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 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.

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.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

OBJECTIVE To provide guidance for pharmaceutical care in patients with severe Cryptococcus gattii infections.METHODS Clinical pharmacists participated in the diagnosis and treatment of a male patient with disseminated Cryptococcus gattii infection （involving the lungs and central nervous system）. Given the patient’s poor response to initial therapy， the clinical pharmacists， based on antimicrobial susceptibility test results， recommended voriconazole as an alternative azole. In response to refractory hypokalemia caused by liposomal amphotericin B， the clinical pharmacists assisted the physician in developing an intensive potassium replacement regimen. Regarding the interaction between voriconazole and nifedipine， the clinical pharmacists proactively identified the risk and intensified monitoring of the patient’s blood pressure. In response to the onset of hepatitis C during treatment， the clinical pharmacists thoroughly weighed the priority of infection treatment and recommended temporarily postponing antiviral therapy for hepatitis C. For the individualized use of voriconazole， the clinical pharmacists repeatedly performed therapeutic drug monitoring （TDM）. Regarding the patient’s poor lesion resolution， the clinical pharmacists participated in multidisciplinary team discussions to clarify the indications for surgery.RESULTS The physician adopted the clinical pharmacists’ recommendations. Following pharmacological treatment and surgical intervention， the patient’s condition stabilized， and he was discharged while still on medication.CONCLUSIONS For severe Cryptococcus gattii infections， clinical pharmacists should focus on pathogen characteristics， strengthen adverse reaction management， pay close attention to drug interactions， conduct TDM， and actively participate in multidisciplinary team collaboration to ensure the safety and efficacy of patient treatment.

ObjectiveTo investigate the mechanism by which Feixin decoction treats hypoxic pulmonary hypertension （HPH） by regulating the peroxisome proliferator-activated receptor gamma （PPARγ）/nuclear factor-kappa B （NF-κB）/NOD-like receptor pyrin domain containing 3 （NLRP3） signaling pathway. MethodsForty-eight male SD rats were randomly allocated into normal， hypoxia， and low-， medium- and high-dose （5.85， 11.7， 23.4 g·kg^-1， respectively） Feixin decoction groups， with 8 rats in each group. Except the normal group， the remaining five groups were placed in a hypoxia chamber with an oxygen concentration of （10.0±0.5）% for 8 h per day， 28 days， and administrated with corresponding drugs during the modeling process. After 4 weeks of treatment， echocardiographic parameters ［pulmonary artery acceleration time （PAT）， pulmonary artery ejection time （PET）， right ventricular anterior wall thickness （RVAWd）， and tricuspid annular plane systolic excursion （TAPSE）］ were measured for each group. The right ventricular systolic pressure （RVSP） was measured by the right heart catheterization method， and the right ventricular hypertrophy index （RVHI） was calculated by weighing the heart. The pathological changes in pulmonary arterioles were observed by hematoxylin-eosin staining. The co-localization of α-smooth muscle actin （α-SMA） with NLRP3， N-terminal gasdermin D （N-GSDMD）， and cysteinyl aspartate-specific proteinase-1 （Caspase-1） in pulmonary arteries was detected by immunofluorescence. The protein levels of PPARγ， NF-κB， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， N-GSDMD， interleukin-1β （IL-1β）， interleukin-18（IL-18）， and cleaved Caspase-1 in the lung tissue was determined by Western blot. The ultrastructural changes in pulmonary artery smooth muscle cells （PASMCs） were observed by transmission electron microscopy. ResultsCompared with the normal group， the hypoxia group showed increased RVSP and RVHI （P<0.01）， decreased right heart function （P<0.01）， increased pulmonary vascular remodeling （P<0.01）， increased co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 in pulmonary arterioles （P<0.01）， up-regulated protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， a down-regulated protein level of PPARγ （P<0.05， P<0.01）， and pyroptosis in PASMCs. Compared with the hypoxia group， Feixin decoction reduced RVSP and RVHI， improved the right heart function and ameliorated pulmonary vascular remodeling （P<0.05， P<0.01）， decreased the co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 （P<0.05， P<0.01）， down-regulated the protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， up-regulated the protein level of PPARγ （P<0.05， P<0.01）， and alleviated pyroptosis in PASMCs. ConclusionFeixin decoction can ameliorate pulmonary vascular remodeling and right heart dysfunction in chronically induced HPH rats by regulating pyroptosis in PASMCs through the PPARγ/NF-κB/NLRP3 pathway.

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.