Risk of papillary thyroid carcinoma and nodular goiter associated with exposure to semi-volatile organic compounds: A multi-pollutant assessment based on machine learning algorithms.

BACKGROUND: Exposure to semi-volatile organic compounds (SVOCs) may link to thyroid nodule risk, but studies of mixed-SVOCs exposure effects are lacking. Traditional analytical methods are inadequate for dealing with mixed exposures, while machine learning (ML) seems to be a good way to fill the gaps in the field of environmental epidemiology research. OBJECTIVES: Different ML algorithms were used to explore the relationship between mixed-SVOCs exposure and thyroid nodule. METHODS: A 1:1:1 age- and gender-matched case-control study was conducted in which 96 serum SVOCs were measured in 50 papillary thyroid carcinoma (PTC), 50 nodular goiters (NG), and 50 controls. Different ML techniques such as Random Forest, AdaBoost were selected based on their predictive power, and variables were selected based on their weights in the models. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the mixed effects of the SVOCs exposure on thyroid nodule. RESULTS: Forty-three of 96 SVOCs with detection rate >80 % were included in the analysis. ML algorithms showed a consistent selection of SVOCs associated with thyroid nodule. Fluazifop-butyl and fenpropathrin are positively associated with PTC and NG in single compound models (all P < 0.05). WQS model shows that exposure to mixed-SVOCs was associated with an increased risk of PTC and NG, with the mixture dominated by fenpropathrin, followed by fluazifop-butyl and propham. In the BKMR model, mixtures showed a significant positive association with thyroid nodule risk at high exposure levels, and fluazifop-butyl showed positive effects associated with PTC and NG. CONCLUSION: This study confirms the feasibility of ML methods for variable selection in high-dimensional complex data and showed that mixed exposure to SVOCs was associated with increased risk of PTC and NG. The observed association was primarily driven by fluazifop-butyl and fenpropathrin. The findings warranted further investigation.

Nursing of Vulvar Cancer Radical Operation Combined with Laparoscopic Inguinal Lymph Node Dissection.

Purpose: The application, development, and care of radical surgery combined with laparoscopic inguinal lymph node dissection for vulvar cancer. Methods: We searched the PubMed, Web of Science, the Cochrane Library, and EMBASE databases for published literature on the care of radical surgery combined with laparoscopic inguinal lymph node dissection for vulvar cancer up to June 2022. We used the following search terms and terms: "vulvar cancer," "injury," "radical vulvar cancer surgery," "laparoscopic inguinal lymph node dissection," and "care." Results: Laparoscopic inguinal lymph node dissection has become a new surgical method for the treatment of vulvar cancer, and it effectively avoids all the problems associated with traditional surgery. In addition, radical vulvar cancer surgery and laparoscopic inguinal lymph node dissection combined with high-quality nursing interventions can promote patients' recovery and reduce the occurrence of complications, which has important clinical significance. Conclusion: This article reviews the application, development, and nursing care of radical vulvar cancer surgery combined with laparoscopic inguinal lymph node dissection.

RIPK3-Dependent Necroptosis Activates MCP-1-Mediated Inflammation in Mice after Intracerebral Hemorrhage.

BACKGROUND: Recent studies have reported that receptor-interacting protein kinase 3 (RIPK3)-dependent necroptosis is related to the pathological process of intracerebral hemorrhage (ICH). Some studies support the view that inhibiting necroptosis is a key mechanism preventing inflammation. Inflammation is a crucial factor contributing to neurological injuries and unfavorable outcomes after ICH. The aim of this study was to clarify the association between necroptosis and monocyte chemoattractant protein-1 (MCP-1)-mediated inflammation and identify a new target for the treatment of ICH. METHODS: An ICH model was established in C57BL/6 mice by injecting collagenase IV into the right basal ganglia. The RIPK3 inhibitor GSK872 was administered through intraventricular injection. Then, we assessed brain edema and neurobehavioral function. Western blotting was employed to detect changes in RIPK3, phospho-mixed lineage kinase domain-like protein (p-MLKL), MCP-1, phospho-c-Jun N-terminal kinase (p-JNK) and interleukin 6 (IL-6) levels in the brain tissue. The localization of RIPK3 and MCP-1 was observed using immunofluorescence staining. Co-immunoprecipitation was performed to determine the interaction between RIPK3 and MCP-1. RESULTS: Compared with the sham group, the levels of RIPK3, p-MLKL, MCP-1, p-JNK and IL-6 were increased post-ICH. GSK872 pretreatment significantly reduced RIPK3, p-MLKL, MCP-1, p-JNK and IL-6 expression, accompanied by mitigated cerebral edema and neurobehavioral defects. RIPK3 and MCP-1 colocalized in the perinuclear region after ICH. We detected the formation of the RIPK3-MCP-1 complex in ICH brain tissue. CONCLUSIONS: There exerted an association between RIPK3 and MCP-1. The inhibition of RIPK3 alleviated MCP-1-mediated inflammation following ICH.