Search

This study aimed to investigate the associations between carbohydrate intake and gout risk, along with interactions between genetic susceptibility and carbohydrates, and the mediating roles of biomarkers. We included 187,387 participants who were free of gout at baseline and completed at least one dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between carbohydrate intake and gout risk. Over a median follow-up of 11.69 years, 2548 incident cases of gout were recorded. Total carbohydrate intake was associated with a reduced gout risk (Q4 vs. Q1: HR 0.67, 95% CI 0.60–0.74), as were total sugars (0.89, 0.80–0.99), non-free sugars (0.70, 0.63–0.78), total starch (0.70, 0.63–0.78), refined grain starch (0.85, 0.76–0.95), wholegrain starch (0.73, 0.65–0.82), and fiber (0.72, 0.64–0.80), whereas free sugars (1.15, 1.04–1.28) were associated with an increased risk. Significant additive interactions were found between total carbohydrates and genetic risk, as well as between total starch and genetic risk. Serum urate was identified as a significant mediator in all associations between carbohydrate intake (total, different types, and sources) and gout risk. In conclusion, total carbohydrate and different types and sources of carbohydrate (excluding free sugars) intake were associated with a reduced risk of gout.

Abstract Presently, face recognition technology is rapidly advancing and has emerged as a crucial field of research. Thangka, being a significant repository of Buddhist imagery, encompass a vast amount of Buddha image data depicting diverse Buddhist themes from various historical epochs. Accurate recognition of facial features in these Buddha images is particularly significant in comprehending the historical evolution of thangka, especially the facial features correlation between Buddha society and secular society. Hence, in this study, 68 facial feature points was employed to obtain using the Dlib deep learning library, from which 16 facial geometric feature indices were derived. These indices served as the foundation for the establishment of a facial measurement standard and aesthetic evaluation index for thangka Buddha. A meticulous evaluation and identification of thangka facial details spanning nearly a millennium were conducted, and the transformation of thangka facial features was analyzed and deliberated from a secular aesthetic perspective. Upon conducting this study, it was discovered that: (1) The deep learning library exhibited effective performance in identifying facial characteristics in thangka Buddha images, and the facial evaluation index proved to be a reliable tool for evaluating both measurement standards and aesthetics. (2) The facial measurement standards depicted in thangka Buddha images have evolved and become increasingly standardized over time, maintaining a highly symmetrical aesthetic. (3) The aesthetic of thangka facial features draw upon the secular Tibetan face as their primary reference(Euclidean distance is 0.42), however, during the 17-19th centuries, Han Chinese facial features were gradually incorporated(Euclidean distance is 0.492), and the degree of fusion between Han Chinese and Tibetan facial aesthetics has become more profound.

Summary: Resistance to cisplatin (cis-dichlorodiamineplatinum, DDP) in ovarian cancer is a significant clinical challenge. Epigallocatechin-3-gallate (EGCG) has shown promise in cancer therapy. However, its effects on DDP-resistant ovarian cancer remain understudied. This study aims to assess the impact of EGCG on DDP-resistant cells and elucidate the associated molecular mechanisms. DDP-resistant cell lines were utilized for biological characterization. EGCG effectively inhibited proliferation, mobility, and induced apoptosis in OC/DDP cells. It downregulated the expression of S100A4 and NF-κB while upregulating p53 expression. These effects were reversed upon overexpression of S100A4 or NF-κB. In vivo experiments confirmed tumor inhibition and KI67 inhibition by EGCG. Moreover, EGCG downregulated the expression of S100A4 and NF-κB while upregulating p53 in xenograft mice compared to those without EGCG treatment. This study suggests that EGCG suppresses cancer progression through the S100A4/NF-κB signaling pathway, involving interaction with p53. EGCG holds potential as an anticancer candidate for OC/DDP.

BackgroundImmunotherapy is significantly revolutionizing cancer treatment and demonstrating promising efficacy in gastric cancer (GC) patients. However, only a subset of patients could derive benefits from targeted monoclonal antibody therapy against programmed death receptor 1 (PD-1). This study aims to identify suitable serum cytokines and blood cell ratios as predictive biomarkers to aid in the selection of GC patients likely to benefit from PD-1 inhibitors.Materials and methodsThis retrospective study included 41 GC patients who received PD-1 inhibitors combined with chemotherapy, 36 GC patients treated solely with chemotherapy, and 33 healthy controls. The study assessed the levels of seven cytokines: interleukin-2 (IL-2), IL-4, IL-6, IL-10, IL-17A, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and various inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), total lymphocyte count (TLC), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). Measurements were obtained using the inpatient system. Univariate and multivariate Cox regression analyses were performed to evaluate the predictive significance of these hematologic parameters for clinical outcomes.ResultsLevels of IL-6, IL-10, TNF-α, NLR, and PLR were significantly elevated in GC patients compared to healthy controls, while TLC and LMR were higher in the control group. Among the 41 patients receiving PD-1 inhibitors and chemotherapy, baseline IL-2 was associated with OS and PFS. Additionally, IL-6 and IL-17A correlated with OS, while NLR was linked to PFS (all P

Land surface phenology (LSP), an important branch of vegetation phenology, which is sensitive to climate change and play important role in ecosystem. As a typical subtropical area, in spite of its complex vegetation structure, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) LSP was not focused fully. Hence, In this study, a long time series LSP data from 2001 to 2020 was obtained based on MODIS normalized difference vegetation index (NDVI) using classical Savitzky-Golay filter. Subsequently, phenology spatial pattern and spatiotemporal trends and their correlation with climate change were analyzed for different vegetation types in the Guangdong-Hong Kong-Macao Greater Bay Area. The results revealed an obvious spatial heterogeneity and significant annual variation trend in vegetation phenology. The start of growing season (SOS) and the end of growing season (EOS) appeared delayed trend and the length of growing season (LOS) showed a prolonged trend, with average slope values of 0.55, 0.52 and 0.81 days per year, respectively. In general, preseason precipitation and solar radiation are the main climatic factors regulating vegetation phenology in the Greater Bay Area, and the enhancement of preseason precipitation and solar radiation is the main reason for the delay of vegetation withering and yellowing period and the extension of growing season. Ecosystems of the Greater Bay Area were mainly depending on preseason precipitation and solar radiation to regulate the leaf senescence and control plant growth duration. The present study can enhance performance of vegetation phenology models and provide useful information on ecological protection in subtropical areas.

Background: Immunotherapy is significantly revolutionizing cancer treatment and demonstrating promising efficacy in gastric cancer (GC) patients. However, only a subset of patients could derive benefits from targeted monoclonal antibody therapy against programmed death receptor 1 (PD-1). This study aims to identify suitable serum cytokines and blood cell ratios as predictive biomarkers to aid in the selection of GC patients likely to benefit from PD-1 inhibitors. Materials and methods: This retrospective study included 41 GC patients who received PD-1 inhibitors combined with chemotherapy, 36 GC patients treated solely with chemotherapy, and 33 healthy controls. The study assessed the levels of seven cytokines: interleukin-2 (IL-2), IL-4, IL-6, IL-10, IL-17A, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and various inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), total lymphocyte count (TLC), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). Measurements were obtained using the inpatient system. Univariate and multivariate Cox regression analyses were performed to evaluate the predictive significance of these hematologic parameters for clinical outcomes. Results: Levels of IL-6, IL-10, TNF-α, NLR, and PLR were significantly elevated in GC patients compared to healthy controls, while TLC and LMR were higher in the control group. Among the 41 patients receiving PD-1 inhibitors and chemotherapy, baseline IL-2 was associated with OS and PFS. Additionally, IL6 and IL-17A correlated with OS, while NLR was linked to PFS (all P<0.05). These factors were identified as independent prognostic indicators in both univariate and multivariate analyses. Furthermore, almost all cytokine levels increased following the initiation of PD-1 inhibitor treatment. Conclusions: The introduction of PD-1 inhibitors alongside chemotherapy in GC impacts serum cytokine levels. IL-2, IL-6, IL-17A, and NLR exhibit potential as reliable circulating predictive biomarkers for identifying patients who may benefit from PD-1 inhibitors combined with chemotherapy. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the clinical impact of combined application of acetylcysteine and methylprednisolone in treating paraquat poisoning (PQP). Methods: The clinical data of 92 PQP patients who received treatment in our hospital for 1 year were analyzed. The patients were equally divided into control group (CG) and study group (SG), based on treatment plans. All patients underwent routine acute-phase treatment, while SG was additionally treated with acetylcysteine in combination with methylprednisolone. After treatment, the renal function, pulmonary fibrosis indices and inflammatory factor levels of both groups were determined. Results: During the 1 - 4 weeks of treatment, there was no statistical difference in the survival rates of patients at various time periods (p > 0.05). After treatment, there were markedly lower levels of blood urea nitrogen (BUN) and serum creatinine (SCr) in SG than in CG. There was lower incidence of pulmonary fibrosis in SG than in CG, although the difference was not significant. Patients in SG had lower HRCT scores and levels of C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) than those in CG (p < 0.05). Conclusion: Acetylcysteine in combination with methylprednisolone significantly reduces the degree of pulmonary fibrosis and improves renal function and inflammatory levels. It has a positive implication for early treatment of patients, especially for the prognosis of patients with mild-to-moderate poisoning. Therefore, the combined therapy has potential for clinical application. [ABSTRACT FROM AUTHOR]