Predicting the association of different levels of physical activity on postoperative pulmonary complications using the international physical activity questionnaire in patients undergoing thoracoscopic lung surgery under general anaesthesia: protocol for a prospective cohort study.

INTRODUCTION: Postoperative pulmonary complications (PPCs) occur frequently in patients undergoing lung surgery under general anaesthesia and are strongly associated with longer postoperative hospital stays and increased mortality. The existing literature has shown that a higher level of preoperative physical activity (PA) plays a positive role in the low incidence of postoperative complications and the quality of life in patients undergoing lung surgery. However, the association between preoperative PA levels and the incidence of PPCs has rarely been studied, particularly in thoracoscopic lung surgery. This study aims to evaluate PA levels in patients undergoing thoracoscopic lung surgery using the International Physical Activity Questionnaire and to investigate the association between PA levels and the incidence of PPCs. METHODS AND ANALYSIS: A total of 204 participants aged 18-80 years undergoing thoracoscopic lung surgery (thoracoscopic wedge resection, thoracoscopic segmentectomy and thoracoscopic lobectomy) will be included in the study. The primary outcome is the incidence of PPCs within the first 5 postoperative days. The secondary outcomes include the number of PPCs, the incidence of PPCs 1 month postoperatively, the arterial blood levels of inflammatory markers, the incidence of postoperative adverse events within the first 5 postoperative days, extubation time, unplanned admission to the intensive care unit, postoperative length of stay and mortality 1 month postoperatively. ETHICS AND DISSEMINATION: The study was reviewed and approved by the Research Ethics Committee of the First Affiliated Hospital of Shandong First Medical University on 31 March 2022 (YXLL-KY-2022(014)) and is registered at ClinicalTrials.gov. We plan to disseminate the data and findings of this study in international and peer-reviewed journals. TRIAL REGISTRATION NUMBER: The trial has been prospectively registered at the clinicaltrials.gov registry (NCT05401253).

Modeling and insights into the structural characteristics of endocrine-disrupting chemicals.

Endocrine-disrupting chemicals (EDCs) can cause serious harm to human health and the environment; therefore, it is important to rapidly and correctly identify EDCs. Different computational models have been proposed for the prediction of EDCs over the past few decades, but the reported models are not always easily available, and few studies have investigated the structural characteristics of EDCs. In the present study, we have developed a series of artificial intelligence models targeting EDC receptors: the androgen receptor (AR); estrogen receptor (ER); and pregnane X receptor (PXR). The consensus models achieved good predictive results for validation sets with balanced accuracy values of 87.37%, 90.13%, and 79.21% for AR, ER, and PXR binding assays, respectively. Analysis of the physical-chemical properties suggested that several chemical properties were significantly (p < 0.05) different between EDCs and non-EDCs. We also identified structural alerts that can indicate an EDC, which were integrated into the web server SApredictor. These models and structural characteristics can provide useful tools and information in the discrimination and mechanistic understanding of EDCs in drug discovery and environmental risk assessment.