bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Inference with Incomplete Knowledge Explains Perceptual Confidence and its Deviations from Accuracy
Authors: Khalvati Koosha , Kiani Roozbeh , Rao Rajesh P. N. 
Published: September 2020

AbstractIn perceptual decisions, subjects infer hidden states of the environment based on noisy sensory information. Here we show that both choice and its associated confidence are explained by a Bayesian framework based on partially observable Markov decision processes (POMDPs). We test our model on monkeys performing a direction-discrimination task with post-decision wagering, demonstrating that the model explains objective accuracy and predicts subjective confidence. Further, we show that the model replicates well-known discrepancies of confidence and accuracy, including the hard-easy effect, opposing effects of stimulus volatility on confidence and accuracy, dependence of confidence ratings on simultaneous or sequential reports of choice and confidence, apparent difference between choice and confidence sensitivity, and seemingly disproportionate influence of choice-congruent evidence on confidence. These effects may not be signatures of sub-optimal inference or discrepant computational processes for choice and confidence. Rather, they arise in Bayesian inference with incomplete knowledge of the environment.
Age and Sex Effects on Advanced White Matter Microstructure Measures in 15,628 Older Adults: A UK Biobank Study
Authors: Lawrence Katherine E. , Nabulsi Leila , Santhalingam Vigneshwaran , Abaryan Zvart , Villalon-Reina Julio E. , Nir Talia M. , Gari Iyad Ba , Zhu Alyssa H. , Haddad Elizabeth , Muir Alexandra M. , Laltoo Emily , Jahanshad Neda , Thompson Paul M. 
Published: September 2020

AbstractA comprehensive characterization of the brain’s white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.
Beware of UVC sanitizers: not all are good
Authors: Arines Justo , Bao-Varela Carmen 
Published: September 2020

ABSTRACTDisinfection is now one of the major concerns of society. Soap, or hydroalcohol are two known ways of sanitizing different objects. Now we can find in the market more sophisticated systems, which provide more confidence on their sanitizing effects, or that allows disinfection of objects that cannot be sanitized with soap or hydroalcoholic solutions. In this work we analyze a commercially available sanitizing device that claims the use of UVC radiation. We will show that this device is not suitable for complete disinfection of the objects introduced on the cabin. We provide spectral characterization of the sources, as well as irradiance measurements inside the cabin. We conclude that the cabin cannot be used for sanitizing most of the objects that are included in the documentation of the device.
The distribution of common-variant effect sizes
Authors: O’Connor Luke Jen 
Published: September 2020

AbstractThe genetic effect-size distribution describes the number of variants that affect disease risk and the range of their effect sizes. Accurate estimates of this distribution would provide insights into genetic architecture and set sample-size targets for future genome-wide association studies. We developed Fourier Mixture Regression (FMR) to estimate common-variant effect-size distributions from GWAS summary statistics. We validated FMR in simulations and in analyses of UK Biobank data, using interim-release summary statistics (max N=145k) to predict the results of the full release (N=460k). Analyzing summary statistics for 10 diseases (avg Neff=169k) and 22 other traits, we estimated the sample size required for genome-wide significant SNPs to explain 50% of SNP-heritability. For most diseases the requisite number of cases is 100k-1M, an attainable number; ten times more would be required to explain 90% of heritability. In well-powered GWAS, genome-wide significance is a conservative threshold, and loci at less stringent thresholds have true positive rates that remain close to 1 if confounding is controlled. Analyzing the shape of the effect-size distribution, we estimate that heritability accumulates across many thousands of SNPs with a wide range of effect sizes: the largest effects (at the 90thpercentile of heritability) are 100 times larger than the smallest (10thpercentile), and while the midpoint of this range varies across traits, its size is similar. These results suggest attainable sample size targets for future GWAS, and they underscore the complexity of genetic architecture.
Prophage-dependent neighbor predation fosters horizontal gene transfer by natural transformation
Authors: Molina-Quiroz Roberto C. , Dalia Triana N. , Camilli Andrew , Dalia Ankur B. , Silva-Valenzuela Cecilia A. 
Published: September 2020

ABSTRACTNatural transformation is a broadly conserved mechanism of horizontal gene transfer (HGT) in bacteria (1) that can shape their evolution through the acquisition of genes that promote virulence, antibiotic resistance, and other traits (2). Recent work has established that neighbor predation via Type VI secretion systems (3), bacteriocins (4) and virulent phages (5), play an important role in promoting HGT. Here, we demonstrate that in chitin estuary microcosms,Vibrio choleraeK139 lysogens exhibit prophage-dependent neighbor predation of non-lysogens to enhance HGT. Through predation of non-lysogens, K139 lysogens also have a fitness advantage in these microcosm conditions. The ecological strategy revealed by our work provides a better understanding of the evolutionary mechanisms used by bacteria to adapt in their natural setting and contributes to our understanding of the selective pressures that may drive prophage maintenance in bacterial genomes.IMPORTANCEProphages are nearly ubiquitous in bacterial species. These integrated phage elements have previously been implicated in horizontal gene transfer (HGT) largely through their ability to carry out transduction (generalized or specialized). Here, we show that prophage-encoded viral particles promote neighbor predation leading to enhanced HGT by natural transformation in the water-borne pathogenVibrio cholerae. Our findings contribute to a comprehensive understanding of the dynamic forces involved in prophage maintenance which ultimately drive the evolution of naturally competent bacteria in their natural environment.
How to use online tools to generate new hypotheses for mammary gland biology research: a case study forWnt7b
Authors: van de Grift Yorick Bernardus Cornelis , Heijmans Nika , van Amerongen Renée 
Published: September 2020

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Luckily, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach.Using regulation ofWnt7bas an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used forin silicoanalyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand thein silicotoolbox.
Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI
Authors: He Jianzhong , Zhang Fan , Xie Guoqiang , Yao Shun , Feng Yuanjing , Bastos Dhiego C. A. , Rathi Yogesh , Makris Nikos , Kikinis Ron , Golby Alexandra J. , O’Donnell Lauren J. 
Published: September 2020

AbstractThe retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. The RGVP has four subdivisions, including two decussating and two non-decussating pathways that cannot be identified on conventional structural magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for RGVP reconstruction. In this study, four tractography methods are compared, including constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) methods. Experiments use diffusion MRI data from 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Quantitative anatomical measurements and expert anatomical judgment are used to assess the advantages and limitations of the four tractography methods. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy and have the highest spatial overlap across subjects. Overall, we find that it is challenging for current tractography methods to both accurately track RGVP fibers that correspond to known anatomy and produce an approximately correct percentage of decussating fibers. We suggest that future algorithm development for RGVP tractography should take consideration of both of these two points.
Common genetic variation in humans impactsin vitrosusceptibility to SARS-CoV-2 infection
Authors: Dobrindt Kristina , Hoagland Daisy A. , Seah Carina , Kassim Bibi , O’Shea Callan P. , Iskhakova Marina , Fernando Michael B. , Deans P.J. Michael , Powell Samuel K. , Javidfar Ben , Murphy Aleta , Peter Cyril , Møeller Rasmus , Garcia Meilin Fernandez , Kimura Masaki , Iwasawa Kentaro , Crary John , Kotton Darrell N. , Takebe Takanori , Huckins Laura M. , tenOever Benjamin R. , Akbarian Schahram , Brennand Kristen J. 
Published: September 2020

ABSTRACTThe host response to SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, demonstrates significant inter-individual variability. In addition to showing more disease in males, the elderly, and individuals with underlying co-morbidities, SARS-CoV-2 can seemingly render healthy individuals with profound clinical complications. We hypothesize that, in addition to viral load and host antibody repertoire, host genetic variants also impact vulnerability to infection. Here we apply human induced pluripotent stem cell (hiPSC)-based models and CRISPR-engineering to explore the host genetics of SARS-CoV-2. We demonstrate that a single nucleotide polymorphism (rs4702), common in the population at large, and located in the 3’UTR of the protease FURIN, impacts alveolar and neuron infection by SARS-CoV-2in vitro. Thus, we provide a proof-of-principle finding that common genetic variation can impact viral infection, and thus contribute to clinical heterogeneity in SARS-CoV-2. Ongoing genetic studies will help to better identify high-risk individuals, predict clinical complications, and facilitate the discovery of drugs that might treat disease.
A network algorithm for the X chromosomal exact test for Hardy-Weinberg equilibrium with multiple alleles
Authors: Graffelman Jan , Ortoleva Leonardo 
Published: September 2020

AbstractStatistical methodology for testing Hardy-Weinberg equilibrium at X chromosomal variants has recently experienced considerable development. Up to a few years ago, testing X chromosomal variants for equilibrium was basically done by applying autosomal test procedures to females only. At present, male alleles can be taken into account in asymptotic and exact test procedures for both the bi- and multiallelic case. However, current X chromosomal exact procedures for multiple alleles rely on a classical full enumeration algorithm and are computationally expensive, and in practice not feasible for more than three alleles. In this article we extend the autosomal network algorithm for exact Hardy-Weinberg testing with multiple alleles to the X chromosome, achieving considerable reduction in computation times for multiallelic variants with up to five alleles. The performance of the X-chromosomal network algorithm is assessed in a simulation study. Beyond four alleles, a permutation test is, in general, the more feasible approach. A detailed description of the algorithm is given and examples of X chromosomal indels and microsatellites are discussed.
The transcription factor ZEB1 regulates stem cell self-renewal and astroglial fate in the adult hippocampus
Authors: Gupta B , Errington AC , Brabletz S , Stemmler MP , Brabletz T , Siebzehnrubl FA 
Published: September 2020

AbstractRadial glia-like (RGL) cells persist in the adult mammalian hippocampus where they give rise to new neurons and astrocytes throughout life. Many studies have investigated the process of adult neurogenesis, but factors deciding between neuronal and astroglial fate are incompletely understood. Here, we evaluate the functions of the transcription factor zinc finger E-box binding homeobox 1 (ZEB1) in adult hippocampal RGL cells using a conditional-inducible mouse model. We find that ZEB1 is necessary for self-renewal of active RGL cells as well as for astroglial lineage specification. Genetic deletion ofZeb1causes differentiation-coupled depletion of RGL cells resulting in an increase of newborn neurons at the expense of newly generated astrocytes. This is due to a shift towards symmetric cell divisions that consume the RGL cell and generate pro-neuronal progenies. We identify ZEB1 as a regulator of stem cell self-renewal and lineage specification in the adult hippocampus.
Fast and easy single-molecule pulldown assay based on agarose microbeads
Authors: Zhao Qirui , Shen Yusheng , Li Xiaofen , Tian Fang , Yu Xiaojie , Yobas Levent , Park Hyokeun , Huang Pingbo 
Published: September 2020

SUMMARYThe recently developed single-molecule pulldown (SiMPull) assay by Jain and colleagues is a highly innovative technique but its wide application is hindered by the high technical barrier and time consumption. We report an innovative, agarose microbead-based approach for SiMPull. We used commercially available, pre-surface-functionalized agarose microbeads to capture the protein of interest together with its binding partners specifically from cell extracts and observed these interactions under a microscope at the single-molecule level. Relative to the original method, microbead-based SiMPull is considerably faster, easier to use, and more reproducible and yet provides similar sensitivity and signal-to-noise ratio; specifically, with the new method, sample-preparation time is substantially decreased (from ∼10 to ∼3 h). These crucial features should facilitate wide application of powerful and versatile SiMPull in common biological and clinical laboratories. Notably, by exploiting the simplicity and ultrahigh sensitivity of microbead-based SiMPull, we used this method in the study of rare auditory hair cells for the first time.
Development of LSTM&CNN Based Hybrid Deep Learning Model to Classify Motor Imagery Tasks
Authors: Uyulan Caglar 
Published: September 2020

AbstractRecent studies underline the contribution of brain-computer interface (BCI) applications to the enhancement process of the life quality of physically impaired subjects. In this context, to design an effective stroke rehabilitation or assistance system, the classification of motor imagery (MI) tasks are performed through deep learning (DL) algorithms. Although the utilization of DL in the BCI field remains relatively premature as compared to the fields related to natural language processing, object detection, etc., DL has proven its effectiveness in carrying out this task. In this paper, a hybrid method, which fuses the one-dimensional convolutional neural network (1D CNN) with the long short-term memory (LSTM), was performed for classifying four different MI tasks, i.e. left hand, right hand, tongue, and feet movements. The time representation of MI tasks is extracted through the hybrid deep learning model training after principal component analysis (PCA)-based artefact removal process. The performance criteria given in the BCI Competition IV dataset A are estimated. 10-folded Cross-validation (CV) results show that the proposed method outperforms in classifying electroencephalogram (EEG)-electrooculogram (EOG) combined motor imagery tasks compared to the state of art methods and is robust against data variations. The CNN-LSTM classification model reached 95.62 % (±1.2290742) accuracy and 0.9462 (±0.01216265) kappa value for datasets with four MI-based class validated using 10-fold CV. Also, the receiver operator characteristic (ROC) curve, the area under the ROC curve (AUC) score, and confusion matrix are evaluated for further interpretations.
Forest fire survival in young, denseBetula ermaniistands on soil scarification sites
Authors: Hayamizu Masato , Nakata Yasutaka , Torita Hiroyuki 
Published: September 2020

AbstractA forest fire in a cool-temperate broad-leaved forest in northern Japan, from 26 May to 19 June 2019, provided an opportunity to examine its effects on young and dense birch (Betula ermaniiCham.) stands in soil scarification sites. To characterise post-fire responses (survival and resprouting) of birch, we set up two plots, 6 months post fire. We investigated trunk diameter at breast height and burn marks on tree trunks (scorch height and charring percentage around the tree bole) of allB. ermaniitrees in both plots. Survival and resprouting of each tree were monitored over 2 years (6 and 16 months post fire). To quantify post-fire vegetation recovery in the forest floor, we manually mapped the dominant understory plant, dwarf bamboo (i.e.Sasa kurilensis(Rupr.) Makino et Shibata), from orthomosaic images obtained by an unmanned aircraft vehicle, and estimated the recovery rate in the second year post fire. Additionally, seedlings of woody species were counted in both plots. Size-dependent survival rates of plants in both plots were similar in the first year post fire. AllB. ermaniitrees died without resprouting in the second year post fire, indicating the lethal effects of fire on young birch trees. Moreover, a high recovery rate of dwarf bamboos over 2 years in both plots and limited seedling establishment of woody plants suggest that the fire resulted in regeneration failure of young stands in the scarification sites. On the basis of these findings, we propose future management of stands in soil scarification sites post fire, considering the vulnerability of young trees and the rapid change in vegetation from young forest to dense birch cover post fire.
Global Profiling of the Lysine Crotonylome in Different Pluripotent States
Authors: Lv Yuan , Bu Chen , Meng Jin , Ward Carl , Volpe Giacomo , Hu Jieyi , Jiang Mengling , Guo Lin , Chen Jiekai , Esteban Miguel A. , Bao Xichen , Cheng Zhongyi 
Published: September 2020

AbstractPluripotent stem cells (PSCs) can be expandedin vitroin different culture conditions, resulting in a spectrum of cell states with distinct properties. Understanding how PSCs transition from one state to another, ultimately leading to lineage-specific differentiation, is important for developmental biology and regenerative medicine. Although there is significant information regarding gene expression changes controlling these transitions, less is known about post-translational modifications of proteins. Protein crotonylation is a newly discovered post-translational modification where lysine residues are modified with a crotonyl group. Here, we employed affinity purification of crotonylated peptides and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to systematically profile protein crotonylation in mouse PSCs in different states including ground, metastable and primed state, as well as metastable PSCs undergoing early pluripotency exit. We successfully identified 3628 high-confidence sites in 1426 proteins. These crotonylated proteins are enriched for factors involved in functions related to pluripotency such as RNA biogenesis, central carbon metabolism and proteasome function. Moreover, we found that increasing the cellular levels of crotonyl-CoA through crotonic acid treatment promotes proteasome activity in metastable PSCs and delays their differentiation, consistent with previous observations showing that enhanced proteasomal activity helps to sustain pluripotency. Our atlas of protein crotonylation will be valuable for further studies of pluripotency regulation and may also provide insights into the role of metabolism in other cell fate transitions.
Critical Interactions Between the SARS-CoV-2 Spike Glycoprotein and the Human ACE2 Receptor
Authors: Taka Elhan , Yilmaz Sema Z. , Golcuk Mert , Kilinc Ceren , Aktas Umut , Yildiz Ahmet , Gur Mert 
Published: September 2020

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human cells upon binding of its spike (S) glycoproteins to ACE2 receptors and causes the coronavirus disease 2019 (COVID-19). Therapeutic approaches to prevent SARS-CoV-2 infection are mostly focused on blocking S-ACE2 binding, but critical residues that stabilize this interaction are not well understood. By performing all-atom molecular dynamics (MD) simulations, we identified an extended network of salt bridges, hydrophobic and electrostatic interactions, and hydrogen bonding between the receptor-binding domain (RBD) of the S protein and ACE2. Mutagenesis of these residues on the RBD was not sufficient to destabilize binding but reduced the average work to unbind the S protein from ACE2. In particular, the hydrophobic end of RBD serves as the main anchor site and unbinds last from ACE2 under force. We propose that blocking the hydrophobic surface of RBD via neutralizing antibodies could prove an effective strategy to inhibit S-ACE2 interactions.