AIMC Topic: Humans

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Revealing the anti-tumor mechanisms of aromatic oil from Amomum villosum through integrated network pharmacology, bioinformatics, machine learning, single-cell sequencing, and cell experiments.

Biochemical and biophysical research communications
The dry fruits of Amomum villosum (Av) are a traditional Chinese medicine used for gastrointestinal disease. Aromatic oil has been reported to have anti-tumor properties. However, its therapeutic potential and molecular mechanisms remain unclear. Int...

Regional-aware and sequence-informed multi-decoder network for robust brain glioma segmentation in multi-parametric MRI.

Computers in biology and medicine
Accurate segmentation of glioblastoma subregions from multi-parametric MRI is essential for diagnosis, surgical planning, and treatment monitoring in neuro-oncology. However, effective delineation of surrounding non-enhancing FLAIR hyperintensity, no...

A filter-level explainability framework for CNNs in histopathology image analysis.

Computers in biology and medicine
Convolutional neural networks (CNNs) have achieved remarkable accuracy in histopathology image classification, yet their decision logic remains largely opaque. Most explainability methods, such as Grad-CAM or SHAP, provide only coarse heatmaps, offer...

Unraveling the Mechanisms of Osteoporosis Triggered by Methylparaben and Monomethyl Phthalate through Integrated Mendelian Randomization, In Silico Simulations, and Experimental Validation.

Environmental science & technology
Endocrine-disrupting chemicals (EDCs) are pervasive environmental hazards that have been linked to osteoporosis (OP), though causal mechanisms remain elusive. Employing an integrated multiomics framework, this study combined bidirectional Mendelian r...

Deep Learning-Assisted G4 Nanowire-Enhanced Carbon Dot Biosensor for Exosomal LncRNA Artificial Intelligence Diagnosis.

Analytical chemistry
Exosomal long noncoding RNAs (lncRNA) have significant potential as a biomarker for early cancer diagnosis. Accurate and sensitive detection of this abnormal expression remains challenging. Herein, we develop an innovative dual-mode photoelectrochemi...

Dynamic Interaction: Synthetic Biology and Cell-Free Biosensors Drive Each Other Forward.

ACS nano
The convergence of synthetic biology and biosensor technology is driving a scientific and technological revolution in biotechnology. Characterized by its interdisciplinary nature, synthetic biology applies engineering principles to design and constru...

Thyroid Function Effects of Mixed Exposure to Urinary Trihalomethanes and Haloacetic Acids: Based on an Integrated Framework of Exposure Assessment, Qualitative Association, and Quantitative Attribution.

Environmental science & technology
Toxicological studies have demonstrated that disinfection byproducts (DBPs) can disrupt thyroid function; however, human epidemiological evidence remains limited. The existing studies focus on a limited number of compounds and lack detailed investiga...

LGABAN: An Integrated Multi-Scale Approach Combining Graph and Sequence Features for Enhanced Prediction of Drug-Protein Interactions.

Journal of chemical information and modeling
The accurate identification of drug-target interactions is crucial for shortening the timeline and lowering the expenses of pharmaceutical research, as the discovery of novel drugs remains a highly complex, resource-intensive, and lengthy endeavor. D...

HGANMDA: A Heterogeneous Graph Adversarial Network for Multimodal Microbe-Drug Association Prediction.

Journal of chemical information and modeling
Accurate prediction of microbe-drug associations (MDAs) is vital for guiding antimicrobial therapy and accelerating drug repositioning. Although experimental validation remains the gold standard, it is costly and time-consuming. Existing models, ofte...

A Framework for Identifying Serum Exosomal Lipid Biomarkers in Alzheimer's Disease.

ACS chemical neuroscience
The escalating global burden of Alzheimer's disease (AD), projected to reach $16.9 trillion by 2050 with disproportionate impacts on low- and middle-income countries and racial minorities, underscores an urgent need for accessible early detection too...