Results 241 to 250 of about 4,875,916 (336)

Deciphering the Metabolic Impact and Clinical Relevance of N‐Glycosylation in Colorectal Cancer through Comprehensive Glycoproteomic Profiling

open access: yesAdvanced Science, EarlyView.
The comprehensive proteomic and N‐glycoproteomic analyses of 45 colorectal cancer tissues with matched normal adjacent tissues identified 7125 intact N‐glycopeptides from 704 glycoproteins. A glycosylation site‐protein function network revealing metabolic dysregulation is constructed and a model differentiating tumors from normal tissues is developed ...
Guobin Liu   +10 more
wiley   +1 more source

Single‐Cell Analysis Clarifies Pathological Heterogeneity in Tenosynovial Giant Cell Tumor and Identifies Biomarkers for Predicting Disease Recurrence

open access: yesAdvanced Science, EarlyView.
MP3 tumor cells, a specific subpopulation of tumor cells in D‐TGCT, regulated the differentiation of CD34+ Fbs into MMP3+ Fbs and APOE+ Fbs through COL6A3 − (ITGAV + ITGB8) interaction. APOE+ Fbs activated IL‐1B+CCL20+ Mφs through the CXCL12/CXCR4 axis. IL‐1B+CCL20+ Mφs and MMP3+ Fbs participated in the local invasion of D‐TGCT.
Yubin Xie   +15 more
wiley   +1 more source

Eosinophils‐Induced Lumican Secretion by Synovial Fibroblasts Alleviates Cartilage Degradation via the TGF‐β Pathway Mediated by Anxa1 Binding

open access: yesAdvanced Science, EarlyView.
Eosinophils play a crucial role in the progression of temporomandibular joint osteoarthritis (TMJOA). This study demonstrates that eosinophils, induced by OVA/IL‐5, promote Lumican secretion in the synovium, which binds to Annexin A1 in chondrocytes, inhibiting transforming growth factor β2 and Smad2/3 phosphorylation.
Wenqian Chen   +12 more
wiley   +1 more source

Neurology of Sign Language [PDF]

open access: hybrid, 2004
J Gordon Millichap
openalex   +1 more source

AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices

open access: yesAdvanced Science, EarlyView.
Triboelectric nanogenerators (TENGs) enable sustainable energy harvesting and self‐powered sensing but face challenges in material optimization, fabrication, and stability. Integrating artificial intelligence (AI) enhances TENG performance through machine learning, improving energy output, adaptability, and predictive maintenance.
Aiswarya Baburaj   +4 more
wiley   +1 more source

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