AIMC Topic: Humans

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Improved CRISPR/Cas9 off-target prediction with DNABERT and epigenetic features.

PloS one
CRISPR/Cas9 is a powerful genome editing tool, but its clinical application is hindered by off-target effects. Accurate computational prediction of these unintended edits is crucial for ensuring the safety and efficacy of therapeutic applications. Wh...

Selective cytotoxicity of anhydroicaritin in ER-positive breast cancer via ESR1-mediated MAPK and apoptotic signaling.

Chemico-biological interactions
Anhydroicaritin (AHI), a chemically characterized prenylated flavonoid, exhibits strong and selective cytotoxicity against estrogen receptor-positive (ER+) breast cancer cells. In this study, we aimed to elucidate its molecular and cellular toxicolog...

HMGCR-driven cholesterol metabolism dysregulation and its role in osteoarthritis diagnosis and immune regulation.

Biochemical and biophysical research communications
Osteoarthritis (OA) is the most common degenerative joint disease, and the complexity of its molecular mechanisms has hindered the development of effective diagnostic and therapeutic strategies. In this study, we integrated five independent OA RNA-se...

Dynamic Changes in Metabolic Syndrome Scores and New-Onset Stroke Risk in Middle-Aged and Older Adults: A Nationwide Prospective Cohort Study in China Aligned With Predictive, Preventive, and Personalized Medicine.

Journal of the American Heart Association
BACKGROUND: Despite the established link between metabolic syndrome (MetS) and stroke incidence, the effects of dynamic and cumulative MetS scores on stroke risk among middle-aged and older populations in China remain inadequately explored. Furthermo...

Machine-learning models based on histological images from healthy donors identify imageQTLs and predict chronological age.

Proceedings of the National Academy of Sciences of the United States of America
Histological images offer a wealth of data. Mining these data holds significant potential for enhancing disease diagnosis and prognosis, though challenges remain, especially in noncancer contexts. In this study, we developed a statistical framework t...

Testing Sentence-in-Noise Recognition With Synthetic Speech and Automatic Speech Recognition.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Characterizing speech-in-noise recognition is fundamental to both clinical audiology and hearing research. Current methods rely on human speech recordings and human testers. However, modern artificial intelligence tools could automate both s...

Pragmatic Approaches to the Evaluation and Monitoring of Artificial Intelligence in Health Care: A Science Advisory From the American Heart Association.

Circulation
The rapid development and integration of artificial intelligence (AI), including predictive, generative, and emerging agentic tools, into cardiovascular and stroke care is outpacing traditional evaluation frameworks and the generation of robust clini...

State of the Art: Evaluation and Medical Management of Nonobstructive Coronary Artery Disease in Patients With Chest Pain: A Scientific Statement From the American Heart Association.

Circulation
Risk stratification of patients with chest pain has traditionally focused on identifying obstructive coronary artery disease (CAD). Using this traditional approach, many symptomatic individuals are found to have nonobstructive CAD. The 2021 American ...

Tb(III)-Functionalized Hydrogen-Bonded Organic Framework with Dual-Emission for Liver Health Biomarker Detection and a Smartphone-Integrated Bionic Visual Diagnostic Platform.

Analytical chemistry
Developing a sensitive analytical platform for monitoring tiopronin (MPG), its metabolite 2-mercaptopropionic acid (MPA), and the key liver biomarker glutathione (GSH) is crucial for liver health assessment. Here, an artificial intelligence-assisted ...

Design of Carbon Nanotube Inhibitors for Main Proteinase of SARS-CoV-2: A Combined Deep Learning and Molecular Dynamics Simulation Study.

The journal of physical chemistry. B
The rapid development of machine learning (ML) and deep learning (DL) methods provides new opportunities for innovative drug discovery. While these techniques are widely used in docking organic molecules (drugs) with protein, an evaluation of the per...