Accurate prediction of acute pancreatitis severity with integrative blood molecular measurements.

Background: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results for stratifying acute pancreatitis (AP) severity.

Results: We identified 11 markers predictive of AP severity and trained an AP stratification model called APSAVE, which classified AP cases within 24 hours at an average area under the curve (AUC) of 0.

Involvement of Sp1/Sp3 in the activation of the GATA-1 erythroid promoter in K562 cells.

GATA-1 is a hematopoietic transcription factor that is essential for the terminal maturation of proerythroblasts, megakaryocytic cells and mast cells. The erythroid-specific promoter of the human GATA-1 gene directs the high expression of a reporter gene in K562 cells. Multiple putative transcription factor binding sites were identified in the promoter from the -860 to the -1 base pair (bp).