Results 161 to 170 of about 7,285,451 (331)

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

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

RKIP overexpression reduces lung adenocarcinoma aggressiveness and sensitizes cells to EGFR‐targeted therapies

open access: yesMolecular Oncology, EarlyView.
RKIP, a metastasis suppressor protein, modulates key oncogenic pathways in lung adenocarcinoma. In silico analyses linked low RKIP expression to poor survival. Functional studies revealed RKIP overexpression reduces tumor aggressiveness and enhances sensitivity to EGFR‐targeted therapies, while its loss promotes resistance.
Ana Raquel‐Cunha   +10 more
wiley   +1 more source

A randomized controlled trial of self-help cognitive behavioural therapy for depression in adults with pulmonary hypertension. [PDF]

open access: yesBr J Health Psychol
Stark ASL   +5 more
europepmc   +1 more source

Data‐driven performance metrics for neural network learning

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri   +2 more
wiley   +1 more source

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