Knowledge-slanted random forest method for high-dimensional data and small sample size with a feature selection application for gene expression data.

The use of prior knowledge in the machine learning framework has been considered a potential tool to handle the curse of dimensionality in genetic and genomics data. Although random forest (RF) represents a flexible non-parametric approach with several advantages, it can provide poor accuracy in high-dimensional settings, mainly in scenarios with small sample sizes. We propose a knowledge-slanted RF that integrates biological networks as prior knowledge into the model to improve its performance and explainability, exemplifying its use for selecting and identifying relevant genes.

Oral manifestations in patients with coronavirus disease 2019 (COVID-19) identified using text mining: an observational study.

Text mining enables search, extraction, categorisation and information visualisation. This study aimed to identify oral manifestations in patients with COVID-19 using text mining to facilitate extracting relevant clinical information from a large set of publications. A list of publications from the open-access COVID-19 Open Research Dataset was downloaded using keywords related to oral health and dentistry.

Integrative analysis of gene and protein expression in atherosclerosis-related pathways modulated by periodontal pathogens. Systematic review.

Unlabelled: The mechanisms modulated by periodontal pathogens in atherosclerosis are not fully understood. Aim: to perform an integrative analysis of gene and protein expression modulated by periodontal pathogens in cells and animal models for atherosclerosis.

Methods: Cochrane, PRISMA and AMSTAR2 guidelines for systematic reviews were followed.

Presence of periodontal pathogenic bacteria in blood of patients with coronary artery disease.

It has been hypothesised that oral bacteria can migrate, through the blood, from the mouth to the arterial plaques, thus exacerbating atherosclerosis. This study compared bacteria present in the peripheral blood of individuals with and without coronary artery disease (CAD). RNA sequences obtained from blood were downloaded from GEO (GSE58150).

Biological knowledge-slanted random forest approach for the classification of calcified aortic valve stenosis.

Background: Calcific aortic valve stenosis (CAVS) is a fatal disease and there is no pharmacological treatment to prevent the progression of CAVS. This study aims to identify genes potentially implicated with CAVS in patients with congenital bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV) in comparison with patients having normal valves, using a knowledge-slanted random forest (RF).

Results: This study implemented a knowledge-slanted random forest (RF) using information extracted from a protein-protein interactions network to rank genes in order to modify their selection probability to draw the candidate split-variables.

Proteomic Architecture of Valvular Extracellular Matrix: FNDC1 and MXRA5 Are New Biomarkers of Aortic Stenosis.

This study analyzed the expression of extracellular matrix (ECM) proteins during aortic valve calcification with mass spectrometry, and further validated in an independent human cohort using RNAseq data. The study reveals that valve calcification is associated with significant disruption in ECM and metabolic pathways, and highlights a strong connection between metabolic markers and ECM remodeling. It also identifies FNDC1 and MXRA5 as novel ECM biomarkers in calcified valves, electing them as potential targets in the development and progression of aortic stenosis.

Differences in Caries Status and Risk Factors among Privileged and Unprivileged Children in Colombia.

Objective: The objective of this study was to compare the ICDAS-II caries status and caries-related factors among children from rural and urban schools in Pasto, Colombia.

Materials And Methods: The study included 120 children (4 - 6 year- old children) from rural (privileged) and urban (unprivileged) schools. Caries was evaluated using the ICDAS-II criteria.

Altered DNA Methylation of Long Noncoding RNA H19 in Calcific Aortic Valve Disease Promotes Mineralization by Silencing NOTCH1.

Background: Calcific aortic valve disease is characterized by an abnormal mineralization of the aortic valve. Osteogenic activity in the aortic valve is under the control of NOTCH1, which regulates the expression of key pro-osteogenic genes such as RUNX2 and BMP2. Long noncoding RNAs (lncRNAs) may reprogram cells by altering the gene expression pattern.

RNA expression profile of calcified bicuspid, tricuspid, and normal human aortic valves by RNA sequencing.

The molecular mechanisms leading to premature development of aortic valve stenosis (AS) in individuals with a bicuspid aortic valve are unknown. The objective of this study was to identify genes differentially expressed between calcified bicuspid aortic valves (BAVc) and tricuspid valves with (TAVc) and without (TAVn) AS using RNA sequencing (RNA-Seq). We collected 10 human BAVc and nine TAVc from men who underwent primary aortic valve replacement.

Calcium Signaling Pathway Genes RUNX2 and CACNA1C Are Associated With Calcific Aortic Valve Disease.

Background: Calcific aortic valve stenosis (AS) is a life-threatening disease with no medical therapy. The genetic architecture of AS remains elusive. This study combines genome-wide association studies, gene expression, and expression quantitative trait loci mapping in human valve tissues to identify susceptibility genes of AS.

Evaluation of links between high-density lipoprotein genetics, functionality, and aortic valve stenosis risk in humans.

Objective: Studies have shown that high-density lipoprotein (HDL)-raising compounds induce regression of aortic valve stenosis (AVS) in animal models. However, whether patients with AVS have an impaired HDL metabolism is unknown.

Approach And Results: A total of 1435 single nucleotide polymorphisms in genes associated with HDL cholesterol levels (in or around GALNT2, LPL, ABCA1, APOA5, SCARB1, LIPC, CETP, LCAT, LIPG, APOC4, and PLTP) were genotyped in 382 patients with echocardiography-confirmed AVS (aortic jet velocity ≥2.

NOTCH1 genetic variants in patients with tricuspid calcific aortic valve stenosis.

Background And Aim Of The Study: Calcific aortic valve stenosis (AS) affects 2-5% of the population aged > 65 years. Functional DNA variants at the NOTCH1 locus result in bicuspid aortic valve (BAV) and severe valve calcification. The contribution of these variants to AS in the population with tricuspid aortic valve (TAV) remains to be determined.

ATP acts as a survival signal and prevents the mineralization of aortic valve.

Calcific aortic valve disease (CAVD) is a disorder related to progressive mineralization of valvular tissue that is a leading cause of heart disease. Thus far, there is no medical treatment to prevent the mineralization of aortic valves. It is generally thought that pathologic mineralization is linked to apoptosis of vascular cells.

Replication of genetic association studies in aortic stenosis in adults.

Only a handful of studies have attempted to unravel the genetic architecture of calcific aortic valve stenosis (AS). The goal of this study was to validate genes previously associated with AS. Seven genes were assessed: APOB, APOE, CTGF, IL10, PTH, TGFB1, and VDR.

The transcriptome of human epicardial, mediastinal and subcutaneous adipose tissues in men with coronary artery disease.

Background: The biological functions of epicardial adipose tissue (EAT) remain largely unknown. However, the proximity of EAT to the coronary arteries suggests a role in the pathogenesis of coronary artery disease (CAD). The objectives of this study were to identify genes differentially regulated among three adipose tissues, namely EAT, mediastinal (MAT) and subcutaneous (SAT) and to study their possible relationships with the development of cardiovascular diseases.