Time trends and area-level socioeconomic inequalities in early childhood development at 2-2.5 years old in England between 2019 and 2025: a local area ecological study. [PDF]
Chua YW +5 more
europepmc +1 more source
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin +12 more
wiley +1 more source
Correction to 'Time Trends in the Rates of ED Visits in Australia, an Age-Period-Cohort Approach'. [PDF]
europepmc +1 more source
Time trends in ICD recommendations and predictors of device activation hypertrophic cardiomyopathy: a real-world cohort study. [PDF]
Marques Antunes M +12 more
europepmc +1 more source
Hydrostatic pressure activates HIF‐1α via β‐catenin to promote stemness in breast cancer cells
To mimic the elevated intestinal fluid pressure in breast cancers, we loaded human breast cancer cells (MCF‐7, MDA‐MB‐453, and BT‐474) to 50 mmHg hydrostatic pressure. Hydrostatic pressure exposure upregulated HIF‐1α and induced stemness in MCF‐7 and BT‐474 cells.
Da Zhai +8 more
wiley +1 more source
Cholangiocarcinoma in Denmark: time trends in mortality following resection. [PDF]
Jensen MD +5 more
europepmc +1 more source
Aquaporin‐3 and aquaporin‐5 impact the development of pancreatic ductal adenocarcinoma spheroids
Schematic representation of the role of aquaporin‐3 (AQP3) and aquaporin‐5 (AQP5) in pancreatic ductal adenocarcinoma (PDAC). Both proteins are upregulated in PDAC and are associated with tumor progression and metastatic potential. Silencing AQP3 or AQP5 in PDAC spheroids results in decreased diameter, area, and overall growth, underscoring their key ...
Catarina Pimpão +3 more
wiley +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source

