Shulan He

Background: Longitudinal evidence linking the body shape index (ABSI) to dementia and its subtypes remains scarce. Furthermore, the use of ABSI and TyG-ABSI as predictors of cognitive decline and dementia is infrequent. Therefore, this study aimed to examine the relationships between the triglyceride-glucose (TyG) index, ABSI, and TyG-ABSI indices and their predictive value for cognitive decline and dementia risk. Methods: This study included 370,744 participants from the UK Biobank. The TyG and ABSI indices were calculated using their respective formulas, while the TyG-ABSI index was derived by multiplying TyG and ABSI. Cognitive decline was defined as scoring in the bottom 25% on cognitive tests, while dementia was diagnosed from first-recorded incidents and algorithmically-defined outcomes. Logistic regressions were employed to assess the associations of TyG, ABSI and TyG-ABSI indices with cognitive decline; Cox regressions were used to analyze the associations of these indices with the risk of all-cause dementia (ACD) and its subtypes. Result: The TyG, ABSI, and TyG-ABSI indices were all significantly associated with cognitive decline. Additionally, compared with the lowest quartiles, the highest quartiles of TyG, ABSI and TyG-ABSI indices were associated with a significantly increased risk of ACD by 33% (HR = 1.33, 95% CI: 1.13–1.57), 79% (HR = 1.79, 95% CI: 1.65–1.94) and 67% (HR = 1.67, 95% CI: 1.54–1.82), respectively. These indices were also significantly associated with the risk of Alzheimer’s disease (AD) and vascular dementia (VD) (all P < 0.05). Conclusion: The TyG, ABSI, and TyG-ABSI indices are significantly and positively linked to the risk of cognitive decline and dementia.

Accumulating evidence links mood instability to an increased risk of adverse outcomes, yet its relationship with neurodegenerative diseases remains underexplored. This study examines the associations between mood instability symptoms and the risk of neurodegenerative diseases, exploring the mediating role of biological aging. The participants in the UK Biobank without a diagnosed neurological condition at baseline were included. Mood instability symptoms were assessed at two time points: baseline (2006–2010, T1) and the third visit (2014 + , T2), using 13 items of mental symptoms (e.g., “mood goes up and down,” “miserable for no reason”). Biological aging was generated by two previously described measures of biological age based on 14 routinely measured clinical biomarkers (PhenoAge, Klemera-Doubal method age). Latent class analysis (LCA) was employed to classify individuals into different psychological clusters. Cox proportional hazard models and mediation analyses were used to examine the associations between mood instability symptoms, biological aging, and adverse health outcomes. The latent transition analysis (LTA) identified latent classes of transition, and multifactor logistic regression was used to examine the sex difference in the probability of transitioning between these latent classes. Of 185,818 included participants, 51.86% were female. During a median follow-up of 14.6 years, we identified three clusters with distinct mood patterns. Compared to individuals with a pattern of “stable,” individuals with severe mood instability symptoms at baseline was significantly associated with an increased risk of all-cause dementia (hazard ratio [HR] = 1.17, 95% CI: 1.02–1.35), Parkinson’s disease (HR = 1.47, 95% CI: 1.21–1.77), and all-cause mortality (HR = 1.07, 95% CI: 1.01–1.14). Accelerated biological aging was also linked to a higher risk of both dementia and Parkinson’s disease. Mediation analyses revealed that biological aging partially mediated the association between severe mood instability symptoms and neurodegenerative diseases, as well as mortality (ranging from 0.78% to 13.6%). Notably, females had a higher risk of transitioning to more severe groups over time. These findings underscore the critical need to focus on severe mood instability symptoms in early intervention strategies to reduce neurodegenerative disease risk, particularly by focusing on emotional well-being in females.

Purpose: High consumption of Ultra-processed foods (UPF) have been identified as a potential risk factor for Non-alcoholic fatty liver disease (NAFLD). Nevertheless, there is limited empirical evidence regarding the impact of UPF, which are typical combination of processed foods, on liver health through alterations in gut microbiota and metabolic processes. We aim to examine the potential impact of UPF on liver health and to explore the role of gut microbiota and metabolites.Methods: This study used Sprague–Dawley rats to mimic modern UPF diets for 90 days. Some serum biochemical indices, inflammatory factors, oxidative stress markers, hematoxylin–eosin (HE) staining of the liver, 16S ribosomal RNA (rRNA) and Liquid chromatography-mass spectrometry (LC–MS) of rat feces were detected.Results: The UPF diet-induced simple steatosis of the liver in rats without affecting the levels of IL-6, GSH, MDA, and SOD. Additionally, it modified the gut microbiota, increasing potentially harmful bacteria, such as norank_f__Desulfovibrionaceae and Staphylococcus, while also elevating the relative abundance of potentially beneficial bacteria, including Dubosiella and Allobaculum. Furthermore, the consumption of UPF led to a metabolomic disorder characterized by disruptions in the sphingolipid signaling pathway, sulfur relay system, and arachidonic acid metabolism.Conclusion: In conclusion, the findings of this study indicate that the consumption of UPF influences the development of simple hepatic steatosis, potentially through alterations in gut microbiota and metabolomics.

Background: China is one of the top countries with the most significant number or proportion of retracted publications, which has garnered significant attention. Methods: Using the Retraction Watch Database, we collected retracted articles written by Chinese authors from 31 provinces in mainland China, spanning the period between January 1, 2012, and December 31, 2023. We used Geographical Information Science to analyze spatial distribution characteristics of retracted articles by Chinese authors and identify high-risk clusters of retracted areas. Results: A total of 14,445 retracted articles authored by researchers from 31 provinces in China between 2012 and 2023 were analyzed. The Spatial trend surface analysis and Gravity center movement indicated a gradual increase in the number of retracted articles from the west to the east. The spatial autocorrelation analysis showed that revealed significant spatial clustering in the distribution of retracted articles across the 31 provinces. The results of the spatial-temporal clustering analysis showed that the hotspots were primarily concentrated in Shandong, Jiangsu, Shanghai, Henan, and Anhui. Conclusion: There is a discernible spatial clustering among these retractions, with a gradual increase in the number of retracted articles from west to east. Shandong, Jiangsu, Shanghai, Henan, and Anhui are the hotspots for retractions.

Microplastics (MPs) can enter the body via plastic products. Given modern plastic exposure, we seek to assess MP exposure in large populations through epidemiological tools. In this quasi-experimental study, every participant filled out a questionnaire, and those who satisfied any of the following requirements were not allowed to continue in the study: Diabetes, ulcerative colitis, Crohn’s disease, infectious diseases. Participants in the exposure and control groups were provided three hot meals in disposable plastic tableware (DPT) (n = 30) or non-DPT (n = 30), respectively. After a month of observation, individuals in the exposure group discontinued the three meals provided in DPT (n = 27) for 1 month as the post-exposure group. Each Participant in the three groups received a questionnaire survey and fecal sample collection. We compared the differences in MP levels between different groups and used the Bland–Altman analysis method to evaluate the consistency of the results obtained by different measurement methods. Statistically significant differences in the total quantity (P (0.80 matching degree) = 0.020; P (0.65 matching degree) < 0.001) and types (Polyethylene Terephthalate (EVA) (P = 0.039), Polyethylene Terephthalate (PET) (P = 0.022), Polyvinyl Butyral (PVB) (P = 0.013), Chlorinated Polyethylene (CPE) (P = 0.039), phenolic epoxy resin (P = 0.012)) of MPs were observed between the exposure and post-exposure groups. The Bland–Altman analysis results indicate that the two methods exhibit good consistency in the three groups (control group: mean difference = 0.54, agreement limits (95% CI) = − 0.44 ~ 1.54; exposure group: mean difference = 0.41, agreement limits (95% CI) = − 0.19 ~ 1.01; post-exposure group: mean difference = 0.19, agreement limits (95% CI) = − 0.63 ~ 1.02). The method based on questionnaire surveys can substitute the method of fecal sample detection to evaluate the exposure of MP particles.