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Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Archaeological evidence indicates that pig domestication had begun by ∼10,500 y before the present (BP) in the Near East, and mitochondrial DNA (mtDNA) suggests that pigs arrived in Europe alongside farmers ∼8,500 y BP. A few thousand years after the introduction of Near Eastern pigs into Europe, however, their characteristic mtDNA signature disappeared and was replaced by haplotypes associated with European wild boars. This turnover could be accounted for by substantial gene flow from local European wild boars, although it is also possible that European wild boars were domesticated independently without any genetic contribution from the Near East. To test these hypotheses, we obtained mtDNA sequences from 2,099 modern and ancient pig samples and 63 nuclear ancient genomes from Near Eastern and European pigs. Our analyses revealed that European domestic pigs dating from 7,100 to 6,000 y BP possessed both Near Eastern and European nuclear ancestry, while later pigs possessed no more than 4% Near Eastern ancestry, indicating that gene flow from European wild boars resulted in a near-complete disappearance of Near East ancestry. In addition, we demonstrate that a variant at a locus encoding black coat color likely originated in the Near East and persisted in European pigs. Altogether, our results indicate that while pigs were not independently domesticated in Europe, the vast majority of human-mediated selection over the past 5,000 y focused on the genomic fraction derived from the European wild boars, and not on the fraction that was selected by early Neolithic farmers over the first 2,500 y of the domestication process.
This report provides a brief review of the 20th annual meeting of the German Language Branch of the Society of Environmental Toxicology and Chemistry (SETAC GLB) held from September 7th to 10th 2015 at ETH (Swiss Technical University) in Zurich, Switzerland. The event was chaired by Inge Werner, Director of the Swiss Centre for Applied Ecotoxicology (Ecotox Centre) Eawag-EPFL, and organized by a team from Ecotox Centre, Eawag, Federal Office of the Environment, Federal Office of Agriculture, and Mesocosm GmbH (Germany). Over 200 delegates from academia, public agencies and private industry of Germany, Switzerland and Austria attended and discussed the current state of science and its application presented in 75 talks and 83 posters. In addition, three invited keynote speakers provided new insights into scientific knowledge ‘brokering’, and—as it was the International Year of Soil—the important role of healthy soil ecosystems. Awards were presented to young scientists for best oral and poster presentations, and for best 2014 master and doctoral theses. Program and abstracts of the meeting (mostly in German) are provided as Additional file 1.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p–Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
Purpose: To stratify differences in visual semantic and quantitative imaging features in intensive care patients with nonspecific mastoid effusions versus patients with acute mastoiditis (AM) requiring surgical treatment. Methods: We included 48 patients (male, 28; female, 20; mean age, 59.5 ± 18.1 years) with mastoid opacification (AM, n = 24; control, n = 24) who underwent clinically indicated cerebral CT between 12/2007 and 07/2018 in this retrospective study. Semantic features described the extend and asymmetry of mastoid and middle-ear cavity opacification and complications like erosive changes. Minimum, maximum and mean Hounsfield unit (HU) values were obtained as quantitative features. We analyzed the features employing univariate testing. Results: Compared to intensive care patients, AM patients revealed asymmetric mastoid or middle-ear cavity opacification (likelihood-ratio (LR) < 0.001). Applying a dedicated threshold of the extent of opacification, AM patients reached significance levels of LR = 0.042 and 0.002 for mastoid and middle-ear cavity opacification. AM cases showed higher maximum and mean HU values (p = 0.009, p = 0.024). Conclusions: We revealed that the extent and asymmetry of mastoid and middle-ear cavity opacification differs significantly between AM patients and intensive care patients. Multicenter research is needed to expand our cohort and possibly pave the way to build a non-invasive predictive model for AM in the future.
Background: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans. Methods: One hundred patients (median age, 69 years; range, 19–94 years) who received CT scans of the thoracolumbar spine and blood-testing for hemoglobin and hematocrit levels ± 24 h between 08/2018 and 11/2019 were retrospectively included. Intraaortic blood was segmented using a spherical volume of interest of 1 cm diameter with consecutive radiomic analysis applying PyRadiomics software. Feature selection was performed applying analysis of correlation and collinearity. The final feature set was obtained to differentiate moderate-to-severe anemia. Random forest machine learning was applied and predictive performance was assessed. A decision-tree was obtained to propose a cut-off value of CT Hounsfield units (HU). Results: High correlation with hemoglobin and hematocrit levels was shown for first-order radiomic features (p < 0.001 to p = 0.032). The top 3 features showed high correlation to hemoglobin values (p) and minimal collinearity (r) to the top ranked feature Median (p < 0.001), Energy (p = 0.002, r = 0.387), Minimum (p = 0.032, r = 0.437). Median (p < 0.001) and Minimum (p = 0.003) differed in moderate-to-severe anemia compared to non-anemic state. Median yielded superiority to the combination of Median and Minimum (p(AUC) = 0.015, p(precision) = 0.017, p(accuracy) = 0.612) in the predictive performance employing random forest analysis. A Median HU value ≤ 36.5 indicated moderate-to-severe anemia (accuracy = 0.90, precision = 0.80). Conclusions: First-order radiomic features correlate with hemoglobin levels and may be feasible for the prediction of moderate-to-severe anemia. High dimensional radiomic features did not aid augmenting the data in our exemplary use case of intraluminal blood component assessment.
Purpose: To identify transjugular intrahepatic portosystemic shunt (TIPS) thrombosis in abdominal CT scans applying quantitative image analysis.
Materials and methods: We retrospectively screened 184 patients to include 20 patients (male, 8; female, 12; mean age, 60.7 ± 8.87 years) with (case, n = 10) and without (control, n = 10) in-TIPS thrombosis who underwent clinically indicated contrast-enhanced and unenhanced abdominal CT followed by conventional TIPS-angiography between 08/2014 and 06/2020. First, images were scored visually. Second, region of interest (ROI) based quantitative measurements of CT attenuation were performed in the inferior vena cava (IVC), portal vein and in four TIPS locations. Minimum, maximum and average Hounsfield unit (HU) values were used as absolute and relative quantitative features. We analyzed the features with univariate testing.
Results: Subjective scores identified in-TIPS thrombosis in contrast-enhanced scans with an accuracy of 0.667 – 0.833. Patients with in-TIPS thrombosis had significantly lower average (p < 0.001), minimum (p < 0.001) and maximum HU (p = 0.043) in contrast-enhanced images. The in-TIPS / IVC ratio in contrast-enhanced images was significantly lower in patients with in-TIPS thrombosis (p < 0.001). No significant differences were found for unenhanced images. Analyzing the visually most suspicious ROI with consecutive calculation of its ratio to the IVC, all patients with a ratio < 1 suffered from in-TIPS thrombosis (p < 0.001, sensitivity and specificity = 100%).
Conclusion: Quantitative analysis of abdominal CT scans facilitates the stratification of in-TIPS thrombosis. In contrast-enhanced scans, an in-TIPS / IVC ratio < 1 could non-invasively stratify all patients with in-TIPS thrombosis.
Structured RNA regions are important gene control elements in prokaryotes and eukaryotes. Here, we show that the mRNA of a cyanobacterial heat shock gene contains a built-in thermosensor critical for photosynthetic activity under stress conditions. The exceptionally short 5´-untranslated region is comprised of a single hairpin with an internal asymmetric loop. It inhibits translation of the Synechocystis hsp17 transcript at normal growth conditions, permits translation initiation under stress conditions and shuts down Hsp17 production in the recovery phase. Point mutations that stabilized or destabilized the RNA structure deregulated reporter gene expression in vivo and ribosome binding in vitro. Introduction of such point mutations into the Synechocystis genome produced severe phenotypic defects. Reversible formation of the open and closed structure was beneficial for viability, integrity of the photosystem and oxygen evolution. Continuous production of Hsp17 was detrimental when the stress declined indicating that shutting-off heat shock protein production is an important, previously unrecognized function of RNA thermometers. We discovered a simple biosensor that strictly adjusts the cellular level of a molecular chaperone to the physiological need.
NeuLAND (New Large-Area Neutron Detector) is the next-generation neutron detector for the R3B (Reactions with Relativistic Radioactive Beams) experiment at FAIR (Facility for Antiproton and Ion Research). NeuLAND detects neutrons with energies from 100 to 1000 MeV, featuring a high detection efficiency, a high spatial and time resolution, and a large multi-neutron reconstruction efficiency. This is achieved by a highly granular design of organic scintillators: 3000 individual submodules with a size of 5 × 5 × 250 cm3 are arranged in 30 double planes with 100 submodules each, providing an active area of 250 × 250 cm2 and a total depth of 3 m. The spatial resolution due to the granularity together with a time resolution of 150 ps ensures high-resolution capabilities. In conjunction with calorimetric properties, a multi-neutron reconstruction efficiency of 50% to 70% for four-neutron events will be achieved, depending on both the emission scenario and the boundary conditions allowed for the reconstruction method. We present in this paper the final design of the detector as well as results from test measurements and simulations on which this design is based.
Despite multidisciplinary local and systemic therapeutic approaches, the prognosis for most patients with brain metastases is still dismal. The role of adaptive and innate anti-tumor response including the Human Leukocyte Antigen (HLA) machinery of antigen presentation is still unclear. We present data on the HLA class II-chaperone molecule CD74 in brain metastases and its impact on the HLA peptidome complexity.
We analyzed CD74 and HLA class II expression on tumor cells in a subset of 236 human brain metastases, primary tumors and peripheral metastases of different entities in association with clinical data including overall survival. Additionally, we assessed whole DNA methylome profiles including CD74 promoter methylation and differential methylation in 21 brain metastases. We analyzed the effects of a siRNA mediated CD74 knockdown on HLA-expression and HLA peptidome composition in a brain metastatic melanoma cell line.
We observed that CD74 expression on tumor cells is a strong positive prognostic marker in brain metastasis patients and positively associated with tumor-infiltrating T-lymphocytes (TILs). Whole DNA methylome analysis suggested that CD74 tumor cell expression might be regulated epigenetically via CD74 promoter methylation. CD74high and TILhigh tumors displayed a differential DNA methylation pattern with highest enrichment scores for antigen processing and presentation. Furthermore, CD74 knockdown in vitro lead to a reduction of HLA class II peptidome complexity, while HLA class I peptidome remained unaffected.
In summary, our results demonstrate that a functional HLA class II processing machinery in brain metastatic tumor cells, reflected by a high expression of CD74 and a complex tumor cell HLA peptidome, seems to be crucial for better patient prognosis.
Predicting adult Attention Deficit Hyperactivity Disorder (ADHD) using vocal acoustic features
(2021)
Background: It is a key concern in psychiatric research to investigate objective measures to support and ultimately improve diagnostic processes. Current gold standard diagnostic procedures for attention deficit hyperactivity disorder (ADHD) are mainly subjective and prone to bias. Objective measures such as neuropsychological measures and EEG markers show limited specificity. Recent studies point to alterations of voice and speech production to reflect psychiatric symptoms also related to ADHD. However, studies investigating voice in large clinical samples allowing for individual-level prediction of ADHD are lacking. The aim of this study was to explore a role of prosodic voice measures as objective marker of ADHD.
Methods: 1005 recordings were analyzed from 387 ADHD patients, 204 healthy controls, and 100 clinical (psychiatric) controls. All participants (age range 18-59 years, mean age 34.4) underwent an extensive diagnostic examination according to gold standard methods and provided speech samples (3 min in total) including free and given speech. Paralinguistic features were calculated, and random forest based classifications were performed using a 10-fold cross-validation with 100 repetitions controlling for age, sex, and education. Association of voice features and ADHD-symptom severity assessed in the clinical interview were analyzed using random forest regressions.
Results and Conclusion ADHD was predicted with AUC = 0.76. The analysis of a non-comorbid sample of ADHD resulted in similar classification performance. Paralinguistic features were associated with ADHD-symptom severity as indicated by random forest regression. In female participants, particularly with age < 32 years, paralinguistic features showed the highest classification performance (AUC = 0.86).
Paralinguistic features based on derivatives of loudness and fundamental frequency seem to be promising candidates for further research into vocal acoustic biomarkers of ADHD. Given the relatively good performance in female participants independent of comorbidity, vocal measures may evolve as a clinically supportive option in the complex diagnostic process in this patient group.
Competing Interest Statement: EA participated and received payments in the national advisory board ADHD of Shire/Takeda. JL is co-founder and CTO of PeakProfiling GmbH. He created audio-features used in this study, that are intellectual property of PeakProfiling GmbH. FH received payments by PeakProfiling GmbH.
Clinical Trial: NCT01104623
Primary determinants of communities in deadwood vary among taxa but are regionally consistent
(2020)
The evolutionary split between gymnosperms and angiosperms has far‐reaching implications for the current communities colonizing trees. The inherent characteristics of dead wood include its role as a spatially scattered habitat of plant tissue, transient in time. Thus, local assemblages in deadwood forming a food web in a necrobiome should be affected not only by dispersal ability but also by host tree identity, the decay stage and local abiotic conditions. However, experiments simultaneously manipulating these potential community drivers in deadwood are lacking. To disentangle the importance of spatial distance and microclimate, as well as host identity and decay stage as drivers of local assemblages, we conducted two consecutive experiments, a 2‐tree species and 6‐tree species experiment with 80 and 72 tree logs, respectively, located in canopy openings and under closed canopies of a montane and a lowland forest. We sampled saproxylic beetles, spiders, fungi and bacterial assemblages from logs. Variation partitioning for community metrics based on a unified framework of Hill numbers showed consistent results for both studies: host identity was most important for sporocarp‐detected fungal assemblages, decay stage and host tree for DNA‐detected fungal assemblages, microclimate and decay stage for beetles and spiders and decay stage for bacteria. Spatial distance was of minor importance for most taxa but showed the strongest effects for arthropods. The contrasting patterns among the taxa highlight the need for multi‐taxon analyses in identifying the importance of abiotic and biotic drivers of community composition. Moreover, the consistent finding of microclimate as the primary driver for saproxylic beetles compared to host identity shows, for the first time that existing evolutionary host adaptions can be outcompeted by local climate conditions in deadwood.
Pollen-based climate reconstructions were performed on two high-resolution pollen marines cores from the Alboran and Aegean Seas in order to unravel the climatic variability in the coastal settings of the Mediterranean region between 15 000 and 4000 years BP (the Lateglacial, and early to mid-Holocene). The quantitative climate reconstructions for the Alboran and Aegean Sea records focus mainly on the reconstruction of the seasonality changes (temperatures and precipitation), a crucial parameter in the Mediterranean region. This study is based on a multi-method approach comprising 3 methods: the Modern Analogues Technique (MAT), the recent Non-Metric Multidimensional Scaling/Generalized Additive Model method (NMDS/GAM) and Partial Least Squares regression (PLS). The climate signal inferred from this comparative approach confirms that cold and dry conditions prevailed in the Mediterranean region during the Oldest and Younger Dryas periods, while temperate conditions prevailed during the Bølling/Allerød and the Holocene. Our records suggest a West/East gradient of decreasing precipitation across the Mediterranean region during the cooler Late-glacial and early Holocene periods, similar to present-day conditions. Winter precipitation was highest during warm intervals and lowest during cooling phases. Several short-lived cool intervals (i.e. Older Dryas, another oscillation after this one (GI-1c2), Gerzensee/Preboreal Oscillations, 8.2 ka event, Bond events) connected to the North Atlantic climate system are documented in the Alboran and Aegean Sea records indicating that the climate oscillations associated with the successive steps of the deglaciation in the North Atlantic area occurred in both the western and eastern Mediterranean regions. This observation confirms the presence of strong climatic linkages between the North Atlantic and Mediterranean regions.
Pollen-based climate reconstructions were performed on two high-resolution pollen – marines cores from the Alboran and Aegean Seas in order to unravel the climatic variability in the coastal settings of the Mediterranean region between 15 000 and 4000 cal yrs BP (the Lateglacial, and early to mid-Holocene). The quantitative climate reconstructions for the Alboran and Aegean Sea records focus mainly on the reconstruction of the seasonality changes (temperatures and precipitation), a crucial parameter in the Mediterranean region. This study is based on a multi-method approach comprising 3 methods: the Modern Analogues Technique (MAT), the recent Non-Metric Multidimensional Scaling/Generalized Additive Model method (NMDS/GAM) and Partial Least Squares regression (PLS). The climate signal inferred from this comparative approach confirms that cold and dry conditions prevailed in the Mediterranean region during the Heinrich event 1 and Younger Dryas periods, while temperate conditions prevailed during the Bølling/Allerød and the Holocene. Our records suggest a West/East gradient of decreasing precipitation across the Mediterranean region during the cooler Late-glacial and early Holocene periods, similar to present-day conditions. Winter precipitation was highest during warm intervals and lowest during cooling phases. Several short-lived cool intervals (i.e., Older Dryas, another oscillation after this one (GI-1c2), Gerzensee/Preboreal Oscillations, 8.2 ka event, Bond events) connected to the North Atlantic climate system are documented in the Alboran and Aegean Sea records indicating that the climate oscillations associated with the successive steps of the deglaciation in the North Atlantic area occurred in both the western and eastern Mediterranean regions. This observation confirms the presence of strong climatic linkages between the North Atlantic and Mediterranean regions.
In der vorliegenden Studie wird die Gehölzentwicklung eines Eichen-Hainbuchenwald-Gebietes bei München während der letzten zwei Jahrzehnte untersucht. Eine Vorhersage der künftigen Gehölzartenzusammensetzung kann aus der Entwicklung der Verjüngung abgeleitet werden. Für die Zukunft wird ein Wechsel in der Baumartenzusammensetzung prognostiziert. So wird insbesondere der Berg-Ahorn an Bedeutung gewinnen, als Nebenbaumarten werden Esche, Ulme und Hainbuche vorhanden sein. Die für das Galio-Carpinetum charakteristische Stiel-Eiche kann sich nicht mehr erfolgreich verjüngen. Diese Arbeit gibt für den Münchener Großraum Hinweise, dass das Galio-Carpinetum seine Verbreitung der Nieder- bzw. Mittelwaldwirtschaft verdankt, also nicht in erster Linie Ausdruck der abiotischen Umweltbedingungen im Sinne des PNV-Konzepts ist. Eine syntaxonomische Neubeurteilung (insbesondere zur Abgrenzung vom Adoxo-Aceretum) dieser Pflanzengesellschaft scheint notwendig zu sein.
The E-pathway of transmembrane proton transfer has been demonstrated previously to be essential for catalysis by the diheme-containing quinol:fumarate reductase (QFR) of Wolinella succinogenes. Two constituents of this pathway, Glu-C180 and heme b(D) ring C (b(D)-C-) propionate, have been validated experimentally. Here, we identify further constituents of the E-pathway by analysis of molecular dynamics simulations. The redox state of heme groups has a crucial effect on the connectivity patterns of mobile internal water molecules that can transiently support proton transfer from the b(D)-C-propionate to Glu-C180. The short H-bonding paths formed in the reduced states can lead to high proton conduction rates and thus provide a plausible explanation for the required opening of the E-pathway in reduced QFR. We found evidence that the b(D)-C-propionate group is the previously postulated branching point connecting proton transfer to the E-pathway from the quinol-oxidation site via interactions with the heme b(D) ligand His-C44. An essential functional role of His-C44 is supported experimentally by site-directed mutagenesis resulting in its replacement with Glu. Although the H44E variant enzyme retains both heme groups, it is unable to catalyze quinol oxidation. All results obtained are relevant to the QFR enzymes from the human pathogens Campylobacter jejuni and Helicobacter pylori.
The majority of bacterial membrane-bound NiFe-hydrogenases and formate dehydrogenases have homologous membrane-integral cytochrome b subunits. The prototypic NiFe-hydrogenase of Wolinella succinogenes (HydABC complex) catalyzes H2 oxidation by menaquinone during anaerobic respiration and contains a membrane-integral cytochrome b subunit (HydC) that carries the menaquinone reduction site. Using the crystal structure of the homologous FdnI subunit of Escherichia coli formate dehydrogenase-N as a model, the HydC protein was modified to examine residues thought to be involved in menaquinone binding. Variant HydABC complexes were produced in W. succinogenes, and several conserved HydC residues were identified that are essential for growth with H2 as electron donor and for quinone reduction by H2. Modification of HydC with a C-terminal Strep-tag II enabled one-step purification of the HydABC complex by Strep-Tactin affinity chromatography. The tagged HydC, separated from HydAB by isoelectric focusing, was shown to contain 1.9 mol of heme b/mol of HydC demonstrating that HydC ligates both heme b groups. The four histidine residues predicted as axial heme b ligands were individually replaced by alanine in Strep-tagged HydC. Replacement of either histidine ligand of the heme b group proximal to HydAB led to HydABC preparations that contained only one heme b group. This remaining heme b could be completely reduced by quinone supporting the view that the menaquinone reduction site is located near the distal heme b group. The results indicate that both heme b groups are involved in electron transport and that the architecture of the menaquinone reduction site near the cytoplasmic side of the membrane is similar to that proposed for E. coli FdnI.
An experiment addressing electron capture (EC) decay of hydrogen-like 142Pm60+ions has been conducted at the experimental storage ring (ESR) at GSI. The decay appears to be purely exponential and no modulations were observed. Decay times for about 9000 individual EC decays have been measured by applying the single-ion decay spectroscopy method. Both visually and automatically analysed data can be described by a single exponential decay with decay constants of 0.0126(7)s−1 for automatic analysis and 0.0141(7)s−1 for manual analysis. If a modulation superimposed on the exponential decay curve is assumed, the best fit gives a modulation amplitude of merely 0.019(15), which is compatible with zero and by 4.9 standard deviations smaller than in the original observation which had an amplitude of 0.23(4).
Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.
We present first data on sub-threshold production of Ks0 mesons and Λ hyperons in Au+Au collisions at sNN=2.4 GeV. We observe an universal 〈Apart〉 scaling of hadrons containing strangeness, independent of their corresponding production thresholds. Comparing the yields, their 〈Apart〉 scaling, and the shapes of the rapidity and the pt spectra to state-of-the-art transport model (UrQMD, HSD, IQMD) predictions, we find that none of them can simultaneously describe these observables with reasonable χ2 values.
No association between Parkinson disease and autoantibodies against NMDA-type glutamate receptors
(2019)
Background: IgG-class autoantibodies to N-Methyl-D-Aspartate (NMDA)-type glutamate receptors define a novel entity of autoimmune encephalitis. Studies examining the prevalence of NMDA IgA/IgM antibodies in patients with Parkinson disease with/without dementia produced conflicting results. We measured NMDA antibodies in a large, well phenotyped sample of Parkinson patients without and with cognitive impairment (n = 296) and controls (n = 295) free of neuropsychiatric disease. Detailed phenotyping and large numbers allowed statistically meaningful correlation of antibody status with diagnostic subgroups as well as quantitative indicators of disease severity and cognitive impairment.
Methods: NMDA antibodies were analysed in the serum of patients and controls using well established validated assays. We used anti-NMDA antibody positivity as the main independent variable and correlated it with disease status and phenotypic characteristics.
Results: The frequency of NMDA IgA/IgM antibodies was lower in Parkinson patients (13%) than in controls (22%) and higher than in previous studies in both groups. NMDA IgA/IgM antibodies were neither significantly associated with diagnostic subclasses of Parkinson disease according to cognitive impairment, nor with quantitative indicators of disease severity and cognitive impairment. A positive NMDA antibody status was positively correlated with age in controls but not in Parkinson patients.
Conclusion: It is unlikely albeit not impossible that NMDA antibodies play a significant role in the pathogenesis or progression of Parkinson disease e.g. to Parkinson disease with dementia, while NMDA IgG antibodies define a separate disease of its own.
Background Anti-angiogenic treatment is believed to have at least cystostatic effects in highly vascularized tumours like pancreatic cancer. In this study, the treatment effects of the angiogenesis inhibitor Cilengitide and gemcitabine were compared with gemcitabine alone in patients with advanced unresectable pancreatic cancer. Methods A multi-national, open-label, controlled, randomized, parallel-group, phase II pilot study was conducted in 20 centers in 7 countries. Cilengitide was administered at 600 mg/m2 twice weekly for 4 weeks per cycle and gemcitabine at 1000 mg/m2 for 3 weeks followed by a week of rest per cycle. The planned treatment period was 6 four-week cycles. The primary endpoint of the study was overall survival and the secondary endpoints were progression-free survival (PFS), response rate, quality of life (QoL), effects on biological markers of disease (CA 19.9) and angiogenesis (vascular endothelial growth factor and basic fibroblast growth factor), and safety. An ancillary study investigated the pharmacokinetics of both drugs in a subset of patients. Results Eighty-nine patients were randomized. The median overall survival was 6.7 months for Cilengitide and gemcitabine and 7.7 months for gemcitabine alone. The median PFS times were 3.6 months and 3.8 months, respectively. The overall response rates were 17% and 14%, and the tumor growth control rates were 54% and 56%, respectively. Changes in the levels of CA 19.9 went in line with the clinical course of the disease, but no apparent relationships were seen with the biological markers of angiogenesis. QoL and safety evaluations were comparable between treatment groups. Pharmacokinetic studies showed no influence of gemcitabine on the pharmacokinetic parameters of Cilengitide and vice versa. Conclusion There were no clinically important differences observed regarding efficacy, safety and QoL between the groups. The observations lay in the range of other clinical studies in this setting. The combination regimen was well tolerated with no adverse effects on the safety, tolerability and pharmacokinetics of either agent.
Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efcient diagnostic algorithms.
Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age,
66 ± 6.6 years) were included in the study. Patients sufered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open–source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms.
Results: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and
ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of 0.93 ± 0.04, 0.91 ± 0.06, and 0.92 ± 0.05, respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02–0.06 for ERG and PIN-4.
Conclusions: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classifcation. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classifcation methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.
Radiative transition of an excited baryon to a nucleon with emission of a virtual massive photon converting to dielectron pair (Dalitz decays) provides important information about baryon-photon coupling at low q2 in timelike region. A prominent enhancement in the respective electromagnetic transition Form Factors (etFF) at q2 near vector mesons ρ/ω poles has been predicted by various calculations reflecting strong baryon-vector meson couplings. The understanding of these couplings is also of primary importance for the interpretation of the emissivity of QCD matter studied in heavy ion collisions via dilepton emission. Dedicated measurements of baryon Dalitz decays in proton-proton and pion-proton scattering with HADES detector at GSI/FAIR are presented and discussed. The relevance of these studies for the interpretation of results obtained from heavy ion reactions is elucidated on the example of the HADES results.
In March 2019 the HADES experiment recorded 14 billion Ag+Ag collisions at √sNN = 2.55 GeV as a part of the FAIR phase-0 physics program. In this contribution, we present and investigate our capabilities to reconstruct and analyze weakly decaying strange hadrons and hypernuclei emerging from these collisions. The focus is put on measuring the mean lifetimes of these particles.