Results 81 to 90 of about 50,436 (310)

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

Unveiling unique protein and phosphorylation signatures in lung adenocarcinomas with and without ALK, EGFR, and KRAS genetic alterations

open access: yesMolecular Oncology, EarlyView.
Proteomic and phosphoproteomic analyses were performed on lung adenocarcinoma (LUAD) tumors with EGFR, KRAS, or EML4–ALK alterations and wild‐type cases. Distinct protein expression and phosphorylation patterns were identified, especially in EGFR‐mutated tumors. Key altered pathways included vesicle transport and RNA splicing.
Fanni Bugyi   +12 more
wiley   +1 more source

Absolute Value Variational Inequalities and Dynamical Systems

open access: yesInternational Journal of Analysis and Applications, 2020
In this paper, we consider the absolute value variational inequalities. We propose and analyze the projected dynamical system associated with absolute value variational inequalities by using the projection method.
Safeera Batool   +2 more
doaj  

Targeting of PTP4A3 overexpression sensitises HGSOC cells towards chemotherapeutic drugs

open access: yesMolecular Oncology, EarlyView.
In HGSOC with normal KRAS expression, high PTP4A3 expression regulates autophagy activation. Conversely, in HGSOC with high KRAS expression, KRAS dictates autophagy control, and PTP4A3 is not required. When high PTP4A3 expression is inhibited, HGSOC cells are preferentially sensitised towards DNA‐damaging agents.
Ana López‐Garza   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy