Primary Care

Comprehensive analysis of Syzygium cumini L. pomace extract as an α-amylase inhibitor: In vitro inhibition, kinetics, and computational studies.

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder characterized by impaired regulation of blood glucose levels. Jamun (Syzygium cumini L.) fruits and seeds have been traditionally used in Ayurveda to manage diabetes. While fruit and seed extracts have been extensively studied for their anti-α-amylase properties, pomace, a byproduct of juice extraction, remains under explored. This...

A cascade nanoreactor based on metal azolate framework integrated natural enzyme for α-glucosidase activity assay and inhibitor screening.

Enzyme cascades have attracted widespread attention owing to the exceptional specificity and efficient signals transduction, however, constrained by the high cost and limited stability of bio-enzymes. In this study, a novel mimic multienzyme nanoreactor (GOx@MAF-7(Fe), i.e. GMF) was developed through a one-step encapsulation of glucose oxidase (GOx) into a metal azolate framework, MAF-7(Fe). Benef...

Integrating Artificial Intelligence in Dermatological Cancer Screening and Diagnosis: Efficacy, Challenges, and Future Directions.

Skin cancer is the most common cancer in the United States, with incidence rates continuing to rise both nationally and globally, posing significant h...

Organoid-Guided Precision Medicine: From Bench to Bedside.

Organoid technology, as an emerging field within biotechnology, has demonstrated transformative potential in advancing precision medicine. This review...

Insulin resistance in type 1 diabetes is a key modulator of platelet hyperreactivity.

AIMS/HYPOTHESIS: Individuals with type 1 diabetes are at increased cardiovascular risk, particularly in the presence of insulin resistance. A prothrom...

Promoting active health with AI technologies: Current status and prospects of high-altitude therapy, simulated hypoxia, and LLM-driven lifestyle rehabilitation approaches.

In the context of the rising global prevalence of obesity, traditional intervention measures have proven insufficient to meet the demands of personali...

A new intelligent method based on cognitive artificial intelligence for predicting transformer remaining useful life.

Electricity is essential in modern life, with consumption expected to rise by 80 % by 2024, making power transformers crucial. In developing countries...

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.

BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear layer, with an upward expansion of the outer nucl...

Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.

BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to ...

Applying user-centred techniques and expert feedback to refine an AI-based app for addressing mobile gaming addiction in adolescents.

BACKGROUND: The prevalent use of smartphones has contributed to a rise in mobile gaming addiction, especially in young people. This study aimed to des...

Managing chronic disease in the digital era: The role of telemedicine apps and platforms.

Chronic diseases such as diabetes, heart disease, or asthma are one of the biggest health challenges of the modern world. Their management requires co...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (...

Detection of β-Thalassemia trait from a heterogeneous population with red cell indices and parameters.

BACKGROUND: India is home to about 42 million people with β-thalassemia trait (βTT) necessitating screening of βTT to stop spread of the disease. Over...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the limited availability of effective treatment optio...

Real-time health monitoring by examining the role of next-generation elements in a medical app.

The healthcare sector is undergoing a profound transformation driven by the rapid rise in healthcare applications (mHealth apps), which are becoming i...

Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.

Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric populations. The escalating incidence of childhood ty...

Evaluation of Perioperative Cardiovascular Event Risk in Gastrointestinal Surgery　- Predictive Modeling and Risk Stratification Using Machine Learning.

BACKGROUND: Preoperative risk assessment is very important to ensure surgical safety and predict postoperative complications. However, no large-scale ...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing to morbidity, mortality and healthcare burden. Desp...

Optimized machine learning mechanism for big data healthcare system to predict disease risk factor.

Heart disease is becoming more and more common in modern society because of factors like stress, inadequate diets, etc. Early identification of heart ...