Machine learning approach to identify phenotypes in patients with ischaemic heart failure with reduced ejection fraction.

Aims: Patients experiencing ischaemic heart failure with reduced ejection fraction (HFrEF) represent a diverse group. We hypothesize that machine learning clustering can help separate distinctive patient phenotypes, paving the way for personalized management.

Methods And Results: A total of 8591 ischaemic HFrEF patients pooled from the EPHESUS and CAPRICORN trials (64 ± 12 years; 28% women) were included in this analysis.

Multiomic profiling of new-onset kidney function decline: insights from the STANISLAS study cohort with a 20-year follow-up.

Background: Identifying the biomarkers associated with new-onset glomerular filtration rate (GFR) decrease in an initially healthy population could offer a better understanding of kidney function decline and help improving patient management.

Methods: Here we described the proteomic and transcriptomic footprints associated with new-onset kidney function decline in an initially healthy and well-characterized population with a 20-year follow-up. This study was based on 1087 individuals from the familial longitudinal Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux (STANISLAS) cohort who attended both visit 1 (from 1993 to 1995) and visit 4 (from 2011 to 2016).

Proteomic profiles of left atrial volume and its influence on response to spironolactone: Findings from the HOMAGE trial and STANISLAS cohort.

Aims: High left ventricular filling pressure increases left atrial volume and causes myocardial fibrosis, which may decrease with spironolactone. We studied clinical and proteomic characteristics associated with left atrial volume indexed by body surface area (LAVi), and whether LAVi influences the response to spironolactone on biomarker expression and clinical variables.

Methods And Results: In the HOMAGE trial, where people at risk of heart failure were randomized to spironolactone or control, we analysed 421 participants with available LAVi and 276 proteomic measurements (Olink) at baseline, month 1 and 9 (mean age 73 ± 6 years; women 26%; LAVi 32 ± 9 ml/m).

Associations of childhood adiposity with adult intima-media thickness and inflammation: a 20-year longitudinal population-based cohort.

Background: The associations between childhood adiposity and adult increased carotid intima-media thickness (cIMT) have been well established, which might be corroborated by the association between adiposity in children and inflammation in adults. However, longitudinal data regarding biological pathways associated with childhood adiposity are lacking.

Methods: The current study included participants from the STANISLAS cohort who had adiposity measurements at age 5-18 years [ N  = 519, mean (SD) age, 13.

Inductive database to support iterative data mining: Application to biomarker analysis on patient data in the Fight-HF project.

Machine learning is now an essential part of any biomedical study but its integration into real effective Learning Health Systems, including the whole process of Knowledge Discovery from Data (KDD), is not yet realised. We propose an original extension of the KDD process model that involves an inductive database. We designed for the first time a generic model of Inductive Clinical DataBase (ICDB) aimed at hosting both patient data and learned models.

Inflammation and remodeling pathways and risk of cardiovascular events in patients with ischemic heart failure and reduced ejection fraction.

Patients with heart failure (HF) and coronary artery disease (CAD) have a high risk for cardiovascular (CV) events including HF hospitalization, stroke, myocardial infarction (MI) and sudden cardiac death (SCD). The present study evaluated associations of proteomic biomarkers with CV outcome in patients with CAD and HF with reduced ejection fraction (HFrEF), shortly after a worsening HF episode. We performed a case-control study within the COMMANDER HF international, double-blind, randomized placebo-controlled trial investigating the effects of the factor-Xa inhibitor rivaroxaban.

Computational Strategy for Minimizing Mycotoxins in Cereal Crops: Assessment of the Biological Activity of Compounds Resulting from Virtual Screening.

Cereal crops are frequently affected by toxigenic species, among which the most common and worrying in Europe are and . These species are the causal agents of grain contamination with type B trichothecene (TCTB) mycotoxins. To help reduce the use of synthetic fungicides while guaranteeing low mycotoxin levels, there is an urgent need to develop new, efficient and environmentally-friendly plant protection solutions.

Impact of smoking on cardiovascular risk and premature ageing: Findings from the STANISLAS cohort.

Background And Aims: Smoking may lead to premature ageing, but the impact on the cardiovascular system and circulating proteins needs further investigation. In the present study, we aim to understand the impact of smoking on heart and vessels and circulating biomarkers of multiple domains including cardiovascular damage, premature ageing and cancer-related pathways.

Methods: The STANISLAS Cohort is a longitudinal familial cohort with detailed cardiovascular examination and biomarker assessment.

Machine Learning-Derived Echocardiographic Phenotypes Predict Heart Failure Incidence in Asymptomatic Individuals.

Objectives: This study sought to identify homogenous echocardiographic phenotypes in community-based cohorts and assess their association with outcomes.

Background: Asymptomatic cardiac dysfunction leads to a high risk of long-term cardiovascular morbidity and mortality; however, better echocardiographic classification of asymptomatic individuals remains a challenge.

Methods: Echocardiographic phenotypes were identified using K-means clustering in the first generation of the STANISLAS (Yearly non-invasive follow-up of Health status of Lorraine insured inhabitants) cohort (N = 827; mean age: 60 ± 5 years; men: 48%), and their associations with vascular function and circulating biomarkers were also assessed.

Head-to-head comparison of clustering methods for heterogeneous data: a simulation-driven benchmark.

The choice of the most appropriate unsupervised machine-learning method for "heterogeneous" or "mixed" data, i.e. with both continuous and categorical variables, can be challenging.

Sex differences in circulating proteins in heart failure with preserved ejection fraction.

Background: Many patients with heart failure with preserved ejection fraction (HFpEF) are women. Exploring mechanisms underlying the sex differences may improve our understanding of the pathophysiology of HFpEF. Studies focusing on sex differences in circulating proteins in HFpEF patients are scarce.

Circulating plasma proteins and new-onset diabetes in a population-based study: proteomic and genomic insights from the STANISLAS cohort.

Objective: Determining the factors associated with new-onset pre-diabetes and type 2 diabetes mellitus (T2D) is important for improving the current prevention strategies and for a better understanding of the disease.

Design: To study the factors (clinical, circulating protein and genetic) associated with new onset pre-diabetes and T2D in an initially healthy (without diabetes) populational familial cohort with a long follow-up (STANISLAS cohort).

Methods: A total of 1506 participants attended both the visit 1 and visit 4, separated by ≈20 years.

Large-Scale Virtual Screening Against the MET Kinase Domain Identifies a New Putative Inhibitor Type.

By using an ensemble-docking strategy, we undertook a large-scale virtual screening campaign in order to identify new putative hits against the MET kinase target. Following a large molecular dynamics sampling of its conformational space, a set of 45 conformers of the kinase was retained as docking targets to take into account the flexibility of the binding site moieties. Our screening funnel started from about 80,000 chemical compounds to be tested in silico for their potential affinities towards the kinase binding site.

Enhanced clinical phenotyping by mechanistic bioprofiling in heart failure with preserved ejection fraction: insights from the MEDIA-DHF study (The Metabolic Road to Diastolic Heart Failure).

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome for which clear evidence of effective therapies is lacking. Understanding which factors determine this heterogeneity may be helped by better phenotyping. An unsupervised statistical approach applied to a large set of biomarkers may identify distinct HFpEF phenotypes.

Bioprofiles and mechanistic pathways associated with Cheyne-Stokes respiration: insights from the SERVE-HF trial.

Introduction: The SERVE-HF trial included patients with heart failure and reduced ejection fraction (HFrEF) with sleep-disordered breathing, randomly assigned to treatment with Adaptive-Servo Ventilation (ASV) or control. The primary outcome was the first event of death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening heart failure. A subgroup analysis of the SERVE-HF trial suggested that patients with Cheyne-Stokes respiration (CSR) < 20% (low CSR) experienced a beneficial effect from ASV, whereas in patients with CSR ≥ 20% ASV might have been harmful.

A Chemosensory GPCR as a Potential Target to Control the Root-Knot Nematode Parasitism in Plants.

Root-knot nematodes (RKN), from the genus, have a worldwide distribution and cause severe economic damage to many life-sustaining crops. Because of their lack of specificity and danger to the environment, most chemical nematicides have been banned from use. Thus, there is a great need for new and safe compounds to control RKN.

Plasma protein biomarkers and their association with mutually exclusive cardiovascular phenotypes: the FIBRO-TARGETS case-control analyses.

Background: Hypertension, obesity and diabetes are major and potentially modifiable "risk factors" for cardiovascular diseases. Identification of biomarkers specific to these risk factors may help understanding the underlying pathophysiological pathways, and developing individual treatment.

Methods: The FIBRO-TARGETS (targeting cardiac fibrosis for heart failure treatment) consortium has merged data from 12 patient cohorts in 1 common database of > 12,000 patients.

Low-Dose Alkylphenol Exposure Promotes Mammary Epithelium Alterations and Transgenerational Developmental Defects, But Does Not Enhance Tumorigenic Behavior of Breast Cancer Cells.

Fetal and neonatal exposure to long-chain alkylphenols has been suspected to promote breast developmental disorders and consequently to increase breast cancer risk. However, disease predisposition from developmental exposures remains unclear. In this work, human MCF-10A mammary epithelial cells were exposed to a low dose of a realistic (4-nonylphenol + 4-tert-octylphenol) mixture.

Discovering associations between adverse drug events using pattern structures and ontologies.

Background: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgroups of patients.

Results: Because ADEs have complex manifestations, we use formal concept analysis and its pattern structures, a mathematical framework that allows generalization using domain knowledge formalized in medical ontologies.

GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease.

Backgound: Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed.

Antimicrobial properties of two novel peptides derived from Theobroma cacao osmotin.

The osmotin proteins of several plants display antifungal activity, which can play an important role in plant defense against diseases. Thus, this protein can be useful as a source for biotechnological strategies aiming to combat fungal diseases. In this work, we analyzed the antifungal activity of a cacao osmotin-like protein (TcOsm1) and of two osmotin-derived synthetic peptides with antimicrobial features, differing by five amino acids residues at the N-terminus.