AIMC Topic: Humans

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From biosensing to perception: Collaborative few-shot learning for explainable digital biomarker identification in high-dimensional biomedical spectra.

Biosensors & bioelectronics
The application of in vitro diagnostic biosensors for early cancer detection remains challenging due to the insufficient representation by a few molecular biomarkers. Digital biomarkers promise comprehensive disease phenotyping but face constraints o...

SPP1 as a key modulator of M2 macrophage polarization promotes endometriosis progression via activation of the FAK/PI3K/AKT pathway: A bioinformatics and experimental study.

International immunopharmacology
Endometriosis (EMs) is a gynecological disorder characterized by chronic inflammation and an aberrant immune microenvironment. In this study, we integrated the GSE6364 dataset from the GEO database to identify differentially expressed genes, and appl...

Identification and predictive machine learning model construction of gut microbiota associated with carcinoembryonic antigens in colorectal cancer.

mSphere
UNLABELLED: Carcinoembryonic antigen (CEA) is a critical colorectal cancer (CRC) biomarker, but its mechanistic link to gut microbiota remains unclear. This study characterized gut microbiota differences between high-CEA (H-CEA) and low-CEA (L-CEA) C...

Global wastewater microbiome reveals core bacterial community and viral diversity with regional antibiotic resistance patterns.

mSystems
Municipal wastewater treatment plants (WWTPs) serve as global repositories for diverse and dynamic microbial communities, reflecting the complex interplay of human activities, environmental conditions, and public health challenges. Despite their impo...

Graph Neural Networks in Modern AI-Aided Drug Discovery.

Chemical reviews
Graph neural networks (GNNs), as topology/structure-aware models within deep learning, have emerged as powerful tools for AI-aided drug discovery (AIDD). By directly operating on molecular graphs, GNNs offer an intuitive and expressive framework for ...

Rapid Template-Transferred Printing of Gelatin-Based Ionogels with Bioinspired Hierarchical Microstructures for Flexible Tactile Sensors.

Biomacromolecules
Flexible pressure sensors are pivotal for e-skin, artificial intelligence interactions, and personalized medicine. Nevertheless, integrating high sensitivity, a broad detection range, and biodegradability remains difficult. Herein, we developed a fle...

Integrating Machine Learning into Free Energy Perturbation Workflows.

Journal of chemical information and modeling
Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein-ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup proc...

MVSL-DSF: Multiview Subspace Representation Learning and Cross-Modal Feature Dynamic Aggregation for Enhanced Drug Side Effect Frequency Prediction.

Journal of chemical information and modeling
Drug side effects increase morbidity and mortality in the relevant medical fields. Assessing the frequency of drug side effects is crucial for drug development and risk-effect analysis. Most current research approaches focus on modeling heterogeneous...

Differentiating Gastric Cancers from Acid Peptic Diseases through Integrative Targeted Proteomics and Machine Learning Approaches.

Journal of proteome research
Gastric cancers (GCs) are often diagnosed in advanced stages owing to nonspecific early symptoms resembling Acid Peptic Diseases (APDs). Despite recent efforts, a simple, liquid biopsy-based multiprotein panel prediagnostic assay capable of different...

Versatile Image-Assisted Cell Sorting by Selective Trapping with Spatiotemporal Multiparameter Targeting.

ACS sensors
Current cell sorting methods often lack versatility, require complex setups, demand large initial cell numbers for reliable sorting, and impose size limitations on target objects. To address these challenges, we introduce two-dimensional sorting with...