Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For high-risk patients requiring intensive care unit stay, predicting transfusion needs during the first 24 h using dynamic risk assessment may improve resuscitation with red blood cell transfusion in admitted patients with severe acute gastrointestinal bleeding. A patient cohort admitted for acute gastrointestinal bleeding (N = 2,524) was identified from the Medical Information Mart for Intensive Care III (MIMIC-III) critical care database and separated into training (N = 2,032) and internal validation (N = 492) sets. The external validation patient cohort was identified from the eICU collaborative database of patients admitted for acute gastrointestinal bleeding presenting to large urban hospitals (N = 1,526). 62 demographic, clinical, and laboratory test features were consolidated into 4-h time intervals over the first 24 h from admission. The outcome measure was the transfusion of red blood cells during each 4-h time interval. A long short-term memory (LSTM) model, a type of Recurrent Neural Network, was compared to a regression-based models on time-updated data. The LSTM model performed better than discrete time regression-based models for both internal validation (AUROC 0.81 vs 0.75 vs 0.75; P < 0.001) and external validation (AUROC 0.65 vs 0.56 vs 0.56; P < 0.001). A LSTM model can be used to predict the need for transfusion of packed red blood cells over the first 24 h from admission to help personalize the care of high-risk patients with acute gastrointestinal bleeding.

Vitamin K epoxide reductase regulation of androgen receptor activity.

Long-term use of warfarin has been shown to be associated with a reduced risk of prostate cancer. Warfarin belongs to the vitamin K antagonist class of anticoagulants, which inhibit vitamin K epoxide reductase (VKOR). The vitamin K cycle is primarily known for its role in γ-carboxylation, a rare post-translational modification important in blood coagulation. Here we show that warfarin inhibits the transcriptional activity of the androgen receptor (AR), an important driver of prostate cancer development and progression. Warfarin treatment or knockdown of its target VKOR inhibits the activity of AR both in cell lines and in mouse prostate tissue. We demonstrate that AR can be γ-carboxylated, and mapped the γ-carboxylation to glutamate residue 2 (E2) using mass spectrometry. However, mutation of E2 and other glutamates on AR failed to suppress the effects of warfarin on AR suggesting that inhibition of AR is γ-carboxylation independent. To identify pathways upstream of AR signaling that are affected by warfarin, we performed RNA-seq on prostates of warfarin-treated mice. We found that warfarin inhibited peroxisome proliferator-activated receptor gamma (PPARγ) signaling, which in turn, inhibited AR signaling. Although warfarin is unfit for use as a chemopreventative due to its anticoagulatory effects, our data suggest that its ability to reduce prostate cancer risk is independent of its anticoagulation properties. Furthermore, our data show that warfarin inhibits PPARγ and AR signaling, which suggests that inhibition of these pathways could be used to reduce the risk of developing prostate cancer.