https://www.selleckchem.com/pr....oducts/k-ras-g12c-in
LC-QTOF MS analysis allowed to identify tentatively five transformation products (TPs) formed during the ANZ degradation process in DW, and two TPs when HWW was used. The main proposed degradation pathways were demethylation and hydroxylation. Different in silico models free available (quantitative) structure-activity relationship ((Q)SAR) software were used to predict the ecotoxicities and environmental fates of ANZ and the TPs. The in silico (Q)SAR predictions indicated that ANZ and the TPs were non-biodegradable compo

https://www.selleckchem.com/products/ABT-263.html
Acute kidney injury (AKI) is common among hospitalized patients and has a significant impact on morbidity and mortality. Although early prediction of AKI has the potential to reduce adverse patient outcomes, it remains a difficult condition to predict and diagnose. The purpose of this study was to evaluate the ability of a machine learning algorithm to predict for AKI as defined by Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or 3 up to 48 hours in advance of onset using convolutional neural networks (CNNs) and patient elect