AIMC Topic: Proteomics

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Beyond single biomarkers: multi-omics strategies to predict immunotherapy outcomes in blood cancers.

Clinical and experimental medicine
Immunotherapy has revolutionized hematologic cancer treatment, yet responses remain unpredictable due to primary resistance, relapse, and life-threatening toxicities. Conventional biomarkers fail to capture the complexity of tumor-immune interactions...

Transformative advances in single-cell omics: a comprehensive review of foundation models, multimodal integration and computational ecosystems.

Journal of translational medicine
Recent advances in single-cell multi-omics technologies have revolutionized cellular analysis, enabling comprehensive exploration of cellular heterogeneity, developmental trajectories, and disease mechanisms at unprecedented resolution. Foundation mo...

The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis.

Nature communications
Lyme neuroborreliosis (LNB), a nervous system infection caused by tick-borne spirochetes of the Borrelia burgdorferi sensu lato complex, is among the most frequent bacterial infections of the nervous system in Europe. Early diagnosis and continuous m...

Decoding herbal medicine: AI-powered omics and network pharmacology.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: As global health challenges continue to evolve, herbal medicines (HMs) have garnered significant scientific interest as a valuable resource for treating complex diseases. However, the chemical complexity of HMs presents considerable chall...

Identification of key diagnostic and prognostic biomarkers for aortic valve stenosis with coronary artery disease through immunological profiling integrating proteomics, single-cell sequencing, and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Aortic valve stenosis with coronary artery disease (AS-CAD) represents a common yet complex cardiovascular comorbidity, characterized by multifactorial pathogenesis and a lack of specific serum biomarkers. These limitations hinder early d...

Harnessing multi-omics and genome-editing technologies for climate-resilient agriculture: bridging AI-driven insights with sustainable crop improvement.

Plant molecular biology
Environmental challenges such as drought, salinity, heavy metal contamination, and nutrient deficiencies threaten global agricultural productivity and food security. These stressors drastically reduce crop yields, necessitating innovative solutions. ...

Mass spectrometry combined with machine learning identifies novel protein signatures as demonstrated with multisystem inflammatory syndrome in children.

Scientific reports
Rapid and accurate diagnosis of emerging inflammatory illnesses is challenging due to overlapping clinical features with existing conditions. We demonstrate an approach that integrates proteomic analysis with machine learning to identify diagnostic p...

Multi-omics reveal critical roles of phosphatidylcholine and sphingomyelin in antipsychotic efficacy for schizophrenia.

Signal transduction and targeted therapy
Nearly 30% of patients with schizophrenia respond inadequately to current antipsychotics, with unclear markers and mechanisms of antipsychotic efficacy. A total of 208 patients with schizophrenia treated for 6 weeks with oral paliperidone were analyz...

Integrated multi-omics and machine learning approach reveals the mechanism of nicotinamide alleviating PFOS-induced hepatotoxicity.

Food & function
: Perfluorooctane sulphonate (PFOS) is a persistent environmental contaminant with well-documented hepatotoxic properties. Nicotinamide, the amide derivative of vitamin B3, is widely utilized as a nutritional supplement and exerts multiple biological...

Mapping Context-Aware Phosphosite Regulation of Protein-Protein Interactions Using Deep Learning and Pan-Cancer Proteomics.

Journal of chemical information and modeling
Phosphorylation dynamically orchestrates the protein-protein interaction (PPI) network that governs cellular signaling, and its dysregulation frequently drives malignant transformation and neurodegeneration. We present PhosPPI-SEQ, an interpretable d...