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SummaryWe present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with millions of cells.Availability and implementationNewWave is implemented as an open-source R package available through the Bioconductor project at https://bioconductor.org/packages/NewWave/Supplementary informationSupplementary data are available at Bioinformatics online.

SummaryPHIST (Phage-Host Interaction Search Tool) predicts prokaryotic hosts of viruses from their genomic sequences. It improves host prediction accuracy at species level over current alignment-based tools (on average by 3 percentage points) as well as alignment-free and CRISPR-based tools (by 14–20 percentage points). PHIST is also two orders of magnitude faster than alignment-based tools making it suitable for metagenomics studies.Availability and implementationGNU-licensed C++ code wrapped in Python API available at: https://github.com/refresh-bio/phistContactandrzej.zielezinski@amu.edu.pl, adam.gudys@polsl.plSupplementary informationSupplementary data are available at publisher Web site.

Статья продолжает цикл работ о методике сознательной реферативной деятельности иностранных студентов при обучении фармации на русском языке. Внимание автора сосредоточено на реферате-резюме, требующем серьезной подготовки во время анализа и синтеза необходимой информации при максимальной компрессии аутентичного первоисточника, где максимально сохраняется основной интерес автора во вторичном тексте. В этом типе реферата указывается на аргументированный выбор нужного вещества/препарата в достижении актуальной лекарственной цели у конкретных пациентов в условиях стационара при наличии определенных преимущественно позитивных результатов терапии без побочного действия либо с таковым минимальным. При составлении реферата-резюме следует ознакомиться с композицией основных видов научной литературы, указав лишь значимую/новую информацию текста. Изучая основы реферирования как речевой деятельности, важно понять его сущность. Необходимо отличать реферат-резюме среди других рефератов, знать требования к нему. Для практического овладения схемой составления реферата-резюме предложен дифференциальный алгоритм чтения с выделением ключевых слов, актуальной темы и проблемы, композиции в соответствии с анализируемыми разделами текста, авторской или принятой методикой исследования, полученным результатам. После первичного прочтения текста оригинала составляется типовой план-схема для написания реферата-резюме по композиции первоисточника. Выполняется система типовых заданий по составлению реферата-резюме, с целью формирования правильного представления о выполнении демонстрируются готовые образцы в ключах для самоконтроля. Важным моментом оформления являются специальные языковые клише: тренинг их употребления в рефератах требует определенного времени в практической деятельности обучаемых студентов. Делается вывод, что при составлении реферата-резюме студенты-фармацевты логически и творчески передают без оценки и интерпретаций основное содержание первоисточника, кратко определяют его идею, обеспечивают достаточное представление о предмете коммуникации в иноязычной компетенции. The article continues a series of works on the methodology of conscious abstracting activities of foreign students in teaching pharmacy in Russian. The author's attention is focused on the abstract-summary, which requires serious preparation during the analysis and synthesis of the necessary information with maximum compression of the authentic primary source. This type of essay indicates the reasoned choice of the desired substance / preparation in achieving the actual medicinal goal in specific patients in a hospital with certain predominantly positive results of therapy with no side effects or with such minimal. When compiling an abstract-summary, you should familiarize yourself with the composition of the main types of scientific literature, indicating only significant / new information of the text. Studying the basics of abstracting as a speech activity, it is important to understand its essence. It is necessary to distinguish the abstract-summary among other abstracts, to know the requirements for it. For practical mastery of the abstract compilation scheme, a differential reading algorithm with the selection of keywords, the current topic and problem, composition in accordance with the analyzed sections of the text, the author's or accepted research methodology, and the results are proposed. After the initial reading of the text of the original, a typical plan is compiled for writing an abstract-summary on the composition of the source. A system of standard tasks for compiling an abstract-summary is being carried out, with the aim of forming the correct idea of the implementation of which ready-made samples in keys for self-control are demonstrated. An important aspect of the design is the special language clichés, the training of their use in essays requires a certain time in the practical activities of students. It is concluded that in the preparation of the abstract-summary, student-pharmacists logically and creatively convey, without evaluation and interpretation, the main content of the primary source, briefly define its idea, provide a sufficient idea of the subject of communication in foreign language competence.

Summary of background data Despite a good understanding of the natural history of spinal synovial cysts (SCs), a widespread agreement regarding their optimal management is still lacking. This is particularly true for SCs occurring at the C1-C2 level, which are rare, but oftentimes lead to a rapidly evolving cervical myelopathy. Methods We report a series of 4 patients (M:F ratio = 1:1; mean age 63.5 years) presenting with progressive cervical myelopathy secondary to ventrally located C1-C2 SCs. All patients underwent a postero-lateral facet-sparing intradural approach with total excision of the SCs. Functional status was assessed pre- and postoperatively with Nurick scale and the modified Japanese Orthopaedic association grading. Furthermore we conducted a systematic review, following PRISMA guidelines of pertinent literature to contextualize the options for surgical management of such lesions. Results Complete excision of the SCs was confirmed radiologically and on histological analysis. All measures of functional status improved post-operatively, and no cyst recurrence or need for instrumented fusion were noted during follow up (range from 22 to 88 months). Conclusion Our experience suggests that the facet-sparing intradural approach provides excellent clinical outcomes without causing any C1–C2 instability. This is in keeping with the take home message emerging from our literature review, which confirms that treatment should aim at radical resection of SCs while minimizing the risk of postoperative instability.

Summary labor pain is described as the most severe pain experienced ever by most women where majority of parturients complained their pain as severe or extremely severe. This stressful condition leads to negative impacts on maternal and fetal physiology. Optimal method of evidence-based management of pain in laboring mothers remains in debate. There is variety of controversial approaches based on different evidences. Therefore, it is important to review recent articles to recommend a relatively safe method that is feasible in our clinical set up to provide appropriate method of labor pain management. The objective of this review was to indicate safer options of labor pain management that help improve maternal care regarding pain management. Methods Google Scholars, PubMed through HINARI, and other search engines were used to search high quality evidences that help to reach appropriate conclusions. Discussion Compared with other techniques, Epidural analgesia is acknowledged as the most effective and the gold standard of labor pain management. Even though epidural analgesia was thought to prolong second stage of labor and increase the rate of instrumental delivery, recent studies have proved that duration of labor and incidence of instrumental delivery is comparable between those who receive epidural and parenteral opioids, there was less neonatal depression, better maternal satisfaction and no increased risk of the rate of cesarean section during labor epidural. Conclusion In the absence of a medical contraindication, maternal request is a sufficient indication for pain relief during labor. The challenge of labor pain management is the choice of the technique. The management should be guided by a thorough evaluation to identify indications and contraindications, and the technique of management should be safe for both the mother and the fetus.

Summary Single-cell sequencing is an increasingly used technology and has promising applications in basic research and clinical translations. However, genotyping methods developed for bulk sequencing data have not been well adapted for single-cell data, in terms of both computational parallelization and simplified user interface. Here, we introduce a software, cellsnp-lite, implemented in C/C++ and based on well-supported package htslib, for genotyping in single-cell sequencing data for both droplet and well-based platforms. On various experimental datasets, it shows substantial improvement in computational speed and memory efficiency with retaining highly concordant results compared to existing methods. Cellsnp-lite, therefore, lightens the genetic analysis for increasingly large single-cell data. Availability and implementation The source code is freely available at https://github.com/single-cell-genetics/cellsnp-lite. Supplementary information Supplementary data are available at Bioinformatics online.

Motivation We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. Results We present multiTFA, a Python implementation of our framework. We evaluated our application using the core Escherichia coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. Availability and implementation Our framework along with documentation is available on https://github.com/biosustain/multitfa. Supplementary information Supplementary data are available at Bioinformatics online.

Background Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. Summary We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat’s capabilities by analyzing a peripheral blood mononuclear cell dataset. Conclusions Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.

SummaryPrincipal component analysis (PCA) is widely used in analyzing single-cell genomic data. Selecting the optimal number of PCs is a crucial step for downstream analyses. The elbow method is most commonly used for this task, but it requires one to visually inspect the elbow plot and manually choose the elbow point. To address this limitation, we developed six methods to automatically select the optimal number of PCs based on the elbow method. We evaluated the performance of these methods on real single-cell RNA-seq data from multiple human and mouse tissues. The perpendicular line method with 20 PCs has the best overall performance, and its results are highly consistent with the numbers of PCs identified manually. We implemented the six methods in an R package, findPC, that objectively selects the number of PCs and can be easily incorporated into any automatic analysis pipeline.Availability and ImplementationfindPC R package is freely available at https://github.com/haotian-zhuang/findPCContactzhicheng.ji@duke.eduSupplementary informationSupplementary data are available at Bioinformatics online.

SummaryMinoTour offers a LIMS system for Oxford Nanopore Technology (ONT) sequencers, with real-time metrics and analysis available permanently for review. Integration of unique real-time automated analysis can reduce the time required to answer biological questions, including mapping and classification of sequence whilst a run is in progress. Real-time sequence data requires new methods of analysis which do not wait for the completion of a run and MinoTour provides a framework to allow users to exploit these features.Availability and ImplementationSource code and documentation are available at https://github.com/LooseLab/minotourcli and https://github.com/LooseLab/minotourapp. Docker images are available from https://hub.docker.com/r/adoni5/, and can be installed using a preconfigured docker-compose script at https://github.com/LooseLab/minotour-docker. An example server is available at http://137.44.59.170.

SummaryA key aspect of microbiome research is analysis of longitudinal dynamics using time series data. A method to visualize both the proportional and absolute change in the abundance of multiple taxa across multiple subjects over time is needed. We developed BiomeHorizon, an open-source R package that visualizes longitudinal compositional microbiome data using horizon plots.Availability and ImplementationBiomeHorizon is available at https://github.com/blekhmanlab/biomehorizon/ and released under the MIT license. A guide with step-by-step instructions for using the package is provided at https://blekhmanlab.github.io/biomehorizon/. The guide also provides code to reproduce all plots in this manuscript.Contactlgrienei@umn.edu, blekhman@umn.edu, iafink@uchicago.eduSupplementary informationNone

SummaryAs the amount of three-dimensional chromosomal interaction data continues to increase, storing and accessing such data efficiently becomes paramount. We introduce Pairs, a block-compressed text file format for storing paired genomic coordinates from Hi-C data, and Pairix, an open-source C application to index and query Pairs files. Pairix (also available in Python and R) extends the functionalities of Tabix to paired coordinates data. We have also developed PairsQC, a collapsible HTML quality control report generator for Pairs files.AvailabilityThe format specification and source code are available at https://github.com/4dn-dcic/pairix, https://github.com/4dn-dcic/Rpairix and https://github.com/4dn-dcic/pairsqc.Contactpeter_park@hms.harvard.edu or burak_alver@hms.harvard.edu

SummaryepiRomics is an R package designed to integrate multi-omics data in order to identify and visualize enhancer regions alongside gene expression and other epigenomic modifications. Regulatory network analysis can be done using combinatory approaches to infer regions of significance such as enhancers, when combining ChIP and histone data. Downstream analysis can identify co-occurrence of these regions of interest with other user-supplied data, such as chromatin availability or gene expression. Finally, this package allows for results to be visualized at high resolution in a stand-alone browser.Availability and ImplementationepiRomics is released under Artistic-2.0 License. The source code and documents are freely available through Github (https://github.com/Huising-Lab/epiRomics).Contactammawla@ucdavis.edu or mhuising@ucdavis.eduSupplementary informationSupplementary data, and methods are available online on biorxiv or Github.

Summary Both dynamic correlations in protein sidechain motions during molecular dynamics (MD) simulations and evolutionary correlations in multiple sequence alignments (MSAs) of homologous proteins may reveal functionally important residues. We developed the R package Bios2cor that provides a unique framework to investigate and, possibly, integrate both analyses. Bios2cor starts with an MSA or an MD trajectory and computes correlation/covariation scores between positions in the MSA or between sidechain dihedral angles or rotamers in the MD trajectory. In addition, Bios2cor provides a variety of tools for the analysis, the visualization and the interpretation of the data. Availability and implementation The R package Bios2cor is available from the Comprehensive R Archive Network, at https://CRAN.R-project.org/package=Bios2cor.

While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack a deep analysis of sex as a variable in this context. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness. Furthermore, MetaFun can be used to perform case-control meta-analyses, allowing researchers with basic programming skills to access this methodology.Availability and implementationMetaFun is freely available athttp://bioinfo.cipf.es/metafunThe back end was implemented in R and Java, and the front end was developed using AngularContactfgarcia@cipf.es,mhidalgo@cipf.esSupplementary informationR code available athttps://gitlab.com/ubb-cipf/metafunr

International audience; The objective of the Motiv@Dom project is to create motivational and enjoyable solutions to help seniors to practice an adapted OR appropriate physical activity at home. Faithful to the Living Lab approach, this project has adopted a user-centered and participative strategy. The users are involved throughout the design process of the Motiv@Dom solution, from the first ideas to the evaluation of the final product. In fact, we do our designing not only by placing the user at the center of our work, but above all “with the seniors” and “for the seniors”, giving them a role just as important as the other actors of Living Lab, such as technology developers, geriatric specialists and professionals of adapted physical activity.

SummaryAccurate and efficient compound annotation is a long-standing challenge for LC−MS-based data (e.g. untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developed metID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation. metID is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials.Availability and implementationhttps://jaspershen.github.io/metID/.Contactjiangzhu@sioc.ac.cn and mpsnyder@stanford.edu

SummaryThe analysis of mutational signatures is becoming increasingly common in cancer genetics, with emerging implications in cancer evolution, classification, treatment decision and prognosis. Recently, several packages have been developed for mutational signature analysis, with each using different methodology and yielding significantly different results. Because of the nontrivial differences in tools’ refitting results, researchers may desire to survey and compare the available tools, in order to objectively evaluate the results for their specific research question, such as which mutational signatures are prevalent in different cancer types. There is a need for a software that can aggregate results from different refitting packages and present them in a user-friendly way to facilitate effective comparison of mutational signatures.Availability and implementationMetaMutationalSigs is implemented using R and python and is available for installation using Docker and available at: https://github.com/EESI/MetaMutationalSigsContactGail Rosen (glr26@drexel.edu).Supplementary informationMore information about the package including test data and results are available at https://github.com/EESI/MetaMutationalSigs

SummaryExtremely large datasets are impossible or very difficult for humans to comprehend by standard mental approaches. Intuitive visualization of genetic variants in genomic sequencing data could help in the review and confirmation process of variants called by automated variant calling programs. To help facilitate interpretation of genetic variant next-generation sequencing (NGS) data we developed VisVariant, a customizable visualization tool that creates a figure showing the overlapping sequence information of thousands of individual reads including the variant and flanking regions.Availability and implementationDetailed information on how to download, install and run VisVariant together with an example is available on our github website [https://github.com/hugging-biorxiv/visvariant].

Summary The self-reporting voice-related quality of life (V-RQOL) instrument has been viewed as a modular index of quality of life for speakers using tracheoesophageal, esophageal (ES), or electrolaryngeal speech. However, V-RQOL has never been studied with pneumatic artificial laryngeal (PA) individuals. This study attempted to quantify the self-assessed voice-related performance of PA and ES speakers in Taiwan via the V-RQOL questionnaire, and further to compare the results for PA and ES speakers. Methods V-RQOL was assessed in 79 PA and 25 ES speakers undergoing total laryngectomy without using tracheoesophageal puncture. Data were collected from members of Taiwan's Association of Laryngectomees. Results There was no significant difference between PA and ES participants in social-emotional, physical functioning and total scores, suggesting both may consider their quality of life comparable with each other. In ES participants, there was a significant effect of time after total laryngectomy in physical functioning and total scores. Conclusions PA speakers did not exhibit more dissatisfaction or disability than ES speakers on 10 statements in the V-RQOL, but after total laryngectomy the ES have been shown to improve over time. Information on the experience of PA and ES speakers could be used by clinicians to inform patients of potential outcomes, and help them select suitable rehabilitation techniques.

SummaryGenome-scale metabolic networks have been reconstructed for hundreds of organisms over the last two decades, with wide-ranging applications, including the identification of drug targets. Constraint-based approaches such as flux balance analysis have been effectively used to predict single and combinatorial drug targets in a variety of metabolic networks. We have previously developed Fast-SL, an efficient algorithm to rapidly enumerate all possible synthetic lethals from metabolic networks. Here, we introduce CASTLE, an online standalone database, which contains synthetic lethals predicted from the metabolic networks of over 130 organisms. These targets include single, double or triple lethal set of genes and reactions, and have been predicted using the Fast-SL algorithm. The workflow used for building CASTLE can be easily applied to other pathogenic models and used to identify novel therapeutic targets.AvailabilityCASTLE is available at https://ramanlab.github.io/CASTLE/Contactkraman@iitm.ac.in

SummaryRecently, novel representation learning algorithms have shown potential for predicting molecular properties. However, unified frameworks have not yet emerged for fairly measuring algorithmic progress, and experimental procedures of different representation models often lack rigorousness and are hardly reproducible. Herein, we have developed MolRep by unifying 16 state-of-the-art models across 4 popular molecular representations for application and comparison. Furthermore, we ran more than 12.5 million experiments to optimize hyperparameters for each method on 12 common benchmark data sets. As a result, CMPNN achieves the best results ranked the 1st in 5 out of 12 tasks with an average rank of 1.75. Relatively, ECC has good performance in classification tasks and MAT good for regression (both ranked 1st for 3 tasks) with an average rank of 2.71 and 2.6, respectively.AvailabilityThe source code is available at:https://github.com/biomed-AI/MolRepSupplementary informationSupplementary data are available online.

SummaryWe developed Quickomics, a feature-rich R Shiny-powered tool to enable biologists to fully explore complex omics statistical analysis results and perform advanced analysis in an easy-to-use interactive interface. It covers a broad range of secondary and tertiary analytical tasks after primary analysis of omics data is completed. Each functional module is equipped with customizable options and generates both interactive and publication-ready plots to uncover biological insights from data. The modular design makes the tool extensible with ease.AvailabilityResearchers can experience the functionalities with their own data or demo RNA-Seq and proteomics datasets by using the app hosted at http://quickomics.bxgenomics.com and following the tutorial, https://bit.ly/3rXIyhL. The source code under GPLv3 license is provided at https://github.com/interactivereport/Quickomics for local installation.Supplementary informationSupplementary materials are available at https://bit.ly/37HP17g.

SummarySynthetic microbial communities (SynComs) constitute an emerging and powerful tool in biological, biomedical, and biotechnological research. Despite recent advances in algorithms for the analysis of culture-independent amplicon sequencing data from microbial communities, there is a lack of tools specifically designed for analysing SynCom data, where reference sequences for each strain are available. Here we present Rbec, a tool designed for the analysis of SynCom data that accurately corrects PCR and sequencing errors in amplicon sequences and identifies intra-strain polymorphic variation. Extensive evaluation using mock bacterial and fungal communities show that our tool outperforms current methods for samples of varying complexity, diversity, and sequencing depth. Furthermore, Rbec also allows accurate detection of contaminants in SynCom experiments.Availability and implementationRbec is freely available as an open-source multi-platform R package. Release versions can be obtained via Bioconductor. The developer version is maintained and can be downloaded at: https://github.com/PengfanZhang/Rbec.Contactgarridoo@mpipz.mpg.de

SummaryWe developed PyLAE - a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimation of many parameters, it can process thousands of genomes within a day. Computational efficiency, straightforward presentation of results, and an ease of installation makesPyLAEa useful tool to study admixed populations.Availability and implementationThe source code and installation manual are available athttps://github.com/smetam/pylae.

SummaryGenes involved in biological pathways are often collocalised in gene clusters, the comparison of which can give valuable insights into their function and evolutionary history. However, comparison and visualisation of gene cluster homology is a tedious process, particularly when many clusters are being compared. Here, we present clinker, a Python based tool, and clustermap.js, a companion JavaScript visualisation library, which used together can automatically generate accurate, interactive, publication-quality gene cluster comparison figures directly from sequence files.Availability and ImplementationSource code and documentation for clinker and clustermap.js is available on GitHub (github.com/gamcil/clinker and github.com/gamcil/clustermap.js, respectively) under the MIT license. clinker can be installed directly from the Python Package Index via pip.ContactE-mail: cameron.gilchrist@research.uwa.edu.au, yitheng.chooi@uwa.edu.au

SummaryQuantitative, reverse transcription polymerase chain reaction (qRT-PCR) has been the gold-standard tool for viral detection during the SARS-CoV-2 pandemic. However, the desperate rush for a quick diagnosis led the use of very different types of machines and proprietary software, leading to an unbearable complexity of data analysis with a limited parameter setup. Here, we present shinyCurves, a shiny web application created to analyse multisource qPCR amplification data from independent multi-plate format. Furthermore, our automated system allows the classification of the results as well as the plot of both amplification and melting curves. Altogether, our web application is an automated qPCR analysis resource available to the research community.AvailabilityThe shinyCurves web application to analyze multisource qPCR amplification data is publicly available under CC license (CC BY-NC-SA 4.0) at https://biosol.shinyapps.io/shinycurves/ and https://github.com/biosol/shinyCurves.

SummaryData sparsity in single-cell experiments prevents an accurate assessment of gene expression when visualised in a low-dimensional space. Here, we introduce Nebulosa, an R package that uses weighted kernel density estimation to recover signals lost through drop-out or low expression.Availability and implementationNebulosa can be easily installed from www.github.com/powellgenomicslab/Nebulosa

SummaryContamination from present-day DNA is a fundamental issue when studying ancient DNA from historical or archaeological material, and quantifying the amount of contamination is essential for downstream analyses. We present AuthentiCT, a command-line tool to estimate the proportion of present-day DNA contamination in ancient DNA datasets generated from single-stranded DNA libraries. The prediction is based solely on the patterns of post-mortem damage observed on ancient DNA sequences. The method has the power to quantify contamination from as few as 10,000 mapped sequences, making it particularly useful for analysing specimens that are poorly preserved or for which little data is available.Contactstephane.peyregne@gmail.com

SummaryThe proposed study will identify microbial communities associated with flare ups and remissions of MEBO (systemic malodor of metabolic origin) or PATM (“People allergic to me”) conditions.BackgroundHuman odor-prints, mostly owing to the microbiome, have proven their value as biomarkers of health and environmental exposures.In recent years, microbial networks responsible for localized malodors (e.g., halitosis [1,2], groin area, foot and axillary odor [3,4]) have been mapped by using next generation sequencing approaches.Intestinal microbes responsible for psychologically debilitating systemic malodor (whole-body and extraoral halitosis), however, remain to be identified. Even a relatively straightforward disorder of choline metabolism trimethylaminuria (TMAU) is thought to exhibit complex host-gene microbiome interactions [5] and has not been sufficiently studied.Mapping gut microbiome is needed to understand human metabolic disfunction, make proper dietary recommendations and develop targeted treatments such as microbial therapies [6–8]. Our preliminary analysis of culture-, PCR- and 16S-RNA-based data found several Operational Taxonomic Units (OTUs) potentially linked to systemic malodor. Proposed controlled pilot study will provide a more comprehensive evaluation and, combined with our prior data [9–12], will help to develop new therapies and treatments.

Surgery for degenerative lumbar spondylolisthesis (DLS) has traditionally been indicated for patients with neurogenic claudication. Surgery improves patients' disability and lower extremity symptoms, but less is known about the impact on back pain.To evaluate changes in back pain after surgery and identify factors associated with these changes in surgically-treated DLS.Retrospective review of prospectively collected data.There were 486 consecutive patients with surgically-treated DLS who were enrolled in the Canadian Spine Outcomes Research Network prospective registry and identified for this study. Patients had demographic data, clinical information, disability (Oswestry Disability Index), and back pain rating scores collected prospectively at baseline, and 12 months follow-up RESULTS: Of the 486 DLS patients, 376 (77.3%) were successfully followed at 12 months. Mean age at baseline was 66.7 (standard deviation [SD] 9.2) years old, and 63% were female. Back pain improved significantly at 12 months, compared with baseline (p.001). Improvement in Numeric Rating Scale (NRS)-back pain ratings was on average 2.97 (SD 2.5) points at one year and clinically significant improvement in back pain was observed in 75% of patients (minimal clinically important difference (MCID) NRS-Pain 1.2 points). Multivariable logistic regression revealed five factors associated with meeting MCID NRS-back pain at 12 month follow up: higher baseline back pain, better baseline physical function (higher SF-12 Physical Component Score), symptoms duration less than 1 to 2 years, and having no intraoperative adverse events.Back pain improved significantly for patients treated surgically for DLS at 1-year follow-up.

SummaryMASTER is a previously published algorithm for protein sub-structure search. Given a database of protein structures and a query structural motif, composed of multiple disjoint segments, it finds all sub-structures from the database that align onto the query to within a pre-specified backbone root-mean-square deviation. Here, we present an improved version of the algorithm, MASTER v.2, in the form of an open-source C++ Application Program Interface library, thereby providing programmatic access to structure search functionality. An entirely reorganized approach to database representation now enables large structural databases to be stored in memory, further simplifying development of automated search-based methods. Given the increasingly important role of structure-based data mining, our improved implementation should find ample uses in structural biology applications.AvailabilityMASTER is available at https://grigoryanlab.org/master/master-v2.php.Contactgevorg.grigoryan@dartmouth.edu

SummaryBrain extracellular matrix (ECM) structure mediates many aspects of neuronal function. Probing changes in ECM structure could provide insights into aging and neurological disease. Herein, we demonstrate the ability to characterize changes in brain ECM structure using multiple particle tracking (MPT). MPT was carried out in organotypic rat brain slices to detect induced and naturally occurring changes in ECM structure. Induced degradation of neural ECM led to a significant increase in nanoparticle diffusive ability in the brain extracellular space. For structural changes that occur naturally during development, an inverse relationship existed between age and nanoparticle diffusion. Using the age-dependent dataset, we applied extreme gradient boosting (XGBoost) to generate models capable of classifying nanoparticle trajectories. Collectively, this work demonstrates the utility of MPT combined with machine learning for measuring changes in brain ECM structure and predicting associated complex features such as developmental age.

SummaryAlthough there is an exponential increase and extensive availability of genome-wide association studies data, the visualization of this data remains difficult for non-specialist users. Current software and packages for visualizing GWAS data are intended for specialists and have been developed to accomplish specific functions, favouring functionality over user experience. To facilitate this, we have developed an R shiny web application, gwaRs, that allows any general user to visualize GWAS data efficiently and effortlessly. The gwaRs web-browser interface allows users to visualize GWAS data using SNP-density, quantile-quantile, Manhattan, and Principal Component Analysis plots.AvailabilityThe gwaRs web application is publicly hosted at https://gwasviz.shinyapps.io/gwaRs/ and R source code is released under the GNU General Public License and freely available at GitHub: https://github.com/LindoNkambule/gwaRs.Contactlindonkambule116@gmail.com

Summary Literature debates whether young persons' participation in social work decisions is tokenistic in nature or it empowers them to shape their world. By and large, young persons deemed at risk remain the targets of intervention. This paper aims to underscore the need to move beyond soliciting young persons' voice merely in order to corroborate information provided by adults and professionals in social work assessment and intervention. Instead, it explicates the philosophical foundation for social workers to treat young persons as knowledgeable agents capable of contributing to professional knowledge. Findings Through reinterpretation of a published case study on children of sex worker mothers in India, this paper highlights how young persons are active agents of their own lives even in extreme dire situations. These children of sex worker mothers were capable of advocating for their own rights as well as that of their mothers. Through the secondary analysis of data, we illustrated the dynamic process of knowledge construction by young persons. Application By paying attention to the young persons' capacity as knowledgeable agents we propose social workers to intentionally incorporate their knowledge in their practice.

Summary: We construct μ p -optimal approximate designs for comparing population curves in hierarchical models with group-specific treatment. Equivalence theorems are given to confirm μ p -optimality of designs and the optimal allocation of sample size in each group. An illustrative application to find μ 1 and μ ∞ -optimal designs is presented for the random slope models with two-treatment group assignments.

Video abstract summary The purpose of this educational video is to describe the surgical technique and required equipment for performing a LeFort partial colpocleisis using surgical footage as well as a low-cost surgical model. Pelvic organ prolapse is very common, and 1 in 9 women will undergo surgery for prolapse by the age of 80. Management options include conservative and surgical treatment. Surgical treatment consists of reconstructive procedures or obliterative procedures. LeFort partial colpocleisis is an obliterative procedure with high success rates and low recurrent rates and is indicated in patients who are no longer having vaginal intercourse and/or have comorbidities that prohibit a more extensive procedure.

Summary This systematic review assesses the effectiveness and safety of vitamin B supplements for the management of neuropathy in people with diabetes. Methods Several databases including, the Cochrane Neuromuscular Specialised Register, CENTRAL, MEDLINE, Embase and CINAHL Plus were searched from their inception until May 2020. Results Five studies were eligible to be included in this review with a total of 348 participants. Overall, the evidence is too uncertain to draw conclusions on the effects of B vitamins in people with DPN. Conclusion It is uncertain whether vitamin B supplements change pain intensity or impairment in the short or long term in people with DPN.

Summary In this review we consider the various roles played by N-methyl- d -aspartate receptors (NMDARs) located on pyramidal neurones in medial prefrontal cortex (mPFC). We focus on recent data from our lab that has investigated how NMDARs contribute to ongoing synaptic transmission in a frequency dependent manner, the plasticity of NMDARs and how this impacts their contribution to synaptic transmission, and finally consider how NMDARs contribute to plasticity induced by synchronous activation of two separate inputs to mPFC

Summary Electronic health records (EHRs) linked with a DNA biobank provide unprecedented opportunities for biomedical research in precision medicine. The Phenome-wide association study (PheWAS) is a widely used technique for the evaluation of relationships between genetic variants and a large collection of clinical phenotypes recorded in EHRs. PheWAS analyses are typically presented as static tables and charts of summary statistics obtained from statistical tests of association between a genetic variant and individual phenotypes. Comorbidities are common and typically lead to complex, multivariate gene–disease association signals that are challenging to interpret. Discovering and interrogating multimorbidity patterns and their influence in PheWAS is difficult and time-consuming. We present PheWAS-ME: an interactive dashboard to visualize individual-level genotype and phenotype data side-by-side with PheWAS analysis results, allowing researchers to explore multimorbidity patterns and their associations with a genetic variant of interest. We expect this application to enrich PheWAS analyses by illuminating clinical multimorbidity patterns present in the data. Availability and implementation A demo PheWAS-ME application is publicly available at https://prod.tbilab.org/phewas_me/. Sample datasets are provided for exploration with the option to upload custom PheWAS results and corresponding individual-level data. Online versions of the appendices are available at https://prod.tbilab.org/phewas_me_info/. The source code is available as an R package on GitHub (https://github.com/tbilab/multimorbidity_explorer). Supplementary information Supplementary data are available at Bioinformatics online.

SummaryTransposable elements (TEs) constitute an import part in eukaryotic genomes, but their classification, especially in the lineage or clade level, is still challenging. For this purpose, we propose TEsorter, which is based on conserved protein domains of TEs. It is easy-to-use, fast with multiprocessing, sensitive and precise to classify TEs especially LTR retrotransposons (LTR-RTs). Its results can also directly reflect phylogenetic relationships and diversities of the classified LTR-RTs.AvailabilityThe code in Python is freely available at https://github.com/zhangrengang/TEsorter.

SummaryTRIBES is a user-friendly pipeline for relatedness detection in genomic data. TRIBES is the first tool which is both accurate up to 7th degree relatives (e.g. third cousins) and combines essential data processing steps into a single user-friendly pipeline. Furthermore, using a proof-of-principle cohort comprising amyotrophic lateral sclerosis cases with known relationship structures and a known causal mutation in SOD1, we demonstrated that TRIBES can successfully uncover disease susceptibility loci. TRIBES has multiple applications in addition to disease gene mapping, including sample quality control in genome wide association studies and avoiding consanguineous unions in family planning.AvailabilityTRIBES is freely available on GitHub: https://github.com/aehrc/TRIBES/Contactnatalie.twine@csiro.auSupplementary informationXXXX

GRAPHICAL ABSTRACT SUMMARY Neuronal ensembles that hold specific memory (memory engrams) have been identified in the hippocampus, amygdala, and cortex. It has been hypothesized that engrams for a specific memory are distributed among multiple brain regions that are functionally connected. Here, we report the hitherto most extensive engram map for contextual fear memory by characterizing activity-tagged neurons in 409 regions using SHIELD-based tissue phenotyping. The mapping was aided by a novel engram index, which identified cFos+ brain regions holding engrams with a high probability. Optogenetic manipulations confirmed previously known engrams and revealed new engrams. Many of these engram holding-regions were functionally connected to the CA1 or amygdala engrams. Simultaneous chemogenetic reactivation of multiple engrams, which mimics natural memory recall, conferred a greater level of memory recall than reactivation of a single engram ensemble. Overall, our study supports the hypothesis that a memory is stored in functionally connected engrams distributed across multiple brain regions.