EfficientNet-based machine learning architecture for sleep apnea identification in clinical single-lead ECG signal data sets.

Objective: Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data sets.

Methods: We conducted our research using a data set consisting of 1656 patients, representing a diverse demographic, from the sleep center of China Medical University Hospital. To detect apnea ECG segments and extract apnea features, we utilized the EfficientNet and some of its layers, respectively.

Utility of polygenic scores across diverse diseases in a hospital cohort for predictive modeling.

Polygenic scores estimate genetic susceptibility to diseases. We systematically calculated polygenic scores across 457 phenotypes using genotyping array data from China Medical University Hospital. Logistic regression models assessed polygenic scores' ability to predict disease traits.

Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.

This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cytometry efficiently identifies various forms of acute leukemia. However, the analysis of flow cytometry can be time-consuming work.

Machine learning approaches for biomarker discovery to predict large-artery atherosclerosis.

Large-artery atherosclerosis (LAA) is a leading cause of cerebrovascular disease. However, LAA diagnosis is costly and needs professional identification. Many metabolites have been identified as biomarkers of specific traits.

Utilizing apolipoprotein E genotypes and associated comorbidities for the assessment of the risk for dementia.

Introduction: Dementia is associated with many comorbidities while being related to Apolipoprotein E () polymorphism. However, it is unclear how these clinical illnesses and genetic factors modify the dementia risk.

Methods: We enrolled 600 dementia cases and 6000 matched non-dementia controls, with identified genotype (ε4/ε4, ε4/ε3, and ε3/ε3).

Structural insights into EphA4 unconventional activation from prediction of the EphA4 and its complex with ribonuclease 1.

It has been shown that several ribonuclease (RNase) A superfamily proteins serve as ligands of receptor tyrosine kinases (RTKs), representing a new concept for ligand/receptor interaction. Moreover, recent studies indicate high clinical values for this type of ligand/RTK interactions. However, there is no structural report for this new family of ligand/receptor.

A Novel Quality-Control Procedure to Improve the Accuracy of Rare Variant Calling in SNP Arrays.

Single-nucleotide polymorphism (SNP) arrays are an ideal technology for genotyping genetic variants in mass screening. However, using SNP arrays to detect rare variants [with a minor allele frequency (MAF) of <1%] is still a challenge because of noise signals and batch effects. An approach that improves the genotyping quality is needed for clinical applications.

Multi-omics profiling reveals microRNA-mediated insulin signaling networks.

Background: MicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells.

Secretory Production of Functional Grouper Type I Interferon from in and .

Nervous necrosis virus (NNV) results in high mortality rates of infected marine fish worldwide. Interferons (IFNs) are cytokines in vertebrates that suppress viral replication and regulate immune responses. Heterologous overexpression of fish IFN in bacteria could be problematic because of protein solubility and loss of function due to protein misfolding.

Enterotype-based Analysis of Gut Microbiota along the Conventional Adenoma-Carcinoma Colorectal Cancer Pathway.

The dysbiosis of human gut microbiota is strongly associated with the development of colorectal cancer (CRC). The dysbiotic features of the transition from advanced polyp to early-stage CRC are largely unknown. We performed a 16S rRNA gene sequencing and enterotype-based gut microbiota analysis study.

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles.