Intensive selection pressure constrains the evolutionary trajectory of SARS-CoV-2 genomes and results in various novel variants with distinct mutation profiles. Point mutations, particularly those within the receptor binding domain (RBD) of SARS-CoV-2 spike (S) protein, lead to the functional alteration in both receptor engagement and monoclonal antibody (mAb) recognition. Here, we review the data of the RBD point mutations possessed by major SARS-CoV-2 variants and discuss their individual effects on ACE2 affinity and immune evasion. Many single amino acid substitutions within RBD epitopes crucial for the antibody evasion capacity may conversely weaken ACE2 binding affinity. However, this weakened effect could be largely compensated by specific epistatic mutations, such as N501Y, thus maintaining the overall ACE2 affinity for the spike protein of all major variants. The predominant direction of SARS-CoV-2 evolution lies neither in promoting ACE2 affinity nor evading mAb neutralization but in maintaining a delicate balance between these two dimensions. Together, this review interprets how RBD mutations efficiently resist antibody neutralization and meanwhile how the affinity between ACE2 and spike protein is maintained, emphasizing the significance of comprehensive assessment of spike mutations.

Background: Anemia and frailty contribute to poor health outcomes in older adults; however, most current research in lower income countries has concentrated on anemia or frailty alone rather than in combination. The aim of the present study was to investigate the association between anemia and frailty in community-dwelling adults aged 50 years and older in China. Methods: The study population was sourced from the 2007/10 SAGE China Wave 1. Anemia was defined as hemoglobin less than 13 g/dL for men and less than 12 g/dL for women. A Frailty Index (FI) was compiled to assess frailty. The association between anemia and frailty was evaluated using a 2-level hierarchical logistic model. Results: The prevalence of anemia was 31.0% (95%CI: 28.4, 33.8%) and frailty 14.7% (95%CI: 13.5, 16.0%). In the univariate regression model, presence of anemia was significantly associated with frailty (OR = 1.62, 95% CI: 1.39, 1.90) and the effect remained consistent after adjusting for various potential confounding factors including age, gender, residence, education, household wealth, fruit and vegetable intake, tobacco use, alcohol comsumption and physical activity (adjusted OR = 1.31, 95% CI:1.09, 1.57). Each 1 g/dL increase in hemoglobin concentration was associated with 4% decrease in the odds of frailty after adjusting for several confounding variables (adjusted OR = 0.96, 95% CI: 0.93, 0.99). Conclusion: Anemia and low hemoglobin concentrations were significantly associated with frailty. Therefore, health care professionals caring for older adults should increase screening, assessment of causes and treatment of anemia as one method of avoiding, delaying or even reversing frailty.

Introduction: The increasing adoption of large language models (LLMs) in public health has raised significant concerns about hallucinations-factually inaccurate or misleading outputs that can compromise clinical communication and policy decisions.Methods: We propose a retrieval-augmented generation framework with multi-evidence guided answer refinement (MEGA-RAG), specifically designed to mitigate hallucinations in public health applications. The framework integrates multi-source evidence retrieval (dense retrieval via FAISS, keyword-based retrieval via BM25, and biomedical knowledge graphs), employs a cross-encoder reranker to ensure semantic relevance, and incorporates a discrepancy-aware refinement module to further enhance factual accuracy.Results: Experimental evaluation demonstrates that MEGA-RAG outperforms four baseline models [PubMedBERT, PubMedGPT, standalone LLM, and LLM with standard retrieval-augmented generation (RAG)], achieving a reduction in hallucination rates by over 40%. It also achieves the highest accuracy (0.7913), precision (0.7541), recall (0.8304), and F1 score (0.7904).Discussion: These findings confirm that MEGA-RAG is highly effective in generating factually reliable and medically accurate responses, thereby enhancing the credibility of AI-generated health information for applications in health education, clinical communication, and evidence-based policy development.

Epidemiological evidence on the association of PM_2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) and its specific components with hypertension and blood pressure is limited. We applied information of participants from the World Health Organization's (WHO) Study on Global Ageing and Adult Health (SAGE) to estimate the associations of long-term PM_2.5 mass and its chemical components exposure with blood pressure (BP) and hypertension incidence in Chinese adults ≥ 50 years during 2007-2018. Generalized linear mixed model and Cox proportional hazard model were applied to investigate the effects of PM_2.5 mass and its chemical components on the incidence of hypertension and BP, respectively. Each interquartile range (IQR = 16.80 μg/m³) increase in the one-year average of PM_2.5 mass concentration was associated with a 17 % increase in the risk of hypertension (HR = 1.17, 95 % CI: 1.10, 1.24), and the population attributable fraction (PAF) was 23.44 % (95 % CI: 14.69 %, 31.55 %). Each IQR μg/m³ increase in PM_2.5 exposure was also related to increases of systolic blood pressure (SBP) by 2.54 mmHg (95 % CI:1.99, 3.10), and of diastolic blood pressure (DBP) by 1.36 mmHg (95 % CI: 1.04, 1.68). Additionally, the chemical components of SO₄^2-, NO₃^-, NH₄⁺, OM, and BC were also positively associated with an increased risk of hypertension incidence and elevated blood pressure. These results indicate that long-term exposure to PM_2.5 mass and its specific components may be major drivers of escalation in hypertension diseases.

In the absence of an effective treatment to alter the progressive course of cognitive decline and dementia, identification of modifiable risk factors that could promote healthy cognitive aging has become a public health research priority. This study seeks to comprehensively determine the contemporaneous associations of a broad spectrum of time-varying modifiable lifestyle factors with age-related cognitive decline in a large population-based cohort of older adults. A total of 5,711 subjects aged 50 and older from the WHO Study on global AGEing and adult health (SAGE) in Shanghai were studied. Repeated measures of lifestyle factors and cognitive performance were conducted in 2009–2010 and 2014–2015. Linear random slope models were used to evaluate the contemporaneous associations between time-varying lifestyle factors and cognitive performance. Person-mean centering method was used to disaggregate the between- and within-person effects in the time-varying lifestyle factors in the random slope models. We found that higher vegetable and fruit consumption, as well as higher level of physical activity were positively associated with all cognitive domains. Body mass index (BMI) was negatively associated with all cognitive domains, whereas waist-to-hip ratio (WHR) was negatively associated with verbal fluency score only. Sedentary time was negatively associated with digit span score but positively associated with verbal fluency score. The between-person effects seem to be more dominant than within-person effects. Overall, our findings suggest better management of multiple lifestyle factors may protect against cognitive decline in later life. Higher vegetable and fruit consumption and physical activity are protective, whereas obesity is detrimental to cognitive decline in older adults. This study underpins the development of multi-domain lifestyle recommendations to promote healthy cognitive aging.