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.

AIM: To evaluate the safety and efficacy of low-dose transscleral cyclophotocoagulation(TSCP)in the management of persistent ocular hypertension after an acute attack of angle-closure glaucoma(AACG).METHODS:This retrospective study enrolled patients diagnosed with persistent ocular hypertension after an acute AACG attack at the No.988 Hospital of the Joint Logistics Support Force of the Chinese PLA between September 2023 and September 2024. All patients underwent low-dose TSCP using a semiconductor diode laser. Subsequent cataract surgery combined with goniosynechialysis was performed once intraocular pressure(IOP)was stabilized. Changes in anterior chamber depth(ACD), best-corrected visual acuity(VA), and IOP were compared before and after TSCP, as well as before and after phacoemulsification. Post-TSCP complications were also documented.RESULTS: A total of 21 patients(21 eyes)were enrolled, including 8 males and 13 females, with a mean age of 67.95±7.25 y. Compared with pre-cyclophotocoagulation values, ACD increased significantly at 3 d post-TSCP(1.49±0.18 vs 1.22±0.21 mm; P<0.001). BCVA and IOP decreased significantly at 1 d post-TSCP, pre-phacoemulsification, 1 wk post-phacoemulsification, and 1 mo post-phacoemulsification compared with pre-TSCP IOP(all P<0.01). Regarding postoperative complications, 2 eyes experienced pain on the day of the procedure, 5 eyes developed mild corneal endothelial folds, 2 eyes exhibited moderate anterior chamber inflammatory reaction, and 12 eyes showed shallow ciliary body detachment. No serious complications occurred during the 1-month follow-up period.CONCLUSION:Low-dose TSCP appears to be an effective bridging therapy for patients with persistent ocular hypertension following an AACG attack. It facilitates rapid IOP reduction, alleviates symptoms, and helps preserve visual function with a favorable safety profile, thereby reducing the risks associated with subsequent intraocular surgery.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

BACKGROUND:The imbalance between bone resorption and bone formation in microgravity environments leads to significant bone loss in astronauts.Current research indicates that bone loss under microgravity conditions is the result of the combined effects of various cells,tissues,and systems. OBJECTIVE:To review different biological effects of microgravity on various cells,tissues,or systems,and summarize the mechanisms by which microgravity leads to the development of osteoporosis. METHODS:Databases such as PubMed,Web of Science,and the Cochrane Database were searched for relevant literature from 2000 to 2023.The inclusion criteria were all articles related to tissue engineering studies and basic research on osteoporosis caused by microgravity.Ultimately,85 articles were included for review. RESULTS AND CONCLUSION:(1)In microgravity environment,bone marrow mesenchymal stem cells tend to differentiate more into adipocytes rather than osteoblasts,and hematopoietic stem cells in this environment are more inclined to differentiate into osteoclasts,reducing differentiation into the erythroid lineage.At the same time,microgravity inhibits the proliferation and differentiation of osteoblasts,promotes apoptosis of osteoblasts,alters cell morphology,and reduces the mineralization capacity of osteoblasts.Microgravity significantly increases the number and activity of osteoclasts.Microgravity also hinders the differentiation of osteoblasts into osteocytes and promotes the apoptosis of osteocytes.(2)In a microgravity environment,the body experiences changes such as skeletal muscle atrophy,microvascular remodeling,bone microcirculation disorders,and endocrine disruption.These changes lead to mechanical unloading in the bone microenvironment,insufficient blood perfusion,and calcium cycle disorders,which significantly impact the development of osteoporosis.(3)At present,the mechanism by which microgravity causes osteoporosis is relatively complex.A deeper study of these physiological mechanisms is crucial to ensuring the health of astronauts during long-term space missions,and provides a theoretical basis for the prevention and treatment of osteoporosis.

The development of traditional Chinese medicine (TCM) diagnosis and treatment has undergone multiple paradigms, evolving from sporadic experiential practices to systematic approaches in syndrome differentiation and treatment and further integration of disease and syndrome frameworks. TCM is a vital component of the medical system, valued alongside Western medicine. Treatment based on syndrome differentiation embodies both personalized treatment and holistic approaches; however, the inconsistency and lack of stability in syndrome differentiation limit clinical efficacy. The existing integration of diseases and syndromes primarily relies on patchwork and embedded systems, where the full advantages of synergy between Chinese and Western medicine are not fully realized. Recently, driven by the development of diagnosis and treatment concepts and advances in analytical technology, Western medicine has been rapidly transforming from a traditional biological model to a precision medicine model. TCM faces a similar need to progress beyond traditional syndrome differentiation and disease-syndrome integration toward a more precise diagnosis and treatment paradigm. Unlike the micro-level precision trend of Western medicine, precision diagnosis and treatment in TCM is primarily reflected in data-driven applications that incorporate information at various levels, including precise syndrome differentiation, medication, disease management, and efficacy evaluation. The current priority is to accelerate the development of TCM precision diagnosis and treatment technology platforms and advance discipline construction in this area.

Background: Diabetic nephropathy (DN) is the most common and serious complication of diabetes mellitus. Shionone (SH), an important triterpenoid compound in the root extract of Aster, might exert a protective effect in DN mice and high glucose cultivated glomerular podocytes. The current study aimed to unravel the underlying mechanism by which SH mitigates DN. We postulate that SH stimulates the expression of sestrin-2 (SESN2), a pivotal stress-inducible protein in the anti-inflammasome machinery. Methods: We utilized high-fat diet combined with streptozotocin (55 mg/kg intraperitoneal) for DN mice model, and high glucose (30 mM, 48 hours) cultured glomerular podocytes for DN cell model to evaluate the effect of SH. We also preformed experimentation on SESN2 deficiency models (SESN2 knockout mice and SESN2 siRNA in cells) to further prove our hypothesis. Results: The results demonstrated that SH effectively suppressed glomerular fibrosis, induced adenosine monophosphate-activated protein kinase (AMPK) phosphorylation, and inhibited NLR family pyrin domain containing 3 (NLRP3) activation. Furthermore, our findings revealed that SH exerted its anti-inflammatory effect through Sesn2-dependent nuclear factor erythroid 2-related factor 2 (Nrf2) nuclear translocation and subsequent activation of its downstream target heme oxygenase-1 (HO-1). Conclusion In summary, our findings suggest that SH serves as a promising therapeutic agent for the treatment of DN-related glomerular fibrosis. SH enhances the expression of SESN2, attenuates α-smooth muscle actin accumulation, and suppresses NLRP3-related inflammation through the Nrf2/HO-1 signaling pathway.

Background: Diabetic nephropathy (DN) is the most common and serious complication of diabetes mellitus. Shionone (SH), an important triterpenoid compound in the root extract of Aster, might exert a protective effect in DN mice and high glucose cultivated glomerular podocytes. The current study aimed to unravel the underlying mechanism by which SH mitigates DN. We postulate that SH stimulates the expression of sestrin-2 (SESN2), a pivotal stress-inducible protein in the anti-inflammasome machinery. Methods: We utilized high-fat diet combined with streptozotocin (55 mg/kg intraperitoneal) for DN mice model, and high glucose (30 mM, 48 hours) cultured glomerular podocytes for DN cell model to evaluate the effect of SH. We also preformed experimentation on SESN2 deficiency models (SESN2 knockout mice and SESN2 siRNA in cells) to further prove our hypothesis. Results: The results demonstrated that SH effectively suppressed glomerular fibrosis, induced adenosine monophosphate-activated protein kinase (AMPK) phosphorylation, and inhibited NLR family pyrin domain containing 3 (NLRP3) activation. Furthermore, our findings revealed that SH exerted its anti-inflammatory effect through Sesn2-dependent nuclear factor erythroid 2-related factor 2 (Nrf2) nuclear translocation and subsequent activation of its downstream target heme oxygenase-1 (HO-1). Conclusion In summary, our findings suggest that SH serves as a promising therapeutic agent for the treatment of DN-related glomerular fibrosis. SH enhances the expression of SESN2, attenuates α-smooth muscle actin accumulation, and suppresses NLRP3-related inflammation through the Nrf2/HO-1 signaling pathway.