bluuebunny/crossref_metadata_2025_split huggingface dataset:
txci-ATAC-seq, a massive-scale single-cell technique to profile chromatin accessibility
Authors: Zhang Hao , Mulqueen Ryan M. , Iannuzo Natalie , Farrera Dominique O. , Polverino Francesca , Galligan James J. , Ledford Julie G. , Adey Andrew C. , Cusanovich Darren A. 
Published: May 2023

AbstractMeasuring chromatin accessibility is a powerful method to identify cell types and states. Performed at single-cell resolution, this assay has generated catalogs of genome-wide DNA regulatory sites, whole-organism cell atlases, and dynamic chromatin reorganization through development. However, the limited throughput of current single-cell approaches poses a challenge for implementing proper study designs, population-scale profiling, and/or very deep profiling of complex samples. To this end, we developed a 10X-compatible combinatorial indexing ATAC sequencing (“txci-ATAC-seq”), which is a combinatorial indexing framework that initially indexes (“pre-indexes”) chromatin within nuclei with barcoded transposases followed by encapsulation and further barcoding using a commercialized droplet-based microfluidics platform (10X Genomics). Leveraging this molecular hashing strategy, we demonstrate that txci-ATAC-seq enables the indexing of up to 200,000 nuclei across multiple samples in a single emulsion reaction, representing a ∼22-fold increase in throughput compared to the standard workflow at the same collision rate. To improve the efficiency of this new technique, we further developed a faster version of the protocol (“Fast-txci-ATAC-seq”) that separates sample pre-processing from library generation and has the potential to profile up to 96 samples simultaneously. We initially benchmarked our assay by generating chromatin accessibility profiles for 230,018 cells from five native tissues across three experiments, including human cortex (28,513 cells), mouse brain (48,997 cells), human lung (15,799 cells), mouse lung (73,280 cells), and mouse liver (63,429 cells). We also applied our method to a club cell secretory protein knockout (CC16-/-) mouse model to examine the biological and technical limitations of the mouse line. By characterizing DNA regulatory landscapes in 76,498 wild-type and 77,638 CC16-/-murine lung nuclei, our investigations uncovered previously unappreciated residual genetic deviations from the reference strain that resulted from the method of gene targeting, which employed embryonic stem cells from the 129 strain. We found that these genetic remnants from the 129 strain led to profound cell-type-specific changes in chromatin accessibility in regulatory elements near a host of genes. Collectively, we defined single-cell chromatin signatures in 384,154 nuclei from 13 primary samples across different species, organs, biological replicates, and genetic backgrounds, establishing txci-ATAC-seq as a robust, high-quality, and highly multiplexable single-cell assay for large-scale chromatin studies.
Limits to selection on standing variation in an asexual population
Authors: Barton Nick , Sachdeva Himani 
Published: May 2023

AbstractWe consider how a population responds to directional selection on standing variation, with no new variation from recombination or mutation. Initially, there areNindividuals with trait valuesz1, …,zN; the fitness of individualiis proportional to. The initial values are drawn from a distributionψwith varianceV0; we give examples of the Laplace and Gaussian distributions. When selection is weak relative to drift, variance decreases exponentially at rate 1/N; since the increase in mean in any generation equals the variance, the expected net change is justNV0, which is the same as Robertson’s (1960) prediction for a sexual population. In contrast, when selection is strong relative to drift, the net change can be found by approximating the establishment of alleles by a branching process in which each allele competes independently with the population mean and the fittest allele to establish is certain to fix. Then, if the probability of survival to timeof an allele with valuezisP(z), with mean, the winning allele is the fittest ofsurvivors drawn from a distribution. WhenNis large, there is a scaling limit which depends on a single parameter; the expecte d ultimate change isfor a Gaussian distribution, andfor a Laplace distribution (where 𝒲is the product log function). This approach also reveals the variability of the process, and its dynamics; we show that in the strong selection regime, the expected genetic variance decreases as ∼t−3at large times. We discuss how these results may be related to selection on standing variation that is spread along a linear chromosome.
BiATNovo: An Attention-based Bidirectional De Novo Sequencing Framework for Data-Independent-Acquisition Mass Spectrometry
Authors: Yang Shu , Wu Siyu , Li Binyang , Liu Yuxiaomei , Li Fangzheng , Qi Jiaxing , Wang Qunying , Liang Xiaohui , Guo Tiannan , Luan Zhongzhi 
Published: May 2023

AbstractDe novo sequencing from tandem mass spectra (MS/MS) data is a key technique for identifying novel peptides. In theory, the Data-Independent Acquisition (DIA) method can fragment all precursor ions in an unbiased and non-targeted fashion. However, each spectrum contains fragments from multiple precursor ions, and the unclear relationship between these ions and their fragments poses a significant challenge to the accuracy of de novo sequencing algorithms. Here we present BiATNovo, an attention-based bidirectional de novo peptide sequencing framework. BiATNovo comprises a bidirectional attention-based model and a bidirectional fusion-reranking post-processing module, which enables efficient capture of relationships between tandem mass spectra, fragment ions, and peptide patterns, while also expanding the candidate set to select the optimal sequence. This framework improves peptide prediction accuracy, particularly for long peptide sequences, and mitigates the imbalance where the initial amino acids are predicted more accurately than the last ones. Evaluation results demonstrate that BiATNovo outperforms existing algorithms, including DeepNovo-DIA and PepNet, in both peptid-level and amino acid-level. Furthermore, when extended to DDA datasets, BiATNovo achieves comparable performance to state-of-the-art models.
Diversity of spider families parasitized by fungal pathogens: a global review
Authors: Nyffeler Martin , Hywel-Jones Nigel 
Published: May 2023

AbstractIn this paper the findings of a global literature and social media survey of spider mycoses are presented. Our survey revealed that spider mycoses occur in the geographic belt between latitude 78°N and 52°S, and that more than 40 out of the known 135 spider families (ca. 30%) are attacked by fungal pathogens. Jumping spiders (Salticidae), cellar spiders (Pholcidae), and sheet-web spiders (Linyphiidae) are the families most frequently reported to be attacked by fungal pathogens (combined >40% of all reported cases). Ninety-two percent of the infections of spiders can be attributed to pathogens in the order Hypocreales (phylum Ascomycota), and almost exclusively the families Cordycipitaceae and Ophiocordycipitaceae. Within the Hypocreales, the asexually reproductive genusGibellulais an historically species-rich and widespread genus of specific spider-pathogenic fungi. For ca. 70 species of spider-pathogenic fungi their hosts could be identified at least to family level. The data presented here reaffirm the findings of previous studies that spider-pathogenic fungi are most common and widespread in tropical and subtropical forested areas, with free-living cursorial hunters – dominated by Salticidae – being the most frequently infected. Cursorial hunters (especially Salticidae) and subterranean cellar spiders (Pholcidae) are the most frequently fungus-infected spiders in North America, whereas web-weavers (especially Linyphiidae and Pholcidae) are the most common spider hosts in Europe. Our survey implies that spider-pathogenic fungi are an important mortality factor for spiders which has hitherto been underestimated.
Distribution and dynamics of chromatin states in theC. elegansgerm line
Authors: Mazzetto Mariateresa , Gonzalez Lauren E. , Sanchez Nancy , Reinke Valerie 
Published: May 2023

ABSTRACTChromatin organization in theC. elegansgerm line is tightly regulated and critical for germ cell differentiation. While certain germline epigenetic regulatory mechanisms have been identified, how they influence chromatin structure and ultimately gene expression remain unclear, in part because most genomic studies have focused on data collected from whole worms. We therefore analyzed publicly available histone modification and chromatin accessibility data from isolated undifferentiated germ nuclei to define chromatin states. We then correlated these states with overall transcript abundance, spatio-temporal expression patterns, and the function of small RNA pathways. Because the essential role of the germ line is to transmit genetic information to the next generation and establish gene expression in the early embryo, we compared epigenetic and transcriptomic profiles from undifferentiated germ cells, oocytes, and embryos to define the epigenetic changes during this developmental transition. The active histone modification H3K4me3 exhibits particularly dynamic remodeling as germ cells differentiate into oocytes. Our results highlight the dynamism of the chromatin landscape in germ cells, and provide a resource for future investigation into epigenetic regulatory mechanisms.
Effectiveness of drugs for COVID-19 inpatients in Japanese medical claim data as average treatment effects with inverse probability weighted regression adjustment: Retrospective observational study
Authors: Mitsushima Shingo , Horiguchi Hiromasa , Taniguchi Kiyosu 
Published: May 2023

AbstractBackgroundPrior studies have indicated that drugs against coronavirus disease 2019 (COVID-19) such as antiviral drugs, anti-inflammatory drugs, steroid and antibody cocktails are expected to prevent severe COVID-19outcomes and death.ObjectWe analyzed medical claim data in Japan to assess the effectiveness of drugs againstCOVID-19.MethodWe applied an average treatment effect model with inverse probability weighted regression adjustment, to the Medical Information Analysis Databank managed by National Hospital Organization in Japan. The outcome was death during hospitalization. Subjects were all inpatients, inpatients with oxygen therapy, and inpatients with respiratory ventilators, by three age classes: all ages, 65 years old or older, and younger than 65 years old. Data on physical characteristics, underlying diseases, administered drugs, the proportion of mutated strains, and vaccine coverage were used as explanatory variables for logistic regression.ResultEstimated results indicated that only an antibody cocktails (sotrovimab, casirivimab and imdevimab) raised the probability of saving life, even though these drugs were administered in few cases. On the other hand, other drugs might raise the probability of death.DiscussionResults indicated that only antibody cocktails was effective to save life using an average treatment effect model with inverse probability weighted regression adjustment. No other drugs such as remdesivir, dexamethasone, baricitinib and tocilizumab were found to be effective to save life, even in the pseudo-situation of random assignment.
Genetic Factors Associated with Suicidal Behaviors and Alcohol Use Disorders in an American Indian Population
Authors: Peng Qian , Gilder David A. , Bernert Rebecca , Karriker-Jaffe Katherine J. , Ehlers Cindy L. 
Published: May 2023

ABSTRACTAmerican Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genesAACSP1,ANK1, andFBXO11. Nonsynonymous rare mutations in four genes includingSERPINF1(PEDF),ZNF30,CD34, andSLC5A9, and non-intronic rare mutations in genesOPRD1,HSD17B3and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.
Mutations in tau protein promote aggregation by favoring extended conformations
Authors: Pounot Kevin , Piersson Clara , Goring Andrew , Weik Martin , Han Songi , Fichou Yann 
Published: May 2023

AbstractAmyloid aggregation of the intrinsically disordered protein (IDP) tau is involved in several diseases, called tauopathies. Mutations in the gene encoding tau are responsible for a class of inherited tauopathies called frontotemporal dementia and parkinsonism linked to chromosome 17Q (FTDP-17). These mutations are thought to trigger FTDP-17 by favoring the formation of tau amyloid fibrils. This work aims at deciphering the mechanisms through which the diseases-associated single point mutations promote amyloid formation. We combined biochemical characterization and small angle X-ray scattering (SAXS) to study six different FTDP-17 derived mutations. We found that the mutations promote aggregation to different degrees and can modulate tau conformational ensembles, intermolecular interactions and liquid-liquid phase separation propensity. In particular, we found a good correlation between the aggregation lag time of the mutants and their radius of gyration. We show that mutations disfavor intramolecular protein interactions which in turn favor extended conformations and promote amyloid aggregation. This work proposes a new connection between the structural features of tau monomers and their propensity to aggregate, providing a novel assay to evaluate aggregation propensity of tau variants.
Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer’s Disease
Authors: Chumin Evgeny J. , Cutts Sarah A. , Risacher Shannon L. , Apostolova Liana G. , Farlow Martin R. , McDonald Brenna C. , Wu Yu-Chien , Betzel Richard , Saykin Andrew J. , Sporns Olaf 
Published: May 2023

AbstractUnderstanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer’s disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer’s Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer’s disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
Integration of a deep learning basal cell carcinoma detection and tumor mapping algorithm into the Mohs micrographic surgery workflow and effects on clinical staffing: a simulated, retrospective study
Authors: Chacko Rachael , Davis Matthew J. , Levy Joshua , LeBoeuf Matthew 
Published: May 2023

AbstractBackgroundStaffing shortages and inadequate healthcare access have driven the development of artificial intelligence (AI)-enabled tools in medicine. Accuracy of these algorithms has been extensively investigated, but research on downstream effects of AI integration into the clinical workflow is lacking.ObjectiveWe aim to analyze how integration of a basal cell carcinoma detection and tumor mapping algorithm in a Mohs micrographic surgery (MMS) unit may impact waiting times in the surgical pathology laboratory and on the floor.MethodsTime spent on each task and slide, staff, and histotechnician waiting times were analyzed over a 20 day period in a MMS unit. A simulated AI workflow was created and the time differences between the real and simulated workflows were compared.ResultsSimulated addition of the algorithm led to improvements of 64% in slide waiting time (1:03:39 per case), 36% in staff waiting time (59:09 per case), and 25% in histotechnician waiting time (25:27 per case).LimitationsA single MMS unit was analyzed and AI integration was performed retrospectively, rather than in real time.ConclusionsAI integration results in significantly reduced slide, staff, and histotechnician waiting time, which enables increased productivity and a streamlined clinical workflow.Capsule summaryThe accuracy of artificial intelligence algorithms has been well established. This study addresses the impact of implementation of such an algorithm into a real-world clinical workflow.Results indicate the potential for increased efficiency and productivity with use of artificial intelligence in Mohs micrographic surgery.
Ex-LactobacillusStrains with Intrinsic Propensity to Stabilize Pickering Oil-in-Water Emulsions
Authors: Muhammed Musemma Kedir , Jiang Xiaoyi , Shekarforoush Elhamalsadat , Whitehead Kathryn , Vogensen Finn K. , Risbo Jens , Arneborg Nils 
Published: May 2023

AbstractKnowledge of surface characteristics is a major step in the evaluation of bacterial cells for potential use as Pickering emulsion stabilizers. Here, the cell surface characteristics of 31 strains of the ex-Lactobacillusgenus were studied with the aim of evaluating their intrinsic abilities to serve as Pickering stabilizers of oil-in-water emulsions. About 77.42% of the tested strains demonstrated relatively highly negative zeta potential (-43.76 mV ≤ zeta potential ≤ -19.23 mV), while ∼58% of the strains demonstrated high cell surface hydrophobicity (microbial adhesion to hexadecane or MATH ≥ 30%). By combining these findings, four different cell surface features were defined (I, II, II and IV). Strains mainly demonstrated the type I surface feature (∼45%), with most expressing strongly negative zeta potential and high surface hydrophobicity (zeta potential < -15 mV and MATH ≥ 30%, respectively). It appeared that the abundance of negative charge on the surfaces of ex-Lactobacilluscells positively influences surface hydrophobicity. Assessment of intrinsic Pickering stabilization potential using 12 selected strains indicated that four strains showed profound droplet size stability. At least one strain was observed to have natural propensity to form relativley compact and small emulsion droplets (63±3 µm), leading to enhanced firmness and storage stability of the Pickering emulsions.
Diving efficiency at depth and pre-breeding foraging effort increase with haemoglobin levels in gentoo penguins
Authors: McComb-Turbitt Sarah P. , Crossin Glenn T. , Tierney Megan , Brickle Paul , Trathan Philip , Williams Tony D. , Auger-Méthé Marie 
Published: May 2023

AbstractIndividual differences in oxygen storage and carrying capacity have been associated with fitness-related traits and, for air-breathing aquatic animals, to diving ability and foraging success. In winter, many seabirds must replenish the energy reserves they have depleted during the breeding period. Thus, winter foraging efficiency can influence their upcoming breeding behaviour. Using gentoo penguins (Pygoscelis papua), we investigate (1) if inter-individual variation in diving efficiency (proportion of time spent at the bottom) is associated with indices of oxygen storage and carrying capacity (haemoglobin, haematocrit, body mass), and (2) if measures of pre-breeding foraging effort (mean trip duration, total time at sea, and vertical distance travelled) are associated with these oxygen indices and breeding status. Haemoglobin was positively correlated with diving efficiency, particularly for deeper dives, and only penguins with high haemoglobin levels frequently dove at depth ≥ 140 m. Such differences could affect resource access. However, potentially because reaching deep offshore waters requires travelling more than foraging nearshore, vertical distance travelled pre-breeding increased with haemoglobin levels. The relationship with haematocrit was non-linear, suggesting that commonly-used analyses may be inappropriate for this index. We found that early-laying penguins spent less time at sea prior to nesting than non-breeding penguins, suggesting that more efficient foragers lay earlier. Given that diving efficiency at depth is linked to aerobic capacity, anthropogenic activities taking place in either nearshore or offshore waters (e.g., shallow water fisheries, offshore oil rigs) may have differing impacts on individuals. Further understanding these links could help the conservation of diving species.