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Periodontitis is associated with abnormal purine metabolism, which is manifested by increased uric acid in host blood and increased expression of the purine-degrading enzyme, xanthine oxidoreductase (XOR), in periodontal tissues. Both XOR and uric acid are pro-oxidative and pro-inflammatory mediators under pathological conditions. Animal studies have found that injection of uric acid promotes the progression of periodontitis and that febuxostat (an XOR inhibitor) improves tissue destruction in periodontitis. Therefore, blocking the source of uric acid may be a therapeutic strategy to control the progression of periodontitis. In this article, the rationality of XOR inhibitors as potential therapeutic drugs for periodontitis is reviewed. The literature review results suggest that XOR inhibitors show antioxidative, anti-inflammatory, and anti-osteoclastic effects, and XOR inhibitors show clinical efficacy in the treatment of infectious, inflammatory and osteolytic diseases. Although there is no direct evidence to support the finding that XOR inhibitors can ameliorate periodontal microecological dysbiosis, these drugs can modulate intestinal microflora dysbiosis, and there is indirect evidence to support a beneficial effect of XOR inhibitors on periodontal microecological dysbiosis. In conclusion, XOR inhibitors may be used as immunomodulators for the adjuvant treatment of periodontitis by inhibiting inflammation, oxidative stress and anti-osteoclast effects.

Objective To describe the occurrence of general surgical complications and establish prediction models for different types of complications based on a multicenter cohort study. Methods Based on Modern Surgery and Anesthesia Safety Management System Construction and Promotion(MSCP), patients who underwent general surgery in 4 hospitals from January to June 2015 and from January to June 2016 were selected as participants, and perioperative data of patients were collected. Logistic regression was used to identify risk factors and predict complications. Results Among 19 223 patients, 830(4.32%) had complications. Among participants who had complications, 371(44.70%) had incision complications, 190(22.89%) had fistula complications, 310(37.35%) had infection complications, 161(19.40%) had failure complications, and 104(12.5%) died. There were significant differences in the risk factors of different types of complications. The risk factors of incision,infection and failure covered the whole perioperative period, while fistula complications mainly focused on the difficulty of surgery and postoperative treatment, and for death outcomes, postoperative risk factors were more severe than preoperative risk factors. The areas under the curves of prediction were between 0.80-0.93. Conclusions In general surgery, different types of complications have different risk factors. The targeted prediction model can avoid the rough simplification of complications and fuzzy influence of each factor, and can provide reference for the prevention of complications.

Humans can be exposed to multiple pollutants in the air and surface water. These environments are non-static, trans-boundary and correlated, creating a complex network, and significant challenges for research on environmental hazards, especially in real-world cancer research. This article reports on a large study (377 million people in 30 provinces of China) that evaluated the combined impact of air and surface water pollution on cancer. We formulate a spatial evaluation system and a common grading scale for co-pollution measurement, and validate assumptions that air and surface water environments are spatially connected and that cancers of different types tend to cluster in areas where these environments are poorer. We observe "dose–response" relationships in both the number of affected cancer types and the cancer incidence with an increase in degree of co-pollution. We estimate that 62,847 (7.4%) new cases of cancer registered in China in 2016 were attributable to air and surface water pollution, and the majority (69.7%) of these excess cases occurred in areas with the highest level of co-pollution. The findings clearly show that the environment cannot be considered as a set of separate entities. They also support the development of policies for cooperative environmental governance and disease prevention. Dissecting the associations between exposure to environmental pollution and cancer risk remains crucial. Here, the authors evaluate the impact of air and water pollution on cancer incidence in China using a spatial evaluation system and show that most excess cancer cases occurred in areas with the highest level of co-pollution. [ABSTRACT FROM AUTHOR]

Background: The current guidelines for managing screen‐detected pulmonary nodules offer rule‐based recommendations for immediate diagnostic work‐up or follow‐up at intervals of 3, 6, or 12 months. Customized visit plans are lacking. Purpose: To develop individualized screening schedules using reinforcement learning (RL) and evaluate the effectiveness of RL‐based policy models. Methods: Using a nested case–control design, we retrospectively identified 308 patients with cancer who had positive screening results in at least two screening rounds in the National Lung Screening Trial. We established a control group that included cancer‐free patients with nodules, matched (1:1) according to the year of cancer diagnosis. By generating 10,164 sequence decision episodes, we trained RL‐based policy models, incorporating nodule diameter alone, combined with nodule appearance (attenuation and margin) and/or patient information (age, sex, smoking status, pack‐years, and family history). We calculated rates of misdiagnosis, missed diagnosis, and delayed diagnosis, and compared the performance of RL‐based policy models with rule‐based follow‐up protocols (National Comprehensive Cancer Network guideline; China Guideline for the Screening and Early Detection of Lung Cancer). Results: We identified significant interactions between certain variables (e.g., nodule shape and patient smoking pack‐years, beyond those considered in guideline protocols) and the selection of follow‐up testing intervals, thereby impacting the quality of the decision sequence. In validation, one RL‐based policy model achieved rates of 12.3% for misdiagnosis, 9.7% for missed diagnosis, and 11.7% for delayed diagnosis. Compared with the two rule‐based protocols, the three best‐performing RL‐based policy models consistently demonstrated optimal performance for specific patient subgroups based on disease characteristics (benign or malignant), nodule phenotypes (size, shape, and attenuation), and individual attributes. Conclusions: This study highlights the potential of using an RL‐based approach that is both clinically interpretable and performance‐robust to develop personalized lung cancer screening schedules. Our findings present opportunities for enhancing the current cancer screening system. [ABSTRACT FROM AUTHOR]