Results 151 to 160 of about 531,456 (310)
We identified adaptor protein ShcD as upregulated in triple‐negative breast cancer and found its expression to be correlated with reduced patient survival and increased invasion in cell models. Using a proteomic screen, we identified novel ShcD binding partners involved in EGFR signaling pathways.
Hayley R. Lau+11 more
wiley +1 more source
This study highlights the importance of multi‐omic analyses in characterizing colorectal cancers. Indeed, our analysis revealed a rare CMS1 exhibiting dampened immune activation, including reduced PD‐1 expression, moderate CD8+ T‐cell infiltration, and suppressed JAK/STAT pathway.
Livia Concetti+10 more
wiley +1 more source
More on the Relations among Categorization, Merge and Labeling, and Their Nature
Koji Hoshi
doaj +1 more source
Transition Processes in Technological Systems: Inspiration from Processes in Biological Evolution. [PDF]
Möller M+3 more
europepmc +1 more source
How and why kinetics, thermodynamics, and chemistry induce the logic of biological evolution. [PDF]
Pross A, Pascal R.
europepmc +1 more source
Stepwise evolution of molecular biological coding [PDF]
Peter R. Wills
openalex +1 more source
Dual targeting of AKT and mTOR using MK2206 and RAD001 reduces tumor burden in an intracardiac colon cancer circulating tumor cell xenotransplantation model. Analysis of AKT isoform‐specific knockdowns in CTC‐MCC‐41 reveals differentially regulated proteins and phospho‐proteins by liquid chromatography coupled mass spectrometry. Circulating tumor cells
Daniel J. Smit+19 more
wiley +1 more source
Chemical roots of biological evolution: the origins of life as a process of development of autonomous functional systems. [PDF]
Ruiz-Mirazo K+2 more
europepmc +1 more source
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain+3 more
wiley +1 more source
Prediction of biological evolution following blood product transfusion during liver transplantation: the contribution of machine learning to decision-making. [PDF]
Duranteau O+11 more
europepmc +1 more source