A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review

Background and Motivation: Cardiovascular disease (CVD) causes the highest mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment is vital. Conventional methods have shown poor performance compared to more recent and fast-evolving Artificial Intelligence (AI) methods. The proposed study reviews the three most recent paradigms for CVD risk assessment, namely multiclass, multi-label, and ensemble-based methods in (i) office-based and (ii) stress-test laboratories. Methods: A total of 265 CVD-based studies were selected using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model. Due to its popularity and recent development, the study analyzed the above three paradigms using machine learning (ML) frameworks. We review comprehensively these three methods using attributes, such as architecture, applications, pro-and-cons, scientific validation, clinical evaluation, and AI risk-of-bias (RoB) in the CVD framework. These ML techniques were then extended under mobile and cloud-based infrastructure. Findings: Most popular biomarkers used were office-based, laboratory-based, image-based phenotypes, and medication usage. Surrogate carotid scanning for coronary artery risk prediction had shown promising results. Ground truth (GT) selection for AI-based training along with scientific and clinical validation is very important for CVD stratification to avoid RoB. It was observed that the most popular classification paradigm is multiclass followed by the ensemble, and multi-label. The use of deep learning techniques in CVD risk stratification is in a very early stage of development. Mobile and cloud-based AI technologies are more likely to be the future. Conclusions: AI-based methods for CVD risk assessment are most promising and successful. Choice of GT is most vital in AI-based models to prevent the RoB. The amalgamation of image-based strategies with conventional risk factors provides the highest stability when using the three CVD paradigms in non-cloud and cloud-based frameworks

Mapping the extent of heterogeneity of human CCR5R CD4R T cells in peripheral blood and lymph nodes

Background: CD4 T cells that express the chemokine receptor, CCR5, are the most important target of HIV-1 infection, but their functions, phenotypes and anatomical locations are poorly understood. We aimed to use multiparameter flow cytometry to better define the full breadth of these cells. Methods: High-parameter fluorescence flow and mass cytometry were optimized to analyse subsets of CCR5 memory CD4 T cells, including CD25highCD127dim Tregs, CXCR3CCR6 Th1-like, CCR6CD161CXCR3 Th17-like, integrins a4ß7 guthoming, CCR4 skin-homing, CD62L lymph node-homing, CD38HLA-DR activated cells, and CD27CD28 cytotoxic T lymphocytes, in a total of 22 samples of peripheral blood, ultrasound-guided fine needle biopsies of lymph nodes and excised tonsils.CCR5 antigen-specific CD4 T cells were studied using the OX40 flow-based assay. Results: 10-20% of CCR5 memory CD4 T cells were Tregs, 10-30% were guthoming, 10-30% were skin-homing, 20-40% were lymph node-homing, 20-50% were Th1-like and 20-40% were Th17-like cells. Up to 30% were cytotoxic T lymphocytes in CMV-seropositive donors, including cells that were either CCR5high-Granzyme K or CCR5dimGranzyme B. When all possible phenotypes were exhaustively analysed, more than 150 different functional and trafficking subsets of CCR5 CD4 T cells were seen. Moreover, a small population of resident CD69Granzyme KCCR5 CD4 T cells was found in lymphoid tissues. CMV and Mycobacterium tuberculosis-specific CD4 T cells were predominantly CCR5. Conclusion: These results reveal for the first time the prodigious heterogeneity of function and trafficking of CCR5 CD4 T cells in blood and in lymphoid tissue, with significant implications for rational approaches to prophylaxis for HIV-1 infection and for purging of the HIV-1 reservoir in those participants already infected

Gastrointestinal adenocarcinomas of the esophagus, stomach, and colon exhibit distinct patterns of genome instability and oncogenesis

A more detailed understanding of the somatic genetic events that drive gastrointestinal adenocarcinomas is necessary to improve diagnosis and therapy. Using data from high-density genomic profiling arrays, we conducted an analysis of somatic copy-number aberrations in 486 gastrointestinal adenocarcinomas including 296 esophageal and gastric cancers. Focal amplifications were substantially more prevalent in gastric/esophageal adenocarcinomas than colorectal tumors. We identified 64 regions of significant recurrent amplification and deletion, some shared and others unique to the adenocarcinoma types examined. Amplified genes were noted in 37% of gastric/esophageal tumors, including in therapeutically targetable kinases such as ERBB2, FGFR1, FGFR2, EGFR, and MET, suggesting the potential use of genomic amplifications as biomarkers to guide therapy of gastric and esophageal cancers where targeted therapeutics have been less developed compared with colorectal cancers. Amplified loci implicated genes with known involvement in carcinogenesis but also pointed to regions harboring potentially novel cancer genes, including a recurrent deletion found in 15% of esophageal tumors where the Runt transcription factor subunit RUNX1 was implicated, including by functional experiments in tissue culture. Together, our results defined genomic features that were common and distinct to various gut-derived adenocarcinomas, potentially informing novel opportunities for targeted therapeutic interventions

Notch Signaling Activates Yorkie Non-Cell Autonomously in Drosophila

In Drosophila imaginal epithelia, cells mutant for the endocytic neoplastic tumor suppressor gene vps25 stimulate nearby untransformed cells to express Drosophila Inhibitor-of-Apoptosis-Protein-1 (DIAP-1), conferring resistance to apoptosis non-cell autonomously. Here, we show that the non-cell autonomous induction of DIAP-1 is mediated by Yorkie, the conserved downstream effector of Hippo signaling. The non-cell autonomous induction of Yorkie is due to Notch signaling from vps25 mutant cells. Moreover, activated Notch in normal cells is sufficient to induce non-cell autonomous Yorkie activity in wing imaginal discs. Our data identify a novel mechanism by which Notch promotes cell survival non-cell autonomously and by which neoplastic tumor cells generate a supportive microenvironment for tumor growth

Air pollution from household solid fuel combustion in India: an overview of exposure and health related information to inform health research priorities

Environmental and occupational risk factors contribute to nearly 40% of the national burden of disease in India, with air pollution in the indoor and outdoor environment ranking amongst leading risk factors. It is now recognized that the health burden from air pollution exposures that primarily occur in the rural indoors, from pollutants released during the incomplete combustion of solid fuels in households, may rival or even exceed the burden attributable to urban outdoor exposures. Few environmental epidemiological efforts have been devoted to this setting, however. We provide an overview of important available information on exposures and health effects related to household solid fuel use in India, with a view to inform health research priorities for household air pollution and facilitate being able to address air pollution within an integrated rural–urban framework in the future

How to use implantable loop recorders in clinical trials and hybrid therapy

Epidemiological studies show that atrial fibrillation (AF) is associated with a doubling of mortality, even after adjustment for confounders. AF can be asymptomatic, but this does not decrease the thromboembolic risk of the patient. Office ECGs, occasional 24-h Holter recordings and long-term ECG event recording might not be sensitive and accurate enough in patients with AF, especially in those with paroxysmal episodes. In one study, 7 days of continuous monitoring with event recorders detected paroxysmal AF in 20 of 65 patients with a previous negative 24-h Holter recording. Over the last decade, enormous improvements have been made in the technology of implantable devices, which can now store significant information regarding heart rhythm. The first subcutaneous implantable monitor (Reveal XT, Medtronic) was validated for continuous AF monitoring by the XPECT study. The dedicated AF detection algorithm uses irregularity and incoherence of R–R intervals to identify and classify patterns in ventricular conduction. Its sensitivity in identifying patients with AF is >96%. Numerous clinical data from continuous monitoring of AF have recently been published. The first applications of this technology have been in the field of surgical and catheter AF ablation. With regard to cryptogenic stroke, an international randomized trial is ongoing to compare standard care with standard care plus the implantable cardiac monitor for AF detection in patients discharged with the diagnosis of cryptogenic stroke: the Crystal AF trial. Continuous AF monitoring provides an optimal picture of daily AF burden, both symptomatic and asymptomatic. Implantable cardiac monitors have high sensitivity, enable better assessment of therapy success and may guide further AF therapy

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Numerical simulations of complex fluid-fluid interface dynamics

Interfaces between two fluids are ubiquitous and of special importance for industrial applications, e.g., stabilisation of emulsions. The dynamics of fluid-fluid interfaces is difficult to study because these interfaces are usually deformable and their shapes are not known a priori. Since experiments do not provide access to all observables of interest, computer simulations pose attractive alternatives to gain insight into the physics of interfaces. In the present article, we restrict ourselves to systems with dimensions comparable to the lateral interface extensions. We provide a critical discussion of three numerical schemes coupled to the lattice Boltzmann method as a solver for the hydrodynamics of the problem: (a) the immersed boundary method for the simulation of vesicles and capsules, the Shan-Chen pseudopotential approach for multi-component fluids in combination with (b) an additional advection-diffusion component for surfactant modelling and (c) a molecular dynamics algorithm for the simulation of nanoparticles acting as emulsifiers.Comment: 24 pages, 12 figure