Dietary shifts in populations undergoing rapid economic transitions have been proposed as partly contributing toward the rapid intergenerational rise in myopia prevalence; however, empirical evidence of the effect of dietary factors on myopia is limited. This study investigated the association between dietary factors and incident myopia in Chinese children aged 10–11 years. We evaluated dietary habits using a 72-item food frequency questionnaire (FFQ) among 7423 children. Myopic status was assessed using the “General Personal Information Questionnaire”. Principal component analysis was used to extract dietary patterns and investigate their association with myopia. After adjusting for potential confounders, participants with the highest adherence to dietary pattern A (95% confidence interval (CI): 0.66–0.92, p for trend = 0.007) and dietary pattern C (95% CI: 0.58–0.80, p for trend < 0.001) had a lower risk of myopia than participants with the least adherence. Both of these dietary patterns are characterized by high consumption of meats, aquatic product, dairy and its products, eggs, legumes, vegetables, fruits, grains, and potatoes. Our findings suggest that other environmental factors, such as those related to the dietary environment, may contribute to the development of myopia. These findings can serve as a reference for diet-related primary prevention of myopia.

Background/Objectives: The prevalence of both myopia and obesity is increasing among children and adolescents around the world. We aimed to examine the association between weight status and myopia in Chinese children and adolescents. Methods: The analysis included 35,108 participants aged 6–17 from a nationwide cross-sectional survey. Results: Our results indicated that girls with overweight and obesity had higher odds ratio (OR) of myopia and mild myopia: ages 6–8 (OR = 1.33, 95% CI: 1.01–1.76; OR = 1.71, 95% CI: 1.14–2.55) and 9–11 (OR = 1.22, 95% CI: 1.03–1.44; OR = 1.31, 95% CI: 1.06–1.62). Myopic boys had higher body fat percentages (BFP) at ages 6–8 (β = 1.18, 95% CI: 0.38–1.98), 9–11 (β = 0.58, 95% CI: 0.08–1.07), and 15–17 (β = 0.42, 95% CI: 0.03–0.80), and higher body mass index (BMI) at ages 9–11 (β = 0.30, 95% CI: 0.12–0.48) and 12–14 (β = 0.19, 95% CI: 0.02–0.38). Girls had higher BFP at ages 9–11 (β = 0.62, 95% CI: 0.19–1.05) and 12–14 (β =0.53, 95% CI: 0.19–0.88) and higher BMI at 9–11 (β = 0.53, 95% CI: 0.34–0.73). Furthermore, the dose–response curves revealed a significant gender- and age-specific association between BMI, BFP, and myopia odds ratio. Conclusions: the study found an association between overweight or obesity and myopia in girls aged 6–11, and indicated that high BFP and BMI are associated with myopia, varying by sex and age.

Background: In the last decades, the molecular epidemiological investigation of Mycobacterium tuberculosis has significantly increased our understanding of tuberculosis epidemiology. However, few such studies have been done in southern Xinjiang, China. We aimed to clarify the molecular epidemic characteristics and their association with drug resistance in the M. tuberculosis isolates circulating in this area. Methods: A total of 347 isolates obtained from southern Xinjiang, China between Sep, 2017 and Sep, 2019 were included to characterize using a 15-locus MIRU-VNTR (VNTR-15_China) typing and spoligotyping, and test for drug susceptibility profiles. Then the lineages and clustering of the isolates were analyzed, as well as their association with drug resistance. Results: Spoligotyping results showed that 60 spoligotype international types (SITs) containing 35 predefined SITs and 25 Orphan or New patterns, and 12 definite genotypes were found, and the top three prevalent genotypes were Beijing genotype (207, 59.7%), followed by CAS1-Delhi (46, 13.6%), and Ural-2 (30, 8.6%). The prevalence of Beijing genotype infection in the younger age group (≤ 30) was more frequent than the two older groups (30~59 and ≥ 60 years old, both P values < 0.05). The Beijing genotype showed significantly higher prevalence of resistance to isoniazid, rifampicin, ethambutol, multi-drug or at least one drug than the non-Beijing genotype (All P values ≤ 0.05). The estimated proportion of tuberculosis cases due to transmission was 18.4% according to the cluster rate acquired by VNTR-15_China typing, and the Beijing genotype was the risk factor for the clustering (OR 9.15, 95% CI: 4.18– 20.05). Conclusion: Our data demonstrated that the Beijing genotype is the dominant lineage, associated with drug resistance, and was more likely to infect young people and contributed to tuberculosis transmission in southern Xinjiang, China. These findings will contribute to a better understanding of tuberculosis epidemiology in this area.

Hyperuricemia has emerged as a significant global health concern, closely associated with various metabolic disorders. The adverse effects frequently observed with current pharmacological treatments for hyperuricemia highlight the urgent need for reliable animal models to elucidate the disease’s pathophysiological mechanisms, thereby facilitating the development of safer and more effective therapies. In this study, we established three rat models of hyperuricemia using potassium oxonate, either alone or in combination with fructose and adenine. Each model exhibited distinct pathological changes, with the combination of potassium oxonate, fructose, and adenine causing significantly more severe damage to liver and kidney functions than potassium oxonate alone. Serum metabolomics analyses revealed profound dysregulation in the metabolic pathways of purine, pyrimidines, and glutathione, underscoring the pivotal role of oxidative stress in the progression of hyperuricemia. We identified key biomarkers such as orotidine, ureidosuccinic acid, uracil, and pseudouridine, which are associated with uric acid-induced damage to hepatic and renal systems. MetOrigin tracing analysis further revealed that differential metabolites related to hyperuricemia are primarily involved in host-microbiome co-metabolic pathways, particularly in purine metabolism, with bacterial phyla such as Pseudomonadota, Actinomycetota, and Ascomycota being closely linked to the critical metabolic processes of uric acid production. These findings not only enhance our understanding of the pathogenic mechanisms underlying hyperuricemia but also provide a robust experimental model foundation for the development of innovative treatment strategies.

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