Objective: To understand the microclimate in primary and secondary school classrooms for the study period during the winter heating season, so as to provide a reference for the revision and improvement of relevant health standards. Methods: In December 2024, stratified random sampling was used to select 30 primary and secondary schools and 180 classrooms from the northern regions with centralized heating (Liaoning Province, Tianjin City) and the southern regions without centralized heating (Shanghai City, Anhui Province, and Jiangxi Province). Indoor temperature, relative humidity, wind speed, CO 2 and other indicators were measured on site. Variance analysis, t-test, Mann-Whitney U test and Kruskal-Wallis H test were used to analyze the differences in the microclimate of classrooms among regions and urban and rural differences. Results: The average temperature in the middle of the classrooms tested on site was (16.47±4.72)℃, and the variance analysis showed that the difference between the regions was statistically significant ( F=27.80, P <0.01). Among them, Tianjin had the highest average temperature of (20.43± 2.12 )℃, followed by Liaoning (19.03±2.23)℃, Shanghai (15.33±5.32)℃, Anhui (12.79±1.74)℃, and Jiangxi (11.69± 1.68 )℃. Horizontal temperature difference was 0.90 (0.50, 1.60)℃, the vertical temperature difference was 0.20 (0.10,0.60)℃, the average relative humidity was (44.39±16.16)%, the wind speed was 0.03(0.01,0.11)m/s, and the differences among different provinces and cities were statistically significant ( H/F =40.62, 82.69, 95.06, 55.28, all P <0.01). The average CO 2 volume concentration in urban areas of Tianjin, Liaoning, and Shanghai was 0.21(0.16,0.30)%, and there was no statistically significant difference ( H=4.65, P =0.10). There were grade differences in relative humidity ( F =3.71, 6.21) and CO 2 ( H =14.72, 12.92) in the north and the south (all P <0.05). In addition, the temperature, relative humidity, wind speed and CO 2 in the middle of the classroom were 42.8%, 67.8%, 100.0% and 22.2% respectively. Conclusions The temperature in the middle of the classroom in the non centralized heating area is lower than the standard, the relative humidity of classroom in the centralized heating area is lower than the standard，and the CO 2 in the classroom in winter is lower than the standard. It is recommended to install heating facilities in schools with low temperatures to increase the temperature and increase the frequency of ventilation in classrooms or adopt mechanical ventilation strategies to reduce CO 2 volume concentration.

Objective To investigate the role and potential mechanism of secreted phosphoprotein 1 (SPP1)⁺ macrophages in the formation of chronic renal allograft fibrosis. Methods The expression features of SPP1⁺ macrophages in renal allografts of chronic allograft dysfunction (CAD) patients were analyzed based on single-cell transcriptome data of renal tissues from patients with CAD. Transcription factor VIPER analysis and DoRothEA transcription factor activity analysis were performed on the single-cell transcriptome data. Renal tissue samples were collected from kidney transplant recipients, including the CAD group (n=5) and the non-renal allograft fibrosis group (CTL group, n=5). A mouse model of chronic allograft rejection was established and divided into the allogeneic kidney transplantation group (CAD group, n=3) and the syngeneic kidney transplantation group (SYN group, n=3). Hematoxylin-eosin staining was used to detect renal tissue injury in mice, and Masson staining was used to detect renal tissue fibrosis. Immunofluorescence staining was performed to detect SPP1 expression in renal tissues of transplant recipients and mouse renal allografts. Bone marrow-derived macrophages (BMDMs) were extracted from mice and subjected to hypoxia stimulation. The expression of hypoxia-inducible factor (HIF)-1α and SPP1 was detected by Western blot, and SPP1 expression was detected by flow cytometry. BMDMs were transfected with HIF-1α overexpression plasmid and HIF-1α small interfering RNA (siRNA) followed by hypoxia intervention, and the expression of HIF-1α and SPP1 was detected by Western blot. Mouse aortic endothelial cells (MAECs) were co-cultured with the supernatant of BMDMs, and the expression of endothelial-mesenchymal transition (EndMT)-related markers was detected by Western blot and immunofluorescence. Results Single-cell transcriptome analysis showed that the proportion of SPP1⁺ macrophages in renal allograft tissues was significantly higher in the CAD group than in the CTL group (P<0.05). The renal injury score and the percentage of interstitial fibrotic area in the CAD group were significantly higher than those in the SYN group (both P<0.05). Immunofluorescence staining showed that the proportion of SPP1⁺ macrophages was increased in the CAD group compared with the CTL group, and also increased in the CAD group compared with the SYN group (both P<0.05). VIPER analysis and DoRothEA transcription factor activity analysis revealed activation of the hypoxia pathway and upregulated expression of transcription factors such as HIF-1α in SPP1⁺ macrophages. SPP1 expression was elevated in BMDMs under hypoxic conditions. Knockdown of HIF-1α inhibited hypoxia-induced SPP1 protein expression, whereas overexpression of HIF-1α upregulated SPP1 protein levels. After co-culture of hypoxia-induced BMDMs with MAECs, the expression levels of EndMT-related markers were increased. Conclusions SPP1⁺ macrophages differentiated under hypoxia are significantly infiltrated in the formation of chronic renal allograft fibrosis, and may promote renal allograft fibrosis by inducing EndMT in renal vascular endothelial cells.

Objective:To analyze the impact of stressful life events on the social activity participation of middle-aged and elderly adults in China, providing a scientific basis for improving their quality of life.Methods:This study was conducted in January 2024.Data were derived from the China health and retirement longitudinal study (CHARLS) conducted from 2011 to 2020. SPSS 25.0 software was used for statistical analysis.Ordered Logistic regression analysis was employed to explore the association between stressful life events experienced over the past decade and the level of social activity participation, with stratified analysis by age, gender, and place of residence.Results:A total of 10 838 middle-aged and elderly adults were included in this study. The proportions of individuals with no social activity participation, low social activity participation, and high social activity participation were 52.07%(5 643/10 838), 24.21%(2 624/10 838), and 23.72%(2 571/10 838), respectively. After adjusting for sociodemographic characteristics and health-related behaviors, individuals who experienced stressful life events were 15.2% less likely to participate in social activities compared to those who did not ( RR=0.848, 95% CI=0.786-0.915).Stratified analysis revealed that the decrease in the likelihood of social activity participation following stressful life events was significantly greater in urban residents than that in rural residents ( Pinteraction=0.004). Conclusion:Experiencing stressful life events over the past decade may reduce the level of social activity participation among middle-aged and elderly adults. It is recommended to strengthen psychological counseling for this population and encourage active social engagement.

Objective:To analyze the research trends and hotspots of bupivacaine liposomes from 1994 to 2023 using bibliometrics.Methods:A comprehensive search was conducted for the literature related to bupivacaine liposomes in the Web of Science Core Collection from 1994 to 2023. The CiteSpace software was used to conduct an in-depth analysis of the included literature data, including publication year, country, institution, author, journal, cited references, keywords, etc.Results:A total of 875 papers related to bupivacaine liposomes were included. The research and development of bupivacaine liposomes were divided into 3 stages: slow development (1994-2011), a sharp rise (2011-2021), and stabilization (2021-2023). The United States was in a leading position in terms of the number of publications, centrality, and author cooperation, and Harvard University had the largest number of publications. de Paula E had the most publications, Bramlett K had the highest number of citations, and Boogaerts J had the highest centrality of publications. Journals such as Anesthesia and Analgesia made significant contributions to this field. The most cited references focused on the infiltration of wounds and the periprosthetic injection of bupivacaine liposomes. The keyword analysis showed that local anesthetics, postoperative pain, etc. were commonly used keywords, and enhanced recovery after surgery was an emerging hotspot. Conclusions:Bupivacaine liposomes show good application prospects in the field of peripheral nerve block due to their unique pharmacological properties and safety characteristics and are expected to prolong the duration of postoperative analgesia. However, there is a difference between the actual effect and the expectation, and more clinical trials are needed to evaluate the curative effect, providing a more solid and reliable theoretical basis and practical guidance for clinical practice.

Objective:To analyze the impact of stressful life events on the social activity participation of middle-aged and elderly adults in China, providing a scientific basis for improving their quality of life.Methods:This study was conducted in January 2024.Data were derived from the China health and retirement longitudinal study (CHARLS) conducted from 2011 to 2020. SPSS 25.0 software was used for statistical analysis.Ordered Logistic regression analysis was employed to explore the association between stressful life events experienced over the past decade and the level of social activity participation, with stratified analysis by age, gender, and place of residence.Results:A total of 10 838 middle-aged and elderly adults were included in this study. The proportions of individuals with no social activity participation, low social activity participation, and high social activity participation were 52.07%(5 643/10 838), 24.21%(2 624/10 838), and 23.72%(2 571/10 838), respectively. After adjusting for sociodemographic characteristics and health-related behaviors, individuals who experienced stressful life events were 15.2% less likely to participate in social activities compared to those who did not ( RR=0.848, 95% CI=0.786-0.915).Stratified analysis revealed that the decrease in the likelihood of social activity participation following stressful life events was significantly greater in urban residents than that in rural residents ( Pinteraction=0.004). Conclusion:Experiencing stressful life events over the past decade may reduce the level of social activity participation among middle-aged and elderly adults. It is recommended to strengthen psychological counseling for this population and encourage active social engagement.

With the rapid development of artificial intelligence technology,Large Language Models(LLMs)have in-creasingly been applied in the medical field,particularly demonstrating significant potential in the prevention and management of medical disputes,patient management,and medical quality control.This article,from the perspective of cooperative governance,summarizes and analyzes the current application of LLMs in the field of medical dispute from the perspectives of the governments,research and development companies,medical staff,patients and all other relevant parties.It delves into the advantages of LLMs in dispute prediction,document writing,quality control,patient management,and case retrieval,and systematically analyzes the challenges faced in data security,privacy protection,professional competence,ethical and legal issues,and personnel utilization.The aim of this article is to provide references and development suggestions for further research and practice of LLMs in the field of medical disputes.

Objective:In carbon ion treatment planning of water phantom, establish a conversion factor calculation system and conversion factor curves for organs at risk (OAR) for microdosimetric kinetic models (MKM) and local effect models (LEM), and validate them in clinical patient planning.Methods:Using a uniform spherical water phantom as the research object, relative biological effectiveness-weighted doses (RWD) for the LEM were re-calculated based on the physical dose of RayStation-MKM. The median dose within the planning target volume (PTV) of LEM and MKM was regarded as the conversion factor. The impacts of single-fraction target prescription dose, spread-out Bragg peak (SOBP) width and depth, shape, and irradiation mode on the conversion factor were assessed, and a conversion factor calculation system was established. Additionally, the accuracy of the conversion factor calculation system was validated using both water phantoms and clinical patient cases. The conversion factor curves for OAR were computed based on clinical patient treatment plans.Results:The primary influencing factors for the conversion factors were the single-fraction prescription dose, target SOBP width and depth. The conversion factors were increased with the increase of SOBP width and target depth, whereas decreased with the increase of the single-fraction prescription dose. Under single-field irradiation, a conversion factor calculation system was established based on above 3 parameters. For the plans of 9 patients, the average difference between the calculated results and the conversion factor calculation system was 0.340% ± 0.203%, and the average difference in the conversion curves for OAR was 2.650% ± 2.399%.Conclusion:A dose conversion factor calculation system and conversion factor curves for OAR for carbon ion radiotherapy are established for MKM and LEM, and their accuracy meets the requirements for use in clinical patient treatment plans.

Objective:To investigate the clinical characteristics and survival outcomes of patients with nasopharyngeal carcinoma (NPC) complicated by multiple primary malignancies (MPCs) in a real-world setting.Methods:A retrospective study was performed on 238 NPC patients with MPCs who received radical radiotherapy at Fujian Cancer Hospital between January 1st, 2004 and December 31st, 2023. The primary endpoints were overall survival (OS) and cumulative survival rate. Survival analysis was conducted using the Kaplan-Meier method with log-rank / Breslow tests, and univariate analysis of prognostic factors was performed using the Cox proportional hazards model.Results:A total of 246 primary malignant tumors were identified in 238 patients, involving 12 organ systems and 39 tumor types. The most common coexisting malignancies occurred in the respiratory and intrathoracic organs [25.2% (62/246)], followed by digestive organ malignancies [22.8% (56/246)], malignancies of the lip, oral cavity, and pharynx [22.8% (56/246)], and thyroid and other endocrine gland malignancies [15.4% (38/246)]. The median OS was 186 months, and the 3-, 5-, and 10-year cumulative survival rates were 90.84%, 85.25%, and 69.45%, respectively. Poorer survival was associated with male sex, age>48 years at onset, locally advanced disease (stage IVA), synchronous MPCs and/or digestive system malignancies, fewer total cycles of chemotherapy, and lack of concurrent or adjuvant chemotherapy.Conclusions:In patients with NPC, MPCs most frequently involve the respiratory system, digestive system, and head and neck organs (including the thyroid). Male sex, older age, locally advanced primary NPC, synchronous and/or digestive system MPCs, fewer chemotherapy cycles, and lach of concurrent or adjuvant chemotherapy were significantly associated with poorer prognosis.

The mortality and disability rates of intracranial aneurysm(IA)remain extremely high.CT angiography(CTA)has been widely used for first-line examination of IA,yet with limited diagnostic accuracy and time-consuming procedures.Artificial intelligence(AI)developed continuously in recent years,which could help to improve the accuracy of diagnosing IA and predicting its rupture.The research progresses of AI in CT A evaluating IA were reviewed in this article.

With the rapid development of artificial intelligence technology,Large Language Models(LLMs)have in-creasingly been applied in the medical field,particularly demonstrating significant potential in the prevention and management of medical disputes,patient management,and medical quality control.This article,from the perspective of cooperative governance,summarizes and analyzes the current application of LLMs in the field of medical dispute from the perspectives of the governments,research and development companies,medical staff,patients and all other relevant parties.It delves into the advantages of LLMs in dispute prediction,document writing,quality control,patient management,and case retrieval,and systematically analyzes the challenges faced in data security,privacy protection,professional competence,ethical and legal issues,and personnel utilization.The aim of this article is to provide references and development suggestions for further research and practice of LLMs in the field of medical disputes.