Identification and validation of a costimulatory molecule-related signature to predict the prognosis for uveal melanoma patients.

Uveal melanoma (UVM) is the most common primary tumor in adult human eyes. Costimulatory molecules (CMs) are important in maintaining T cell biological functions and regulating immune responses. To investigate the role of CMs in UVM and exploit prognostic signature by bioinformatics analysis. This study aimed to identify and validate a CMs associated signature and investigate its role in the progression and prognosis of UVM. The expression profile data of training cohort and validation cohort were downloaded from The Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) dataset. 60 CM genes were identified, and 34 genes were associated with prognosis by univariate Cox regression. A prognostic signature was established with six CM genes. Further, high- and low-risk groups were divided by the median, and Kaplan-Meier (K-M) curves indicated that high-risk patients presented a poorer prognosis. We analyzed the correlation of gender, age, stage, and risk score on prognosis by univariate and multivariate regression analysis. We found that risk score was the only risk factor for prognosis. Through the integration of the tumor immune microenvironment (TIME), it was found that the high-risk group presented more immune cell infiltration and expression of immune checkpoints and obtained higher immune scores. Enrichment analysis of the biological functions of the two groups revealed that the differential parts were mainly related to cell-cell adhesion, regulation of T-cell activation, and cytokine-cytokine receptor interaction. No differences in tumor mutation burden (TMB) were found between the two groups. GNA11 and BAP1 have higher mutation frequencies in high-risk patients. Finally, based on the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) dataset, drug sensitivity analysis found that high-risk patients may be potential beneficiaries of the treatment of crizotinib or temozolomide. Taken together, our CM-related prognostic signature is a reliable biomarker that may provide ideas for future treatments for the disease.

Changes in the content of Puerarin-PLGA nanoparticles in mice under the influence of alcohol and analysis of their antialcoholism.

To observe the metabolic changes and antialcoholic effect of Puerarin-PLGA nanoparticles (PUE-NP) in mice. PUE-NP was prepared and characterized by particle size distribution and morphology. The mouse models with acute alcoholism were established to observe their behavioral changes after alcohol poisoning. The expressions of biologically active enzymes such as CRE, BUN, AST, ALT in serum and SOD and TLR4 in liver of mice in each group were detected, and the pathological changes in liver and kidney tissues were observed by HE staining. The PUE-NP metabolism in mice was determined by in vitro release assay and HPLC. PUE-NP nanoparticles had good morphology and structure, and the mouse models with alcohol poisoning were established successfully. Compared with alcohol group, puerarin and PUE-NP increased the disappearance latency time of righting reflex, and the recovery time of righting reflex was significantly shortened. Water maze results showed that Puerarin and PUE-NP had inhibitory effect on impaired memory. HPLC results showed that PUE-NP reached its peak in mice after 1 h, and the content percentage was twice that of puerarin preparation alone, and the distribution time of puerarin concentration in vivo was prolonged, indicating that PLGA nanoparticles had a loading and slow-release effect on puerarin and increased the bioavailability of puerarin in mice. In addition, compared with the alcohol group, Puerarin and PUE-NP improved serum ALT, AST, CRE, and BUN levels in mice, enhanced SOD activity in liver, and inhibited TLR4 expression. The effect was better in the PUE-NP group than in the Puerarin group. PUE-NP delayed the release and metabolism of Puerarin and had better effect in the treatment of the alcoholic liver and kidney injury.

Time series study on the effects of daily average temperature on the mortality from respiratory diseases and circulatory diseases: a case study in Mianyang City.

BACKGROUND: Climate change caused by environmental pollution is the most important one of many environmental health hazards currently faced by human beings. In particular, the extreme temperature is an important risk factor for death from respiratory and circulatory diseases. This study aims to explore the meteorological-health effect and find out the vulnerable individuals of extreme temperature events in a less developed city in western China. METHOD: We collected the meteorological data and data of death caused by respiratory and circulatory diseases in Mianyang City from 2013 to 2019. The nonlinear distributed lag model and the generalized additive models were combined to study the influence of daily average temperature (DAT) on mortality from respiratory and circulatory diseases in different genders, ages. RESULTS: The exposure-response curves between DAT and mortality from respiratory and circulatory diseases presented a nonlinear characteristic of the "V" type. Cumulative Relative Risk of 30 days (CRR30) of deaths from respiratory diseases with 4.48 (2.98, 6.73) was higher than that from circulatory diseases with 2.77 (1.96, 3.92) at extremely low temperature, while there was no obvious difference at extremely high temperature. The health effects of low temperatures on the respiratory system of people of all ages and genders were persistent, while that of high temperatures were acute and short-term. The circulatory systems of people aged < 65 years were more susceptible to acute effects of cold temperatures, while the effects were delayed in females and people aged ≥65 years. CONCLUSION: Both low and high temperatures increased the risk of mortality from respiratory and circulatory diseases. Cold effects seemed to last longer than heat did.