What, When, and Why: Viscoelastic Hemostatic Assays and Their Uses in Trauma Resuscitation.

Viscoelastic hemostatic assays (VHAs) have become a valuable tool in guiding transfusion therapy, particularly in trauma care. While various forms of VHA exist, all provide a quantitative assessment of clot kinetics, strength, and dissolution. Studies have demonstrated that VHA can reduce both mortality and utilization of blood products in the general population.

Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.

Cryogenic phonon detectors with transition-edge sensors achieve the best sensitivity to sub-GeV/c dark matter interactions with nuclei in current direct detection experiments. In such devices, the temperature of the thermometer and the bias current in its readout circuit need careful optimization to achieve optimal detector performance. This task is not trivial and is typically done manually by an expert.

Combinatorial Separation of Cd and Te from CdTe via Chemical Vapour Transport with Sulfur and Air/Methane Treatment for the Recovery of Critical Resources from Thin Film Solar Cells.

Elemental Te and Cd are successfully recovered from CdTe via a combinatorial process involving chemical vapor transport (CVT) using sulfur as transport agent giving elemental Te being deposited. Separation is successfully enabled by the first process for CVT of Te starting with CdTe. Cd is subsequently recovered by an oxidation of the formed CdS to CdO followed by reduction to Cd metal with natural gas, in which Cd can also be separated via the gas phase.

Quality Assurance and Technology-Enabled Curation of Oncology Real-World Data: The Importance of Individual Quality Reviews.

Quality assurance is the foundation of clinical data abstraction. Meaningful insights can only be drawn from quality data. Through the development of robust quality-control processes for technology-enabled curation, Syapse's certified tumor registrars enrich real-world oncology data, supporting oncology patient care and research for a network of community health systems.

Biology-inspired graph neural network encodes reactome and reveals biochemical reactions of disease.

Functional heterogeneity of healthy human tissues complicates interpretation of molecular studies, impeding precision therapeutic target identification and treatment. Considering this, we generated a graph neural network with Reactome-based architecture and trained it using 9,115 samples from Genotype-Tissue Expression (GTEx). Our graph neural network (GNN) achieves adjusted Rand index (ARI) = 0.