E2A selectively regulates TGF‐β–induced apoptosis in KRAS‐mutant non‐small cell lung cancer
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)’
Sifan Liu, Dongchu Sun
doaj +3 more sources
Detecting multiple spatial disease clusters: information criterion and scan statistic approach. [PDF]
Takahashi K, Shimadzu H.
europepmc +1 more source
KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer
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]
Gkekas A +5 more
europepmc +1 more source
Improved Parsimonious Topic Modeling Based on the Bayesian Information Criterion. [PDF]
Wang H, Miller D.
europepmc +1 more source
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
Change Point Detection in Panel Linear Regression Models Based on Jump Information Criterion. [PDF]
Zhao W, Fan L, Xia Z.
europepmc +1 more source
A stress test to evaluate the usefulness of Akaike information criterion in short-term earthquake prediction. [PDF]
Tozzi R, Masci F, Pezzopane M.
europepmc +1 more source
Selecting an optimal set of parameters using an
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

