities.
Methods: A total data material of 64.8 h (3885.74 min) of nine (three m/six f) neurologists (assistant physicians) was collected. Kinematic data were collected using the CUELA system (electro-goniometry). In addition, the occupational tasks performed on-site were subject to a detailed objective activity analysis. All activities were assigned to the categories "Office activities" (I), "Measures on patients" (II) and "Other activities" (III). The angle values of each body region (evaluation parameters) were evaluated according to ergonomic ISO standards.
Results: Only 3.4% of the working hours were spent with (II), while 50.8% of time was spent with (I) and 45.8% with (III). All tasks of category (II) revealed an increased ergonomic risk to the head, neck, trunk and back areas. During category (I) especially neck and back movements in the sagittal plane showed higher ergonomic risk levels.
Conclusion: Despite frequently performed awkward body positions in (II), the ergonomic risk is considered as rather low, since the percentage time share totaled only 3.4%. As a result, "Office activities" have been detected as high predictor to cause stress load on the musculoskeletal system in the daily work of neurologists.
By running a temperature series of molecular dynamics (MD) simulations starting from the known low-temperature phase, the experimentally observed phase transition in a `jumping crystal' was captured, thereby providing a prediction of the unknown crystal structure of the high-temperature phase and clarifying the phase-transition mechanism. The phase transition is accompanied by a discontinuity in two of the unit-cell parameters. The structure of the high-temperature phase is very similar to that of the low-temperature phase. The anisotropic displacement parameters calculated from the MD simulations readily identified libration as the driving force behind the phase transition. Both the predicted crystal structure and the phase-transition mechanism were verified experimentally using TLS (translation, libration, screw) refinement against X-ray powder diffraction data.
Motivated by recent reports of a quantum-disordered ground state in the triangular lattice compound NaRuO2, we derive a jeff = 1/2 magnetic model for this system by means of first-principles calculations. The pseudospin Hamiltonian is dominated by bond-dependent off-diagonal Γ interactions, complemented by a ferromagnetic Heisenberg exchange and a notably antiferromagnetic Kitaev term. In addition to bilinear interactions, we find a sizable four-spin ring exchange contribution with a strongly anisotropic character, which has been so far overlooked when modeling Kitaev materials. The analysis of the magnetic model, based on the minimization of the classical energy and exact diagonalization of the quantum Hamiltonian, points toward the existence of a rather robust easy-plane ferromagnetic order, which cannot be easily destabilized by physically relevant perturbations.
Background: Novel microscopic techniques which bypass the resolution limit in light microscopy are becoming routinely established today. The higher spatial resolution of super-resolution microscopy techniques demands for precise correction of drift, spectral and spatial offset of images recorded at different axial planes.
Methods: We employ a hydrophilic gel matrix for super-resolution microscopy of cellular structures. The matrix allows distributing fiducial markers in 3D, and using these for drift correction and multi-channel registration. We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores at different axial planes. We calculate a correction matrix for each spectral channel, correct for drift, spectral and spatial offset in 3D.
Results and discussion: We demonstrate single-molecule super-resolution microscopy with photoswitchable fluorophores in a hydrophilic gel matrix. We distribute multi-color fiducial markers in the gel matrix and correct for drift and register multiple imaging channels. We perform two-color super-resolution imaging of click-labeled DNA and histone H2B in different axial planes, and demonstrate the quality of drift correction and channel registration quantitatively. This approach delivers robust microscopic data which is a prerequisite for data interpretation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
For genus g=2i≥4 and the length g−1 partition μ=(4,2,…,2,−2,…,−2) of 0, we compute the first coefficients of the class of D¯¯¯¯(μ) in PicQ(R¯¯¯¯g), where D(μ) is the divisor consisting of pairs [C,η]∈Rg with η≅OC(2x1+x2+⋯+xi−1−xi−⋯−x2i−1) for some points x1,…,x2i−1 on C. We further provide several enumerative results that will be used for this computation.
Background & Aims: Elimination of chronic HBV/HDV infection remains a major global health challenge. Targeting excessive hepatitis B surface antigen (HBsAg) release may provide an interesting window of opportunity to break immune tolerance and to achieve a functional cure using additional antivirals.
Methods: We evaluated a HBsAg-specific human monoclonal antibody, as part of either a prophylactic or therapeutic strategy, against HBV/HDV infection in cell culture models and in human-liver chimeric mice. To assess prophylactic efficacy, mice were passively immunized prior to infection with HBV or HBV/HDV (coinfection and superinfection setting). Therapeutic efficacy was assessed in HBV and HBV/HDV-coinfected mice receiving 4 weeks of treatment. Viral parameters (HBV DNA, HDV RNA and HBsAg) were assessed in mouse plasma.
Results: The antibody could effectively prevent HBV/HDV infection in a dose-dependent manner with IC50 values of ∼3.5 ng/ml. Passive immunization showed complete protection of mice from both HBV and HBV/HDV coinfection. Moreover, HDV superinfection was either completely prevented or at least attenuated in HBV-infected mice. Finally, antibody treatment in mice with established HBV/HDV infection resulted in a significant decline in viremia and a concomitant drop in on-treatment HBsAg, with a moderate viral rebound following treatment cessation.
Conclusion: We present data on a valuable antibody candidate that could complement other antivirals in strategies aimed at achieving functional cure of chronic HBV and HDV infection.
Impact and implications: Patients chronically infected with HBV may eventually develop liver cancer and are at great risk of being superinfected with HDV, which worsens and accelerates disease progression. Unfortunately, current treatments can rarely eliminate both viruses from chronically infected patients. In this study, we present data on a novel antibody that is able to prevent chronic HBV/HDV infection in a mouse model with a humanized liver. Moreover, antibody treatment of HBV/HDV-infected mice strongly diminishes viral loads during therapy. This antibody is a valuable candidate for further clinical development.
We provide a Hopf boundary lemma for the regional fractional Laplacian (−Δ)sΩ, with Ω ⊂ RN a bounded open set. More precisely, given u a pointwise or weak super-solution of the equation (−Δ)s u = c(x)u in Ω, we show that the ratio u(x)∕(dist(x, 𝜕Ω))2s−1 is strictly Ω positive as x approaches the boundary 𝜕Ω of Ω. We also prove a strong maximum principle for distributional super-solutions.
Breast cancer is fast becoming the leading cause of oncologic morbidity and mortality among women worldwide. Demographic changes in Asia, Southeast Asia, and South America will further accelerate this trend. Different specialties are involved in the treatment of breast cancer patients: gynecology, surgery, pathology, hematology/oncology, radiology, radiation oncology, and nuclear medicine. Optimal results are seen in countries providing standardized breast cancer care in certified breast centers. The present article provides an overview of current state-of-the-art treatment strategies and explains the contributions of different specialties to optimal and individualized care for breast cancer patients. Breast cancer will be one of the most important health issues facing physicians involved with women’s health and a basic understanding of current treatment objectives will be essential medical knowledge for everyone taking care of female patients.
The geminal frustrated Lewis pair tBu2PCH2B(Fxyl)2 (1; Fxyl=3,5-(CF3)2C6H3) is accessible in 65 % yield from tBu2PCH2Li and (Fxyl)2BF. According to NMR spectroscopy and X-ray crystallography, 1 is monomeric both in solution and in the solid state. The intramolecular P⋅⋅⋅B distance of 2.900(5) Å and the full planarity of the borane site exclude any significant P/B interaction. Compound 1 readily activates a broad variety of substrates including H2, EtMe2SiH, CO2/CS2, Ph2CO, and H3CCN. Terminal alkynes react with heterolysis of the C−H bond. Haloboranes give cyclic adducts with strong P−BX3 and weak R3B−X bonds. Unprecedented transformations leading to zwitterionic XP/BCX3 adducts occur on treatment of 1 with CCl4 or CBr4 in Et2O. In less polar solvents (C6H6, n-pentane), XP/BCX3 adduct formation is accompanied by the generation of significant amounts of XP/BX adducts. FLP 1 catalyzes the hydrogenation of PhCH=NtBu and the hydrosilylation of Ph2CO with EtMe2SiH.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Low-caloric formula diets can improve hemodynamic parameters of patients with type 2 diabetes. We, therefore, hypothesized that persons with overweight or obesity can benefit from a high-protein, low-glycemic but moderate-caloric formula diet. This post-hoc analysis of the Almased Concept against Overweight and Obesity and Related Health Risk- (ACOORH) trial investigated the impact of a lifestyle intervention combined with a formula diet (INT, n = 308) compared to a control group with lifestyle intervention alone (CON, n = 155) on hemodynamic parameters (systolic and diastolic blood pressure (SBP, DBP), resting heart rate (HR), and pulse wave velocity (PWV)) in high-risk individuals with prehypertension or hypertension. INT replaced meals during the first 6 months (1 week: 3 meals/day; 2–4 weeks: 2 meals/day; 5–26 weeks: 1 meal/day). Study duration was 12 months. From the starting cohort, 304 (68.3%, INT: n = 216; CON: n = 101) participants had a complete dataset. Compared to CON, INT significantly reduced more SBP (−7.3 mmHg 95% CI [−9.2; −5.3] vs. −3.3 mmHg [−5.9; −0.8], p < 0.049) and DBP (−3.7 mmHg [−4.9; −2.5] vs. −1.4 mmHg [−3.1; 0.2], p < 0.028) after 12 months. Compared to CON, INT showed a pronounced reduction in resting HR and PWV after 6 months but both lost significance after 12 months. Changes in SBP, DBP, and PWV were significantly associated positively with changes in body weight and fat mass (all p < 0.05) and resting HR correlated positively with fasting insulin (p < 0.001) after 12 months. Combining a lifestyle intervention with a high-protein and low-glycemic formula diet improves hemodynamic parameters to a greater extent than lifestyle intervention alone in high-risk individuals with overweight and obesity.
We present a hierarchy of polynomial time lattice basis reduction algorithms that stretch from Lenstra, Lenstra, Lovász reduction to Korkine–Zolotareff reduction. Let λ(L) be the length of a shortest nonzero element of a lattice L. We present an algorithm which for k∈N finds a nonzero lattice vector b so that |b|2⩽(6k2)nkλ(L)2. This algorithm uses O(n2(kk+o(k))+n2)log B) arithmetic operations on O(n log B)-bit integers. This holds provided that the given basis vectors b1,…,bn∈Zn are integral and have the length bound B. This algorithm successively applies Korkine–Zolotareff reduction to blocks of length k of the lattice basis. We also improve Kannan's algorithm for Korkine-Zolotareff reduction.
Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to potential underlying mechanisms.
The transcription factor vitamin D receptor (VDR) is the high affinity nuclear target of the biologically active form of vitamin D3 (1,25(OH)2D3). In order to identify pure genomic transcriptional effects of 1,25(OH)2D3, we used VDR cistrome, transcriptome and open chromatin data, obtained from the human monocytic cell line THP-1, for a novel hierarchical analysis applying three bioinformatics approaches. We predicted 75.6% of all early 1,25(OH)2D3-responding (2.5 or 4 h) and 57.4% of the late differentially expressed genes (24 h) to be primary VDR target genes. VDR knockout led to a complete loss of 1,25(OH)2D3–induced genome-wide gene regulation. Thus, there was no indication of any VDR-independent non-genomic actions of 1,25(OH)2D3 modulating its transcriptional response. Among the predicted primary VDR target genes, 47 were coding for transcription factors and thus may mediate secondary 1,25(OH)2D3 responses. CEBPA and ETS1 ChIP-seq data and RNA-seq following CEBPA knockdown were used to validate the predicted regulation of secondary vitamin D target genes by both transcription factors. In conclusion, a directional network containing 47 partly novel primary VDR target transcription factors describes secondary responses in a highly complex vitamin D signaling cascade. The central transcription factor VDR is indispensable for all transcriptome-wide effects of the nuclear hormone.
Objectives: To compare efficacy and safety of ixekizumab (IXE) to adalimumab (ADA) in biological disease-modifying antirheumatic drug-naïve patients with both active psoriatic arthritis (PsA) and skin disease and inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARDs).
Methods: Patients with active PsA were randomised (1:1) to approved dosing of IXE or ADA in an open-label, head-to-head, blinded assessor clinical trial. The primary objective was to evaluate whether IXE was superior to ADA at week 24 for simultaneous achievement of a ≥50% improvement from baseline in the American College of Rheumatology criteria (ACR50) and a 100% improvement from baseline in the Psoriasis Area and Severity Index (PASI100). Major secondary objectives, also at week 24, were to evaluate whether IXE was: (1) non-inferior to ADA for achievement of ACR50 and (2) superior to ADA for PASI100 response. Additional PsA, skin, treat-to-target and quality-of-life outcome measures were assessed at week 24.
Results: The primary efficacy endpoint was met (IXE: 36%, ADA: 28%; p=0.036). IXE was non-inferior for ACR50 response (IXE: 51%, ADA: 47%; treatment difference: 3.9%) and superior for PASI100 response (IXE: 60%, ADA: 47%; p=0.001). IXE had greater response versus ADA in additional PsA, skin, nail, treat-to-target and quality-of-life outcomes. Serious adverse events were reported in 8.5% (ADA) and 3.5% (IXE) of patients.
Conclusions: IXE was superior to ADA in achievement of simultaneous improvement of joint and skin disease (ACR50 and PASI100) in patients with PsA and inadequate response to csDMARDs. Safety and tolerability for both biologicals were aligned with established safety profiles.
A handling study to assess use of the Respimat(®) Soft Mist™ inhaler in children under 5 years old
(2015)
Background: Respimat® Soft Mist™ Inhaler (SMI) is a hand-held device that generates an aerosol with a high, fine-particle fraction, enabling efficient lung deposition. The study objective was to assess inhalation success among children using Respimat SMI, and the requirement for assistance by the parent/caregiver and/or a valved holding chamber (VHC).
Methods: This open-label study enrolled patients aged <5 years with respiratory disease and history of coughing and/or recurrent wheezing. Patients inhaled from the Respimat SMI (air only; no aerosol) using a stepwise configuration: “1” (dose released by child); “2” (dose released by parent/caregiver), and “3” (Respimat SMI with VHC, facemask, and parent/caregiver help). Co-primary endpoints included the ability to perform successful inhalation as assessed by the investigators using a standardized handling questionnaire and evaluation of the reasons for success. Inhalation profile in the successful handling configuration was verified with a pneumotachograph. Patient satisfaction and preferences were investigated in a questionnaire.
Results: Of the children aged 4 to <5 years (n=27) and 3 to <4 years (n=30), 55.6% and 30.0%, respectively, achieved success without a VHC or help; with assistance, another 29.6% and 10.0%, respectively, achieved success, and the remaining children were successful with VHC. All children aged 2 to <3 years (n=20) achieved success with the Respimat SMI and VHC. Of those aged <2 years (n=22), 95.5% had successful handling of the Respimat SMI with VHC and parent/caregiver help. Inhalation flow profiles generally confirmed the outcome of the handling assessment by the investigators. Most parent/caregiver and/or child respondents were satisfied with operation, instructions for use, handling, and ease of holding the Respimat SMI with or without a VHC.
Conclusions: The Respimat SMI is suitable for children aged <5 years; however, children aged <5 years are advised to add a VHC to complement its use.
The haloarchaeon Haloferax volcanii contains nearly 2800 small non-coding RNAs (sRNAs). One intergenic sRNA, sRNA132, was chosen for a detailed characterization. A deletion mutant had a growth defect and thus underscored the importance of sRNA132. A microarray analysis identified the transcript of an operon for a phosphate-specific ABC transporter as a putative target of sRNA132. Both the sRNA132 and the operon transcript accumulated under low phosphate concentrations, indicating a positive regulatory role of sRNA132. A kinetic analysis revealed that sRNA132 is essential shortly after the onset of phosphate starvation, while other regulatory processes take over after several hours. Comparison of the transcriptomes of wild-type and the sRNA132 gene deletion mutant 30 min after the onset of phosphate starvation revealed that sRNA132 controls a regulon of about 40 genes. Remarkably, the regulon included a second operon for a phosphate-specific ABC transporter, which also depended on sRNA132 for rapid induction in the absence of phosphate. Competitive growth experiments of the wild-type and ABC transporter operon deletion mutants underscored the importance of both transporters for growth at low phosphate concentrations. Northern blot analyses of four additional members of the sRNA132 regulon verified that all four transcripts depended on sRNA132 for rapid regulation after the onset of phosphate starvation. Importantly, this is the first example for the transient importance of a sRNA for any archaeal and bacterial species. In addition, this study unraveled the first sRNA regulon for haloarchaea.
The caddisfly subfamily Drusinae BANKS comprises roughly 100 species inhabiting mountain ranges in Europe, Asia Minor and the Caucasus. A 3-gene phylogeny of the subfamily previously identified three major clades that were corroborated by larval morphology and feeding ecologies: scraping grazers, omnivorous shredders and filtering carnivores. Larvae of filtering carnivores exhibit unique head capsule complexities, unknown from other caddisfly larvae. Here we assess the species-level relationships within filtering carnivores, hypothesizing that head capsule complexity is derived from simple shapes observed in the other feeding groups. We summarize the current systematics and taxonomy of the group, clarify the systematic position of Cryptothrix nebulicola, and present a larval key to filtering carnivorous Drusinae. We infer relationships of all known filtering carnivorous Drusinae and 34 additional Drusinae species using Bayesian species tree analysis and concatenated Bayesian phylogenetic analysis of 3805bp of sequence data from six gene regions (mtCOI5-P, mtCOI3-P, 16S mrDNA, CADH, WG, 28S nrDNA), morphological cladistics from 308 characters, and a total evidence analysis. All analyses support monophyly of the three feeding ecology groups but fail to fully resolve internal relationships. Within filtering carnivores, variation in head setation and frontoclypeus structure may be associated with progressive niche adaptation, with less complex species recovered at a basal position. We propose that diversification of complex setation and frontoclypeus shape represents a recent evolutionary development, hypothetically enforcing speciation and niche specificity within filtering carnivorous Drusinae.
Autophagy is a highly conserved catabolic process cells use to maintain their homeostasis by degrading misfolded, damaged and excessive proteins, nonfunctional organelles, foreign pathogens and other cellular components. Hence, autophagy can be nonselective, where bulky portions of the cytoplasm are degraded upon stress, or a highly selective process, where preselected cellular components are degraded. To distinguish between different cellular components, autophagy employs selective autophagy receptors, which will link the cargo to the autophagy machinery, thereby sequestering it in the autophagosome for its subsequent degradation in the lysosome. Autophagy receptors undergo post-translational and structural modifications to fulfil their role in autophagy, or upon executing their role, for their own degradation. We highlight the four most prominent protein modifications – phosphorylation, ubiquitination, acetylation and oligomerisation – that are essential for autophagy receptor recruitment, function and turnover. Understanding the regulation of selective autophagy receptors will provide deeper insights into the pathway and open up potential therapeutic avenues.
Autophagy is a highly conserved catabolic process cells use to maintain their homeostasis by degrading misfolded, damaged and excessive proteins, nonfunctional organelles, foreign pathogens and other cellular components. Hence, autophagy can be nonselective, where bulky portions of the cytoplasm are degraded upon stress, or a highly selective process, where preselected cellular components are degraded. To distinguish between different cellular components, autophagy employs selective autophagy receptors, which will link the cargo to the autophagy machinery, thereby sequestering it in the autophagosome for its subsequent degradation in the lysosome. Autophagy receptors undergo post-translational and structural modifications to fulfil their role in autophagy, or upon executing their role, for their own degradation. We highlight the four most prominent protein modifications – phosphorylation, ubiquitination, acetylation and oligomerisation – that are essential for autophagy receptor recruitment, function and turnover. Understanding the regulation of selective autophagy receptors will provide deeper insights into the pathway and open up potential therapeutic avenues.
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information.
Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
Justification: In Mexico, the number of unidentified bodies has been steadily rising for years. By now, more than 50,000 bodies are considered unidentified. Forensic laboratories that could perform comparative molecular genetic investigation are often overburdened and examinations can take months. Therefore, pragmatic approaches that can help to identify more unknown bodies must be sought. The increased use of distinctive physical features might be one, and the high rate of tattooed people in Mexico points towards a great potential of tattoos as a tool for identification. The prerequisite for a comparison of antemortem (missing persons) and postmortem (unknown bodies) data is an objective description of the particularities, e.g., of the tattoos. The aim of this study was to establish an objective classification for tattoo motives, taking into consideration local preferences.
Methods: In the database of the medicolegal services of the Instituto Jaliscience de Ciencias Forenses (IJCF) in Guadalajara, postmortem data of 1000 tattooed bodies from 2019 were evaluated. According to sex and age, the tattooed body localization and the tattoo motives were categorized.
Results: The 1000 tattooed deceased showed tattoos on 2342 body localizations. The motives were grouped and linked to the following 11 keywords (with decreasing frequency): letters/numbers, human, symbol (other), plant, symbol (religious), animal, object, fantasy/demon/comic, tribal/ornament/geometry, other, unrecognizable.
Conclusion: Using the proposed classification, tattoo motives can be described objectively and classified in a practical way. If used for antemortem (missing persons) and postmortem (unknown bodies) documentation, motives can be searched and compared efficiently—helping to identify unknown bodies.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.
As part of the Next Generation EU (NGEU) program, the European Commission has pledged to issue up to EUR 250 billion of the NGEU bonds as green bonds, in order to confirm their commitment to sustainable finance and to support the transition towards a greener Europe. Thereby, the EU is not only entering the green bond market, but also set to become one of the biggest green bond issuers. Consequently, financial market participants are eager to know what to expect from the EU as a new green bond issuer and whether a negative green bond premium, a so-called Greenium, can be expected for the NGEU green bonds. This research paper formulates an expectation in regards to a potential Greenium for the NGEU green bonds, by conducting an interview with 15 sustainable finance experts and analyzing the public green bond market from September 2014 until June 2021, with respect to a potential green bond premium and its underlying drivers. The regression results confirm the existence of a significant Greenium (-0.7 bps) in the public green bond market and that the Greenium increases for supranational issuers with AAA rating, such as the EU. Moreover, the green bond premium is influenced by issuer sector and credit rating, but issue size and modified duration have no significant effect. Overall, the evaluated expert interviews and regression analysis lead to an expected Greenium for the NGEU green bonds of up to -4 bps, with the potential to further increase in the secondary market.
Ferroptosis is an iron-dependent form of cell death, which is triggered by disturbed membrane integrity due to an overproduction of lipid peroxides. Induction of ferroptosis comprises several alterations, i.e. altered iron metabolism, response to oxidative stress, or lipid peroxide production. At the physiological level transcription, translation, and microRNAs add to the appearance and/or activity of building blocks that negatively or positively balance ferroptosis. Ferroptosis contributes to tissue damage in the case of, e.g., brain and heart injury but may be desirable to overcome chemotherapy resistance. For a more complete picture, it is crucial to also consider the cellular microenvironment, which during inflammation and in the tumor context is dominated by hypoxia. This graphical review visualizes basic mechanisms of ferroptosis, categorizes general inducers and inhibitors of ferroptosis, and puts a focus on microRNAs, iron homeostasis, and hypoxia as regulatory components.
Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between multiple neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking the multivariate nature of interactions: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable because of the combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm uses interaction delays reconstructed for directed bivariate interactions to tag potentially spurious edges on the basis of their timing signatures in the context of the surrounding network. Such tagged interactions may then be pruned, which produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation in MATLAB to test the algorithm’s performance on simulated networks as well as networks derived from magnetoencephalographic data. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.
The membrane proximal external region (MPER) of the HIV-1 glycoprotein gp41 is targeted by the broadly neutralizing antibodies 2F5 and 4E10. To date, no immunization regimen in animals or humans has produced HIV-1 neutralizing MPER-specific antibodies. We immunized llamas with gp41-MPER proteoliposomes and selected a MPER-specific single chain antibody (VHH), 2H10, whose epitope overlaps with that of mAb 2F5. Bi-2H10, a bivalent form of 2H10, which displayed an approximately 20-fold increased affinity compared to the monovalent 2H10, neutralized various sensitive and resistant HIV-1 strains, as well as SHIV strains in TZM-bl cells. X-ray and NMR analyses combined with mutagenesis and modeling revealed that 2H10 recognizes its gp41 epitope in a helical conformation. Notably, tryptophan 100 at the tip of the long CDR3 is not required for gp41 interaction but essential for neutralization. Thus bi-2H10 is an anti-MPER antibody generated by immunization that requires hydrophobic CDR3 determinants in addition to epitope recognition for neutralization similar to the mode of neutralization employed by mAbs 2F5 and 4E10.
Wetlands such as bogs, swamps, or freshwater marshes are hotspots of biodiversity. For 5.1 million km2 of inland wetlands, the dynamics of area and water storage, which strongly impact biodiversity and ecosystem services, were simulated using the global hydrological model WaterGAP. For the first time, the impacts of both human water use and man‐made reservoirs (WUR) and future climate change (CC) on wetlands around the globe were quantified. WUR impacts are concentrated in arid/semiarid regions, where WUR decreased mean wetland water storage by more than 5% on 8.2% of the mean wetland area during 1986–2005 (Am), with highest decreases in groundwater depletion area. Using output of three climate models, CC impacts on wetlands were quantified, distinguishing unavoidable impacts [i.e., at 2 °C global warming (GW)] from avoidable impacts (difference between 3 °C and 2 °C impacts). Even unavoidable CC impacts are projected to be much larger than WUR impacts, also in arid/semiarid regions. On most wetland area with reliable estimates, avoidable CC impacts are more than twice as large as unavoidable impacts. In case of 2 °C GW, half of Am is estimated to be unaffected by mean storage changes of more than 5%, but only one third in case of 3 °C GW. Temporal variability of water storage will increase for most wetlands. Wetlands in dry regions will be affected the most, particularly by water storage decreases in the dry season. Different from wealthier countries, low‐income countries will dominantly suffer from a decrease in wetland water storage due to CC.