bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic Colocalization of Genetic Variants from Complex and Molecular Traits: Promise and Limitations
Authors: Hukku Abhay , Pividori Milton , Luca Francesca , Pique-Regi Roger , Im Hae Kyung , Wen Xiaoquan 
Published: July 2020

AbstractColocalization analysis has emerged as a powerful tool to uncover the overlapping of causal variants responsible for both molecular and complex disease phenotypes. The findings from colocalization analysis yield insights into the molecular pathways of complex diseases. In this paper, we conduct an in-depth investigation of the promise and limitations of the available colocalization analysis approaches. Focusing on variant-level colocalization approaches, we first establish the connections between various existing methods. We proceed to discuss the impacts of various controllable analytical factors and uncontrollable practical factors on outcomes of colocalization analysis through realistic simulations and real data examples. We identify a single analytical factor, the specification of prior enrichment levels, which can lead to severe inflation of false-positive colocalization findings. Meanwhile, the combination of many other analytical and practical factors all lead to diminished power. Consequently, we recommend the following strategies for the best practice of colocalization analysis: i) estimating prior enrichment level from the observed data; and ii) separating fine-mapping and colocalization analysis. Our analysis of 4,091 complex traits and the multi-tissue eQTL data from the GTEx (version 8) suggests that colocalizations of molecular QTLs and GWAS traits are widespread in many complex traits. However, only a small proportion can be confidently identified from currently available data due to a lack of power. Our findings should serve as an important benchmark for the current and future integrative genetic association analysis applications.
Genome-scale CRISPR screening for modifiers of cellular LDL uptake
Authors: Emmer Brian T. , Sherman Emily J. , Lascuna Paul J. , Graham Sarah E. , Willer Cristen J. , Ginsburg David 
Published: July 2020

ABSTRACTHypercholesterolemia is a causal and modifiable risk factor for atherosclerotic cardiovascular disease. A critical pathway regulating cholesterol homeostasis involves the receptor-mediated endocytosis of low-density lipoproteins into hepatocytes, mediated by the LDL receptor. We applied genome-scale CRISPR screening to query the genetic determinants of cellular LDL uptake in HuH7 cells cultured under either lipoprotein-rich or lipoprotein-starved conditions. Candidate LDL uptake regulators were validated through the synthesis and secondary screening of a customized library of gRNA at greater depth of coverage. This secondary screen yielded significantly improved performance relative to the primary genome-wide screen, with better discrimination of internal positive controls, no identification of negative controls, and improved concordance between screen hits at both the gene and gRNA level. We then applied our customized gRNA library to orthogonal screens that tested for the specificity of each candidate regulator for LDL versus transferrin endocytosis, the presence or absence of genetic epistasis withLDLRdeletion, the impact of each perturbation on LDLR expression and trafficking, and the generalizability of LDL uptake modifiers across multiple cell types. These findings identified several previously unrecognized genes with putative roles in LDL uptake and suggest mechanisms for their functional interaction with LDLR.
Neural divergence and hybrid disruption between ecologically isolatedHeliconiusbutterflies
Authors: Montgomery Stephen H. , Rossi Matteo , McMillan W. Owen , Merrill Richard M. 
Published: July 2020

SummaryThe importance of behavioural evolution during speciation is well established, but we know little about how this is manifest in sensory and neural systems. Although a handful of studies have linked specific neural changes to divergence in host or mate preferences associated with speciation, how brains respond to broad environmental transitions, and whether this contributes to reproductive isolation, remains unknown. Here, we examine divergence in brain morphology and neural gene expression between closely related, but ecologically distinct,Heliconiusbutterflies. Despite on-going gene flow, sympatric species pairs within themelpomene-cydnocomplex are consistently separated across a gradient of open to closed forest and decreasing light intensity. By generating quantitative neuroanatomical data for 107 butterflies, we show thatH. melpomeneandH. cydnohave substantial shifts in brain morphology across their geographic range, with divergent structures clustered in the visual system. These neuroanatomical differences are mirrored by extensive divergence in neural gene expression. Differences in both morphology and gene expression are heritable, exceed expected rates of neutral divergence, and result in intermediate traits in first generation hybrid offspring. This likely disrupts neural system function, leading to a mismatch between the environment and the behavioral response of hybrids. Our results suggest that disruptive selection on both neural function and external morphology result in coincident barriers to gene flow, thereby facilitating speciation.
Isomerization of antimalarial drug WR99210 explains its inactivity in a commercial stock
Authors: Remcho T. Parks , Guggilapu Sravanthi D. , Cruz Phillip , Nardone Glenn A. , Heffernan Gavin , O’Connor Robert D. , Bewley Carole A. , Wellems Thomas E. , Lane Kristin D. 
Published: July 2020

ABSTRACTWR99210, a former antimalarial drug candidate now widely used for the selection ofPlasmodiumtransfectants, selectively targets the parasite dihydrofolate reductase thymidine synthase bifunctional enzyme (DHFR-TS) but not human DHFR, which is not fused with TS. Accordingly, WR99210 and plasmids expressing humandhfrhave become valued tools for the genetic modification of parasites in the laboratory. Concerns over the ineffectiveness of WR99210 from some sources encouraged us to investigate the biological and chemical differences of supplies from two different companies (compounds1and2). Compound1proved effective at low nanomolar concentrations againstPlasmodium falciparumparasites, whereas compound2was ineffective even at micromolar concentrations. Intact and fragmented mass spectra indicated identical molecular formulae of the unprotonated (free base) structures of1and2; however, the compounds displayed differences by thin layer chromatography, reverse phase high performance liquid chromatography, and ultraviolet-visible spectroscopy, indicating important isomeric differences. Structural evaluations by1H,13C, and15N nuclear magnetic resonance spectroscopy confirmed1as WR99210 and2as an isomeric dihydrotriazine. Induced fit, computational docking models showed that1binds tightly and specifically in theP. falciparumDHFR active site whereas2fits poorly to the active site in loose and varied orientations. Stocks and concentrates of WR99210 should be monitored for the presence of isomer2, particularly when they are not supplied as the hydrochloride salt or are exposed to basic conditions that can promote isomerization. Absorption spectroscopy may serve for assays of the unrearranged and rearranged triazines.
Early postmortem mapping of SARS-CoV-2 RNA in patients with COVID-19 and correlation to tissue damage
Authors: Deinhardt-Emmer Stefanie , Wittschieber Daniel , Sanft Juliane , Kleemann Sandra , Elschner Stefan , Haupt Karoline F. , Vau Vanessa , Häring Clio , Rödel Jürgen , Henke Andreas , Ehrhardt Christina , Bauer Michael , Philipp Mike , Gaßler Nikolaus , Nietzsche Sandor , Löffler Bettina , Mall Gita 
Published: July 2020

AbstractClinical observations indicate that COVID-19 is a systemic disease. An investigation of the viral distribution within the human body in correlation to tissue damage can help understanding the pathophysiology of SARS-CoV-2 infection.We present a detailed mapping of viral RNA in 61 tissues and organs of 11 deceased patients with the diagnosis COVID-19. The autopsies were performed within the (very) early postmortem interval (mean: 5.6 hours) to avoid bias due to viral RNA and tissue degradation. Viral loads, blood levels of cytokines, prothrombotic factors as well as macro- and micro-morphology were correlated.Very high (> 104copies/ml) viral loads were detected in the lungs of most patients and then correlated to severe tissue damage. Intact viral particles could be verified in the lung tissue by transmission electron microscopy. Viral loads in the lymph nodes were associated with a loss of follicular architecture. Viral RNA was detected throughout further extra-pulmonary tissues and organs without visible tissue damage. Inflammatory cytokines as well as the prothrombotic factors were elevated in all patients.In conclusion, the dissemination of SARS-CoV-2-RNA throughout the body supports the hypothesis of a maladaptive host response with viremia and multi-organ dysfunction.
Predictive Neural Computations Support Spoken Word Recognition: Evidence from MEG and Competitor Priming
Authors: Wang Yingcan Carol , Sohoglu Ediz , Gilbert Rebecca A. , Henson Richard N. , Davis Matthew H. 
Published: July 2020

AbstractHuman listeners achieve quick and effortless speech comprehension through computations of conditional probability using Bayes rule. However, the neural implementation of Bayesian perceptual inference remains unclear. Competitive-selection accounts (e.g. TRACE) propose that word recognition is achieved through direct inhibitory connections between units representing candidate words that share segments (e.g.hygieneandhijackshare /haidʒ/). Manipulations that increase lexical uncertainty should increase neural responses associated with word recognition when words cannot be uniquely identified. In contrast, predictive-selection accounts (e.g. Predictive-Coding) proposes that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words likehygieneandhijackwill increase prediction error and hence neural activity only at later time points when different segments are predicted. We collected MEG data from male and female listeners to test these two Bayesian mechanisms and used a competitor priming manipulation to change the prior probability of specific words. Lexical decision responses showed delayed recognition of target words (hygiene) following presentation of a neighbouring prime word (hijack) several minutes earlier. However, this effect was not observed with pseudoword primes (higent) or targets (hijure). Crucially, MEG responses in the STG showed greater neural responses for word-primed wordsafterthe point at which they were uniquely identified (after /haidʒ/ inhygiene) but notbeforewhile similar changes were again absent for pseudowords. These findings are consistent with accounts of spoken word recognition in which neural computations of prediction error play a central role.Significance StatementEffective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words; that is, Bayesian perceptual inference. This study specifies the neural mechanisms that support spoken word recognition by testing two distinct implementations of Bayes perceptual inference. Most established theories propose direct competition between lexical units such that inhibition of irrelevant candidates leads to selection of critical words. Our results instead support predictive-selection theories (e.g. Predictive-Coding): by comparing heard and predicted speech sounds, neural computations of prediction error can help listeners continuously update lexical probabilities, allowing for more rapid word identification.
Plasmodium DEH is ER-localized and crucial for oocyst mitotic division during malaria transmission
Authors: Guttery David S. , Pandey Rajan , Ferguson David J. P. , Wall Richard J. , Brady Declan , Gupta Dinesh , Holder Anthony A. , Tewari Rita 
Published: July 2020

AbstractCells use fatty acids (FAs) for membrane biosynthesis, energy storage and the generation of signaling molecules. 3-hydroxyacyl-CoA dehydratase – DEH – is a key component of very long chain FA (VLCFA) synthesis. Here, we further characterized in-depth the location and function of DEH, applying in silico analysis, live cell imaging, reverse genetics and ultrastructure analysis using the mouse malaria model Plasmodium berghei. DEH is evolutionarily conserved across eukaryotes, with a single DEH in Plasmodium spp. and up to three orthologs in the other eukaryotes studied. DEH-GFP live-cell imaging showed strong GFP fluorescence throughout the life-cycle, with areas of localized expression in the cytoplasm and a circular ring pattern around the nucleus that colocalized with ER markers. Δdeh mutants showed a small but significant reduction in oocyst size compared to WT controls from day 10 post-infection onwards and endomitotic cell division and sporogony were completely ablated, blocking parasite transmission from mosquito to vertebrate host. Ultrastructure analysis confirmed degeneration of Δdeh oocysts, and a complete lack of sporozoite budding. Overall, DEH is evolutionarily conserved, localizes to the ER and plays a crucial role in sporogony.
Muribaculaceae genomes assembled from metagenomes suggest genetic drivers of differential response to acarbose treatment in mice
Authors: Smith Byron J. , Miller Richard A. , Schmidt Thomas M. 
Published: July 2020

AbstractThe drug acarbose is used to treat diabetes, and, by inhibiting α-amylase in the small intestine, increases the amount of starch entering the lower digestive tract. This results in changes to the composition of the microbiota and their fermentation products. Acarbose also increases longevity in mice, an effect that has been correlated with increased production of the short-chain fatty acids propionate and butyrate. In experiments replicated across three study sites, two distantly related species in the bacterial family Muribaculaceae were dramatically more abundant in acarbose-treated mice, distinguishing these responders from other members of the family. Bacteria in the family Muribaculaceae are predicted to produce propionate as a fermentation end product and are abundant and diverse in the guts of mice, although few isolates are available. We reconstructed genomes from metagenomes (MAGs) for nine populations of Muribaculaceae to examine factors that distinguish species that respond positively to acarbose. We found two closely related MAGs (B1A and B1B) from one responsive species that both contain a polysaccharide utilization locus with a predicted extracellular α-amylase. These genomes also shared a periplasmic neopullulanase with another, distantly related MAG (B2) representative of the only other responsive species. This gene differentiated these three MAGs from MAGs representative of non-responding species. Differential gene content in B1A and B1B may be associated with the inconsistent response of this species to acarbose across study sites. This work demonstrates the utility of culture-free genomics for inferring the ecological roles of gut bacteria including their response to pharmaceutical perturbations.ImportanceThe drug acarbose is used to treat diabetes by preventing the breakdown of starch in the small intestine, resulting in dramatic changes in the abundance of some members of the gut microbiome and its fermentation products. In mice, several of the bacteria that respond most positively are classified in the family Muribaculaceae, members of which produce propionate as a primary fermentation product. Propionate has been associated with gut health and increased longevity in mice. We found that genomes of the most responsive Muribaculaceae showed signs of specialization for starch fermentation, presumably providing them a competitive advantage in the large intestine of animals consuming acarbose. Comparisons among genomes enhance existing models for the ecological niches occupied by members of this family. In addition, genes encoding one type of enzyme known to participate in starch breakdown were found in all three genomes from responding species, but none of the other genomes.
Evolution of COVID-19 Pandemic in India
Authors: Asad Ali , Srivastava Siddharth , Verma Mahendra K. 
Published: July 2020

AbstractA mathematical analysis of patterns for the evolution of COVID-19 cases is key to the development of reliable and robust predictive models potentially leading to efficient and effective governance against COVID-19. Towards this objective, we study and analyze the temporal growth pattern of COVID-19 infection and death counts in various states of India. Our analysis up to August 4, 2020, shows that several states (namely Maharashtra, Tamil Nadu, West Bengal) have reachedt2power-law growth, while Gujarat and Madhya Pradesh exhibit linear growth. Delhi has reachedphase and may flatten in the coming days. However, some states have deviated from the universal pattern of the epidemic curve. Uttar Pradesh and Rajasthan show a gradual rise in the power-law regime, which is not the usual trend. Also, Bihar, Karnataka, and Kerala are exhibiting a second wave. In addition, we report that initially, the death counts show similar behavior as the infection counts. Later, however, the death growth rate declines as compared to the infection growth due to better handling of critical cases and increased immunity of the population. These observations indicate that except Delhi, most of the Indian states are far from flattening their epidemic curves.
Differential COVID-19 case positivity in New York City neighborhoods: socioeconomic factors and mobility
Authors: Lamb Matthew R. , Kandula Sasikiran , Shaman Jeffrey 
Published: July 2020

AbstractNew York City has been one of the hotspots of the COVID-19 pandemic and during the first two months of the outbreak considerable variability in case positivity was observed across the city’s ZIP codes. In this study, we examined: a) the extent to which the variability in ZIP code level cases can be explained by aggregate markers of socioeconomic status and daily change in mobility; and b) the extent to which daily change in mobility independently predicts case positivity.Our analysis indicates that the markers considered together explained 56% of the variability in case positivity through April 1 and their explanatory power decreased to 18% by April 30. Our analysis also indicates that changes in mobility during this time period are not likely to be acting as a mediator of the relationship between ZIP-level SES and case positivity. During the middle of April, increases in mobility were independently associated with decreased case positivity. Together, these findings present evidence that heterogeneity in COVID-19 case positivity during the New York City spring outbreak was largely driven by residents’ socioeconomic status.
Development of the IcanSDM scale to assess primary care clinicians’ ability to adopt shared decision-making
Authors: Giguere Anik MC , Bogza Laura-Mihaela , Coudert Laetitia , Carmichael Pierre-Hugues , Renaud Jean-Sébastien , Légaré France , Lindig Anja , Voyer Philippe 
Published: July 2020

AbstractIntroductionImplementation of shared decision making (SDM) remains a challenge. To support implementation studies, we sought to develop and validate the IcanSDM scale that assesses clinicians’ perceptions of their ability to adopt SDM.MethodsAn expert panel reviewed the literature on clinician-reported barriers to SDM adoption, to create an 11-item preliminary scale. A convenience sample of 16 clinicians from Québec (Canada) completed the IcanSDM and the Belief about Capabilities subscale of the CPD-Reaction instrument (BCap), before and after SDM training. We audio-recorded their comments as they completed the scale. We measured IcanSDM’s internal consistency, sensitivity to change and correlation with BCap. Partial correlation coefficients and item analyses suggested removing three items. We then tested the 8-item IcanSDM with a new sample of 17 clinicians.ResultsIn the 11-item IcanSDM version, three items lacked clarity or responsiveness, or showed negative partial correlations with the whole instrument. We thus removed these items. The revised 8-item version gave Cronbach’s alphas of 0.63 before and 0.71 after training, and a 16% improvement in IcanSDM total score after training, compared to before training (p<0.0001). We also found a significant correlation between IcanSDM and the BCap before training (p=0.02), but not after (p=0.46).DiscussionIcanSDM is the only instrument measuring this construct. It could thus help bridge the gap in our ability to understand the determinants of clinicians’ SDM behavior intentions and thus help improve SDM implementation impacts and efforts. IcanSDM requires testing with a larger sample to confirm its responsiveness.Lessons for practiceIcanSDM assesses clinicians’ perceived ability to adopt shared decision making.IcanSDM demonstrated adequate validity and reliability but needs more testing to confirm its responsiveness.IcanSDM is promising to assess the impacts of training in shared decision making and other initiatives to implement shared decision making.
Using the infection fatality rate to predict the evolution of Covid-19 in Brazil
Authors: Cecconello M. S. , Diniz G. L. , Silva E. B. 
Published: July 2020

AbstractIn this work we are going to use estimates of Infection Fatality Rate (IFR) for Covid-19 in order to predict the evolution of Covid-19 in Brazil. To this aim, we are going to fit the parameters of the SIR model using the official deceased data available by governmental agencies. Furthermore, we are going to analyse the impact of social distancing policies on the transmission parameters.
Cytogenetic signatures of recurrent pregnancy losses
Authors: Yatsenko Svetlana. A. , Quesada-Candela Cristina , Saller Devereux N. , Beck Stacy , Jaffe Ronald , Kostadinov Stefan , Yanowitz Judith , Rajkovic Aleksandar 
Published: July 2020

ABSTRACTObjectivesTo investigate the incidence of chromosomal abnormalities in the products of conception (POC) of patients with spontaneous miscarriages (SM) and with recurrent pregnancy losses (RPL), and to determine biological mechanisms contributing to RPL.DesignRetrospective cohort study.SettingUniversity-affiliated medical center.PatientsDuring a 20-years period, 12,096 POC samples underwent classical chromosome analysis as a part of standard clinical care.InterventionsCytogenetic findings were classified into six categories and compared between the SM and RPL cohorts.Main Outcome MeasuresRPL-specific cytogenetic abnormalities and sex bias in POCs with autosomal aneuploidy.ResultsAnalysis of a large cohort of RPL patients has identified an increased incidence of inherited and de novo structural chromosome abnormalities, recurrent polyploid conceptions, and complex mosaic alterations. These abnormalities are the signature of genomic instability, posing a high risk of genetic abnormalities to offspring independent of maternal age. Predominance of male conceptions in the RPL cohort points toward X-linked etiology and gender-specific intolerance for certain genetic abnormalities.ConclusionsOur study showed several possible genetic etiologies of RPL, including parental structural chromosome rearrangements, predisposition to meiotic nondisjunction and genomic instability in patients with karyotypically abnormal POCs. Loss of karyotypically normal fetuses might be attributed to defects in genes essential for fetal development and survival, as well as aberrations affecting the X chromosome structure or function. Molecular studies of parental and POC genomes will help to identify inherited defects in genes involved in meiotic divisions and DNA repair to confirm our hypotheses, and to discover novel fetal-essential genes.