bluuebunny/crossref_metadata_2025_split huggingface dataset:
Opaganib in COVID-19 pneumonia: Results of a randomized, placebo-controlled Phase 2a trial
Authors: Winthrop Kevin L. , Skolnick Alan W. , Rafiq Adnan M. , Beegle Scott H. , Suszanski Julian , Koehne Guenther , Barnett-Griness Ofra , Bibliowicz Aida , Fathi Reza , Anderson Patricia , Raday Gilead , Eagle Gina , Ben-Yair Vered Katz , Minkowitz Harold S. , Levitt Mark L. , Gordon Michael S. 
Published: August 2021

ABSTRACTBackgroundOpaganib, an oral sphingosine kinase-2 inhibitor with antiviral and anti-inflammatory properties, was shown to inhibit SARS-CoV-2 replication in vitro. We thus considered that opaganib could be beneficial for moderate to severe COVID-19 pneumonia. The objective of the study was to evaluate the effect of opaganib on supplemental oxygen requirements, time to hospital discharge and its safety in COVID-19 pneumonia hospitalized patients requiring supplemental oxygen.MethodsThis Phase 2a, randomized, double-blind, placebo-controlled study was conducted between July and December 2020 in eight sites in the USA. Forty-two enrolled patients received opaganib (n=23) or placebo (n=19) added to standard of care for up to 14 days and were followed up for 28 days after their last dose of opaganib/placebo.ResultsThe relative decrease in total supplemental oxygen requirement from baseline to Day 14 was 61.6% in the opaganib versus 46.7% in the placebo arms. By Day 14, 50.0% of patients in the opaganib and 22.2% in the placebo group no longer required supplemental oxygen for at least 24 hours, while 86.4% and 55.6%, respectively, were discharged from hospital. The incidence of ≥ Grade 3 treatment-emergent adverse events was 17.4% and 33.3% in the opaganib and placebo groups, respectively. Three deaths occurred in each group.ConclusionsIn this proof-of-concept study, hypoxic, hospitalized patients receiving oral opaganib required less supplementary oxygen and had earlier hospital discharge, with no safety concerns arising. These findings support further evaluation of opaganib in this population.SummaryUpon receiving opaganib, patients with COVID-19 pneumonia who were hospitalized and required supplemental oxygen showed symptomatic clinical improvement compared to placebo, with less supplemental oxygen requirement, resulting in earlier hospital discharge, and no safety concerns arising.
The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States
Authors: Zhang Senqi , Sun Li , Zhang Daiwei , Li Pin , Liu Yue , Anand Ajay , Xie Zidian , Li Dongmei 
Published: August 2021

AbstractBackgroundMental health illness is a growing problem in recent years. During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media.ObjectiveIn this study, we aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the United States and infer the demographic composition of Twitter users who had mental health concerns.MethodsCOVID-19 related tweets from March 5th, 2020 to January 31st, 2021 were collected through Twitter streaming API using COVID-19 related keywords (e.g., “corona”, “covid19”, “covid”). By further filtering using mental health keywords (e.g., “depress”, “failure”, “hopeless”), we extracted mental health-related tweets from the US. Topic modeling using the Latent Dirichlet Allocation model was conducted to monitor users’ discussions surrounding mental health concerns. Demographic inference using deep learning algorithms (including Face++ and Ethnicolr) was performed to infer the demographic composition of Twitter users who had mental health concerns during the COVID-19 pandemic.ResultsWe observed a positive correlation between mental health concerns on Twitter and the COVID-19 pandemic in the US. Topic modeling showed that “stay-at-home”, “death poll” and “politics and policy” were the most popular topics in COVID-19 mental health tweets. Among Twitter users who had mental health concerns during the pandemic, Males, White, and 30-49 age group people were more likely to express mental health concerns. In addition, Twitter users from the east and west coast had more mental health concerns.ConclusionsThe COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males, White) were more likely to have mental health concerns during the COVID-19 pandemic.
Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract
Authors: Shams Boshra , Wang Ziqian , Roine Timo , Aydogan Baran , Vajkoczy Peter , Lippert Christoph , Picht Thomas , Fekonja Lucius S. 
Published: August 2021

AbstractAlong tract statistics enables white matter characterization using various diffusion MRI (dMRI) metrics. Here, we applied a machine learning (ML) method to assess the clinical utility of dMRI metrics along corticospinal tracts (CST), investigating whether motor glioma patients can be classified with respect to their motor status. The ML-based analysis included developing models based on support vector machine (SVM) using histogram-based measures of dMRI-based tract profiles (e.g., mean, standard deviation, kurtosis and skewness), following a recursive feature elimination (RFE) method based on SVM (SVM-RFE). Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% AUC). Incorporating the patients’ demographics and clinical features such as age, tumor WHO grade, tumor location, gender and resting motor threshold (RMT) into our designed models demonstrated that these features were not as effective as microstructural measures. The results revealed that ADC, FA and RD contributed more than other features to the model.
Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis
Authors: Blair David R , Hoffmann Thomas J , Shieh Joseph T 
Published: August 2021

AbstractClinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a rare disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis (CPA), a model-based approach that uses symptom data to infer latent quantitative traits that capture disease-related phenotypic variability. By applying this approach to 50 Mendelian diseases in two large cohorts of patients, we found that these quantitative traits reliably captured disease severity. We then conducted genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that was predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.
Pathway profiling of a novel SRC inhibitor, AZD0424, in combination with MEK inhibitors
Authors: Dawson John C , Munro Alison , Macleod Kenneth , Muir Morwenna , Timpson Paul , Williams Robert J , Frame Margaret , Brunton Valerie G , Carragher Neil O 
Published: August 2021

AbstractA more comprehensive understanding of how cells respond to drug intervention, the likely immediate signalling responses and how resistance may develop within different microenvironments allows us anticipate how cells adapt to targeted therapy enabling more informed prediction of rational drug combinations. The non-receptor tyrosine kinase SRC regulates many cellular signalling processes and pharmacological inhibition has long been a target of drug discovery projects for the treatment of cancer. Here we describe thein vitroandin vivocharacterisation of the small molecule SRC inhibitor, AZD0424. We show that AZD0424 potently inhibits the phosphorylation of tyrosine-416 of SRC (IC50 ∼ 100 nM) in many cancer cell lines; however inhibition of cell viability, via a G1 cell cycle arrest, was observed only in a sub-set of cancer cell lines in the low (on target) micromolar range. We profiled the changes in intracellular pathway signalling in cancer cells following exposure to AZD0424 and other targeted therapies using Reverse Phase Protein Array analysis. We demonstrate that SRC is activated in response to MEK inhibitor (trametinib or AZD6244)-treatment of KRAS mutant colorectal cell lines (HCT116 and DLD1) and that AZD0424 abrogates this. Cell lines treated with trametinib or AZD6244 in combination with AZD0424 revealed reduction of EGFR, FAK and SRC compensatory activation, and, synergistically inhibits cell viabilityin vitro. In vivo, trametinib-treatment of mice bearing HCT116 tumours increased phosphorylation of SRC on Tyr416, and when combined with AZD0424, inhibition of tumour growth is greater than trametinib alone. We also demonstrate that drug-induced resistance to trametinib is not re-sensitised by AZD0424 treatmentin vitro, likely as a result of multiple compensatory signalling mechanisms; however inhibition of SRC remains an effective way to block invasion of trametinib resistant tumour cells. These data imply that inhibiting SRC may offer a useful addition to MEK inhibitor combination strategies.
Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity
Authors: Tejavibulya Link , Peterson Hannah , Greene Abigail , Gao Siyuan , Rolison Max , Noble Stephanie , Scheinost Dustin 
Published: August 2021

AbstractHandedness influences differences in lateralization of language areas as well as dominance of motor and somatosensory cortices. However, differences in whole brain functional organization due to handedness have been relatively understudied beyond pre-specified networks of interest. Functional connectivity offers the ability to unravel differences in the functional organization of the whole brain. Here, we compared connectivity profiles of left- and right-handed individuals using data-driven parcellations of the whole brain. We explored differences in connectivity profiles of previously established regions of interest, and showed functional organization differences between primarily left- and primarily right-handed individuals in the motor, somatosensory, and language areas using functional connectivity. We then proceeded to investigate these differences in the whole brain and found that the functional organization of left- and right-handed individuals are not specific to regions of interest. In particular, we found that connections between and within-hemispheres and the cerebellum show distinct patterns of connectivity. Together these results shed light on regions of the brain beyond those traditionally explored that contribute to differences in the functional organization of left- and right-handed individuals.
dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using single cell time-course gene expression data
Authors: Xu Yu , Chen Jiaxing , Lyu Aiping , Cheung William K , Zhang Lu 
Published: August 2021

AbstractTime-course single-cell RNA sequencing (scRNA-seq) data have been widely applied to reconstruct the cell-type-specific gene regulatory networks by exploring the dynamic changes of gene expression between transcription factors (TFs) and their target genes. The existing algorithms were commonly designed to analyze bulk gene expression data and could not deal with the dropouts and cell heterogeneity in scRNA-seq data. In this paper, we developed dynDeepDRIM that represents gene pair joint expression as images and considers the neighborhood context to eliminate the transitive interactions. dynDeepDRIM integrated the primary image, neighbor images with time-course into a four-dimensional tensor and trained a convolutional neural network to predict the direct regulatory interactions between TFs and genes. We evaluated the performance of dynDeepDRIM on five time-course gene expression datasets. dynDeepDRIM outperformed the state-of-the-art methods for predicting TF-gene direct interactions and gene functions. We also observed gene functions could be better performed if more neighbor images were involved.
Direct multiplex recombinase polymerase amplification for rapid detection of Staphylococcus aureus and Pseudomonas aeruginosa in food
Authors: Tran Diem Hong , Tran Hau Thi , Pham Trang Nguyen Minh , Phung Huong Thi Thu 
Published: August 2021

AbstractFoodborne illness undermines human health by causing fever, stomachache and even lethality. Among foodborne bacterial pathogens, Staphylococcus aureus and Pseudomonas aeruginosa are of extraordinary significance which drive reasons of food and beverage poisoning in numerous cases. Today, PCR has been widely used to examine the presence of different foodborne pathogens. However, PCR requires specialized equipment and skillful personnel which limit its application in the field. Recently, there is an emerging of isothermal PCR methods in which the reactions occur at low and constant temperature, allowing their application in restricted-resource settings. In this work, multiplex Recombinase Polymerase Amplification (RPA) was used to simultaneously detect S. aureus and P. aeruginosa with high sensitivity and specificity. The limit detection of multiplex RPA was 10 and 30 fg/reaction of genomic DNAs of S. aureus and P. aeruginosa, respectively. Besides, the reaction time was reduced to only 25 minutes with a low incubation temperature of 39 °C. Markedly, multiplex RPA reactions succeeded to directly detect as low as 1 and 5 CFU/reaction of S. aureus and P. aeruginosa cells, respectively without the requirement of extracting DNA genome. Moreover, the multiplex RPA reliably detected the two foodborne bacteria in milk, fruit juice and bottled water samples. In general, the direct multiplex RPA described in this study is a rapid, simple, sensitive and efficient alternative tool that could be used to detect the presence of S. aureus and P. aeruginosa without the necessity of costly devices and high-trained staff.
Simple Model for Encoding Natural Images by Retinal Ganglion Cells with Nonlinear Spatial Integration
Authors: Liu Jian K. , Karamanlis Dimokratis , Gollisch Tim 
Published: August 2021

AbstractA central goal in sensory neuroscience is to understand the neuronal signal processing involved in the encoding of natural stimuli. A critical step towards this goal is the development of successful computational encoding models. For ganglion cells in the vertebrate retina, the development of satisfactory models for responses to natural visual scenes is an ongoing challenge. Standard models typically apply linear integration of visual stimuli over space, yet many ganglion cells are known to show nonlinear spatial integration, in particular when stimulated with contrast-reversing gratings. We here study the influence of spatial nonlinearities in the encoding of natural images by ganglion cells, using multielectrode-array recordings from isolated salamander and mouse retinas. We assess how responses to natural images depend on first- and second-order statistics of spatial patterns inside the receptive field. This leads us to a simple extension of current standard ganglion cell models. We show that taking not only the weighted average of light intensity inside the receptive field into account but also its variance over space can partly account for nonlinear integration and substantially improve response predictions of responses to novel images. We find that response predictions for salamander ganglion cell classes with large receptive fields profit most from including spatial contrast information. Finally, we demonstrate how this model framework can be used to assess the spatial scale of nonlinear integration. Our results underscore that nonlinear spatial stimulus integration in the salamander retina translates to stimulation with natural images. Furthermore, the introduced model framework provides a simple, yet powerful extension of standard models and may serve as a benchmark for the development of more detailed models of the nonlinear structure of receptive fields.Author SummaryFor understanding how sensory systems operate in the natural environment, an important goal is to develop models that capture neuronal responses to natural stimuli. For retinal ganglion cells, which connect the eye to the brain, current standard models often fail to capture responses to natural visual scenes. This shortcoming is at least partly rooted in the fact that ganglion cells may combine visual signals over space in a nonlinear fashion. We here show that a simple model, which not only considers the average light intensity inside a cell’s receptive field but also the variance of light intensity over space, can partly account for these nonlinearities and thereby improve current standard models. This provides an easy-to-obtain benchmark for modeling ganglion cell responses to natural images.
Single-embryo phosphoproteomics reveals the importance of intrinsic disorder in cell cycle dynamics
Authors: Valverde Juan M , Dubra Geronimo , van den Toorn Henk , van Mierlo Guido , Vermeulen Michiel , Heck Albert J.R. , Knipscheer Puck , Krasinska Liliana , Fisher Daniel , Altelaar Maarten 
Published: August 2021

SummarySwitch-like cyclin-dependent kinase (CDK)-1 activation is thought to underlie the abruptness of mitotic onset, but how CDKs can simultaneously phosphorylate many diverse substrates is unknown, and direct evidence for such phosphorylation dynamics in vivo is lacking. Here, we analysed protein phosphorylation states in single Xenopus embryos throughout synchronous cell cycles. Over a thousand phosphosites were dynamic in vivo, and assignment of cell cycle phases using egg extracts revealed hundreds of S-phase phosphorylations. Targeted phosphoproteomics in single embryos showed switch-like mitotic phosphorylation of diverse protein complexes. The majority of cell cycle-regulated phosphosites occurred in CDK consensus motifs, and 72% located to intrinsically disordered regions. Dynamically phosphorylated proteins, and documented substrates of cell cycle kinases, are significantly more disordered than phosphoproteins in general. Furthermore, 30-50% are components of membraneless organelles. Our results suggest that phosphorylation of intrinsically disordered proteins by cell cycle kinases, particularly CDKs, allows switch-like mitotic cellular reorganisation.
Re-polyadenylation occurs predominantly on maternal mRNA degradation intermediates during mammalian oocyte-to-embryo transition
Authors: Liu Yusheng , Zhang Yiwei , Nie Hu , Liu Zhonghua , Wang Jiaqiang , Lu Falong 
Published: August 2021

AbstractThe nascent mRNA transcribed in the nucleus is cleaved and polyadenylated before it is transported to the cytoplasm for translation1. Polyadenylation can also occur in the cytoplasm for post-transcriptional regulation, especially in neurons, oocytes and early embryos1,2. Recently, we revealed transcriptome-wide maternal mRNA cytoplasmic re-polyadenylation during the mammalian oocyte-to-embryo transition (OET)3-6. However, the mechanism of re-polyadenylation during mammalian OET, including the sites to be re-polyadenylated and the enzymes involved, is still poorly understood. Here, by analyzing the PAIso-seq1 and PAIso-seq2 poly(A) inclusive transcriptome data during OET in mice, rats, pigs, and humans, we reveal conserved re-polyadenylation of mRNA degradation intermediates. These re-polyadenylated mRNA degradation intermediates account for over half of the polyadenylated mRNA during OET in all four species. We find that mRNA degradation intermediates for re-polyadenylation are generated through Btg4-mediated deadenylation in both mouse and human. Interestingly, the poly(A) tails on the re-polyadenylated mRNA degradation intermediates are of different lengths and contain different levels of non-A residues compared to regular polyadenylation sites, suggesting specific regulation and function of these poly(A) tails in mammalian OET. Together, our findings reveal the maternal mRNA degradation intermediates as substrates for conserved cytoplasmic dominant re-polyadenylation during mammalian OET, and uncover the mechanism of production of these mRNA degradation intermediates. These findings provide new insights into mRNA post-transcriptional regulation, and a new direction for the study of mammalian OET.
Allosteric regulation of 3CL protease of SARS-CoV-2 and SARS-CoV observed in the crystal structure ensemble
Authors: Kidera Akinori , Moritsugu Kei , Ekimoto Toru , Ikeguchi Mitsunori 
Published: August 2021

AbstractThe 3C-like protease (3CLpro) of SARS-CoV-2 is a potential therapeutic target for COVID-19. Importantly, it has an abundance of structural information solved as a complex with various drug candidate compounds. Collecting these crystal structures (83 Protein Data Bank (PDB) entries) together with those of the highly homologous 3CLpro of SARS-CoV (101 PDB entries), we constructed the crystal structure ensemble of 3CLpro to analyze the dynamic regulation of its catalytic function. The structural dynamics of the 3CLpro dimer observed in the ensemble were characterized by the motions of four separate loops (the C-loop, E-loop, H-loop, and Linker) and the C-terminal domain III on the rigid core of the chymotrypsin fold. Among the four moving loops, the C-loop (also known as the oxyanion binding loop) causes the order (active)–disorder (collapsed) transition, which is regulated cooperatively by five hydrogen bonds made with the surrounding residues. The C-loop, E-loop, and Linker constitute the major ligand binding sites, which consist of a limited variety of binding residues including the substrate binding subsites. Ligand binding causes a ligand size dependent conformational change to the E-loop and Linker, which further stabilize the C-loop via the hydrogen bond between the C-loop and E-loop. The T285A mutation from SARS-CoV 3CLpro to SARS-CoV-2 3CLpro significantly closes the interface of the domain III dimer and allosterically stabilizes the active conformation of the C-loop via hydrogen bonds with Ser1 and Gly2; thus, SARS-CoV-2 3CLpro seems to have increased activity relative to that of SARS-CoV 3CLpro.
ZetaSuite, A Computational Method for Analyzing Multi-dimensional High-throughput Data, Reveals Genes with Opposite Roles in Cancer Dependency
Authors: Hao Yajing , Shao Changwei , Zhao Guofeng , Fu Xiang-Dong 
Published: August 2021

AbstractThe rapid advance of high-throughput technologies has enabled the generation of two-dimensional or even multi-dimensional high-throughput data, e.g., genome-wide siRNA screen (1st dimension) for multiple changes in gene expression (2nd dimension) in many different cell types or tissues or under different experimental conditions (3rd dimension). We show that the simple Z-based statistic and derivatives are no longer suitable for analyzing such data because of the accumulation of experimental noise and/or off-target effects. Here, we introduce ZetaSuite, a statistical package designed to score and rank hits from two-dimensional screens, construct regulatory networks based on response similarities, and eliminate off-targets. Applying this method to two large cancer dependency screen datasets, we identify not only genes critical for cell fitness, but also those required for constraining cell proliferation. Strikingly, most of those cancer constraining genes function in DNA replication/repair checkpoint, suggesting that cancer cells also need to protect their genomes for long-term survival.