Results 161 to 170 of about 831,124 (298)

E2A selectively regulates TGF‐β–induced apoptosis in KRAS‐mutant non‐small cell lung cancer

open access: yesMolecular Oncology, EarlyView.
Ability to induce apoptosis by TGF‐β is frequently lost in advanced lung adenocarcinoma despite intact TGF‐β signaling. We identify E2A as a mutant KRAS–dependent mediator of resistance to TGF‐β–induced apoptosis. TGF‐β induces E2A via SMAD3 in mutant KRAS cells, and E2A silencing restores apoptosis and enhances radiation response in cell lines ...
Sergei Chuikov   +3 more
wiley   +1 more source

Discussion of ‘Prior-based Bayesian Information Criterion (PBIC)’

open access: yesStatistical Theory and Related Fields, 2019
Sifan Liu, Dongchu Sun
doaj   +3 more sources

KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer

open access: yesMolecular Oncology, EarlyView.
Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan   +16 more
wiley   +1 more source

Update to Trial Forge Guidance 2: addition of the Value of Information criterion. [PDF]

open access: yesTrials
Gkekas A   +5 more
europepmc   +1 more source

Heterozygous loss‐of‐function alleles associate the conserved 3′‐5′ exoribonuclease EXOSC10 with hypersensitivity to the anticancer drug 5‐fluorouracil

open access: yesMolecular Oncology, EarlyView.
EXOSC10, an essential nuclear RNA exosome‐associated 3′‐5′ exoribonuclease, is inhibited by the anticancer drug 5‐fluorouracil (5‐FU), and EXOSC10 depletion increases 5‐FU sensitivity. The colon‐cancer variant EXOSC10S402T, located in a proteolysis motif, is stable and nuclear but nonfunctional in vivo.
Radhika Sain   +10 more
wiley   +1 more source

Selecting an optimal set of parameters using an

open access: yes, 2008
The selection of an optimal set of parameters from a larger one is a well known identification problem in classification or clustering algorithms. The Akaike criterion has been developed to estimate the (Markov) order in auto regressive models.
Akaike Like Criterion, R. Moddemeijer A
core  

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