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The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
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.
During the measurement campaign FROST 2 (FReezing Of duST 2), the Leipzig Aerosol Cloud Interaction Simulator (LACIS) was used to investigate the influence of various surface modifications on the ice nucleating ability of Arizona Test Dust (ATD) particles in the immersion freezing mode. The dust particles were exposed to sulfuric acid vapor, to water vapor with and without the addition of ammonia gas, and heat using a thermodenuder operating at 250 °C. Size selected, quasi monodisperse particles with a mobility diameter of 300 nm were fed into LACIS and droplets grew on these particles such that each droplet contained a single particle. Temperature dependent frozen fractions of these droplets were determined in a temperature range between −40 °C ≤T≤−28 °C. The pure ATD particles nucleated ice over a broad temperature range with their freezing behavior being separated into two freezing branches characterized through different slopes in the frozen fraction vs. temperature curves. Coating the ATD particles with sulfuric acid resulted in the particles' IN potential significantly decreasing in the first freezing branch (T>−35 °C) and a slight increase in the second branch (T≤−35 °C). The addition of water vapor after the sulfuric acid coating caused the disappearance of the first freezing branch and a strong reduction of the IN ability in the second freezing branch. The presence of ammonia gas during water vapor exposure had a negligible effect on the particles' IN ability compared to the effect of water vapor. Heating in the thermodenuder led to a decreased IN ability of the sulfuric acid coated particles for both branches but the additional heat did not or only slightly change the IN ability of the pure ATD and the water vapor exposed sulfuric acid coated particles. In other words, the combination of both sulfuric acid and water vapor being present is a main cause for the ice active surface features of the ATD particles being destroyed. A possible explanation could be the chemical transformation of ice active metal silicates to metal sulfates. The strongly enhanced reaction between sulfuric acid and dust in the presence of water vapor and the resulting significant reductions in IN potential are of importance for atmospheric ice cloud formation. Our findings suggest that the IN concentration can decrease by up to one order of magnitude for the conditions investigated.
During the measurement campaign FROST 2 (FReezing Of duST 2), the Leipzig Aerosol Cloud Interaction Simulator (LACIS) was used to investigate the influences of various surface modifications on the immersion freezing behavior of Arizona Test Dust (ATD) particles. The dust particles were exposed to sulfuric acid vapor, to water vapor with and without the addition of ammonia gas, and heat using a thermodenuder operating at 250 °C. Size selected, quasi monodisperse particles with a mobility diameter of 300 nm were fed into LACIS and droplets grew on these particles such that each droplet contained a single particle. Temperature dependent frozen fractions of these droplets were determined in a temperature range between −40 °C ≤ T ≤ −28 °C. The pure ATD particles nucleated ice over a~broad temperature range with their freezing behavior being separated into two freezing branches characterized through different slopes in the frozen fraction vs. temperature curves. Coating the ATD particles with sulfuric acid resulted in the particles' IN potential significantly decreasing in the first freezing branch (T > −35 °C) and a slight increase in the second branch (T≤ −35 °C). The addition of water vapor after the sulfuric acid coating caused the disappearance of the first freezing branch and a strong reduction of the IN ability in the second freezing branch. The presence of ammonia gas during water vapor exposure had a negligible effect on the particles' IN ability compared to the effect of water vapor. Heating in the thermodenuder led to a decreased IN ability of the sulfuric acid coated particles for both branches but the additional heat did not or only slightly change the IN ability of the pure ATD and the water vapor exposed sulfuric acid coated particles. In other words, the combination of both sulfuric acid and water vapor being present is a main cause for the ice active surface features of the ATD particles being destroyed. A possible explanation could be the chemical transformation of ice active metal silicates to metal sulfates. From an atmospheric point of view, and here specifically the influences of atmospheric aging on the IN ability of dust particles, the strongly enhanced reaction between sulfuric acid and dust in the presence of water vapor, and the resulting significant reductions in IN potential, are certainly very interesting.
HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
(2021)
Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10−3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
Background: Predicted increases in suicide were not generally observed in the early months of the COVID-19 pandemic. However, the picture may be changing and patterns might vary across demographic groups. We aimed to provide a timely, granular picture of the pandemic's impact on suicides globally.
Methods: We identified suicide data from official public-sector sources for countries/areas-within-countries, searching websites and academic literature and contacting data custodians and authors as necessary. We sent our first data request on 22nd June 2021 and stopped collecting data on 31st October 2021. We used interrupted time series (ITS) analyses to model the association between the pandemic's emergence and total suicides and suicides by sex-, age- and sex-by-age in each country/area-within-country. We compared the observed and expected numbers of suicides in the pandemic's first nine and first 10-15 months and used meta-regression to explore sources of variation.
Findings: We sourced data from 33 countries (24 high-income, six upper-middle-income, three lower-middle-income; 25 with whole-country data, 12 with data for area(s)-within-the-country, four with both). There was no evidence of greater-than-expected numbers of suicides in the majority of countries/areas-within-countries in any analysis; more commonly, there was evidence of lower-than-expected numbers. Certain sex, age and sex-by-age groups stood out as potentially concerning, but these were not consistent across countries/areas-within-countries. In the meta-regression, different patterns were not explained by countries’ COVID-19 mortality rate, stringency of public health response, economic support level, or presence of a national suicide prevention strategy. Nor were they explained by countries’ income level, although the meta-regression only included data from high-income and upper-middle-income countries, and there were suggestions from the ITS analyses that lower-middle-income countries fared less well.
Interpretation: Although there are some countries/areas-within-countries where overall suicide numbers and numbers for certain sex- and age-based groups are greater-than-expected, these countries/areas-within-countries are in the minority. Any upward movement in suicide numbers in any place or group is concerning, and we need to remain alert to and respond to changes as the pandemic and its mental health and economic consequences continue.
Low risk anomalies?
(2016)
This paper shows theoretically and empirically that beta- and volatility-based low risk anomalies are driven by return skewness. The empirical patterns concisely match the predictions of our model which generates skewness of stock returns via default risk. With increasing downside risk, the standard capital asset pricing model increasingly overestimates required equity returns relative to firms' true (skew-adjusted) market risk. Empirically, the profitability of betting against beta/volatility increases with firms' downside risk. Our results suggest that the returns to betting against beta/volatility do not necessarily pose asset pricing puzzles but rather that such strategies collect premia that compensate for skew risk.
Ophthalmo-acromelic syndrome (OAS), also known as Waardenburg Anophthalmia syndrome, is defined by the combination of eye malformations, most commonly bilateral anophthalmia, with post-axial oligosyndactyly. Homozygosity mapping and subsequent targeted mutation analysis of a locus on 14q24.2 identified homozygous mutations in SMOC1 (SPARC-related modular calcium binding 1) in eight unrelated families. Four of these mutations are nonsense, two frame-shift, and two missense. The missense mutations are both in the second Thyroglobulin Type-1 (Tg1) domain of the protein. The orthologous gene in the mouse, Smoc1, shows site- and stage-specific expression during eye, limb, craniofacial, and somite development. We also report a targeted pre-conditional gene-trap mutation of Smoc1 (Smoc1tm1a) that reduces mRNA to ~10% of wild-type levels. This gene-trap results in highly penetrant hindlimb post-axial oligosyndactyly in homozygous mutant animals (Smoc1tm1a/tm1a). Eye malformations, most commonly coloboma, and cleft palate occur in a significant proportion of Smoc1tm1a/tm1a embryos and pups. Thus partial loss of Smoc-1 results in a convincing phenocopy of the human disease. SMOC-1 is one of the two mammalian paralogs of Drosophila Pentagone, an inhibitor of decapentaplegic. The orthologous gene in Xenopus laevis, Smoc-1, also functions as a Bone Morphogenic Protein (BMP) antagonist in early embryogenesis. Loss of BMP antagonism during mammalian development provides a plausible explanation for both the limb and eye phenotype in humans and mice.
In situ single particle analysis of ice particle residuals (IPRs) and out-of-cloud aerosol particles was conducted by means of laser ablation mass spectrometry during the intensive INUIT-JFJ/CLACE campaign at the high alpine research station Jungfraujoch (3580 m a.s.l.) in January–February 2013. During the 4-week campaign more than 70 000 out-of-cloud aerosol particles and 595 IPRs were analyzed covering a particle size diameter range from 100 nm to 3 µm. The IPRs were sampled during 273 h while the station was covered by mixed-phase clouds at ambient temperatures between −27 and −6 °C. The identification of particle types is based on laboratory studies of different types of biological, mineral and anthropogenic aerosol particles. The outcome of these laboratory studies was characteristic marker peaks for each investigated particle type. These marker peaks were applied to the field data. In the sampled IPRs we identified a larger number fraction of primary aerosol particles, like soil dust (13 ± 5 %) and minerals (11 ± 5 %), in comparison to out-of-cloud aerosol particles (2.4 ± 0.4 and 0.4 ± 0.1 %, respectively). Additionally, anthropogenic aerosol particles, such as particles from industrial emissions and lead-containing particles, were found to be more abundant in the IPRs than in the out-of-cloud aerosol. In the out-of-cloud aerosol we identified a large fraction of aged particles (31 ± 5 %), including organic material and secondary inorganics, whereas this particle type was much less abundant (2.7 ± 1.3 %) in the IPRs. In a selected subset of the data where a direct comparison between out-of-cloud aerosol particles and IPRs in air masses with similar origin was possible, a pronounced enhancement of biological particles was found in the IPRs.
In-situ single particle analysis of ice particle residuals (IPR) and out-of-cloud aerosol particles was conducted by means of laser ablation mass spectrometry during the intensive INUIT-JFJ/CLACE campaign at the high alpine research station Jungfraujoch (3580 m a.s.l.) in January/February 2013. During the four week campaign more than 70000 out-of-cloud aerosol particles and 595 IPR were analyzed covering a particle size diameter range from 100 nm to 3 μm. The IPR were sampled during 273 hours while the station was covered by mixed-phase clouds at ambient temperatures between -27 °C and -6 °C. The identification of particle types is based on laboratory studies of different types of biological, mineral and anthropogenic aerosol particles. As outcome instrument specific marker peaks for the different investigated particle types were obtained and applied to the field data. The results show that the sampled IPR contain a larger relative amount of natural, primary aerosol, like soil dust (13 %) and minerals (11 %), in comparison to out-of-cloud aerosol particles (2 % and <1 %, respectively). Additionally, anthropogenic aerosol particles, like particles from industrial emissions and lead-containing particles, were found to be more abundant in the IPR than in the out-of-cloud aerosol. The out of-cloud aerosol contained a large fraction of aged particles (30 %, including organic material and secondary inorganics), whereas this particle type was much less abundant (3 %) in the IPR. In a selected subset of the data where a direct comparison between out-of-cloud aerosol particles and IPR in air masses with similar origin was possible, a pronounced enhancement of biological particles was found in the IPR.
Locating a vocalizing animal can be useful in many fields of bioacoustics and behavioral research, and is often done in the wild, covering large areas. In zoos, however, the application of this method becomes particularly difficult, because, on the one hand, the animals are in a relatively small area and, on the other hand, reverberant environments and background noise complicate the analysis. Nevertheless, by localizing and analyzing animal sounds, valuable information on physiological state, sex, subspecies, reproductive state, social status, and animal welfare can be gathered. Therefore, we developed a sound localization software that is able to estimate the position of a vocalizing animal precisely, making it possible to assign the vocalization to the corresponding individual, even under difficult conditions. In this study, the accuracy and reliability of the software is tested under various conditions. Different vocalizations were played back through a loudspeaker and recorded with several microphones to verify the accuracy. In addition, tests were carried out under real conditions using the example of the giant otter enclosure at Dortmund Zoo, Germany. The results show that the software can estimate the correct position of a sound source with a high accuracy (median of the deviation 0.234 m). Consequently, this software could make an important contribution to basic research via position determination and the associated differentiation of individuals, and could be relevant in a long-term application for monitoring animal welfare in zoos.
The 16O ( gamma ,p0) reaction has been studied with linearly polarized bremsstrahlung photons in and below the giant E1 resonance. The parity of the absorbed radiation was determined from the observed azimuthal asymmetry of the emitted protons. Combined with unpolarized measurements the polarized results determine the proton decay amplitudes of the M1 resonance at Ex=16.2 MeV in 16O. The shape of the unpolarized 16O ( gamma ,p3) angular distribution in the giant E1 resonance was derived from the measured analyzing power. NUCLEAR REACTIONS 16O( gamma ,p), E=15-25 MeV; measured analyzing power theta =90° linearly polarized bremsstrahlung; 16O dipole levels deduced pi ; 16.2 MeV 1+ resonance deduced p0 decay amplitudes; 16O GEDR deduced p3 angular distribution.
The parities of eleven J=1 levels in 208Pb were determined by nuclear resonance fluorescence scattering of linearly polarized photons. A new 1+ level at Ex=5.846 MeV with Gamma 02 / Gamma =1.2±0.4 eV was found. This level can probably be identified with the theoretically predicted isoscalar 1+ state in 208Pb. All other bound dipole states below 7 MeV with Gamma 02 / Gamma >1.5 eV have negative parity. The 1- assignment to the 4.842-MeV level is of special significance because of previous conflicting results about its parity.
We present the measured correlation functions for pi+ pi-, pi- pi- and pi+ pi+ pairs in central S+Ag collisions at 200 GeV per nucleon. The Gamov function, which has been traditionally used to correct the correlation functions of charged pions for the Coulomb interaction, is found to be inconsistent with all measured correlation functions. Certain problems which have been dominating the systematic uncertainty of the correlation analysis are related to this inconsistency. It is demonstrated that a new Coulomb correction method, based exclusively on the measured correlation function for pi+ pi- pairs, may solve the problem.
The transverse momentum and rapidity distributions of negative hadrons and participant protons have been measured for central 32S+ 32S collisions at plab=200 GeV/c per nucleon. The proton mean rapidity shift < Delta y>~1.6 and mean transverse momentum <pT>~0.6 GeV/c are much higher than in pp or peripheral AA collisions and indicate an increase in the nuclear stopping power. All pT spectra exhibit similar source temperatures. Including previous results for K0s Lambda , and Lambda -bar, we account for all important contributions to particle production.
Experimental results are presented for 180 in silico designed octapeptide sequences and their stabilizing effects on the major histocompatibility class I molecule H-2Kb. Peptide sequence design was accomplished by a combination of an ant colony optimization algorithm with artificial neural network classifiers. Experimental tests yielded nine H-2Kb stabilizing and 171 nonstabilizing peptides. 28 among the nonstabilizing octapeptides contain canonical motif residues known to be favorable for MHC I stabilization. For characterization of the area covered by stabilizing and non-stabilizing octapeptides in sequence space, we visualized the distribution of 100,603 octapeptides using a self-organizing map. The experimental results present evidence that the canonical sequence motives of the SYFPEITHI database on their own are insufficient for predicting MHC I protein stabilization.
Animals living in human care for several generations face the risk of losing natural behaviors, which can lead to reduced animal welfare. The goal of this study is to demonstrate that meerkats (Suricata suricatta) living in zoos can assess potential danger and respond naturally based on acoustic signals only. This includes that the graded information of urgency in alarm calls as well as a response to those alarm calls is retained in captivity. To test the response to acoustic signals with different threat potential, meerkats were played calls of various animals differing in size and threat (e.g., robin, raven, buzzard, jackal) while their behavior was observed. The emitted alarm calls were recorded and examined for their graded structure on the one hand and played back to them on the other hand by means of a playback experiment to see whether the animals react to their own alarm calls even in the absence of danger. A fuzzy clustering algorithm was used to analyze and classify the alarm calls. Subsequently, the features that best described the graded structure were isolated using the LASSO algorithm and compared to features already known from wild meerkats. The results show that the graded structure is maintained in captivity and can be described by features such as noise and duration. The animals respond to new threats and can distinguish animal calls that are dangerous to them from those that are not, indicating the preservation of natural cooperative behavior. In addition, the playback experiments show that the meerkats respond to their own alarm calls with vigilance and escape behavior. The findings can be used to draw conclusions about the intensity of alertness in captive meerkats and to adapt husbandry conditions to appropriate welfare.
Methodik
(2002)
Die vegetationskundliche und strukturelle Zuordnung der Lebensraumtypen erfolgt nach der vorrangig von Braun-Blanquet entwickelten Vegetationsklassifizierung, einer hierarchischen Gliederung der Vegetationstypen (Syntaxonomie), die die Ebenen der Assoziation, des Verbandes, der Ordnung und der Klasse umfasst. Hierbei ist die Assoziation die grundlegende Einheit, in der die Pflanzengesellschaften zusammengefasst werden, die sich durch gleiche charakteristische Arten(gruppen)kombinationen auszeichnen. Der Verband vereinigt ähnliche Assoziationen. Das sind bereits umfassendere, jedoch standörtlich noch recht einheitliche Vegetationseinheiten. In Ordnungen werden ähnliche Verbände zusammengefasst. Die Klasse vereinigt ähnliche Ordnungen.
Background: SAMHD1 mediates resistance to anti-cancer nucleoside analogues, including cytarabine, decitabine, and nelarabine that are commonly used for the treatment of leukaemia, through cleavage of their triphosphorylated forms. Hence, SAMHD1 inhibitors are promising candidates for the sensitisation of leukaemia cells to nucleoside analogue-based therapy. Here, we investigated the effects of the cytosine analogue CNDAC, which has been proposed to be a SAMHD1 inhibitor, in the context of SAMHD1. Methods: CNDAC was tested in 13 acute myeloid leukaemia (AML) cell lines, in 26 acute lymphoblastic leukaemia (ALL) cell lines, ten AML sublines adapted to various antileukaemic drugs, 24 single cell-derived clonal AML sublines, and primary leukaemic blasts from 24 AML patients. Moreover, 24 CNDAC-resistant sublines of the AML cell lines HL-60 and PL-21 were established. The SAMHD1 gene was disrupted using CRISPR/Cas9 and SAMHD1 depleted using RNAi, and the viral Vpx protein. Forced DCK expression was achieved by lentiviral transduction. SAMHD1 promoter methylation was determined by PCR after treatment of genomic DNA with the methylation-sensitive HpaII endonuclease. Nucleoside (analogue) triphosphate levels were determined by LC-MS/MS. CNDAC interaction with SAMHD1 was analysed by an enzymatic assay and by crystallisation. Results: Although the cytosine analogue CNDAC was anticipated to inhibit SAMHD1, SAMHD1 mediated intrinsic CNDAC resistance in leukaemia cells. Accordingly, SAMHD1 depletion increased CNDAC triphosphate (CNDAC-TP) levels and CNDAC toxicity. Enzymatic assays and crystallisation studies confirmed CNDAC-TP to be a SAMHD1 substrate. In 24 CNDAC-adapted acute myeloid leukaemia (AML) sublines, resistance was driven by DCK (catalyses initial nucleoside phosphorylation) loss. CNDAC-adapted sublines displayed cross-resistance only to other DCK substrates (e.g. cytarabine, decitabine). Cell lines adapted to drugs not affected by DCK or SAMHD1 remained CNDAC sensitive. In cytarabine-adapted AML cells, increased SAMHD1 and reduced DCK levels contributed to cytarabine and CNDAC resistance. Conclusion: Intrinsic and acquired resistance to CNDAC and related nucleoside analogues are driven by different mechanisms. The lack of cross-resistance between SAMHD1/ DCK substrates and non-substrates provides scope for next-line therapies after treatment failure.
This paper presents results from the "INUIT-JFJ/CLACE 2013" field campaign at the high alpine research station Jungfraujoch in January/February 2013. The chemical composition of ice particle residuals (IPR) in a size diameter range of 200–900 nm was measured in orographic, convective and non-convective clouds with a single particle mass spectrometer (ALABAMA) under ambient conditions characterized by temperatures between −28 and −4 °C and wind speed from 0.1 to 21 km h−1. Additionally, background aerosol particles in cloud free air were investigated. The IPR were sampled from mixed-phase clouds with two inlets which selectively extract small ice crystals in-cloud, namely the Counterflow Virtual Impactor (Ice-CVI) and the Ice Selective Inlet (ISI). The IPR as well as the aerosol particles were classified into seven different particle types: (1) black carbon, (2) organic carbon, (3) black carbon internally mixed with organic carbon, (4) minerals, (5) one particle group (termed "BioMinSal") that may contain biological particles, minerals, or salts, (6) industrial metals, and (7) lead containing particles. For any sampled particle population it was determined by means of single particle mass spectrometer how many of the analyzed particles belonged to each of these categories. Accordingly, between 20 and 30% of the IPR and roughly 42% of the background particles contained organic carbon. The measured fractions of minerals in the IPR composition varied from 6 to 33%, while the values for the "BioMinSal" group were between 15 and 29%. Four percent to 31% of the IPR contained organic carbon mixed with black carbon. Both inlets delivered similar results of the chemical composition and of the particle size distribution, although lead was found only in the IPR sampled by the Ice-CVI. The results show that the ice particle residual composition varies substantially between different cloud events, which indicates the influence of different meteorological conditions, such as origin of the air masses, temperature and wind speed.
During January/February 2013, at the High Alpine Research Station Jungfraujoch a measurement campaign was carried out, which was centered on atmospheric ice-nucleating particles (INP) and ice particle residuals (IPR). Three different techniques for separation of INP and IPR from the non-ice-active particles are compared. The Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI) sample ice particles from mixed phase clouds and allow for the analysis of the residuals. The combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Counterflow Virtual Impactor (IN-PCVI) provides ice-activating conditions to aerosol particles and extracts the activated INP for analysis.Collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine size, chemical composition and mixing state. All INP/IPR-separating techniques had considerable abundances (median 20 – 70 %) of instrumental contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH+IN-PCVI: steel particles). Also, potential sampling artifacts (e.g., pure soluble material) occurred with a median abundance of < 20 %. While these could be explained as IPR by ice break-up, for INP their IN-ability pathway is less clear. After removal of the contamination artifacts, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Soot was a minor contributor. Lead was detected in less than 10 % of the particles, of which the majority were internal mixtures with other particle types. Sea-salt and sulfates were identified by all three methods as INP/IPR. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also separated many submicron IPR. As strictly parallel sampling could not be performed, a part of the discrepancies between the different techniques may result from variations in meteorological conditions and subsequent INP/IPR composition. The observed differences in the particle group abundances as well as in the mixing state of INP/IPR express the need for further studies to better understand the influence of the separating techniques on the INP/IPR chemical
composition.
Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b – Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.