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.

ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease （COPD） under disease-syndrome combination， thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations （≥2 times/year） and infrequent acute exacerbations （<2 times/year） according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression， and a nomogram model was constructed. The model performance was assessed based on the area under the curve （AUC）， calibration curves， and decision curve analysis （DCA）. ResultsThe differences in baseline characteristics between the frequent acute exacerbations group （1 196 cases） and infrequent acute exacerbations group （833 cases） were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors： body mass index （BMI）， hospitalization days， number of smoking years， place of residence， use of noninvasive ventilators， oxygen-demanding therapy， liver cirrhosis， use of systemic glucocorticosteroids， and traditional Chinese medicine syndrome （phlegm and stasis obstructing the lung）. The nomogram model showed good discrimination and calibration in both the training set （AUC=0.748） and validation set （AUC=0.774）. ConclusionThe risk prediction model for frequent acute exacerbations of COPD， integrating traditional Chinese medicine syndrome， constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.

Early caries confined to the enamel layer represent a critical window for achieving noninvasive intervention in caries management. Caries management has shifted from the traditional “drill-and-fill” model toward a modern paradigm centered on caries risk and lesion management. Based on contemporary concepts, this review systematically summarizes recent advances in early caries management, including caries risk assessment, early diagnosis, treatment strategy selection, and follow-up monitoring, while highlighting the major challenges currently being faced, and further reviewing and discussing the application of artificial intelligence (AI) in early caries management. In terms of risk management, conventional systems including the American Dental Association, Caries Management by Risk Assessment, Cariogram, and the Caries-Risk Assessment Tool remain mainstays in clinical practice. However, AI offers predictive capability through higher-dimensional data processing and the integration of numerous influencing factors, with the potential to improve the accuracy of risk stratification. For diagnosis, visual inspection, tactile examination, and bitewing radiography remain fundamental methods, yet their sensitivity for early caries—particularly proximal lesions—is limited. The application of optical technologies, including quantitative light-induced fluorescence, optical coherence tomography, near-infrared light transillumination, fiber-optic transillumination, and laser-induced fluorescence, enables digital characterization of caries lesions, providing a data foundation for demineralization assessment, lesion activity evaluation, and AI model development. The management of early caries primarily relies on noninvasive and minimally invasive approaches. Remineralization therapy is suitable for superficial lesions, resin infiltration offers the dual advantages of inhibiting lesion progression and improving aesthetics, and microabrasion and bleaching may serve as adjunctive aesthetic treatments. Emerging modalities such as laser, ozone, and photodynamic therapy have also demonstrated potential. Treatment decision-making should comprehensively consider lesion activity, patient caries risk status, demineralization depth, patient compliance, and treatment preferences. However, precise quantification of demineralization depth remains challenging, and standardized decision-making criteria are still lacking. Follow-up management should be individualized based on risk stratification, with attention to lesion changes, patient compliance, and the risk of recurrence. In summary, intelligent and precision-based approaches are expected to define the future of early caries management, and the application of AI in risk prediction, image analysis, and clinical decision support is anticipated to further enhance the efficiency and effectiveness of early caries diagnosis and treatment.

ObjectiveTo investigate the effect of repetitive peripheral magnetic stimulation (rPMS) combined with upper limb intelligent robotic training on muscle tension, motor function and cortical excitability in children with unilateral spastic cerebral palsy (USCP). MethodsFrom March, 2023 to December, 2024, 90 children with USCP admitted to Children's Hospital of Soochow University were selected and randomly divided into control group (n = 30), rPMS group (n = 30) and combined group (n = 30). The control group received conventional occupational therapy. The rPMS group received rPMS intervention followed by conventional occupational therapy. The combined group received rPMS followed by upper limb intelligent robot training, for four weeks. Before and after treatment, muscle tension of biceps brachii was assessed using the modified Ashworth Scale (MAS); upper limb motor function was evaluated using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and upper limb intelligent parameters; and cortical excitability was measured using transcranial magnetic stimulation (TMS), including resting motor threshold (RMT) and motor-evoked potential (MEP) amplitude of the affected hemisphere. ResultsAfter treatment, MAS grades improved in all groups (|Z| > 3.523, P < 0.001), and the improvement in the combined group was superior to that in the control group (P < 0.05). Significant intra-group (F > 65.21, P < 0.001), inter-group (F > 17.94, P < 0.001) and interaction effects (F > 5.36, P < 0.01) were observed in FMA-UE scores, upper limb intelligent parameters and TMS parameters. Post Hoc analysis showed that the combined group demonstrated significantly greater improvements in FMA-UE scores, upper limb intelligent parameters, and TMS parameters compared with both the control and rPMS groups (all P < 0.01). Except for FMA-UE scores, the rPMS group showed significantly greater improvements than the control group in upper limb intelligent parameters (mechanical feedback, trajectory, and range of motion) and TMS parameters (RMT and MEP amplitude) (P < 0.05). ConclusionrPMS combined with upper limb intelligent robotic training can reduce upper limb muscle tension, improve motor function, and enhance cortical excitability in children with USCP.

Objective:To analyze the clinical characteristics of children with head and neck rhabdomyosarcoma (RMS) and to summarize the mid-long term efficacy of Beijing Children′s Hospital Rhabdomyosarcoma 2006 (BCH-RMS-2006) regimen and China Children′s Cancer Group Rhabdomyosarcoma 2016 (CCCG-RMS-2016) regimen.Methods:A retrospective cohort study. Clinical data of 137 children with newly diagnosed head and neck RMS at Beijing Children′s Hospital, Capital Medical University from March 2013 to December 2021 were collected. Clinical characteristic of patients at disease onset and the therapeutic effects of patients treated with the BCH-RMS-2006 and CCCG-RMS-2016 regimens were compared. The treatments and outcomes of patients with recurrence were also summarized. Survival analysis was performed by Kaplan-Meier method, and Log-Rank test was used for comparison of survival rates between groups.Results:Among 137 patients, there were 80 males (58.4%) and 57 females (41.6%), the age of disease onset was 59 (34, 97) months. The primary site in the orbital, non-orbital non-parameningeal, and parameningeal area were 10 (7.3%), 47 (34.3%), and 80 (58.4%), respectively. Of all patients, 32 cases (23.4%) were treated with the BCH-RMS-2006 regimen and 105 (76.6%) cases were treated with the CCCG-RMS-2016 regimen. The follow-up time for the whole patients was 46 (20, 72) months, and the 5-year progression free survival (PFS) and overall survival (OS) rates for the whole children were (60.4±4.4)% and (69.3±4.0)%, respectively. The 5-year OS rate was higher in the CCCG-RMS-2016 group than in BCH-RMS-2006 group ((73.0±4.5)% vs. (56.6±4.4)%, χ2=4.57, P=0.029). For the parameningeal group, the 5-year OS rate was higher in the CCCG-RMS-2016 group (61 cases) than in BCH-RMS-2006 group (19 cases) ((57.3±7.6)% vs. (32.7±11.8)%, χ2=4.64, P=0.031). For the group with meningeal invasion risk factors, the 5-year OS rate was higher in the CCCG-RMS-2016 group (54 cases) than in BCH-RMS-2006 group (15 cases) ((57.7±7.7)% vs. (30.0±12.3)%, χ2=4.76, P=0.029). Among the 10 cases of orbital RMS, there was no recurrence. In the non-orbital non-parameningeal RMS group (47 cases), there were 13 (27.6%) recurrences, after re-treatment, 7 cases survived. In the parameningeal RMS group (80 cases), there were 40 (50.0%) recurrences, with only 7 cases surviving after re-treatment. Conclusions:The overall prognosis for patients with orbital and non-orbital non-parameningeal RMS is good. However, children with parameningeal RMS have a high recurrence rate, and the effectiveness of re-treatment after recurrence is poor. Compared with the BCH-RMS-2006 regimen, the CCCG-RMS-2016 regimen can improve the treatment efficacy of RMS in the meningeal region.

BACKGROUND:Socket-shield technique can effectively maintain labial soft and hard tissues,but the incidence of postoperative complications such as exposure and displacement of root shield is relatively high.It is speculated that the root shield may be exposed and displaced due to excessive load after long-term function of dental implants. OBJECTIVE:Through three-dimensional finite element analysis,we aim to study the influence of varying root shield thicknesses on the stress distribution,equivalent stress peaks,and displacement in the root shield,periodontal ligaments,implant,and surrounding alveolar bone under normal occlusal loading.We also attempt to analyze the correlation between the thickness of the root shield and occurrence of mechanical events such as root shield exposure,displacement,and fracture. METHODS:Cone-beam CT data of a patient who met the indication standard of socket-shield technique for maxillary central incisor were retrieved from database.Reverse engineering techniques were used to build models of the maxillary bone and root shield,while forward engineering was used to create models for the implant components based on their parameters.Models depicting various root shield thicknesses(0.5,1.0,1.5,and 2.0 mm)were created using Solidworks 2022 software.ANSYS Workbench 2021 software was then used to simulate and analyze the effects of varying root shield thicknesses on stress distribution,equivalent stress peaks,and displacement of the root shields,periodontal ligaments,implants,and surrounding alveolar bone under normal occlusion. RESULTS AND CONCLUSION:(1)In all root shield models,the stress was concentrated on the palatal cervical side,both sides of the edges and the lower edge of the labial side.As the thickness of the root shield increased,the equivalent stress peak and displacement showed a decreasing trend.The 0.5 mm thickness model produced a stress concentration of 176.20 MPa,which exceeded the yield strength(150 MPa)of tooth tissue.(2)The periodontal ligament stress in each group was concentrated in the neck margin and upper region.With the increase of root shield thickness,the equivalent stress peak and displacement of periodontal ligament showed a decreasing trend.(3)Implant stress in all models was concentrated in the neck of the implant and the joint of the implant-repair abutment,and the labial side was more concentrated than the palatal side.With the increase of root shield thickness,the equivalent stress peak of the implant in the model showed an increasing trend.(4)In each group of models,stress of cortical bone concentrated around the neck of the implant and the periphery of the root shield,and the labial side was more concentrated than the palatal side.With the increase of the thickness of the root shield,the equivalent stress peak around the root shield decreased;the peak value of the equivalent stress of the bone around the neck of the implant showed an increasing trend.In the model,the stress of cancellous bone was mainly concentrated around the neck of the lip of the implant,the top of the thread,the root tip and the lower margin of the root shield,and the labial side was more concentrated than the palatal side.With the increase of the thickness of the root shield,the peak value of the equivalent stress of the bone around the root shield in the model showed a decreasing trend.The minimum principal stress of cortical bone in each group of models was concentrated around the neck of the implant,exhibiting a fan-shaped distribution.As the thickness of the root shield increased,the minimum principal stress of cortical bone showed an increasing trend.(5)These results indicate that different thicknesses of the root shield have different biomechanical effects.The root shield with a thickness of 0.5 mm is easy to fracture.For patients with sufficient bone width,the root shield with a thickness of 2.0 mm is an option to reduce the risk of complications such as root shield exposure,fracture,and displacement.Meanwhile,it should be taken into account to protect the periodontal ligament in the preparation process,and rounding treatments ought to be carried out on both sides and the lower edge of the root shield.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

AIM: To evaluate the clinical efficacy of intense pulsed light(IPL)therapy in patients with primary Sjogren's syndrome-related dry eye(SS-DE).METHODS:In this prospective randomized trial, 82 cases(82 eyes)diagnosed with moderate-to-severe SS-DE at our hospital from January 2023 to December 2023 were selected. If both eyes meet the criteria, one eye will be randomly selected for inclusion, and if one eye meets the inclusion criteria, the eye will be selected for enrollment. They were randomly assigned to either an experiment group receiving dextran hydroxypropyl methylcellulose eye drops and 0.05% cyclosporine A eye drops plus IPL therapy, or a control group receiving dextran hydroxypropyl methylcellulose eye drops and 0.05% cyclosporine A eye drops. Ocular surface disease index(OSDI)score, tear meniscus height(TMH), noninvasive tear breakup time(NITBUT), meibomian gland loss score, Schirmer I test(SⅠt), corneal fluorescein staining(CFS)score, conjunctival lissamine green staining(CLGS)score, lipid layer thickness(LLT), blink frequency, corneal Langerhans cell density(CLCD)and complications of both groups were assessed at baseline and at 4, 8, and 12 wk after treatment.RESULTS:There were 6 cases lost to follow-up in the experiment group, with a missing rate of 14.6%, and 1 case was lost to follow-up in the control group, with a missing rate of 2.4%, and valid data were eventually obtained from 35 cases(35 eyes)in the experiment group and 40 cases(40 eyes)in the control group. Baseline parameters did not differ significantly between the two groups of patients(all P>0.05). At 4, 8 and 12 wk after treatment, both groups showed significant reductions in OSDI scores, CFS scores, CLGS score, blink frequency, and CLCD, while the reductions were significantly greater in the experiment group compared to the control group(all P<0.05). The experiment group also demonstrated significant increases in TMH, SⅠt, and NITBUT at 4, 8 and 12 wk after treatment, which were significantly greater than those observed in the control group(all P<0.05). No significant intergroup differences were observed in LLT, meibomian gland loss score in the experiment group at any time point(all P>0.05). Furthermore, no severe ocular or cutaneous complications were associated with IPL treatment.CONCLUSION:IPL significantly improves ocular signs and symptoms, enhances aqueous tear secretion, and reduces ocular surface inflammation in patients with SS-DE, with no significant adverse reactions observed.

Objective To explore the real experiences of nutrition impact symptoms in esophageal cancer patients during diagnosis and treatment,and to provide references for developing nutritional management strategies.Methods Using purposive sampling,15 esophageal cancer patients admitted to the thoracic surgery department of a tertiary grade A hospital in Guangzhou from October to December 2024 were selected for semi-structured interviews.Thematic analysis was used for data analysis.Results 4 themes and 12 sub-themes were identified:①Multiple symptom perceptions:esophageal obstruction-dysphagia,appetite-affecting symptoms,multiple symptom over-lap,and individual differences in symptom perception.② Insufficient symptom cognition:overestimation of symptom controllability and biased symptom attribution.③ Negative emotional reactions:anxiety and fear about eating,frustration with declining eating function,and helplessness and guilt about losing control over eating.④ Di-verse symptom coping strategies:avoidance coping,adaptive coping,and active nutritional management.Conclusion The nutrition impact symptom experiences of esophageal cancer patients are complex and diverse.Healthcare professionals should promptly identify and assess nutrition impact symptoms,provide nutrition health education,strengthen psychological guidance,and develop culturally distinctive individualized nutritional management strategies.

Objective:To develop an artificial intelligence-based model for automated recognition of serum indices using machine vision and deep learning.Methods:This study was a cross-sectional study.Serum sample images were collected fromWest China Hospital of Sichuan University from September 21, 2020 to January 20, 2023 using the imaging device of the fully automated sample pre-processing system. A computer random number generator was used to randomly select one whole hour each day, and all serum sample images processed within that hour were included. After excluding samples with unqualified images and missing serum index results, a total of 5, 534 samples were included. These were divided into a training set and a test set in an 8∶2 ratio using Python random shuffle function, and 4, 458 samples were in the training set and 1, 076 samples were in the test set. After manual inspection, the serum regions were annotated using the MATLAB Image Labeler tool and converted into YOLO format, and a YOLO v5-based model was constructed for automatic serum region extraction. The actual values of lipemia index (L-index), hemolysis index (H-index), and icterus index (I-index) were measured using the automatic biochemical analyzerwith matched reagent kits. A serum index regression model was constructed based on the MobileNet v2 network using the PyTorch 1.10.0 framework. The grading performance of the model was evaluated using accuracy, Kappa coefficient, sensitivity, specificity, positive predictive value, and negative predictive value. Regression performance was assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Bland-Altman analysis.Results:The overall accuracy rates for grading L-index, H-index, and I-index were 98.88%, 95.26%, and 92.47%, respectively, with Kappa coefficients of 0.72, 0.72, and 0.59. For L-index, MAE was 5.11, RMSE was 9.77, and R2 was 0.78. For H-index, MAE was 5.18, RMSE was 8.99, and R2 was 0.89. For I-index, MAE was 1.13, RMSE was 3.01, and R2 was 0.71. Bland-Altman analysis showed that 95.5%, 95.1%, and 95.7% of the data points fell within the consistency intervals for L-index, H-index, and I-index, respectively.Conclusion:The study developed an artificial intelligence-based serum index regression modelto estimate serum indices with high efficiency and accuracy. It shows great potential for reducing laboratory costs, improving clinical testing efficiency, and promoting intelligent development in laboratory medicine.