Optimizing ADAMTS13 prophylaxis to reduce relapse and organ failure in congenital thrombotic thrombocytopenic purpura. [PDF]
Joly BS +76 more
europepmc +1 more source
Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)
Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao +5 more
wiley +1 more source
Understanding Outcomes in Onco-critical Care: The Role of Frailty and Organ Failure. [PDF]
Ramamoorthy SV, Siddiqui SS.
europepmc +1 more source
Electroactive Metal–Organic Frameworks for Electrocatalysis
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source
Leptospirosis: An unusual cause of pulmonary haemorrhage and multi-organ failure. [PDF]
Chami BLB, Zgheib AJ.
europepmc +1 more source
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
Pancreatitis Unveiled: Linking Pathogenesis, Organ Failure, and Emerging Predictive Biomarkers. [PDF]
Anbazhagan PK +4 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Rapid development of extensive myocardial calcification in a diabetic patient with multi-organ failure: a case report. [PDF]
Marzouki S +3 more
europepmc +1 more source

