AIMC Topic: Humans

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Integrating machine learning with in silico studies and Quantum Chemistry: Exploring novel compounds through multiscale screening targeting the CDK2 enzyme.

Computers in biology and medicine
Cyclin-dependent kinase 2 (CDK2) modulates the progression of the cell cycle, and its dysregulation results in unchecked cellular proliferation, establishing it as a pivotal target in oncological therapies. We implemented a comprehensive screening pi...

Unlocking clinical quantum oncology through quantum control.

European journal of cancer (Oxford, England : 1990)
Quantum technologies present a transformative frontier for oncology, promising significant advancements in diagnostics, treatment precision, and drug discovery. The clinical realization of this potential is fundamentally reliant on mastering quantum ...

Rank labels scaffold social cognitive maps in the hippocampal-entorhinal system.

NeuroImage
How do humans construct mental representations of social hierarchies in the absence of direct interpersonal interactions? In many real-world contexts, humans rely on symbolic rank labels-such as titles or performance ratings-to navigate social hierar...

Transformative potential of artificial intelligence in US CDC HIV interventions: balancing innovation with health privacy.

AIDS (London, England)
Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment through the application of advanced technologies such as machine learning (ML), deep learning (DL), and generative AI (Gen AI). These technologies can ...

StackPIP: An Effective Computational Framework for Accurate and Balanced Identification of Proinflammatory Peptides.

Journal of chemical information and modeling
Proinflammatory peptides (PIPs) play a crucial role in immune response modulation by orchestrating cytokine release and leukocyte recruitment. Accurate identification of PIPs is essential for understanding inflammation-related diseases and developing...

Rapid Fluorescence Lifetime Imaging through One-Dimensional Deep Learning Optimization.

Analytical chemistry
Traditional fluorescence lifetime imaging (FLIM) provides valuable quantitative insights for biomedical and molecular biology research, but often relies on computationally intensive datafitting methods to extract meaningful metrics. To address this l...

MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.

Analytical chemistry
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...

Human and animal models for studying hemorrhagic shock.

Scandinavian journal of trauma, resuscitation and emergency medicine
BACKGROUND: Studying the physiological response to severe hemorrhage remains challenging in real-world patients. Animal and human models mitigate some of the challenges by facilitating controlled studies on hemorrhagic shock. Here, we comment on exis...

Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.

Orphanet journal of rare diseases
OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopathic pulmonary fibrosis (IPF). This study aimed to identify lipid-related genes implicated in IPF pathogenesis.

USP5-Mediated PD-L1 deubiquitination regulates immunotherapy efficacy in melanoma.

Journal of translational medicine
BACKGROUND: The role of post-translational modifications(PTMs) in PD-L1-mediated immune resistance and melanoma progression remains poorly understood.