Objective: To analyze the developmental trajectories of clustered health risk behaviors and their association with self-esteem and lonelinesss among junior high school students, so as to provide a reference for formulating comprehensive prevention and control measures of health risk behaviors among adolescents. Methods: In October 2023, 1 165 first year junior high school students from two schools of Jishou City in Hunan Province were selected by convenient sampling method for three follow up surveys (T1:October 2023; T2:April 2024; T3:October 2024). The Adolescent Health Risk Behavior Questionnaire, Rosenberg Self esteem Scale and Loneliness Scale were used to assess health risk behaviors, self esteem and loneliness, respectively. Latent growth curve modeling and latent growth mixture modeling were applied to analyze the developmental trajectories of clustered health risk behaviors among junior high school students. Logistic regression was used to analyze the association of the developmental trajectories of clustered health risk behaviors with self esteem and loneliness among junior high school students. Results: The overall developmental trajectories among junior high school students showed a declining trend (intercept=0.15, slope=-1.65, both P <0.05), with three heterogeneous categories:low risk improvement group ( n =862, 74.0%), moderate risk stable group ( n =260, 22.3%), and high risk deterioration group ( n =43, 3.7%). After adjusting the status of the left behind individuals，using the low risk improvement group as the reference category in multinomial Logistic regression analysis, results indicated that higher loneliness scores among junior high school students increased the risks of belonging to the moderate risk stable group ( OR=1.02, 95%CI =1.00- 1.04 ) and the high risk deterioration group ( OR=1.04, 95%CI =1.00-1.08), while higher self esteem scores reduced the risks of belonging to the moderate risk stable group ( OR=0.93, 95%CI =0.91-0.96) and the high risk deterioration group ( OR=0.88, 95%CI =0.83-0.94) (all P <0.05). Conclusions The overall trend of clustered health risk behaviors among junior high school students gradually improves, and the self esteem and loneliness are significant correlative factors. Targeted intervention measures should be developed for the junior high school students, with a focus on enhancing their self esteem and alleviating loneliness.

Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Recent research from the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) indicates that breast cancer is the most prevalent malignant tumor among women, posing a significant threat to women's health. Surgery remains the primary therapeutic modality for breast cancer. Recently, endoscopic and robotic breast surgical techniques have gained acceptance among both surgeons and patients. However, considerable variation exists in surgical approaches and outcomes. To standardize these techniques, facilitate their broader clinical adoption, and ultimately improve patient care, the Endoscopic-robotic Breast Surgery Clinical Trials Consortium (ErBSCTC) of China has developed this guideline. This document encompasses the technologies and instrumentation utilized in endoscopic and robotic breast surgery, surgical techniques, perioperative management, complication handling, long-term follow-up, and oncologic outcomes, aiming to provide evidence-based guidance for healthcare professionals involved in the prevention, diagnosis, and treatment of breast diseases.

Breast cancer is the most common malignant tumor among women in China, with surgery being one of the primary treatment modalities. Endoscopic/robotic breast surgery (ErBS) is gaining widespread acceptance among patients and surgeons alike due to its advantages of minimal invasiveness, superior cosmetic outcomes, and accelerated recovery. However, substantial heterogeneity currently exists across China regarding patient selection, standardized operative techniques, perioperative management, and complication handling, underscoring the urgent need for evidence-based consensus guidelines. To promote standardization and ensure consistent quality of ErBS, the Chinese Endoscopic-Robotic Breast Surgery Clinical Trials Consortium (CErBSCTC) has systematically reviewed the latest high-quality evidence and formulated the "Protocol for China Endoscopic and Robotic Breast Surgery Guidelines (2026 edition)", which outlines a comprehensive methodology for guideline development.

Objective: To investigate the characteristics of public health emergencies in Jinhua City, Zhejiang Province from 2014 to 2023, so as to provide the reference for prevention and control of public health emergencies. Methods: Data of public health emergencies and related information in Jinhua City from 2014 to 2023 were collected through Emergency Public Reporting System of Chinese Disease Prevention and Control Information System. Attack rates, and distribution of time, areas and places were descriptively analyzed. Results: A total of 276 public health emergencies were reported in Jinhua City from 2014 to 2023. There were 10 324 reported cases and 7 deaths, with an attack rate of 0.32%. There were 53 Ⅳ-level (19.20%) and 223 unclassified public health emergencies (80.80%). Infectious disease emergencies were predominant types, accounting for 97.83% (270 events). The three most common infectious disease emergencies were other infectious diarrhea (42.03%), influenza (21.01%) and COVID-19 (16.30%). The reported public health emergencies peaked in November and December, with 66 and 45 events reported, respectively. The three most counties (cities, districts) included Yiwu City, Wucheng District and Lanxi City, accounting for 24.28% (67 events), 18.48% (51 events) and 11.96% (33 events), respectively. School and preschool institutions were predominant places where public health emergencies occurred (198 events, 71.74%). Conclusions The public health emergencies in Jinhua City from 2014 to 2023 were Ⅳ-level and unclassified emergencies, and infectious disease emergencies were predominant. November and December were the peak reporting periods, and schools and preschool institutions were the main places where these events occurred.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.