Construction and validation of a clinical prediction model for sepsis using peripheral perfusion index to predict in-hospital and 28-day mortality risk.

Sepsis is a clinical syndrome caused by infection, leading to organ dysfunction due to a dysregulated host response. In recent years, its high mortality rate has made it a significant cause of death and disability worldwide. The pathophysiological process of sepsis is related to the body's dysregulated response to infection, with microcirculatory changes serving as early warning signals that guide clinical treatment.

Celastrol enhances the viability of random-pattern skin flaps by regulating autophagy through the AMPK-mTOR-TFEB axis.

In reconstructive and plastic surgery, random-pattern skin flaps (RPSF) are often used to correct defects. However, their clinical usefulness is limited due to their susceptibility to necrosis, especially on the distal side of the RPSF. This study validates the protective effect of celastrol (CEL) on flap viability and explores in terms of underlying mechanisms of action.

Self-Adaptive Image Thresholding within Nonextensive Entropy and the Variance of the Gray-Level Distribution.

In order to automatically recognize different kinds of objects from their backgrounds, a self-adaptive segmentation algorithm that can effectively extract the targets from various surroundings is of great importance. Image thresholding is widely adopted in this field because of its simplicity and high efficiency. The entropy-based and variance-based algorithms are two main kinds of image thresholding methods, and have been independently developed for different kinds of images over the years.