Results 201 to 210 of about 12,692,953 (333)
Balance the scales of Technology Justice
Animated infographic from Technology Justice: A Call to ActionInfographic encouraging action to achieve Technology Justice.
Practical Action
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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
Commentary: Interventricular Differences in Action Potential Duration Restitution Contribute to Dissimilar Ventricular Rhythms in ex vivo Perfused Hearts. [PDF]
Kucher A, Stroobandt RX.
europepmc +1 more source
PO-05-003 EMPAGLIFLOZIN SHORTENED THE PROLONGED ACTION POTENTIAL DURATION IN HUMAN INDUCED PLURIPOTENT STEM CELL-DERIVED CARDIOMYOCYTES WITH THIN FILAMENT HYPERTROPHIC CARDIOMYOPATHY [PDF]
Wei Zhou +4 more
openalex +1 more source
Engaging the practice of Indigenous yarning in Action Research
This paper discusses the technique of ‘yarning’ as an action research process relevant for policy development work with Aboriginal peoples. Through a case study of an Aboriginal community-based smoking project in the Australian State of Victoria, the ...
Fredericks, Bronywn, Adams, Karen
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UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová +2 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

