Metabolomics and Artificial Intelligence (AI) assisted metabolomics in the diagnosis of non-tuberculous mycobacterial infections: progress and challenges. [PDF]
Murthy MK, Gupta VK, Maurya AP.
europepmc +1 more source
Slc44a2 Deficiency Unveils an IFN‐I–Dependent Feedback Control of pDC Egress
Working model of SLC44A2‐mediated maintenance of pDC homeostasis. This model illustrates two central mechanisms by which SLC44A2 regulates pDC homeostasis: (1) SLC44A2 limits IFN‐I production by exporting amino acids (T, N, Q), thereby preventing spontaneous pDC activation.
Ruiqun Chen +11 more
wiley +1 more source
A machine learning‑enhanced serum metabolomics model for non‑invasive detection of gastric cancer. [PDF]
Ye X, Xing J, Niu L, Ding S, Song X.
europepmc +1 more source
Large‐scale UK Biobank analyses identify clinical and proteomic signatures for early prediction of valvular heart disease and its subtypes. Proteins add predictive value for VHD, AVS, and MVR, with outcome‐specific compact panels showing translational potential. Multi‐layer evidence highlights matrix remodeling, protease regulation, immune inflammation,
Zhihao Jiang +10 more
wiley +1 more source
Vitamin D status and <i>Helicobacter pylori</i> infection: clinical associations and lipid pathway differences in an exploratory metabolomics sub-study. [PDF]
El Shamieh S +8 more
europepmc +1 more source
To address the multifaceted imbalance in diabetic keratopathy, a light‐responsive biomimetic platform (WCNx‐Rh2) is developed and integrates glucose degradation, immune modulation, and antibacterial defense through a designed heterojunction and screened immunomodulator. WCNx‐Rh2 reduces AGEs/ROS and inflammatory signaling, reprogramming dendritic cells
Mengzhen Zhao +8 more
wiley +1 more source
Metabolomics and ultra-processed foods intake: A scoping review protocol. [PDF]
Peixoto TDN, Rocha ALMA, Pedrosa LFC.
europepmc +1 more source
ABSTRACT Background Therapeutic resistance limits durable survival in advanced/metastatic renal cell carcinoma (RCC) treated with first‐line tyrosine kinase inhibitor (TKI) plus immune checkpoint inhibitor (ICI). We sought to define key resistance drivers and actionable targets.
Jinchen Luo +16 more
wiley +1 more source
ML-BUSMetab: Machine Learning-Based Metabolomic Profiling for Predicting Aspirin Response in Colorectal Cancer Chemoprevention: A Multi-Model Explainable Artificial Intelligence Approach with External Validation. [PDF]
Pınar A, Arslan AK, Çolak C.
europepmc +1 more source

