Objective To evaluate the cost-utility of risdiplam in the treatment of pediatric spinal muscular atrophy （SMA） and analyze changes in patients’ out-of-pocket economic burden under the medical insurance scenarios. Methods A Markov model was developed from the healthcare system perspective to compare the long-term costs and quality-adjusted life years （QALYs） of risdiplam treatment versus conventional therapy. The incremental cost-utility ratio （ICUR） was calculated. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the robustness of the model. On this basis, health insurance scenarios were simulated to evaluate patients’ individual economic burden. Results Base-case analysis showed that risdiplam treatment generated additional health benefits but substantially increased medical costs. The resulting ICUR did not demonstrate a clear cost-utility advantage under the current willingness-to-pay threshold. Sensitivity analyses indicated that the model results were relatively robust, with drug costs and key utility parameters being the main drivers of economic outcomes. Health insurance scenario analysis demonstrated that increasing reimbursement levels and reducing patient copayment rates could significantly alleviate patients’ financial burden. Conclusion Risdiplam for pediatric SMA faces economic challenges under the current health insurance payment framework in China. However, optimizing health insurance reimbursement policies and developing multi-tiered healthcare security mechanisms may improve its affordability and accessibility.

Objective: To examine the association of physical activity with cognitive function and mental health among primary school students based on latent subgroup identification and dose response modeling, and to clarify cognitive-psychological profiles and the protective role of physical exercise, so as to provide evidence based support for physical exercise promoting mental health among primary school students. Methods: A study was conducted among 546 primary school students aged 8-12 years old from a primary school in Shanghai from March to June 2025. Physical fitness indicators, including vital capacity, 50 m sprint, sit and reach, and 1 min rope skipping were measured. Physical exercise was assessed by using the Physical Activity Rating Scale-3 (PARS-3), and mental health was assessed by using the Revised Child Anxiety and Depression Scale, 47-item version (RCADS-47). Cognitive function was assessed by using Stroop, N-back, and task-switching tasks. Latent profile analysis (LPA) was performed for cognitive-psychological health of primary school students based on seven cognitive indicators and six psychological indicators. Multivariable Logistic regression, trend test, and restricted cubic spline (RCS) analysis were used to examine associations between physical exercise and psychological highrisk status. Results: Five cognitive psychological health subgroups were identified:high symptom and impaired cognition group ( n =40, 7.3%), low cognition and low symptom group ( n =108, 19.8% ), and high cognition and high symptom group ( n =110, 20.2%), cognitive advantage and psychologically healthy group ( n = 272, 49.8%), and extremely high symptom and cognitively vulnerable group ( n =16, 2.9%). Among them, the high symptom and impaired-cognition group and extremely high symptom and cognitively vulnerable group were classified as psychologically high risk types. Significant differences were observed across subgroups in psychological symptoms, cognitive function, some physical fitness indicators and physical exercise level, except for body weight, body mass index, and sit and reach ( F =2.64-297.53, all P < 0.05). The results of the multivariate Logistic regression analysis indicated that high level sports, including high total volume of physical exercise, single session duration >30 min, high intensity, and frequency ≥3 times/week, was associated with lower psychological high risk status ( OR =0.20, 0.36, 0.33, 0.40, all P <0.05). Trend analysis showed that total volume of physical exercise and single session exercise duration were negatively associated with psychological high risk status among primary school students ( OR =0.98, 0.79, both P trend <0.05). RCS analysis showed no statistically significant overall or nonlinear association between total volume of physical exercise and psychological high risk status ( χ 2=2.92, 0.01, both P >0.05). Conclusions Cognitive-psychological health among primary school students is heterogeneous. Physical exercise is associated with psychological health improvement and may show a threshold effect, with total volume of physical exercise and single session exercise duration being the key dimensions.

Prescription optimization is a crucial aspect in the study of traditional Chinese medicine （TCM） compounds. In recent years， the introduction of mathematical methods， data mining techniques， and artificial neural networks has provided new tools for elucidating the compatibility rules of TCM compounds. The study of TCM compounds involves numerous variables， including the proportions of different herbs， the specific extraction parts of each ingredient， and the interactions among multiple components. These factors together create a complex nonlinear dose-effect relationship. In this context， it is essential to identify methods that suit the characteristics of TCM compounds and can leverage their advantages for effective application in new drug development. This paper provided a comprehensive review of the cutting-edge optimization experimental design methods applied in recent studies of TCM compound compatibilities. The key technical issues， such as the optimization of source material selection， dosage optimization of compatible herbs， and multi-objective optimization indicators， were discussed. Furthermore， the evaluation methods for component effects were summarized during the optimization process， so as to provide scientific and practical foundations for innovative research in TCM and the development of new drugs based on TCM compounds.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Aim To investigate the effect of Zhenwu decoction on inflammation,oxidative stress and apopto-sis of human glomerular epithelial cells(HGEC)in-duced by lipopolysaccharide(LPS)based on Nrf2/HO-1 signaling pathway,and to explore the underlying mechanism.Methods HGEC were treated with LPS(1.0 mg·L-1)for 24 h to construct an oxidative damage model.On this basis,2.5％,5％and 10％Zhenwu decoction-containing serum were added to the low,medium and high dose groups of Zhenwu decoc-tion,and a normal group was set up.The changes of cell activity were assessed by MTT method and LDH method.The contents of TNF-α,IL-6,IL-10,SOD,CAT,GSH-Px,ROS and MDA in each group were de-tected by ELISA.The apoptosis of each group was de-tected by flow cytometry.The mRNA and protein ex-pressions of Bax,Bcl-2,caspase-3,caspase-9 and Nrf2/HO-1 pathway were detected by RT-qPCR and Western blot,respectively.Results Compared to the normal group,the model group of HGEC exhibited increased levels of inflammatory cytokines,enhanced oxidative stress response and aggravated apoptosis;after inter-vention with various doses of Zhenwu decoction,the in-flammatory levels in HGEC were reduced,oxidative damage and apoptosis were effectively ameliorated,and the mRNA and protein expression levels of the Nrf2/HO-1 signaling pathway were upregulated.Conclu-sions Zhenwu decoction can protect HGEC from LPS-induced inflammation and oxidative damage and im-prove apoptosis.The mechanism may be related to the activation of Nrf2/HO-1 signaling pathway.

Objective:To compare the efficacy and safety of a domestic hair follicle extraction system versus traditional follicular unit excision (FUE) in extracting hair follicles for the treatment of androgenetic alopecia (AGA) .Methods:A multicenter, randomized, self-controlled clinical trial was conducted on AGA patients aged 18 - 59 years who were recruited from the Huashan Hospital, Fudan University, the Affiliated Hangzhou First People's Hospital, and the China-Japan Friendship Hospital between June 2023 and September 2024. Each patient's scalp was randomly divided into two sides (experimental side vs. control side) using an envelope method. The experimental side underwent robotic hair transplantation with a domestic hair follicle extraction system, and the control side underwent traditional FUE. Hair follicles were extracted from the safe donor area in the occipital region, and implanted into the ipsilateral hair loss area. The primary outcome was the hair transection rate which was calculated immediately after follicular extraction. The secondary outcomes included the hair follicle unit loss rate and the change in hair density at the recipient site on postoperative day 14. Safety was evaluated by assessing the incidence of folliculitis at the donor site on postoperative day 14 and the overall incidence of adverse events. Surgical outcomes were evaluated at 9 months after surgery. Comparisons of evaluation indicators among groups were performed by using a paired t test or Wilcoxon signed-rank test. Results:A total of 55 patients with AGA (51 males and 4 females, aged 32.71 ± 5.75 years) completed the hair follicle transplantation and postoperative follow-up. The hair transection rate ( M[ Q1, Q3]) was 6.65% (4.56%, 10.16%) in the experimental group and 5.28% (3.04%, 8.89%) in the control group (difference = 1.24%, 95% CI: -0.24%, 2.65%) . The hair follicle unit loss rate was 2.00% (1.00%, 3.50%) in the experimental group and 0.50% (0, 2.00%) in the control group, with a significant difference between the two groups ( P = 0.008) . On postoperative day 14, there was no significant difference in the hair density between the experimental group and control group (72.20 ± 25.95 per cm 2vs. 76.49 ± 30.84 per cm 2, P = 0.173) . At 9-month follow-up, both groups showed improvement in the investigator's overall score in the recipient areas. Seven adverse events occurred in 7 subjects (12.72%) in each group, and all were mild folliculitis. Conclusion:The domestic hair follicle extraction system demonstrated comparable efficacy and safety to the traditional FUE in hair transplantation.