Results 141 to 150 of about 2,277,171 (268)
Rapid dopaminergic signatures in movement: Reach vigor reflects reward prediction error and learned expectation. [PDF]
Korbisch CC, Ahmed AA.
europepmc +1 more source
Targeting p38α in cancer: challenges, opportunities, and emerging strategies
p38α normally regulates cellular stress responses and homeostasis and suppresses malignant transformation. In cancer, however, p38α is co‐opted to drive context‐dependent proliferation and dissemination. p38α also supports key functions in cells of the tumor microenvironment, including fibroblasts, myeloid cells, and T lymphocytes.
Angel R. Nebreda
wiley +1 more source
Evaluating the psychological mechanisms underlying new Olympic sports consumption: the expectation disconfirmation theory framework applied to Millennials' and Generation Z's experiences. [PDF]
Jang YS, Choi JY, Lim SY.
europepmc +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source
Placebo, nocebo: Believing in the field of medicine
Karin Meissner, Karin Meissner
doaj +1 more source
Expectation Effects Based on Newly Learnt Object-Scene Associations Are Modulated by Spatial Frequency. [PDF]
Kikkawa M, Feuerriegel D, Garrido MI.
europepmc +1 more source
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge +17 more
wiley +1 more source
Dissociable dynamic effects of expectation during statistical learning. [PDF]
McDermott HH +3 more
europepmc +1 more source
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source

