Cardiac ultrasomics for acute myocardial infarction risk stratification and prediction of all-cause mortality: a feasibility study.

Background: Current risk stratification tools for acute myocardial infarction (AMI) have limitations, particularly in predicting mortality. This study utilizes cardiac ultrasound radiomics (i.e.

Arglabin: A mediator of inflammasome modulated and independent myocardial injury (PARA-AMI study).

Background: Arglabin is a plant alkaloid (sesquiterpene lactone) that is used as an anticancer drug. It has potential anti-diabetic and anti-atherogenic effects.

Purpose: Arglabin has drawn particular attention because of its therapeutic effects as an anti-inflammatory agent in multiple diseases.

Evaluation of antimicrobial efficacy of immunoglobulin Y (IgY) against periodontal biofilm.

Background And Objectives: To determine the action of immunoglobulin Y (IgY) on supragingival microbiota and on subgingival microbiota in patients with gingivitis and periodontitis through microbial reduction assay.

Methodology: 40 systemically healthy patients were divided into two groups (gingivitis and periodontitis) with 20 patients per group. Supragingival and subgingival plaque samples were collected from each patient in Group I and Group II, respectively.

Strain data augmentation enables machine learning of inorganic crystal geometry optimization.

Machine-learning (ML) models offer the potential to rapidly evaluate the vast inorganic crystalline materials space to efficiently find materials with properties that meet the challenges of our time. Current ML models require optimized equilibrium structures to attain accurate predictions of formation energies. However, equilibrium structures are generally not known for new materials and must be obtained through computationally expensive optimization, bottlenecking ML-based material screening.