ObjectiveTo analyze the characteristics of 150 patients with spinal cord injury complicated with spasticity. MethodsA cross-sectional survey was conducted on 150 patients with spinal cord injury accompanied by spasticity from September, 2019 to December, 2024. Their age, gender, cause of injury, injury site, severity of injury, spasticity severity and other indicators were recorded. The relationships between different characteristics were analyzed, and a correlation analysis of disease duration, spasticity grade, injury level, injury severity and age were conducted. ResultsThere was no significant difference in age distribution between patients with tetraplegia and paraplegia (Z = 0.806, P = 0.420). The proportions of trauma (χ² = 3.982, P = 0.046) and tetraplegia (χ² = 10.559, P = 0.010) were higher in males than in females. Trauma was the main cause of injury in both tetraplegia and paraplegia patients; the proportion of tetraplegia was higher than paraplegia in trauma patients, while paraplegia was higher than tetraplegia in non-trauma patients (χ² = 11.885, P < 0.001). Patients with tetraplegia was dominated by incomplete injury, whereas patients with paraplegia was dominated by complete injury (χ² = 10.885, P = 0.012). Grade A injury was predominant in trauma patients (P = 0.003). Spasticity grade showed a very weak positive correlation with disease duration (r = 0.175, P = 0.032) and age (r = 0.168, P = 0.040). Injury severity showed a very weak positive correlation with age (r = 0.183, P = 0.025). ConclusionCharacteristics of patients with spinal cord injury complicated with spasticity is different with gender, cause of injury, injury level, injury severity.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To explore the application value of three mainstream large language models in the diagnosis, differential diagnosis, and treatment decision support of the primary diseases related to pediatric liver transplantation. Methods Seventy-nine cases of pediatric liver transplantation-related diseases diagnosed through pathological or clinical follow-up data were collected from Renji Hospital, Shanghai Jiao Tong University School of Medicine or published high-quality case reports. These cases covered 25 types of primary diseases such as cholestatic liver disease, metabolic diseases, and tumors. Standardized prompts were used to input the case information into the DeepSeek-R1, ChatGPT-4o and Grok-3 models, and the accuracy of their preliminary diagnosis and differential diagnosis based on basic clinical data was evaluated. The final diagnosis accuracy and the response time after supplementary examination were also assessed, as well as the completeness and rationality of their analysis of disease treatment principles. Results In the initial diagnosis and differential diagnosis stage, the comprehensive accuracy of DeepSeek-R1 was the highest [72.1%, 95% confidence interval (CI) 61.4% - 80.8%], and there was a statistically significant difference in the comprehensive accuracy of the three models for initial diagnosis (P = 0.008). After adding further examination information, the final diagnosis accuracy of the three models increased, with DeepSeek-R1 at 88.6% (95% CI 79.7% - 93.9%), ChatGPT-4o at 87.3% (95% CI 78.2% - 93.0%), and Grok-3 at 78.5% (95% CI 68.2% - 86.1%). There was no statistically significant difference among the three models (P = 0.05). The scores given by experts for the treatment principles showed good consistency (Kappa = 0.769). In addition, the response time of ChatGPT-4o is shorter than that of the other two models [(24 ± 7) s]. Conclusions Large language models demonstrate good efficacy in the diagnosis and treatment decision-making process of various pediatric liver diseases, have a good application prospect for auxiliary diagnosis and decision support, and are expected to help improve the accuracy and efficiency of clinical diagnosis and treatment of pediatric liver transplantation-related primary diseases.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective: To explore a simple, effective, and safe method for excluding false positives and identifying infections by comprehensively evaluating blood donors with reactive HIV screening results, thereby providing a basis for developing management strategies for such donors. Methods: HIV testing data of blood donors from our laboratory from January 2022 to December 2024 were collected. The results of ELISA and nucleic acid testing (NAT) were combined with confirmatory results from the CDC and analyzed. Results: A total of 605 929 samples were tested for HIV over the three-year period, with 682 reactive samples (reactive rate: 11.25 per 10 000). All were sent to the CDC for Western blot (WB) confirmation, resulting in 53 confirmed positives ((confirmed positive rate: 7.77%). Among these, 619 samples showed isolated HIV Ag&Ab reactivity with non-reactive NAT (HIV Ag&Ab+-&HIV RNA or NAT NR), with a confirmed infection rate of 0%; 9 samples showed dual HIV Ag&Ab reactivity with non-reactive NAT (HIV Ag&Ab++&HIV RNA NR or NAT NR), also with 0% confirmed infection; 52 samples showed dual HIV Ag&Ab reactivity and reactive NAT (HIV Ag&Ab++&HIV RNA R or NAT R), all confirmed as positive (100% infection rate); and 2 HIV Ag&Ab dual-reactive samples without NAT detection were also confirmed infected (100%). For all four HIV Ag&Ab assays, the S/CO values in the true positive group with dual reactivity were significantly higher than those in the false-positive groups (P<0.05). The S/CO distributions for both single-reactive false positives and dual-reactive false positives were narrow, with the upper box (Q3, 75th percentile) below optimal cutoff values in all cases (The optimal cutoff values for the four reagents were 5.00, 11.67, 8.50, and 20.90, respectively). Conclusion: Blood donors with positive NAT results in HIV blood screening are permanently deferred. Donors with dual positive HIV Ag&Ab but negative NAT results are classified and managed based on the S/CO values of HIV Ag&Ab and the optimal screening thresholds. Donors with single positive HIV Ag&Ab but negative NAT results are placed under evaluation status and retain their eligibility to donate blood. Optimizing the management measures for blood donors and establishing a scientific stratified management and assessment mechanism can effectively maintain the stability of the blood donor team.

ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

Objective: To fabricate a hydrogel loaded with inositol hexaphosphate-zinc and preliminarily evaluate its performance in self-mineralization and osteoinduction, thereby providing a theoretical basis for the development of bone regeneration materials. Methods: The hydrogel framework (designated DF0) was formed by copolymerizing methacryloyloxyethyltrimethylammonium chloride and four-armed poly(ethylene glycol) acrylate, followed by sequentially loading inositol hexaphosphate anions via electrostatic interaction and zinc ions via chelation. The hydrogel loaded only with inositol hexaphosphate anions was named DF1, while the co-loaded hydrogel was named DF2. The self-mineralization efficacy of the DF0 , DF1 and DF2 hydrogels was characterized using scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and selected area electron diffraction (SAED). The biocompatibility was assessed via live/dead cell staining and a CCK-8 assay. The osteoinductive capacity of the DF0 , DF1 and DF2 hydrogels on MC3T3-E1 cells was assessed via alkaline phosphatase (ALP) and Alizarin Red S (ARS) staining. In the aforementioned cell experiments, cells cultured in standard medium served as the control group Results: The DF0, DF1, and DF2 hydrogels were successfully synthesized. Notably, DF1 and DF2 exhibited distinct self-mineralization within 6 days. Results from TEM, EDS, and SAED confirmed that the mineralization products were amorphous calcium phosphate in group DF1, and amorphous calciumzinc phosphate in group DF2. Biocompatibility tests revealed that none of the hydrogels (DF0, DF1, and DF2) adversely affected cell viability or proliferation. In osteogenic induction experiments, both ALP and ARS staining were intensified in the DF1 and DF2 groups, with the most profound staining observed in the DF2 group. Conclusion The developed inositol hexaphosphate-zinc hydrogel (DF2) demonstrates the dual capacity to generate calcium-phosphate compounds through self-mineralization while exhibiting excellent osteoinductive properties. This biocompatible, dual-promoting osteogenic hydrogel presents a novel strategy for bone regeneration.

OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

In the context of the digital-intelligent era of traditional Chinese medicine （TCM）， the lack of clinical thinking is a pressing issue that limits the overall effectiveness of TCM and talent cultivation. The "disease-pulse-syndrome-treatment differentiation" thinking model， originally developed by ZHANG Zhongjing in the Treatise on Cold Damage and Miscellaneous Diseases （Shang Han Za Bing Lun）， has served as a guideline and paradigm followed by generations of medical practitioners. This study aims to construct a digitalized "disease-pulse-syndrome-treatment differentiation" thinking system， develop a digital assessment system， and implement it for practical application. The goal is to recommend a digitalized assessment model for TCM and provide a reference for the integrated innovation of talent cultivation in medicine， education， and research. First， based on the complex diagnostic and treatment framework of the Treatise on Cold Damage Diseases （Shang Han Lun）， the research team previously established a "process" + "result" thinking model that included four processes and ten steps. This study integrates knowledge unit theory and digital technology to create a digital system for "disease-pulse-syndrome-treatment differentiation" with a dual-control model of "process control" and "result control". The system consists of 46 items across three categories： knowledge body （W=20%）， knowledge element （W=30%）， and knowledge element associations （W=50%）. Second， a mixed-methods research design was employed， combining qualitative and quantitative approaches. The Delphi method was used to establish hierarchical levels and screen items， while the analytic hierarchy process （AHP） was used to assign weights. Expert surveys were conducted to reach a consensus and further validate the rationale and necessity of the system. Finally， based on the system architecture and integrating key computer technologies， a digital assessment system for "disease-pulse-syndrome-treatment differentiation" was developed. The Treatise on Cold Damage Diseases （Shang Han Lun） was used as a case study to validate the system's feasibility. Statistical results showed that the difficulty level of the assessment question bank was moderate （DL ranging from 0.65 to 0.89）， with good discrimination （D>0.4）， and reasonable reliability and validity （Cronbach's α=0.84， KMO=0.72， Bartlett's test P<0.01）. The system can perform process-oriented evaluations of candidates' thinking in "disease-pulse-syndrome-treatment differentiation" and effectively achieve the goal of clinical thinking assessment through a combination of "process control" and "result control". The examination system offers three major advantages. It standardizes， objectifies， and streamlines the assessment of thought processes， facilitates the organic transformation of TCM education from outcome-based education to thinking-based education， and from exam-oriented education to competency-oriented education， and promotes the practical transformation of TCM assessments from qualitative to quantitative evaluation， as well as from theory to practice. In summary， this system not only represents a technological upgrade to traditional examinations but also empowers the cultivation and assessment of clinical talent in the digital-intelligent era， demonstrating broad application prospects.

Dry eye disease(DED)and depression(DEP), though anatomically and clinically distinct, show significant epidemiological, pathophysiological, and prognostic interplay. Their co-occurrence has risen sharply in recent years, yet the mechanisms driving this comorbidity remain under-investigated. This review systematically synthesizes current evidence, highlighting that pro-inflammatory cytokines, neuro-regulatory imbalance, mitochondrial dysfunction, and gut-microbiota dysbiosis constitute a shared molecular network, while sleep deprivation and antidepressant use further amplify the vicious cycle. By identifying limitations in existing studies, this review proposes future research directions to offer new theoretical and clinical insights for managing DED-DEP comorbidity.