AIM: To investigate the changes in serum levels of platelet-derived growth factor A(PDGFA), heme oxygenase 1(HMOX1)and suppressor of cytokine signaling 6(SOCS6)in patients with diabetic retinopathy(DR)at different stages, and their predictive value for prognosis. METHODS: Patients diagnosed with DR in Zibo No.148 Hospital from April 2023 to April 2024 were included as the study group, and patients with simple type 2 diabetes mellitus(T2DM)during the same period were included as the control group. DR patients were separated into non proliferative DR group(NPDR group)and proliferative DR group(PDR group)based on DR staging, and into good prognosis group and poor prognosis group based on prognosis. Enzyme-linked immunosorbent assay(ELISA)method was used to detect serum levels of PDGFA, HMOX1, and SOCS6, and Pearson method was performed to analyze their correlation with laboratory indicators. Multivariate logistic regression was used to explore the risk factors affecting poor prognosis in DR patients. Receiver operating characteristic(ROC)curves were plotted to explore the prognostic value of serum PDGFA, HMOX1, and SOCS6 levels for DR patients. RESULTS: Totally 128 DR patients(67 males and 61 females)with the mean age 50.65±8.57 y were included. The control group consisted of 120 T2DM patients(63 males, 57 females)with the mean age of 50.32±8.65 y. The NPDR group comprised 74 patients(39 males, 35 females)with mean age of 50.42±8.71 y; the PDR group included 54 patients(28 males, 26 females)with the mean age of 50.96±8.40 y; The good prognosis group comprised 81 patients(43 males, 38 females)with the mean age of 50.51±8.62 y; the poor prognosis group included 47 patients(24 males, 23 females)with the mean age of 50.89±8.48 y. Compared with the control group, the study group had significantly higher serum levels of PDGFA, HMOX1, and SOCS6(all P<0.05). The PDR group had significantly higher serum levels of PDGFA, HMOX1, and SOCS6 than the NPDR group(all P<0.05). The poor prognosis group had significantly higher serum levels of FBG, HbA1c, SOD, MDA, IL-6, TNF-α, PDGFA, HMOX1, and SOCS6 than the good prognosis group(all P<0.05). The serum PDGFA of DR patients was positively related to FBG, HbA1c, IL-6, and TNF-α levels(all P<0.05), HMOX1 was positively related to FBG, HbA1c, SOD, MDA, IL-6, and TNF-α levels(all P<0.05), and SOCS6 was positively related to FBG, IL-6, and TNF-α levels(all P<0.05). Elevated levels of serum PDGFA, HMOX1, SOCS6, and HbA1c were risk factors for the prognosis of DR patients(all P<0.05). The AUC values of serum PDGFA, HMOX1, and SOCS6 alone in predicting the prognosis of DR patients were 0.806, 0.822, and 0.826, respectively. The AUC of their joint prediction was 0.912, and the joint prediction was superior to individual prediction(Z joint-PDGFA=2.183, P=0.029; Z joint-HMOX1=2.308, P=0.021; Z joint-SOCS6=2.620, P=0.009). CONCLUSION: Serum PDGFA, HMOX1, SOCS6 are significantly correlated with DR staging and prognosis, all showing high predictive efficiency for the prognosis of DR patients, with certain clinical value.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Objective: To analyze epidemiological trends and changing characteristics of syphilis among students in Yunnan Province from 2005 to 2023, so as to provide evidence for the comprehensive prevention and control of syphilis in schools. Methods: The case data of syphilis among students in Yunnan Province from 2005 to 2023 were obtained from the China Information System for Disease Control and Prevention. The Joinpoint regression model was used to conduct a time trend analysis of the reported incidence rate of syphilis. Results: From 2005 to 2023, a cumulative total of 3 191 cases of syphilis were reported in schools in Yunnan Province(1 248 male cases and 1 943 female cases). The reported incidence rate rose continuously from 0.17/100 000 in 2005 to 8.26/100 000 in 2023, with an average annual percent change (AAPC) of 24.89%( Z =13.18, P <0.01). The reported incidence rate was higher in female students than in male students ( χ 2=229.48, P <0.05). The incidence rates in the primary school, junior high school, senior high school and higher education were 0.21/100 000, 2.42/100 000, 4.45/100 000 and 6.29/100 000 respectively, and the difference was statistically significant (χ 2=3 432.84, P <0.05). The average annual growth rate was the highest in the junior high school stage(AAPC= 30.68% , Z =7.57, P <0.05),followed by the senior high school stage (AAPC=24.28%, Z = 5.70 , P <0.05).The reported incidence rate of primary and secondary syphilis increased from 0.12/100 000 in 2005 to 2.06/ 100 000 in 2023, with an AAPC of 16.86% ( Z = 4.57, P <0.05). Conclusions The overall reported incidence rate of syphilis among students in schools in Yunnan Province shows a sustained upward trend, with the most rapid annual increase observed in junior high schools. Schools should prioritize syphilis education and expand awareness campaigns to curb transmission.

ObjectiveTo explore the regulation of hypothalamic-pituitary-gonadal （HPG） axis by modified Erxian decoction in rats with perimenopausal syndrome （PMS） and to further analyze the expression of proteins related to the silent information regulator 1 （SIRT1）/hypothalamic kisspeptin （Kisspeptin）/gonadotropin-releasing hormone （GnRH） signaling pathway in the arcuate nucleus region （ARC） of the hypothalamus， so as to reveal the potential target of action and molecular biological mechanism of modified Erxian decoction for the treatment of perimenopausal syndrome. MethodsAn animal model was established via the incomplete castration method， with successful modeling confirmed by the exfoliated cervical cell smear method. The 48 rats were divided into six groups based on the randomization principle after successful modeling， including a sham operation group， a model group， an estradiol valerate group （0.09 mg∙kg^-1∙d^-1）， high-， medium-， and low-dose modified Erxian decoction groups （7.614， 3.807，1.903 5 g∙kg^-1∙d^-1）， with 8 rats in each group. The estradiol valerate group and the high-， medium- and low-dose modified Erxian decoction groups were continuously administered by gavage for 28 days， and the indicators were detected 24 hours after the last administration. Body weights and uterine indices were measured. The pathological changes of the uterus were observed by hematoxylin-eosin （HE） staining. Enzyme-linked immunosorbent assay （ELISA） was performed to measure the levels of estradiol （E₂）， follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， and gonadotropin-releasing hormone （GnRH）. Real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot were used to determine the expression levels of SIRT1， Kisspeptin， kisspeptin receptor （GPR54）， and GnRH in the ARC region of the hypothalamus and gonadotropin-releasing hormone receptor （GnRH-R） in pituitary. ResultsCompared with the sham operation group， rats in the model group had a significantly increased body weight （P0.01）， reduced wet weight and index of uterus （P0.01）， endometrial thinning or atrophy， glandular atrophy， and a decreasing number of glands. Additionally， serum levels of E₂ and the expression of SIRT1 in the ARC region of the hypothalamus significantly decreased （P0.01）. Serum levels of FSH， LH， and GnRH， the expression of Kisspeptin， GPR54， and GnRH in the ARC region of the hypothalamus， and GnRH-R in pituitary significantly increased （P0.01）. Compared with the model group， the estradiol valerate group and the high-， medium-dose modified Erxian decoction groups had significantly reduced body weight， serum levels of FSH， LH， and GnRH， and expression of Kisspeptin， GPR54， and GnRH in the ARC region of the hypothalamus and GnRH-R in pituitary （P0.05， P0.01） and significantly increased wet weight and index of uterus， serum level of E₂， and expression of SIRT1 in the ARC region of the hypothalamus （P0.05， P0.01）. In addition， they showed thickened endometrium， increased number of endometrial glands， and improved glandular atrophy. ConclusionModified Erxian decoction regulates the function of the HPG axis through multi-targets， and its mechanism of action may be related to the up-regulation of the expression of SIRT1 in the ARC region of the hypothalamus， the inhibition of the over-activation of the Kisspeptin/GnRH signaling pathway， the regulation of the expression of GnRH-R in the pituitary， the restoration of secretion balance of gonadotropins， and the elevation of the estrogen level. This study provides an experimental basis for the interpretation of the scientific connotation of modified Erxian decoction in the treatment of perimenopausal syndrome and a theoretical reference for the development of a novel therapeutic strategy based on the SIRT1/Kisspeptin/GnRH pathway.

Intelligent acupuncture-moxibustion medical equipment is an important force in promoting the inheritance, innovation, and modernization of acupuncture-moxibustion. This paper reviews the development status of intelligent acupuncture-moxibustion medical equipment and related new technologies, as well as the challenges faced. It is found that, with the advancement of technologies such as big data and artificial intelligence, acupuncture-moxibustion medical equipment has shown characteristics of greater precision, miniaturization, intelligence, and portability. However, deficiencies remain in areas such as standardization and regulation, including relatively low rates of effective transformation and a lack of innovation in research outcomes. Therefore, there is an urgent need to formulate corresponding strategies: improving the development of relevant standards for intelligent acupuncture-moxibustion medical equipment, encouraging the integration of medicine and engineering, cultivating interdisciplinary talents, and strengthening the protection of invention patents. It is necessary to establish a demand-oriented pathway connecting "equipment development, equipment evaluation, product formation" through multiple stages such as talent training and research project initiation, thereby promoting the modernization and standardization of intelligent acupuncture-moxibustion medical equipment and supporting the revitalization of traditional medicine.
Moxibustion/instrumentation* ; Humans ; Acupuncture Therapy/trends* ; Artificial Intelligence

OBJECTIVE To observe the current status and influencing factors for the water contamination of humid-ification tanks of ventilators of the patients undergoing invasive mechanical ventilation.METHODS Totally 139 hu-midified water samples were collected from the patients who received invasive mechanical ventilation in The First Medical Center of Chinese PLA General Hospital from Jul.2024 to Nov.2024.The humidified water samples were collected,cultured and identified on Day 1,3,5 and 7 after humidification tanks replacement.RESULTS Among the 139 samples,25 were tested positive for pathogens,with the positive test rate 17.99％;the positive test rate was highest(33.33％,8/24)in respiratory intensive care unit.The positive test rate was 12.90％on Day 1,18.42％on Day 3,15.00％on Day 5 and 26.67％on Day 7,showing an upward trend.The result of bacterial culture showed that the percentage of isolated Burkholderia cepacia was highest(36.00％).The result of analysis of the related factors for positive test of humidified water samples showed that the sample adding pattern was as-sociated with the isolation rate(P＜0.05).Only 1 case was diagnosed with ventilator-associated pneumonia(VAP)after the humidified water was detected with pathogens and varied in the pathogens.CONCLUSIONS There is an association between the status of water contamination of the ventilator humidification tanks and usage duration of humidification tank.It is necessary to attach great importance to the contamination of humidification tanks,carry out standard management,and implement the prevention and control measures in an all-round way.

Objective:By analyzing peripheral blood indicators, we constructed and validated a novel lung cancer prediction model using machine learning algorithms for riskassessment of lung cancer.Methods:A retrospective case-control design was conducted on the clinical data of 194 newly diagnosed lung cancer patients [mean age: (66.80±9.09) years, 126 males and 68 females] admitted to Qilu Second Hospital of Shandong University between January 9, 2020, and December 31, 2024, serving as the case group. During the same period, 290 healthy individuals undergoing physical examinations [mean age: (61.18±14.31) years, 155 males and 135 females J were enrolled as the control group. A total of 46 peripheral blood indicators-including routine blood tests, coagulation parameters, liver function markers, and tumor-related indices-along with two basic characteristics (age and sex) were included in the analysis. Eleven machinelearning algorithms including logistic regression, randomforest, support vector classifier, extreme gradient boosting, gradient boosting decision tree, decision tree, multilayer perceptron, linear discriminant analysis, adaptive boosting, Gaussian naive Bayes and light gradient-boosting machine-were trained for early diagnosis of lung-cancer.Model performance was evaluated by the area under the ROC, accuracy, positive predictive value, negative predictive value, F1-score and 95% confidence interval (95% CI). The best performing algorithm was selected, and feature importance was ranked with Shapley Additive Planation(SHAP) values. Results:The support-vector classifier achieved the best performance for predicting lung-cancer risk (AUC=0.974; 95 % CI 0.951-0.989) and was retained for final model establishment. After 20 rounds of stratified 10-fold cross-validation the mean AUC was 0.950; learning-curve, decision-curve and calibration analyses confirmed its superior generalizability, clinical utility and calibration.SHAPley additive explanations and decision-tree feature importance consistently identified neuron-specific enolase, carcinoembryonic antigen, and squamous-cell carcinoma antigen as the three most critical predictors of lung-cancer risk. Conclusion:An SVM-based lung cancer prediction model was successfully established to determine the risk of developing lung cancer.