The global burden of cataracts and its attributable risk factors in 204 countries and territories: a systematic analysis of the global burden of disease study.

Introduction: The global distribution and trends in the attributable burden of cataract risk have rarely been systematically explored. To guide the development of targeted and accurate cataract screening and treatment strategies, we analyzed the burden of cataract disease attributable to known risk factors. Method: This study utilized detailed cataract data from the Global Burden of Disease e 2019, and we analyzed disability-adjusted life years (DALYs) e each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. Results: The results revealed that from 1990-2019, the global age-standardized DALYs of e attributable to particulate matter pollution, smoking, high fasting glucose plasma and high BMI showed steady downward trends (1990-2009: EAPC = -0.21 [-0.57 -0.14]); 2000-2009: EAPC = -0.95 [-1.01 -0.89]; 2010-2019: EAPC = -1.41 [-1.8 -1.02]). The age-standardized DALYs and mortality caused by each risk factor were highest in the low-middle sociodemographic index (SDI) region (EAPC = -1.77[(-2.19--1.34)]). The overall disease burden of cataracts is lower in males than in females. When analyzing the EAPCs of cataract disease burden for each risk factor individually, we found that the age-standardized disability-adjusted life years caused by particulate matter pollution and smoking decreased (PMP1990-2009: EAPC = -0.53 [-0.9--0.16]; 2000-2009: EAPC = -1.39 [-1.45--1.32]; 2010-2019: EAPC = -2.27 [-2.75--1.79]; smoking 2000 to 2009: EAPC = -1.51 [-1.6--1.43], 2009 to 2019: EAPC = -1.34 [-1.68--1])), while high fasting plasma glucose and high body mass index increased annually (HFPG1990 to 1999: EAPC = 1.27 [0.89-1.65], 2000 to 2009: EAPC = 1.02 [0.82-1.22], 2010-2019: EAPC = 0.44 [0.19-0.68]; HBMI 1990 to 1999: EAPC = 1.65 [1.37-1.94], 2000 to 2009: EAPC = 1.56 [1.43-1.68], 2010-2019: EAPC = 1.47 [1.18-1.77]). Disscussion: The burden of cataracts caused by ambient particulate matter and smoking is increasing in low, low-middle SDI areas, and specific and effective measures are urgently needed. The results of this study suggest that reducing particulate matter pollution, quitting smoking, controlling blood glucose, and lowering BMI could play important roles in reducing the occurrence of cataracts, especially in older people.

DRGKB: a knowledgebase of worldwide diagnosis-related groups' practices for comparison, evaluation and knowledge-guided application.

As a prospective payment method, diagnosis-related groups (DRGs)'s implementation has varying effects on different regions and adopt different case classification systems. Our goal is to build a structured public online knowledgebase describing the worldwide practice of DRGs, which includes systematic indicators for DRGs' performance assessment. Therefore, we manually collected the qualified literature from PUBMED and constructed DRGKB website. We divided the evaluation indicators into four categories, including (i) medical service quality; (ii) medical service efficiency; (iii) profitability and sustainability; (iv) case grouping ability. Then we carried out descriptive analysis and comprehensive scoring on outcome measurements performance, improvement strategy and specialty performance. At last, the DRGKB finally contains 297 entries. It was found that DRGs generally have a considerable impact on hospital operations, including average length of stay, medical quality and use of medical resources. At the same time, the current DRGs also have many deficiencies, including insufficient reimbursement rates and the ability to classify complex cases. We analyzed these underperforming parts by domain. In conclusion, this research innovatively constructed a knowledgebase to quantify the practice effects of DRGs, analyzed and visualized the development trends and area performance from a comprehensive perspective. This study provides a data-driven research paradigm for following DRGs-related work along with a proposed DRGs evolution model. Availability and implementation: DRGKB is freely available at http://www.sysbio.org.cn/drgkb/. Database URL: http://www.sysbio.org.cn/drgkb/.

Fermented formulation of Silybum marianum seeds: Optimization, heavy metal analysis, and hepatoprotective assessment.

BACKGROUND: Fermented formulations are extensively used in Ayurveda due to several benefits like improved palatability, bioavailability, pharmacological potential, and shelf life. These formulations can also quench the heavy metals from the plant material and thus reduce the toxicity. Seeds of Silybum marianum (L.) Gaertn. are widely used for the management of many liver diseases. STUDY DESIGN AND METHODS: In the present study, we developed a novel fermented formulation of S. marianum seeds and evaluated parameters like safety (heavy metal analysis) and effectiveness (hepatoprotective). As the developed formulation's validation is crucial, the critical process variables (time, pH, and sugar concentration) are optimized for alcohol and silybin content using the Box-Behnken design (BBD). RESULTS: The response surface methodology coupled with BBD predicted the optimized conditions (fermentation time (28 days), pH 5.6, and sugar concentration (22.04%)) for the development of a fermented formulation of the selected herb. Moreover, the alcohol content (6.5 ± 0.9%) and silybin concentration (26.1 ± 2.1%) were confirmed in optimized formulation by GC-MS and HPTLC analysis. The optimized formulation was also analyzed for heavy metals (Pb, As, Hg, and Cd); their concentration is significantly less than the decoction of herbs. Further, the comparative evaluation of the developed formulation with the marketed formulation also confirmed that the fermented formulation's silybin concentration and percentage release were significantly enhanced. In addition, the developed fermented formulation's percentage recovery of HepG2 cell lines after treatment with CCl4 was significantly improved compared with the marketed formulation. CONCLUSION: It can be summarized that the developed fermented formulation improves safety and effectiveness compared to other market formulations. Finally, it can be concluded that the developed fermented formulation could be further explored as a better alternative for developing Silybum marianum preparation.

Association Between Urinary Bisphenols and Body Composition Among American Adults: Cross-Sectional National Health and Nutrition Examination Survey Study.

BACKGROUND: Bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) are widely used in various consumer products. They are environmental contaminants with estrogenic properties that have been linked to various health outcomes. Understanding their impact on body composition is crucial for identifying potential health risks and developing preventive strategies. However, most current studies have only focused on their relationship with BMI. OBJECTIVE: This study aimed to investigate the association between urinary levels of BPA, BPS, and BPF and body composition, including BMI, lean mass, and fat mass, in a large population-based sample. METHODS: We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey 2003-2016. Body composition data were assessed using dual-energy X-ray absorptiometry, which provided precise measurements of lean mass, fat mass, and other indicators. We used multivariate linear regression models to estimate the associations, adjusting for potential confounders such as age, gender, race, socioeconomic factors, and lifestyle variables. RESULTS: The results revealed significant associations between bisphenol exposure and body composition. After adjusting for covariates, BPS showed a positive association with BMI, with quartiles 3 and 4 having 0.91 (95% CI 0.34-1.48) and 1.15 (95% CI 0.55-1.74) higher BMI, respectively, compared with quartile 1 (P<.001). BPA was negatively associated with total lean mass (TLM) and appendicular lean mass, with quartiles 2, 3, and 4 having -7.85 (95% CI -11.44 to -4.25), -12.33 (95% CI -16.12 to -8.54), and -11.08 (95% CI -15.16 to -7.01) lower TLM, respectively, compared with quartile 1 (P<.001). BPS was negatively associated with TLM, with quartiles 3 (ß=-10.53, 95% CI -16.98 to -4.08) and 4 (ß=-11.14, 95% CI -17.83 to -4.45) having significantly lower TLM (P=.005). Both BPA and BPS showed a positive dose-response relationship with trunk fat (BPA: P=.002; BPS: P<.001) and total fat (BPA: P<.001; BPS: P=.01). No significant association was found between BPF and any body composition parameter. CONCLUSIONS: This large-sample study highlights the associations between urinary levels of BPA and BPS and alterations in body composition, including changes in lean mass, fat mass, and regional fat distribution. These findings underscore the importance of understanding the potential health risks associated with bisphenol exposure and emphasize the need for targeted interventions to mitigate adverse effects on body composition.

Assessment of the impact of intravenous antibiotics treatment on gut microbiota in patients: Clinical data from pre-and post-cardiac surgery.

Background and aims: Surgical site infection is a common complication after surgery. Periprocedural antibiotics are necessary to prescribe for preventing or treating infections. The present study aimed to explore the effect of intravenous antibiotics on gut microbiota and menaquinone biosynthesis in patients, especially in elderly patients undergoing cardiac surgery. Methods: A total of 388 fecal samples were collected from 154 cardiac surgery patients. The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified and sequenced on a MiSeq PE300. The gut microbiota diversity of samples was analyzed in terms of α- and ß-diversity at the OTU level. The different groups were classified according to antibiotics in combinations and single antibiotics. PICRUSt2 was used for preliminary prediction of the gut microbiota function for menaquinone biosynthesis. Results: The intravenously administered antibiotics which are excreted via bile represents the main antibiotics that could disturb the gut microbiota's composition in cardiac surgery patients, especially for elderly patients. The effect of antibiotics on gut microbiota is produced after antibiotics treatments over one week. The recovery of gut microbiota to the state of pre-antibiotics may require over two weeks of antibiotics withdrawal. Sex factor doesn't represent as an influencer in gut microbiota composition. Long-term use of cefoperazone-sulbactam may affect coagulation function. Conclusions: The composition of the gut microbiota had a significant change post-intravenous antibiotics treatment in cardiac surgery patients. The richness and diversity of gut microbiota are increased in elderly patients.

Review of MARCH-INSIDE & complex networks prediction of drugs: ADMET, anti-parasite activity, metabolizing enzymes and cardiotoxicity proteome biomarkers.

In this communication we carry out an in-depth review of a very versatile QSPR-like method. The method name is MARCH-INSIDE (MARkov CHains Ivariants for Network Selection and DEsign) and is a simple but efficient computational approach to the study of QSPR-like problems in biomedical sciences. The method uses the theory of Markov Chains to generate parameters that numerically describe the structure of a system. This approach generates two principal types of parameters Stochastic Topological Indices (sto-TIs). The use of these parameters allows the rapid collection, annotation, retrieval, comparison and mining structures of molecular, macromolecular, supramolecular, and non-molecular systems within large databases. Here, we review and comment by the first time on the several applications of MARCH-INSIDE to predict drugs ADMET, Activity, Metabolizing Enzymes, and Toxico-Proteomics biomarkers discovery. The MARCH-INSIDE models reviewed are: a) drug-tissue distribution profiles, b) assembling drug-tissue complex networks, c) multi-target models for anti-parasite/anti-microbial activity, c) assembling drug-target networks, d) drug toxicity and side effects, e) web-server for drug metabolizing enzymes, f) models in drugs toxico-proteomics. We close the review with some legal remarks related to the use of this class of QSPR-like models.