In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

Metabolomics-Based Study of Clinical and Animal Plasma Samples in Coronary Heart Disease with Blood Stasis Syndrome

The aim of this study is to explore a bridge connecting the mechanism basis and macro syndromes of coronary heart disease with experimental animal models. GC-MS technique was used to detect the metabolites of plasma samples in mini swine models with myocardial infarction (MI) and patients with unstable angina (UA). 30 metabolites were detected in the plasma samples of more than 50 percent of model group and control group in swine, while 37 metabolites were found in the plasma samples of UA patients and healthy control group. 21 metabolites in the plasma samples of swine model and 20 metabolites in patients with UA were found of significant value. Among which, 8 shared metabolites were found of low level expression in both swine model and UA patients. Independent Student's t-test, principal component analysis (PCA), and hierarchicalcluster analysis (HCA) were orderly applied to comprehend inner rules of variables in the data. The 8 shared metabolites could take place of the 21 or 20 metabolites in classification of swine model with MI and UA patients, which could be considered as a bridge connecting the mechanism basis and macrosyndromes of swine model with MI and UA patients

Side by Side Battery Technologies with Lithium‐Ion Based Batteries

In recent years, the electrochemical power sources community has launched massive research programs, conferences, and workshops on the “post Li battery era.” However, in this report it is shown that the quest for post Li‐ion and Li battery technologies is incorrect in its essence. This is the outcome of a three day discussion on the future technologies that could provide an answer to a question that many ask these days: Which are the technologies that can be regarded as alternative to Li‐ion batteries? The answer to this question is a rather surprising one: Li‐ion battery technology will be here for many years to come, and therefore the use of “post Li‐ion” battery technologies would be misleading. However, there are applications with needs for which Li‐ion batteries will not be able to provide complete technological solutions, as well as lower cost and sustainability. In these specific cases, other battery technologies will play a key role. Here, the term “side‐by‐side technologies” is coined alongside a discussion of its meaning. The progress report does not cover the topic of Li‐metal battery technologies, but covers the technologies of sodium‐ion, multivalent, metal–air, and flow batteries

Structural Aspects of P2-Type Na0.67Mn0.6Ni0.2Li0.2O2 (MNL) Stabilization by Lithium Defects as a Cathode Material for Sodium-Ion Batteries

A known strategy for improving the properties of layered oxide electrodes in sodium-ion batteries is the partial substitution of transition metals by Li. Herein, the role of Li as a defect and its impact on sodium storage in P2-Na0.67Mn0.6Ni0.2Li0.2O2 is discussed. In tandem with electrochemical studies, the electronic and atomic structure are studied using solid-state NMR, operando XRD, and density functional theory (DFT). For the as-synthesized material, Li is located in comparable amounts within the sodium and the transition metal oxide (TMO) layers. Desodiation leads to a redistribution of Li ions within the crystal lattice. During charging, Li ions from the Na layer first migrate to the TMO layer before reversing their course at low Na contents. There is little change in the lattice parameters during charging/discharging, indicating stabilization of the P2 structure. This leads to a solid-solution type storage mechanism (sloping voltage profile) and hence excellent cycle life with a capacity of 110 mAh g-1 after 100 cycles. In contrast, the Li-free compositions Na0.67Mn0.6Ni0.4O2 and Na0.67Mn0.8Ni0.2O2 show phase transitions and a stair-case voltage profile. The capacity is found to originate from mainly Ni3+/Ni4+ and O2-/O2-δ redox processes by DFT, although a small contribution from Mn4+/Mn5+ to the capacity cannot be excluded. © 2021 The Authors. Advanced Functional Materials published by Wiley-VCH Gmb

Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in chinese patients with lung squamous cell carcinoma

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations.

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts