A familiar face at childbirth makes a difference
Peer-Reviewed Publication
Updates every hour. Last Updated: 4-Feb-2025 06:08 ET (4-Feb-2025 11:08 GMT/UTC)
A new Dartmouth-led study finds that pregnant individuals who were unable to have their desired emotional support persons present during childbirth were more likely to have higher levels of perceived childbirth stress than those who were not missing their support people. The findings are published in Evolution, Medicine, & Public Health.
New research from the University of Minnesota and Boston University School of Public Health (BUSPH) shows that death rates for early adults, or adults aged 25-44, rose sharply during the COVID-19 pandemic and remain higher than expected post-pandemic. Heightened death rates during the COVID-19 pandemic intensified an already negative trend for early adults, which began around 2010. As a result, early adult death rates in 2023 were about 70 percent higher than they might have been if death rates had not begun to rise about a decade before the pandemic.
The study found that the rates of patients leaving before medically advised increased during the COVID-19 pandemic. There were 721 million emergency department visits from 2016 to 2021, of which 194 million (26.9 percent) occurred after March 2020. Patients left before medically advised in 5.9 million emergency department visits during the study period—especially in the second, third and fourth quarters of 2020 and fourth quarter of 2021—for a 53.6 percent increase over pre-pandemic levels. The researchers noted that the increase could be the result of concern about COVID-19 infection and dissatisfaction with longer waiting times and other factors triggered by the surge in pandemic-related demands on hospitals.
Sepsis is deadly because it varies so greatly between different patients, and within individual patients over time, making it hard to diagnose and treat effectively. But scientists writing in Frontiers in Science explain how we can tackle the challenge by understanding sepsis as the result of multiple types of immune dysregulation. Using systems immunology to understand its mechanisms and target treatments, the researchers argue that we can tackle a major under-recognized cause of deaths worldwide, prevent deaths from future pandemic diseases, and treat survivors’ lingering symptoms.
Researchers have developed a powerful tool that can detect variants of SARS-CoV-2 with high transmission potential before they become widespread. This approach could significantly support public health efforts to control outbreaks and help identify new variants that need closer monitoring.
Researchers from Zhejiang University and HKUST (Guangzhou) have introduced ProtET, an innovative AI-powered multi-modal protein editing model published in Health Data Science. ProtET leverages advanced transformer-structured encoders and a hierarchical training paradigm to align protein sequences with natural language instructions, enabling precise and controllable protein editing.
The model was trained on over 67 million protein-biotext pairs from Swiss-Prot and TrEMBL databases and demonstrated significant improvements across key benchmarks, including 16.9% enhanced protein stability, optimized enzyme catalytic activity, and improved antibody-antigen binding affinity. ProtET’s zero-shot capabilities successfully designed SARS-CoV antibodies with stable 3D structures, highlighting its real-world biomedical applications.
This research represents a major advancement in AI-driven protein engineering, offering a scalable and interactive tool for scientific discovery, synthetic biology, and therapeutic development.