Time trends in malaria incidence from 1992 to 2021 in high-risk regions: an age‑period‑cohort analysis based on the Global Burden of Disease study 2021.

Objectives: Malaria, caused by plasmodium parasites, remains one of the world's most significant infectious diseases due to its high incidence and mortality. This study aims to analyze malaria incidence globally, identify high-risk regions, and examine long-term trends in incidence to provide important evidence for malaria eradication.

Methods: We used data from the Global Burden of Disease Study (GBD) 2021, applying the age-period-cohort model to estimate the effects of age, period and cohort on malaria incidence from 1992 to 2021.

Sinularin Exerts Anti-cancer Effects by Inducing Oxidative Stress-mediated Ferroptosis, Apoptosis, and Autophagy in Prostate Cancer Cells.

Introduction: Prostate cancer is the second-leading cause of cancer death in men. Sinularin is a soft coralsderived natural compound that has anticancer activity in many cancer cells. However, the pharmacological action of sinularin in prostate cancer is unclear.

Propagation and self-healing properties of Bessel-Gaussian beam carrying orbital angular momentum in an underwater environment.

In this paper, we report on experimental demonstration of the propagation and self-healing property of Bessel-Gaussian (BG) beam carrying orbital angular momentum (OAM) in an underwater environment. Especially, the effects of topological charge, temperature gradient, and salinity on the transmission and self-reconstruction of BG beam in underwater turbulence are analyzed. The results show that the detection probabilities both for propagation and self-healing greatly decrease with temperature gradient, and gradually decrease with salinity.

An ant colony optimization based algorithm for identifying gene regulatory elements.

It is one of the most important tasks in bioinformatics to identify the regulatory elements in gene sequences. Most of the existing algorithms for identifying regulatory elements are inclined to converge into a local optimum, and have high time complexity. Ant Colony Optimization (ACO) is a meta-heuristic method based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of real ants.