ObjectiveTo explore the effects of Jingui Shenqiwan （JSW） and Liuwei Dihuangwan （LDW） on the reproductive ability and brain function of normal mice and compare the actions of the two medications. MethodsSeven groups of female and male mice were divided at a ratio of 2∶1. Except for the control group， the other six groups were as follows： a group of both males and females receiving JSW （3.0 g·kg^-1）， a group of both males and females receiving LDW （4.5 g·kg^-1）， a group of males receiving water and females receiving JSW， a group of males receiving water while females receiving LDW， a group of females receiving water while males receiving JSW， and a group of females receiving water while males receiving LDW. Each group was administered the drug for 14 days and then caged together at a 2∶1 （female∶male） ratio to detect the number of pregnant mice and calculate the pregnancy rate. Pregnant mice continued receiving the drug until they naturally gave birth， which was followed by the observation of newborn mice， calculation of their average number， and the measurement of the offspring's preference for sugar water and neonatal recognition index. At the end of the experiment， the weights of the thymus and spleen were measured to calculate the organ coefficients， and mRNA or protein expression was analyzed in the brain and testes or ovaries. A 1% sucrose solution was used to examine the euphoria of their brain reward systems， while novel object recognition test （NOR） was applied to assess their memory capabilities. mRNA expression was detected using real-time quantitative polymerase chain reaction （Real-time PCR） assay， and protein expression was analyzed with Western blot. ResultsCompared with the control group， oral administration of JSW to both male and female mice for 14 days significantly increased the pregnancy rate of female mice on day 2 after being caged together （P<0.05）， while LDW showed a trend but no statistical significance. Additionally， compared with the control group， JSW could upregulate the gene expression of gonadotropin-releasing hormone （GnRH） in the thalamus， as well as reproductive stem cell factor （SCF） and tyrosine kinase receptor （c-Kit） in the testes and reproductive stem cell marker mouse vasa homologue （MVH） in the ovaries， upregulate the expression of proteins influencing neuronal functional activity， such as brain-derived neurotrophic factor （BDNF）， in hippocampal neurons （P<0.05）， and enhance sucrose preference in male mice （P<0.05）. Compared with the control group， JSW significantly increased sucrose preference and novel object recognition index in offspring mice （P<0.05）， which was related to the upregulation of hippocampal dopamine D1 receptor （D1R） and N-methyl-D-aspartate receptor （Nmdar） gene expression. Compared with the control group， both JSW and LDW could upregulate the protein expression of glucocorticoid receptor （GR）， BDNF， and tyrosine kinase receptor B （TrkB） in the hippocampus of offspring mice （P<0.05）. ConclusionJSW significantly enhances the reproductive ability of normal mice， which is not only related to the release of gonadotropin but also associated with its regulation of brain function. Additionally， JSW has a certain regulatory effect on the brain function of the offspring mice.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Objective To summarize the clinical efficacy of modified Morrow surgery in the treatment of hypertrophic obstructive cardiomyopathy. Methods A retrospective analysis was conducted on the clinical data of patients with hypertrophic obstructive cardiomyopathy treated with modified Morrow surgery at Zhongshan Hospital Affiliated to Fudan University from 2020 to 2023. Results A total of 318 patients were enrolled, including 156 males and 162 females, with an average age of (55.6±13.1) years. Preoperative echocardiography showed a mean interventricular septal thickness of (18.1±3.8) mm, peak left ventricular outflow tract pressure difference of (86.4±24.9) mm Hg. The surgery time was (162.3±51.0) min, extracorporeal circulation time was (80.9±31.0) min, and aortic occlusion time was (44.8±20.8) min. After the surgery, transesophageal echocardiography showed that the interventricular septal thickness was (11.0±1.8) mm and left ventricular outflow tract peak pressure difference was (9.4±5.1) mm Hg. The incidence rate of postoperative complete left bundle branch block was 45.3%, Ⅲ° atrioventricular block was 3.8%, and postoperative newly developed atrial fibrillation was 3.1%. The postoperative hospital stay was (6.6±4.9) days, and one perioperative death occurred, with a mortality rate of 0.3%. The follow-up time was (10.3±9.4) months, during which the transthoracic echocardiography revealed a ventricular septal thickness of (12.9±2.9) mm and a peak left ventricular outflow tract pressure difference of (13.9±10.0) mm Hg. Conclusion The modified Morrow procedure for the treatment of hypertrophic obstructive cardiomyopathy is safe and effective, with good results in the short and medium term.

Objective: To evaluate the effectiveness of school-family-community comprehensive intervention aimed at reducing sugar sweetened beverage(SSB) consumption among primary and secondary school students, so as to provide scientific basis for relevant departments to formulate campus sugar reduction measures for primary and secondary school students. Methods: In October 2023, a multi stage random cluster sampling method was used to select four primary schools (grade 4) and four junior high schools (grade 7) in Nanjing City, and they were randomly divided into the intervention group ( n =1 601) and the control group ( n = 1 433 ) (primary and secondary schools). The intervention group received a one year comprehensive intervention activity with the theme of “drinking less SSBs and enjoying a healthy life” for one consecutive year. The measures included the school conducting health education courses (once a month, 15 minutes each time), environmental support (posting promotional posters, changing them once a month), class bulletin board and interest projects (once a semester); interventions for families included conducting parent lectures (once per semester 30 min each time), new media (once a month) and hand in hand activities (once per semester); community carried out square promotion and create a supportive environment (post promotional posters and replace them once a month). The control group did not receive any intervention measures except regular health education classes. Self administered questionnaires were used to collect knowledge, attitudes, and intake of SSB at the baseline and after the intervention among primary and secondary school students. Results: After the intervention, the proportion of students in the intervention group with an SSB related knowledge awareness rate of 60% or above was 91.4%, which was higher than that of the control group (81.9%) ( χ 2=60.35, P < 0.01 ). The reporting rate of the behavior of choosing to drink beverages when thirsty in the intervention group was 25.4%, which was lower than that of the control group (33.3%); the reporting rates of informing parents about the hazards of sugar sweetened beverages and paying attention to nutrition labels were 62.0% and 78.0% respectively, both of which were higher than those of the control group (52.3%, 65.9%); the reporting rate of having sugar sweetened beverages at home frequently was 43.7% in the intervention group, which was lower than that of the control group (62.3%); the reporting rate of parents restricting the consumption of sugar sweetened beverages was 84.1%, which was higher than that of the control group (78.4%) ( χ 2= 22.66, 29.05, 54.40, 104.84, 16.24, all P <0.05). The reporting rate of students in the intervention group who consumed sugar sweetened beverages more than 4 times per week was 21.5%, which was lower than that of the control group (28.6%), and the difference was statistically significant ( χ 2=20.36, P <0.01). Conclusion The comprehensive intervention of school-family-community can effectively improve primary and secondary school students knowledge and attitudes regarding SSBs and reduce their consumption of these beverages.

By reviewing the physical biological research on the activation of acupoint effects by acupuncture， this paper explains the activation mechanism from the perspective of the generation and transmission of mechanical signals caused by acupuncture， and reveals the physical-chemical coupling processes in the acupoint microenvironment. Future research should focus on locally mechanosensitive cells， further exploring how acupuncture mechanical signals trigger dynamic changes in cells and molecules in the acupoints， and the physical-chemical information transduction mechanism， which will provide scientific evidence for the acupoint activation during acupuncture. Related studies will contribute to a deeper understanding of the scientific principles behind acupuncture and promote its clinical application and development.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective To clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

The machine learning is used increasingly and widely in acupuncture prescription optimization, intelligent treatment and precision medicine, and has obtained a certain achievement. But, there are still some problems remained to be solved such as the poor interpretability of the model, the inconsistency of data quality of acupuncture research, and the clinical application of constructed models. Researches in future should focus on the acquisition of high-quality clinical and experimental data sets, take various machine learning algorithms as the basis, and construct professional models to solve various problems, so as to drive the high-quality development of acupuncture research.
Acupuncture Therapy/trends* ; Machine Learning ; Humans ; Algorithms