AI Medical Compendium

Rapid, non-invasive diagnosis of tuberculosis using desorption separation ionization mass spectrometry (DSI-MS) and urinary carbonyl metabolite fingerprints.

Talanta Jan 13, 2026

Tuberculosis (TB) remains a leading global infectious disease that demands rapid, non-invasive diagnostic solutions. Here, we present a rapid urine-based diagnostic platform that integrates desorption separation ionization mass spectrometry (DSI-MS) ... read more

Recent advances in gold and zinc oxide nanoparticles: Antibiofilm action, mechanisms beyond ROS generation, and in vivo efficacy.

Microbiological research Jan 13, 2026

Gold (Au) and zinc oxide (ZnO) nanoparticles (AuNPs/ZnONPs, respectively) are well-established antimicrobial nanomaterials with broad-spectrum activity and multifaceted mechanisms of action. This review highlights recent advances, focusing on their a... read more

Time-resolved fluorescence imaging of methylene blue reveals heterogeneous polarity in living cells.

Journal of photochemistry and photobiology. B, Biology Jan 13, 2026

The paper presents time-resolved fluorescence analysis of methylene blue (MB) in solutions and in living cells in vitro. The analysis of MB fluorescence lifetime in solutions of different pH, viscosity and polarity revealed its independence on acidit... read more

SERS-based deep learning approach for early detection of gestational diabetes mellitus.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 13, 2026

Early and precise diagnosis of gestational diabetes mellitus (GDM) is crucial for improving maternal and neonatal outcomes and reducing the risk of adverse pregnancy events. However, current clinical screening methods for GDM still exhibit limitation... read more

Characteristics of phosphorus-solubilizing bacteria and mediated phosphorus cycle in sediments of urban river-lake interfaces.

Water research Jan 13, 2026

Urban river-lake interfaces are crucial areas for substance migration and transformation, and prone to algal blooms. However, the phosphorus (P) cycle in urban river-lake interfaces has not been comprehensively investigated, especially for the minera... read more

The flavor analysis of three table grapes (Shine Muscat, Kyoho, and Muscat of Alexandria) and their flavor prediction based on machine learning.

Food chemistry Jan 13, 2026

Table grapes are produced for direct consumption compared to wine grapes for winemaking. Aroma significantly influences table grape quality, and harvest timing is crucial. This study investigated the aroma profiles of three table grapes (Kyoho (JF), ... read more

Automated high-throughput microscopy screening unveiled new Listeria monocytogenes genes involved in cell infection.

Microbiological research Jan 13, 2026

To uncover novel genetic factors required for Listeria monocytogenes cell infection, we developed an automated high-throughput microscopy screening pipeline that integrates GFP-expressing bacteria with machine learning-based image analysis. Using thi... read more

Identifying endoplasmic reticulum stress-related key genes of vascular dementia using bioinformatics and biological experiments.

Biochemical and biophysical research communications Jan 13, 2026

Vascular dementia (VaD) is the second most common type of dementia, yet its pathogenesis is not fully understood, and effective diagnostic and therapeutic tools are lacking. While endoplasmic reticulum stress (ERS) is associated with VaD and is recog... read more

High-frequency dynamics of dissolved carbon fluxes from machine learning and their contribution to carbon budgets in tidal marsh wetlands in the Yangtze River Estuary, China.

Water research Jan 13, 2026

Accurately quantifying the carbon budgets of coastal wetlands is crucial; however, methodological constraints have limited our understanding of lateral carbon exchange. In this study, we take advantage of machine learning algorithms to develop a high... read more

SAGCN: A syntactic aware multi-branch graph attention network with structural bias for aspect sentiment triplet extraction.

Neural networks : the official journal of the International Neural Network Society Jan 13, 2026

Aspect-based sentiment triplet extraction (ASTE), a newly developed and complex subtask within aspect-based sentiment analysis, focuses on detecting aspect terms, opinion terms, and establishing sentiment polarity from human language, thereby extract... read more

Artificial Intelligence Medical Compendium