One hundred days into the new federal administration, a new poll reports that major segments of the U.S. public anticipate they will lose trust in public health recommendations with the changes in health agency leadership. The poll, conducted among a national sample of U.S. adults, found that 44% of the public says having the new leaders in charge of federal public health agencies will make them trust health recommendations coming from these organizations less than they used to (including 14% who say “a little less” and 30% who say “a lot less”). A significantly smaller share (28%) say changes will make them trust recommendations more (including 18% who say “a little more” and just 10% who say “a lot more”).

Scientists believe they have found a way to improve warning systems for vulnerable communities threatened by humid heatwaves, which are on the rise due to climate change and can be damaging and even fatal to human health. The University of Leeds led study is the first ever analysis of how patterns of recent rainfall can interact with dry or moist land conditions to influence the risk of extreme humid heat in the global tropics and subtropics.  

In April 2025, the internationally renowned academic journal The Journal of the American Medical Association (JAMA) (Impact Factor: 63.5) published online a study titled “Non-Risk-Based Lung Cancer Screening With Low-Dose Computed Tomography”, led by Professors Jianxing He and Wenhua Liang from the First Affiliated Hospital of Guangzhou Medical University and the National Clinical Research Center for Respiratory Disease. 

 

This research, focusing on lung cancer screening strategies, revealed that the non-risk-based (universal) screening approach - unrestricted by traditional high-risk criteria - achieved a comparable detection rate of lung cancer among individuals not classified as high-risk relative to those who were. The findings underscore the necessity of evaluating the effectiveness of lung cancer screening in non-high-risk populations and developing biomarker-based enrichment strategies to refine pre-screening selection in this subgroup.