Devices and Vaccines

Dual nanozyme sensor enables rapid at-home cancer surveillance.

Early detection of cancer is critical for improving patient survival rates, and current in vitro diagnostic methods show great potential, particularly for point-of-care applications. However, challenges such as time consumption, high costs, and reliance on sophisticated equipment limit their widespread use, especially in resource-limited regions. Here, we have developed a smartphone-assisted minia...

Bridging Spectral Gaps: Cross-Device Model Generalization in Blood-Based Infrared Spectroscopy.

This paper presents a solution to the challenge of cross-device model generalization in blood-based infrared spectroscopy. As infrared spectroscopy becomes increasingly popular for analyzing human blood, ensuring that machine learning models trained on one device can be effectively transferred to others is essential. However, variations in device characteristics often reduce model performance when...

A Review of Cross-Species Transmission Mechanisms of Influenza Viruses.

The cross-species transmission of influenza viruses represents a critical link in the pandemic of zoonotic diseases. This mechanism involves multi-lev...

Leafing a mark on immunity: Quercetin-3-O-D-glucopyranoside and quercetin-3-O-(2″,6″-digalloyl)-β-D-galactopyranoside-rich Melia azedarach L. extract's immunoinflammatory effects on an sRBC-immunized BALB/c model.

Melia azedarach L. (Meliaceae) (MA) leaves are traditionally used for inflammatory disorders, yet their immunomodulatory effects on lymphocytes remain...

Using machine learning models to predict post-revascularization thrombosis in PAD.

BACKGROUND: Graft/ stent thrombosis after lower extremity revascularization (LER) is a serious complication in patients with peripheral arterial disea...

Serum Vitamin D and the Risk of SARS-CoV-2 and Seasonal Influenza Infection During the Twindemic Period.

BACKGROUND & AIMS: The association between circulating vitamin D levels and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) o...

The Role of Artificial Intelligence in Providing Real-Time Guidance During Interventional Cardiology Procedures: A Narrative Review.

Integrating artificial intelligence (AI) in interventional cardiology revolutionizes procedural guidance, particularly in high-stakes environments suc...

A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health.

Pesticides and other synthetic agrochemicals play a critical role in emerging agricultural practices by enhancing crop productivity and protecting aga...

AI-Enabled Piezoelectric Wearable for Joint Torque Monitoring.

Joint health is critical for musculoskeletal (MSK) conditions that are affecting approximately one-third of the global population. Monitoring of joint...

Multifractal analysis and support vector machine for the classification of coronaviruses and SARS-CoV-2 variants.

This study presents a novel approach for the classification of coronavirus species and variants of SARS-CoV-2 using Chaos Game Representation (CGR) an...

Transformer-based deep learning enables improved B-cell epitope prediction in parasitic pathogens: A proof-of-concept study on Fasciola hepatica.

BACKGROUND: The identification of B-cell epitopes (BCEs) is fundamental to advancing epitope-based vaccine design, therapeutic antibody development, a...

Development and precision evaluation of a robotic system for oral implant surgery using personalized digital guides and optical spatial positioning technology.

Oral implant surgery demands a high level of precision and expertise, making the integration of robotic assistance an optimal solution. This study int...

A population based optimization of convolutional neural networks for chronic kidney disease prediction.

Chronic kidney disease (CKD) is a global public health concern, and the timely detection of the disease is priceless. Most of the classical machine le...

Role of artificial intelligence in advancing immunology.

Artificial intelligence (AI) has revolutionized various biomedical fields, particularly immunology, by enhancing vaccine development, immunotherapies,...

A comparative study on TB incidence and HIVTB coinfection using machine learning models on WHO global TB dataset.

Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a significant global public health threat. HIV co-infectio...

Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning.

The design of proteins capable effectively binding to specific protein targets is crucial for developing therapies, diagnostics, and vaccine candidate...

A random forest-based predictive model for classifying BRCA1 missense variants: a novel approach for evaluating the missense mutations effect.

The right classification of variants is the key to pre-symptomatic detection of disease and conducting preventive actions. Since BRCA1 has a high inci...

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can ...

Vaccinology in the artificial intelligence era.

Artificial intelligence (AI) has already transformed vaccine antigen design and could transform the entire vaccinology pipeline, including immune resp...

An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).

The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, remains a challenge. The Gastro-Intestinal Pacemake...