抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Data Mining Practical Machine Learning Tools and Techniques

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

/pdf/analysis-of-protein-coding-genetic-variation-in-60-706-43wjw7d23z.pdf

Analysis of protein-coding genetic variation in 60,706 humans

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Background: Single-cell RNA sequencing (scRNA-seq) technology is now becoming a widely applied method of transcriptome exploration that helps to reveal cell-type composition as well as cell-state heterogeneity for specific biological processes. Distinct sequencing platforms and processing pipelines may contribute to various results even for the same sequencing samples. Therefore, benchmarking sequencing platforms and processing pipelines was considered as a necessary step to interpret scRNA-seq data. However, recent comparing efforts were constrained in sequencing platforms or analyzing pipelines. There is still a lack of knowledge of analyzing pipelines matched with specific sequencing platforms in aspects of sensitivity, precision, and so on. Methods: We downloaded public scRNA-seq data that was generated by two distinct sequencers, NovaSeq 6000 and MGISEQ 2000. Then data was processed through the Drop-seq-tools, UMI-tools and Cell Ranger pipeline respectively. We calculated multiple measurements based on the expression profiles of the six platform-pipeline combinations. Results: We found that all three pipelines had comparable performance, the Cell Ranger pipeline achieved the best performance in precision while UMI-tools prevailed in terms of sensitivity and marker calling. Conclusions: Our work provided an insight into the selection of scRNA-seq data processing tools for two sequencing platforms as well as a framework to evaluate platform-pipeline combinations.

Comparative analysis of NovaSeq 6000 and MGISEQ 2000 single-cell RNA sequencing data

BACKGROUND AND OBJECTIVES
Observational studies have shown that energy restriction could be beneficial for controlling bodyweight in patients with polycystic ovary syndrome (PCOS). We aim to compare the effects of a high-protein diet (HPD), a high-protein and high-dietary fiber diet (HPHFD), and a calorie-restricted diet (CRD) on metabolic health and gut microbiota in overweight/obese PCOS patients.


METHODS AND STUDY DESIGN
We will enroll a total of 90 overweight/obese PCOS patients into this eight-week open-label randomised controlled trial. Participants will be randomly assigned to three groups: CRD group (energy coefficient 20 kcal/kg.day, water ≥1500 mL, 0.8-1.2 g/kg protein, carbohydrate energize 55-60%, and fat energize 25-30%), HDP group (energy coefficient 20 kcal/kg.day, water ≥1500 mL, and 1.5-2.0 g/kg protein) and HPHFD group (based on the high protein diet with 15 g more dietary fiber supplement). The primary outcome is body weight, body fat percentage, and lean body mass. The secondary outcomes will include changes in blood lipids, inflammation, glucose tolerance, blood pressure, and gut microbiota compositions. Between-group differences in adiposity measurements at baseline will be compared using one-way analysis of variance (ANOVA) or Kruskal-Wallis test when appropriate. Within-group difference after 8-week intervention will be compared using paired t-test or Wilcoxon signed rank test. Between-group differences in adiposity measurements after 8-week diet intervention will be compared using linear mixed model and ANCOVA. The gut microbiota will be analyzed using 16S amplicon sequencing and the sequencing data will be analyzed using the standardized QIIME2 piperline.

Effects of three medical nutrition therapies on nutritional metabolism and intestinal flora in overweight/obese with polycystic ovary syndrome (PCOS): Study protocol for a randomised controlled trial.

http://www.cell.com/article/S2666675823000747/pdf

Current Progress, Challenges and Future Perspectives of Language Models for Protein Representation and Protein Design

Abstract Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen detection is an indispensable tool for epidemic surveillance in the post-pandemic era. Faced with irregular performance, a comprehensive external quality assessment (EQA) scheme was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the analytical performance and status of SARS-CoV-2 antigen tests. Methods The EQA panel included ten lyophilized samples containing serial 5-fold dilutions of inactivated SARS-CoV-2-positive supernatants of the Omicron BA.1 and BA.5 strains and negative samples, which were classified into “validating” samples and “educational” samples. Data were analyzed according to qualitative results for each sample. Results A total of 339 laboratories in China participated in this EQA scheme, and 378 effective results were collected. All validating samples were correctly reported by 90.56 % (307/339) of the participants and 90.21 % (341/378) of the datasets. The positive percent agreement (PPA) was >99 % for samples with concentrations of 2 × 107 copies/mL but was 92.20 % (697/756) for 4 × 106 copies/mL and 25.26 % (382/1,512) for 8 × 105 copies/mL samples. Colloidal gold was the most frequently used (84.66 %, 320/378) but showed the lowest PPAs (57.11 %, 1,462/2,560) for positive samples compared with fluorescence immunochromatography (90 %, 36/40) and latex chromatography (79.01 %, 335/424). Among 11 assays used in more than 10 clinical laboratories, ACON showed a higher sensitivity than other assays. Conclusions The EQA study can help to validate whether it’s necessary to update antigen detection assays for manufacturers and provide participants with information about the performance of assays to take the first step toward routine post-market surveillance.

/pdf/performance-evaluation-of-sars-cov-2-antigen-detection-in-7kdxlwqs.pdf

Performance evaluation of SARS-CoV-2 antigen detection in the post-pandemic era: multi-laboratory assessment

Simple Summary Radiotherapy for cancer patients can cause abnormal DNA methylation. We developed a computational workflow that can identify crucial methylation alterations related to treatment exposure in childhood cancer survivors. Abstract Radiotherapy is a helpful treatment for cancer, but it can also potentially cause changes in many molecules, resulting in adverse effects. Among these changes, the occurrence of abnormal DNA methylation patterns has alarmed scientists. To explore the influence of region-specific radiotherapy on blood DNA methylation, we designed a computational workflow by using machine learning methods that can identify crucial methylation alterations related to treatment exposure. Irrelevant methylation features from the DNA methylation profiles of 2052 childhood cancer survivors were excluded via the Boruta method, and the remaining features were ranked using the minimum redundancy maximum relevance method to generate feature lists. These feature lists were then fed into the incremental feature selection method, which uses a combination of deep forest, k-nearest neighbor, random forest, and decision tree to find the most important methylation signatures and build the best classifiers and classification rules. Several methylation signatures and rules have been discovered and confirmed, allowing for a better understanding of methylation patterns in response to different treatment exposures.

/pdf/detecting-blood-methylation-signatures-in-response-to-bdpmnk63.pdf

Tao Huang

Papers

Comparative analysis of NovaSeq 6000 and MGISEQ 2000 single-cell RNA sequencing data

Effects of three medical nutrition therapies on nutritional metabolism and intestinal flora in overweight/obese with polycystic ovary syndrome (PCOS): Study protocol for a randomised controlled trial.

Current Progress, Challenges and Future Perspectives of Language Models for Protein Representation and Protein Design

Performance evaluation of SARS-CoV-2 antigen detection in the post-pandemic era: multi-laboratory assessment

Detecting Blood Methylation Signatures in Response to Childhood Cancer Radiotherapy via Machine Learning Methods