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 introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

Objective: To analyze the association between insufficient sleep and score of depressive symptoms among junior and senior high school students, so as to provide a scientific reference for targeted early intervention measures of adolescents depressive symptoms. Methods: From September to November 2023, a stratified cluster random sampling method was used to select 96 080 junior and senior high school students from 409 schools in 113 districts and counties in Shaanxi Province. A questionnaire survey was conducted using the 2023 Shaanxi Provincial Common Student Diseases and Health Influencing Factors Survey Form, and their height and weight were measured. Propensity score (PS) matched (1∶1) analysis was used to match participants with insufficient sleep to those sufficient sleep students. Through the gradual correction of the confounders, three multilevel linear models were established to analyze the association between insufficient sleep and depressive symptoms score, and subgroup analysis was conducted afterward. Results: A total of 70 135 (73.00%) students had insufficient sleep. After PS matching, 25 894 pairs were matched. Before PS matching, after adjusting for gender, educational stage, region, adolescent characteristics, boarding status, smoking, alcohol consumption, outdoor activities and body mass index grouping, linear regression analysis results showed that compared with students who got adequate sleep, students who lacked sleep had an increase of 1.39 scores ( B=1.39, 95%CI =1.28-1.51) in depressive symptoms; after PS matching, students with insufficient sleep got an increase of 1.32 scores ( B=1.32, 95%CI =1.17- 1.45 ) in depressive symptoms score compared with those who had adequate sleep (both P <0.05). Conclusions The insufficient sleep is associated with the increase of the depressive symptoms score of junior and senior high school students. It is recommended that junior and senior high school students should keep a good sleeping habit, so as to reduce the prevalence of depressive symptoms.

Natural polyphenols are a group of components widely found in traditional Chinese medicines and have been demonstrated to delay or prevent the development of aging and age-related diseases in recent years. As far as we know, the studies of natural polyphenols in aging and aging-related diseases have never been extensively reviewed. In the present paper, we reviewed recent advances of natural polyphenols in aging and common age-related diseases and the current technological methods to improve the bioavailability of natural polyphenols. The results showed that natural polyphenols have the potential to prevent or treat aging and common age-related diseases through multiple mechanisms. Nanotechnology, structural modifications, and matrix processing could provide strong technical support for the development of natural polyphenols to prevent or treat aging and age-related diseases. In conclusion, natural polyphenols have important potential in the prevention and treatment of aging and age-related diseases.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

ObjectiveMicrotube associated protein-2 （MAP-2）， alpha-tubulin （α-tubulin）， and synaptophysin （SYP） are important proteins in neuronal signal communication. This paper observed the effects of modified Zhigancao Tang on the expression of serum α-Synuclein （α-Syn） and its oligomers， MAP-2， α-tubulin， and SYP of patients with liver and kidney deficiency of Parkinson's disease （PD）， analyzed their correlation， and evaluated the therapeutic effect of modified Zhigancao Tang in patients with liver and kidney deficiency of PD based on α-Syn transmission pathway mediated by neuronal communication in vivo. MethodsA total of 60 patients with PD who met the inclusion criteria were randomly divided into a treatment group （30 cases） and a control group （30 cases）. Both groups were treated on the basis of PD medicine， and the treatment group was treated with modified Zhigancao Tang. Both groups were treated for 12 weeks. The changes in UPDRS score， TCM syndrome score， and expression of serum α-Syn and its oligomers， MAP-2， α-tubulin， and SYP were observed before and after 12 weeks of treatment in each group. The correlation between the above-mentioned serum biological indexes and the levels of serum α-Syn and its oligomers was analyzed. ResultsAfter treatment， the TCM syndrome score， UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ score of the treatment group were significantly decreased （P<0.05， P<0.01）. The UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ scores in the treatment group were significantly decreased compared with those in the control group after treatment （P<0.05）. After treatment， the total effective rate of the control group was 63.3% （19/30）， and that of the treatment group was 86.7% （26/30）. The clinical effect of the observation group was better than the control group （Z=-2.03， P<0.05）. The total effective rate of the observation group was better than that of the control group， and the difference was statistically significant （χ²=5.136， P<0.05）. After treatment， the oligomer level of serum α-Syn and MAP-2 level in the treatment group were significantly decreased （P<0.05， P<0.01）. The levels of serum α-Syn and its oligomers， as well as α-tubulin in the treatment group， were significantly decreased compared with those in the control group after treatment （P<0.05， P<0.01）. Serum α-Syn was correlated with serum MAP-2 and α-Syn oligomer in patients with PD （P<0.05， P<0.01） but not correlated with serum SYP . Serum α-Syn oligomers of patients with PD were correlated with serum MAP-2 and α-tubulin （P<0.05， P<0.01） but not correlated with serum SYP level. Serum SYP of patients with PD was correlated with serum MAP-2 （P<0.05）. ConclusionModified Zhigancao Tang has a therapeutic effect on patients with liver and kidney deficiency of PD by inhibiting the production of α-Syn oligomers and intervening α-Syn microtubule transport pathway in vivo.

ObjectiveTo explore the effects of the Tai Chi training on bone density， bone turnover markers， and heart rate variability for people with high-risk osteoporosis， and to provide evidence for the prevention of osteoporosis at early stage. MethodsSixty-six cases of people with high risk of osteoporosis were included， and they were divided into 33 cases each in the intervention group and the control group using the random number table method. The control group received osteoporosis health education three times a week， and the intervention group received Tai Chi training under the guidance of a trainer three times a week for 40 mins each time on the basis of the control group， and both groups were intervened for 12 weeks. Dual-energy X-ray absorptiometry was used to measure the bone density of L₁~L₄ vertebrae， bilateral femoral necks and bilateral total hips in the two groups before and after the intervention； enzyme-linked immunosorbent assay was used to determine bone turnover markers before and after the intervention， including pro-collagen type Ⅰ pro-amino-terminal prepropyl peptide （P1NP） and β-collagen type Ⅰ cross-linking carboxy-terminal peptide （β-CTX）. Seven cases with good compliance in the intervention group were selected. After wearing the heart rate sensor， they successively performed Tai Chi training and walking activities recommended by the guideline for 20 mins each， and the heart rate variability （HRV） during exercise was collected， including time-domain indexes such as standard deviation of normal sinus intervals （SDNN）， root-mean-square of the difference between adjacent RR intervals （RMSSD）， frequency-domain metrics such as low-frequency power （LF）， high-frequency power （HF）， and low-frequency/high-frequency power ratio （LF/HF）， as well as nonlinear metrics such as approximate entropy （ApEn）， sample entropy （SampEn）. ResultsFinally， 63 cases were included in the outcome analysis， including 30 cases in the intervention group and 33 cases in the control group. After the intervention， the differences of L₁~L₄ vertebrae， bone density of bilateral femoral neck and bilateral total hip in the intervention group were not statistically significant when compared with those before intervention （P＞0.05）， while the bone density of all parts of the control group decreased significantly compared with that before intervention （P＜0.05）， and the difference in the bone density of the L₁~L₄ vertebrae， bilateral femoral neck， and the right total hip before and after the intervention of the intervention group was smaller than that of the control group （P＜0.05）. The differences in P1NP and β-CTX between groups before and after intervention was not statistically significant （P＞0.05）. Compared with walking exercise， LF decreased， HF increased and LF/HF decreased during Tai Chi exercise （P＜0.05）； the time domain indexes and non-linear indexes between groups had no statistically significant difference （P＞0.05）. ConclusionTai Chi exercise can maintain lumbar， hip， and femoral bone density and improve sympathetic/parasympathetic balance in people at high risk for osteoporosis， but cannot significantly improve bone turnover markers.

OBJECTIVE: To retrospectively analyze the characteristics and influencing factors of COVID-19 infection in patients with multiple myeloma (MM) who underwent autologous hematopoietic stem cell transplantation (AHSCT). METHODS: The clinical data of MM patients who underwent AHSCT in Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from May 26, 2021 to December 26, 2022 were collected. The onset of COVID-19 infection, corresponding symptoms and laboratory tests were followed up in outpatient or by the means of telephone contact and online questionnaires. Related analysis was then performed. RESULTS: This study included 96 patients, and 72 cases among them were infected with COVID-19 while 24 cases were uninfected. Logistic regression analysis showed that vaccination did not significantly reduce the risk of COVID-19 infection, but patients who received two doses of the vaccine had a lower risk of developing moderate and severe disease than those who did not receive or received one dose (OR =0.06, P =0.029). Patients who received daratumumab before had a higher risk of COVID-19 infection (OR =5.78, P =0.039), while those with a history of immunomodulatory drugs (IMiDs) had the opposite effect (OR =0.31, P =0.028). The use of both drugs did not affect the severity of COVID-19 infection. CONCLUSION For MM patients undergoing AHSCT as first-line chemotherapy, COVID-19 vaccination does not significantly reduce the infection rate, but it plays a role in preventing moderate and severe cases. The application of antineoplastic drugs with different mechanisms has a certain impact on the susceptibility to the COVID-19, which should be considered comprehensively when creating treatment plans.
Humans ; Multiple Myeloma/complications* ; COVID-19/epidemiology* ; Hematopoietic Stem Cell Transplantation ; Transplantation, Autologous ; Retrospective Studies ; Risk Assessment ; Risk Factors ; Male ; Female ; Middle Aged ; SARS-CoV-2 ; Adult ; Antibodies, Monoclonal

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.