bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physiological and life history changes associated with seasonal adaptation in the cactophilic Drosophila mojavensis
Authors: Shaible Tierney M. , Matzkin Luciano M. 
Published: November 2021

AbstractMany insects inhabiting temperate climates are faced with changing environmental conditions throughout the year. Depending on the species, these environmental fluctuations can be experienced within a single generation or across multiple generations. Strategies for dealing with these seasonal changes vary across populations. Drosophila mojavensis is a cactophilic Drosophila species endemic to the Sonoran Desert. The Sonoran Desert regularly reaches temperatures of 50°C in the summer months. As individuals of this population are rare to collect in the summer months, we therefore simulated in a temperature and light controlled chamber the cycling temperatures experienced by D. mojavensis in the Sonoran Desert from April to July (four generations) to understand the physiological and life history changes that allow this population to withstand these conditions. In contrast to our hypothesis of a summer aestivation, we found that D. mojavensis continue to reproduce during the summer months, albeit with lower viability, but the longevity of the population is highly reduced during this period. As expected, stress resistance increased during the summer months in both the adult and the larval stages. This study examines several strategies for withstanding the Sonoran Desert summer conditions which may be informative in the study of other desert endemic species.
A single cell atlas of human and mouse white adipose tissue
Authors: Emont Margo P. , Jacobs Christopher , Essene Adam L. , Pant Deepti , Tenen Danielle , Colleluori Georgia , Di Vincenzo Angelica , Jørgensen Anja M. , Dashti Hesam , Stefek Adam , McGonagle Elizabeth , Strobel Sophie , Laber Samantha , Agrawal Saaket , Westcott Gregory P. , Kar Amrita , Veregge Molly L. , Gulko Anton , Srinivasan Harini , Kramer Zachary , De Filippis Eleanna , Merkel Erin , Ducie Jennifer , Boyd Christopher G. , Gourash William , Courcoulas Anita , Lin Samuel J. , Lee Bernard T. , Morris Donald , Tobias Adam , Khera Amit V. , Claussnitzer Melina , Pers Tune H. , Giordano Antonio , Ashenberg Orr , Regev Aviv , Tsai Linus T. , Rosen Evan D. 
Published: November 2021

ABSTRACTWhite adipose tissue (WAT), once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic, heterogenous, and involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control, and host defense1. High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition1, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and type 2 diabetes (T2D)2. Here, we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.
Regulation of prostate androgens by megalin and 25-hydroxyvitamin D status: Mechanism for high prostate androgen in African American men
Authors: Garcia Jason , Krieger Kirsten D. , Loitz Candice , Perez Lillian , Richards Zachary A. , Helou Yves , Kregel Steve , Celada Sasha , Mesaros Clementina A. , Gann Peter H. , Willnow Thomas E. , Griend Donald Vander , Kittles Rick , Prins Gail S. , Penning Trevor , Nonn Larisa 
Published: November 2021

ABSTRACTVitamin D deficiency is associated with an increased risk of prostate cancer (PCa) mortality and is hypothesized to contribute to PCa aggressiveness and disparities in African American populations. The prostate epithelium was recently shown to express megalin, an endocytic receptor that internalizes globulin-bound hormones, which suggests regulation of prostate hormone levels, in contrast to the free hormone hypothesis. Here, we demonstrated that megalin imports testosterone bound to sex hormone-binding globulin into prostate cells. Prostatic loss of Lrp2 (megalin) in a mouse model resulted in reduced prostate testosterone and dihydrotestosterone (DHT) levels. Megalin expression was regulated and suppressed by 25-hydroxyvitamin D (25D) in cell lines, patient-derived prostate epithelial cells, and prostate tissue explants, indicating a negative feedback loop. In patent samples, the relationships between hormones support this feedback mechanism, as prostatic DHT levels are higher in African American men and are inversely correlated with serum 25D status. Megalin levels are reduced in localized PCa by the Gleason grade and in patients with future disease recurrence. Our findings suggest that the free hormone hypothesis should be revisited for testosterone and highlight the impact of vitamin D deficiency on prostate androgen levels, which are known drivers of PCa. Thus, we revealed a mechanistic link between vitamin D and PCa disparities observed in African Americans.
Robust and generalizable segmentation of human functional tissue units
Authors: Godwin Leah L. , Ju Yingnan , Sood Naveksha , Jain Yashvardhan , Quardokus Ellen M. , Bueckle Andreas , Longacre Teri , Horning Aaron , Lin Yiing , Esplin Edward D. , Hickey John W. , Snyder Michael P. , Patterson N. Heath , Spraggins Jeffrey M. , Börner Katy 
Published: November 2021

AbstractThe Human BioMolecular Atlas Program aims to compile a reference atlas for the healthy human adult body at the cellular level. Functional tissue units (FTU, e.g., renal glomeruli and colonic crypts) are of pathobiological significance and relevant for modeling and understanding disease progression. Yet, annotation of FTUs is time consuming and expensive when done manually and existing algorithms achieve low accuracy and do not generalize well. This paper compares the five winning algorithms from the “Hacking the Kidney” Kaggle competition to which more than a thousand teams from sixty countries contributed. We compare the accuracy and performance of the algorithms on a large-scale renal glomerulus Periodic acid-Schiff stain dataset and their generalizability to a colonic crypts hematoxylin and eosin stain dataset. Results help to characterize how the number of FTUs per unit area differs in relationship to their position in kidney and colon with respect to age, sex, body mass index (BMI), and other clinical data and are relevant for advancing pathology, anatomy, and surgery.
scHiCSRS: A Self-Representation Smoothing Method with Gaussian Mixture Model for Imputing single cell Hi-C Data
Authors: Xie Qing , Lin Shili 
Published: November 2021

AbstractMotivationSingle cell Hi-C techniques make it possible to study cell-to-cell variability in genomic features. However, excess zeros are commonly seen in single cell Hi-C (scHi-C) data, making scHi-C matrices extremely sparse and bringing extra difficulties in downstream analysis. The observed zeros are a combination of two events: structural zeros for which the loci never interact due to underlying biological mechanisms, and dropouts or sampling zeros where the two loci interact but are not captured due to insufficient sequencing depth. Although quality improvement approaches have been proposed as an intermediate step for analyzing scHi-C data, little has been done to address these two types of zeros. We believe that differentiating between structural zeros and dropouts would benefit downstream analysis such as clustering.ResultsWe propose scHiCSRS, a self-representation smoothing method that improves the data quality, and a Gaussian mixture model that identifies structural zeros among observed zeros. scHiC-SRS not only takes spatial dependencies of a scHi-C 2D data structure into account but also borrows information from similar single cells. Through an extensive set of simulation studies, we demonstrate the ability of scHiCSRS for identifying structural zeros with high sensitivity and for accurate imputation of dropout values in sampling zeros. Downstream analysis for three real datasets show that data improved from scHiCSRS yield more accurate clustering of cells than simply using observed data or improved data from several comparison methods.Availability and ImplementationThe scHiCSRS R package, together with the processed real and simulated data used in this study, are available on Github at https://github.com/sl-lin/scHiCSRS.git.Contactshili@stat.osu.eduSupplementary informationSupplementary data are available online.
Estimating the rates of crossover and gene conversion from individual genomes
Authors: Setter Derek , Ebdon Sam , Jackson Ben , Lohse Konrad 
Published: November 2021

AbstractRecombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the two processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We presentheRho, a simple composite likelihood scheme for co-estimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at two loci. We applyheRhoto simulations and data from the house mouseMus musculus castaneus, a well studied model. Our analyses show i) that the rates of crossover and gene conversion can be accurately co-estimated at the level of individual chromosomes and ii) that previous estimates of the population scaled rate of recombinationunder a pure crossover model are likely biased.
2-Guanidino-quinazoline promotes the readthrough of nonsense mutations underlying human genetic diseases
Authors: Bidou Laure , Bugaud Olivier , Merer Goulven , Coupet Matthieu , Hatin Isabelle , Chirkin Egor , François Pauline , Cintrat Jean-Christophe , Namy Olivier 
Published: November 2021

AbstractPremature termination codons (PTCs) account for 10% to 20% of genetic diseases in humans. The gene inactivation resulting from PTC can be counteracted by the use of drugs stimulating PTC readthrough, thereby restoring production of the full-length protein. However, a greater chemical variety of readthrough inducers is required to broaden the medical applications of this therapeutic strategy. In this study, we developed a new reporter cell line and performed high-throughput screening (HTS) to identify potential new readthrough inducers. After three successive assays, we isolated 2-guanidino-quinazoline (TLN468). We assessed the clinical potential of this drug as a potent readthrough inducer on the 40 PTCs most frequently responsible for Duchenne muscular dystrophy. We found that TLN468 was more efficient than gentamicin, and acted on a broader range of sequences, without inducing the readthrough of natural stop codons.
REDigest: a Python GUI for In-Silico Restriction Digestion Analysis of Genes or Complete Genome Sequences
Authors: Singh Abhijeet 
Published: November 2021

ABSTRACTRestriction fragment length polymorphism (RFLP) is a technology for the molecular characterization of DNA and widely used genome mapping, medical genetics, molecular microbiology and forensics etc. Terminal restriction fragment length polymorphism (T-RFLP), a variant of RFLP is extensively used in environmental microbiology for the microbial community profiling based on the restriction digestion profile of marker gene (16S rRNA, FTHFS etc.) amplicons. At present, there is a lack of a tool which can perform in-silico restriction digestion of a large number of sequences at a time, in an interactive way and as an output produce sequences of the restriction fragments and visualization plot. I have developed a graphical user interface based software “REDigest” for the in-silico restriction digestion analysis for gene or genome sequences. The REDigest software program with a graphical user interface is freely available at https://github.com/abhijeetsingh1704/REDigest.
Combining dictionary- and rule-based approximate entity linking with tuned BioBERT
Authors: Mobasher Ghadeer , Mertová Lukrécia , Ghosh Sucheta , Krebs Olga , Heinlein Bettina , Müller Wolfgang 
Published: November 2021

AbstractChemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.
Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
Authors: Jiang Xiyuan , Ye Shuai , Sohrabpour Abbas , Bagić Anto , He Bin 
Published: November 2021

AbstractNon-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients’ interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.
Structural Basis for pH-Gating of the K+ Channel TWIK1 at the Selectivity Filter
Authors: Turney Toby S. , Li Vivian , Brohawn Stephen G. 
Published: November 2021

AbstractTWIK1 is a widely expressed pH-gated two-pore domain K+ channel (K2P) that contributes to cardiac rhythm generation and insulin release from pancreatic beta cells. TWIK1 displays unique properties among K2Ps including low basal activity and inhibition by extracellular protons through incompletely understood mechanisms. Here, we present cryo-EM structures of TWIK1 in lipid nanodiscs at high and low pH that reveal a novel gating mechanism at the K+ selectivity filter. At high pH, TWIK1 adopts an open conformation. At low pH, protonation of an extracellular histidine results in a cascade of conformational changes that close the channel by sealing the top of the selectivity filter, displacing the helical cap to block extracellular ion access pathways, and opening gaps for lipid block of the intracellular cavity. These data provide a mechanistic understanding for extracellular pH-gating of TWIK1 and show how diverse mechanisms have evolved to gate the selectivity filter of K+ channels.
Scalable estimation of microbial co-occurrence networks with Variational Autoencoders
Authors: Morton James T. , Silverman Justin , Tikhonov Gleb , Lähdesmäki Harri , Bonneau Rich 
Published: November 2021

AbstractEstimating microbe-microbe interactions is critical for understanding the ecological laws governing microbial communities. Rapidly decreasing sequencing costs have promised new opportunities to estimate microbe-microbe interactions across thousands of uncultured, unknown microbes. However, typical microbiome datasets are very high dimensional and accurate estimation of microbial correlations requires tens of thousands of samples, exceeding the computational capabilities of existing methodologies. Furthermore, the vast majority of microbiome studies collect compositional metagenomics data which enforces a negative bias when computing microbe-microbe correlations. The Multinomial Logistic Normal (MLN) distribution has been shown to be effective at inferring microbe-microbe correlations, however scalable Bayesian inference of these distributions has remained elusive. Here, we show that carefully constructed Variational Autoencoders (VAEs) augmented with the Isometric Log-ratio (ILR) transform can estimate low-rank MLN distributions thousands of times faster than existing methods. These VAEs can be trained on tens of thousands of samples, enabling co-occurrence inference across tens of thousands of microbes without regularization. The latent embedding distances computed from these VAEs are competitive with existing beta-diversity methods across a variety of mouse and human microbiome classification and regression tasks, with notable improvements on longitudinal studies.
Zymomonas mobilis ZM4 utilizes an acetaldehyde dehydrogenase to produce acetate
Authors: Felczak Magdalena M. , TerAvest Michaela A. 
Published: November 2021

AbstractZymomonas mobilis is a promising bacterial host for biofuel production but further improvement has been hindered because some aspects of its metabolism remain poorly understood. For example, one of the main byproducts generated by Z. mobilis is acetate but the pathway for acetate production is unknown. Acetaldehyde oxidation has been proposed as the major source of acetate and an acetaldehyde dehydrogenase was previously isolated from Z. mobilis via activity guided fractionation, but the corresponding gene has never been identified. We determined that the locus ZMO1754 (also known as ZMO_RS07890) encodes an NADP+-dependent acetaldehyde dehydrogenase that is responsible for acetate production by Z. mobilis. Deletion of this gene from the chromosome resulted in a growth defect in oxic conditions, suggesting that acetaldehyde detoxification is an important role of acetaldehyde dehydrogenase. The deletion strain also exhibited a near complete abolition of acetate production, both in typical laboratory conditions and during lignocellulosic hydrolysate fermentation. Our results show that ZMO1754 encodes the major acetaldehyde dehydrogenase in Z. mobilis and we therefore rename the gene aldB based on functional similarity to the Escherichia coli acetaldehyde dehydrogenase.ImportanceBiofuel production from non-food crops is an important strategy for reducing carbon emissions from the transportation industry but it has not yet become commercially viable. An important avenue to improve biofuel production is to enhance the characteristics of fermentation organisms by genetic engineering. To make genetic modifications successful, we must gain sufficient information about the genome and metabolism of the organism to enable rational design and engineering. Here, we improved understanding of Zymomonas mobilis, a promising biofuel producing bacterium, by identifying a metabolic pathway and associated gene that lead to byproduct formation. This information may be used in the future for genetic engineering to reduce byproduct formation during biofuel production.
SARS-CoV-2 Delta vaccine breakthrough transmissibility in Alachua, Florida
Authors: Magalis Brittany Rife , Rich Shannan , Tagliamonte Massimiliano S , Mavian Carla , Cash Melanie N , Riva Alberto , Marini Simone , Amador David Moraga , Zhang Yanping , Shapiro Jerne , Horine Amelia , Starostik Petr , Pieretti Maura , Vega Samantha , Lacombe Ana Paula , Salinas Jessica , Stevenson Mario , Myers Paul , Morris J. Glenn , Lauzardo Michael , Prosperi Mattia , Salemi Marco 
Published: November 2021

ABSTRACTBackgroundSARS-CoV-2 Delta variant has caused a dramatic resurgence in infections in the United Sates, raising questions regarding potential transmissibility among vaccinated individuals.MethodsBetween October 2020 and July 2021, we sequenced 4,439 SARS-CoV-2 full genomes, 23% of all known infections in Alachua County, Florida, including 109 vaccine breakthrough cases. Univariate and multivariate regression analyses were conducted to evaluate associations between viral load (VL) level and patient characteristics. Contact tracing and phylogenetic analysis were used to investigate direct transmissions involving vaccinated individuals.ResultsThe majority of breakthrough sequences with lineage assignment were classified as Delta variants (74.6%) and occurred, on average, about three months (104 ± 57.5 days) after full vaccination, at the same time (June-July 2021) of Delta variant exponential spread within the county. Six Delta variant transmission pairs between fully vaccinated individuals were identified through contact tracing, three of which were confirmed by phylogenetic analysis. Delta breakthroughs exhibited broad VL values during acute infection (IQR 1.2 – 8.64 Log copies/ml), on average 38% lower than matched unvaccinated patients (3.29 – 10.81 Log copies/ml, p<0.00001). Nevertheless, 49-50% of all breakthroughs, and 56-60% of Delta-infected breakthroughs exhibited VL above the transmissibility threshold (4 Log copies/ml) irrespective of time post vaccination.ConclusionsDelta infection transmissibility and general VL patterns in vaccinated individuals suggest limited levels of sterilizing immunity that need to be considered by public health policies. In particular, ongoing evaluation of vaccine boosters should address whether extra vaccine doses might curb breakthrough contribution to epidemic spread.