OBJECTIVE To provide reference for medical institutions to establish the record management mode and review rules of off-label use of 5-aminolevulinic acid （ALA） in photodynamic therapy based on the level of evidence. METHODS All ALA-containing outpatient prescriptions in the rational drug use system in our hospital from January 1， 2024 to December 31， 2025 were retrospectively collected. Based on the drug instructions， the current status of off-label use of ALA in photodynamic therapy was identified . The relevant studies in Micromedex， PubMed， CNKI， Wanfang Data and other databases were systematically searched as the relevant evidence-based evidence of ALA off-label use. According to the Off-label Drug Use Filing Standard of the hospital，the evidence-based evaluation method was used to evaluate the evidence-based evidence of ALA off-label use and carry out hierarchical management. RESULTS A total of 1 803 effective prescriptions were included， of which 676 （37.49%） were off-label use， distributed in the dermatology department （564 prescriptions，83.43%） and the plastic surgery department （112 prescriptions，16.57%）. All 676 prescriptions were off-indications medication， involving ten types of skin diseases， primarily including moderate to severe acne （39.94%）， skin warts （25.44%）， Bowen’s disease （11.98%）， and others. According to evidence-based evidence，off-label uses such as moderate to severe acne， actinic keratosis， and Bowen’s disease were managed according to the evidence categoryⅠ orⅡ.The uses of extramammary Paget’s disease and rosacea were managed according to the evidence category Ⅲ.The uses of lichen sclerosus and keloids were managed according to the evidence category Ⅳ.The results of evidence-based evaluation showed that 92.01% of off-label use in our hospital had high-level evidence-based support （ evidence category was gradeⅠ-Ⅱ）. CONCLUSIONS Off-label uses supported by high-level evidence， such as moderate to severe acne， skin warts， and Bowen’s disease， can be managed under filing category Ⅰ or Ⅱ. For the use of lichen sclerosus and keloids， evidence-based evidence is insufficient and should be strictly restricted.The vast majority of ALA off-label use in our hospital has sufficient evidence-based basis.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveTo systematically identify the main chemical components of Linggui Zhugan granules （LGZGG）， and to explore the pharmacodynamic substance basis for the treatment of metabolic dysfunction-associated steatohepatitis （MASH）. MethodsThe chemical components of LGZGG were systematically analyzed by ultra-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. The protein-protein interaction （PPI） network and "compound prescription-disease-component-target" network were constructed by network target analysis to predict the potential pharmacodynamic substances and core targets of LGZGG in the treatment of MASH. The potential pharmacodynamic substances were enriched by macroporous adsorption resin， and the chemical composition of the LGZGG-50% ethanol elution fraction （LGZGG-50） was analyzed by UPLC-Q-TOF-MS/MS. The mouse model of MASH was established by feeding a high-fat， high-cholesterol， and high-fructose diet for 12 weeks. Mice were randomly allocated into normal， model， positive drug （MGL-3196， 1 mg·kg^-1）， LGZGG （crude drug， 34 g·kg^-1·d^-1）， LGZGG-50 （crude drug， 34 g·kg^-1·d^-1） groups. The levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglyceride （TG）， low-density lipoprotein cholesterol （LDL-C）， and high-density lipoprotein cholesterol （HDL-C） in the serum were measured， and the pathological changes in the liver tissue were observed by hematoxylin-eosin （HE） and Sirius red staining. The in vivo efficacy of LGZGG and LGZGG-50 in the treatment of MASH was evaluated on the basis of the findings. The expression levels of adenosine monophosphate-activated protein kinase （AMPK）， phosphorylated AMPK （p-AMPK）， silent information regulator 2-related enzyme 1 （SIRT1）， peroxisome proliferator-activated receptor α （PPARα）， and carnitine palmitoyltransferase 1A （CPT1A） in the liver tissue were determined by Western blot to verify the regulatory effects of core targets. ResultsA total of 83 chemical components were identified from LGZGG， including 20 flavonoids， 13 terpenoids， 17 organic acids， 7 amino acids， 11 glycosides， 3 nucleosides， 3 aromatics， 3 alkaloids， 2 phenylpropanoids， 2 sugars， 1 nucleic acid， and 1 steroid. A total of 134 common targets were obtained by network target analysis. The core targets included SIRT1， PPARα， nuclear factor-kappa B subunit 1 （NF-κB1）， and interleukin-6 （IL-6）. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis revealed that the targets were mainly enriched in the AMPK， PPAR and other signaling pathways. The topological analysis of the "compound prescription-disease-component-target" network showed that the potential pharmacodynamic substances of LGZGG against MASH were flavonoids and terpenoids. The relative content of flavonoids and terpenes in LGZGG-50 were 74.00% and 62.41% in positive and negative ion modes， respectively， indicating that LGZGG-50 effectively enriched total flavonoids and total terpenoids. The results of in vivo efficacy showed that compared with the model group， LGZGG and LGZGG-50 reducef the body weight， liver weight， serum TG， GLU， and ALT levels of MASH mice （P<0.05，P<0.01）， and LGZGG additionally increased the HDL-C level （P<0.01）. Both groups alleviated the pathological damage in the liver tissue. The results of Western blot showed that compared with the model group， the protein levels of p-AMPK/AMPK， SIRT1， PPARα， and CPT1A were up-regulated in the LGZGG group （P<0.05，P<0.01）， and those of p-AMPK/AMPK and CPT1A were up-regulated in the LGZGG-50 group （P<0.01）. ConclusionLGZGG ameliorates MASH， with the main pharmacodynamic substances being flavonoids and terpenoids. The mechanism may be related to the regulation of AMPK/SIRT1/PPARα signaling pathway， improvement of lipid metabolism， and alleviation of pathological damage in the liver tissue.

ObjectiveTo compare the performance of different automatic evaluation methods for detecting pattern hallucinations generated by large language models （LLMs） in traditional Chinese medicine （TCM） syndrome differentiation and to identify a strategy with higher overall discriminative performance against expert manual judgment. MethodsA standardized TCM syndrome-differentiation dataset containing 598 cases was constructed from case reports published in Chinese core journals indexed by Peking University Core Journals or Chinese Science Citation Database. Each of the 598 cases was submitted to five Chinese LLMs， with each model generating one syndrome-pattern output per case， yielding 2990 outputs in total. The 598 outputs generated by Qwen3-Next-80B-A3B-Thinking were independently annotated for syndrome-pattern hallucinations by two licensed TCM physicians with intermediate or higher professional titles. Disagreements were adjudicated by a third licensed TCM physician with a senior associate professional title and more than 10 years of clinical experience. The resulting consensus annotations served as the reference labels for training and validating the automated evaluation method. Based on these reference labels， three categories of automated evaluation methods were developed and compared following a progressive strategy from text-level semantic similarity， to syndrome-element structural consistency， and finally multi-feature fusion. Method A employed sentence-embedding models based on semantic similarity between pattern texts. Method B adopted a rule-based threshold method using weighted Jaccard coefficients of disease-location and disease-nature syndrome elements. Method C utilized a machine-learning classifier integrating syndrome-element matching scores， missing and redundant syndrome-element counts， and multiple semantic-similarity features. Five-fold cross-validation was used to evaluate the discriminative performance of each method against manual judgment. The optimal method was then applied to uniformly assess the pattern hallucination rates of five LLMs. ResultsIn method A， text2vec-large-chinese showed best overall performance， with an area under the receiver operating characteristic curve （AUROC）， area under the precision-recall curve （PR-AUC）， F1-score， sensitivity， and specificity of 0.849， 0.884， 0.794， 0.801， and 0.691， respectively. In method B， the corresponding metrics of the rule-based syndrome-element Jaccard threshold method were 0.848， 0.851， 0.817， 0.845， and 0.684， respectively； those of the LLM-based syndrome-element Jaccard method were 0.872， 0.906， 0.795， 0.764， and 0.780， respectively. In method C， the multilayer perceptron （MLP） classifier showed the best overall performance， with AUROC， PR-AUC， F1-score， sensitivity， and specificity of 0.933， 0.951， 0.871， 0.857， and 0.846， respectively. Under the unified evaluation framework combining DeepSeek-R1 syndrome-element extraction and MLP classifier， the estimated pattern hallucination rates of the five LLMs ranged from 56.0% to 77.4%. ConclusionAmong the three automatic evaluation methods， Method C integrating syndrome-element discrepancy features and text semantic features using an MLP classifier showed the highest overall discriminative performance against manual judgment， and is more suitable for evaluating syndrome hallucinations in LLM-based TCM syndrome differentiation tasks.

OBJECTIVE To construct and evaluate a perioperative pharmaceutical care model for orthopedic joint replacement based on clinical pharmacy specialty collaboration and medication therapy management （MTM）， so as to provide a reference for improving the level of clinical rational drug use and reducing medical costs.METHODS Patients undergoing orthopedic joint replacement were taken as the research subjects. A specialized collaboration group was established， consisting of the head of the clinical pharmacy group， ward-based clinical pharmacists， and multi-specialty clinical pharmacists. The practice path， service contents，and workflow of MTM for the perioperative period of orthopedic joint replacement were clarified，and a perioperative pharmaceutical care model for orthopedic joint replacement was developed. Data of patients in the orthopedic diagnosis-related groups （DRG）-IC29 group of the department of orthopedics in Daping Hospital，Army Medical University were collected from July 2022 to June 2023 （pre-intervention， 581 cases） and from July 2023 to June 2024 （post-intervention， 843 cases）. The work-implementation indicators in the post-intervention period were counted， and the efficiency indicators and pharmaceutical management indicators were compared between the pre- and post-intervention periods. Meanwhile，200 patients were randomly selected from the pre-intervention and post-intervention groups， respectively， to evaluate the rate of rational medical orders.RESULTS From July 2023 to June 2024， the collaboration group implemented MTM for 843 patients undergoing orthopedic joint replacement via the established perioperative pharmaceutical care model. A total of 1 163 drug‑related problems （DRPs） were identified， and 79 patients with high medication‑related risks were screened out. The most common types of DRPs included （possible） adverse drug events/reactions （48.93%）， unnecessary drug therapy （21.58%）， and ineffective drug therapy （16.25%）. Among the 1 163 DRPs， 895 （76.96%） were completely resolved. Compared with the pre‑intervention period， the post‑intervention period showed reductions in average hospitalization cost per case， average drug cost per case， average length of hospital stay， proportion of drug cost， utilization rate and use intensity of antibacterial agents， and per‑capita drug cost of six main drug categories. The rate of rational medical orders increased from 78.25% to 98.11%.CONCLUSIONS The perioperative pharmaceutical care model for orthopedic joint replacement based on clinical pharmacy specialty collaboration and MTM can help pharmacists identify and resolve DRPs during the perioperative period of orthopedic joint replacement，improve the level of clinical rational drug use，and reduce treatment costs.

Objective:To analyze the risk factors for human cytomegalovirus (HCMV) infection in pediatric recipients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT).Methods:Clinical data of children who underwent first allo-HSCT were retrospectively analyzed from March 2017 to November 2024. A total of 259 pediatric allo-HSCT recipients were analyzed through comparing HCMV infection group (n=115) and Non-HCMV infection group (n=144). Clinical characteristics were compared, and risk factors for HCMV infection were analyzed using univariate and multivariate logistic regression.Results:The result of univariate analysis showed that adrenoleukodystrophy (ALD), length of hospitalization, duration of antiviral therapy, and bacterial infection were significantly associated with HCMV infection in pediatric allo-HSCT recipients ( P<0.05). The result of multivariate analysis showed that ALD was an independent protective factor against HCMV infection of allo-HSCT recipients ( P<0.05) [OR=0.22, 95% CI: 0.06-0.86], while umbilical cord blood transplantation (UCBT) was an independent risk factor for HCMV infection in allo-HSCT recipients ( P<0.05) [OR=6.13, 95% CI: 1.34-28.04]. When the area under the ROC curve (AUC) for predicting post-transplant relapse based on HCMV viral load was 0.75 (95% CI: 0.55-0.94, P=0.014) and at the cutoff value of 3×10 3 copies/ml, the sensitivity and specificity for predicting relapse were 81.13% and 66.67%, respectively. Conclusions:HCMV infection in pediatric allo-HSCT recipients may lead to longer hospitalization and increased risk of relapse.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.

Objective:To evaluate the effectiveness and safety of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in children with stage 4/M neuroblastoma (NB).Methods:This study was a prospective, single-arm, multicenter clinical trial conducted by Sun Yat-sen Memorial Hospital, Children′s Hospital of Nanjing Medical University, Children′s Hospital, Zhejiang University School of Medicine, the First Affiliated Hospital of Guangxi Medical University, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. From March, 2019 to August, 2023, 25 children with confirmed with stage 4/M NB and received allo-HSCT were enrolled. The patients received either unrelated cord blood transplantation (UCBT) or peripheral blood stem cell transplantation (PBSCT). Conditioning regimens for UCBT was fludarabine+busulfan+cyclophosphamide+topotecan, and for PBSCT was fludarabine+busulfan+melphalan+thiotepa+antithymocyte globulin, respectively. Until the last follow-up date of September, 2023, the overall survival (OS) rate and event free survival (EFS) rate were analyzed to evaluate efficacy. The engraftment rate and transplant-related complications were statistically assessed to evaluate safety. Survival analysis was performed using the Kaplan-Meier method.Results:Of the 25 patients, there were 15 males and 10 females. The age at transplantation was 5.7 (3.8, 7.3) years. The engraft rate was 100%, with recovery time of neutrophil as 15.7 (12.5, 17.0) d, and the recovery time of platelets as 33.5 (18.0, 48.0) d. Seventeen of the 25 children (68%) developed acute graft versus host disease (aGVHD), occurred at 18.0 (13.0, 22.5) d after transplantation, including 13 of grade Ⅲ-Ⅳ cases. The main sites of aGVHD were skin and intestinal tract. After treatment, 13 cases improved, 4 patients developed chronic graft-versus-host disease (cGVHD). After allo-HSCT, 14 children received maintenance therapy. Twenty of the 25 patients survived, the 2-year cumulative OS rate was (80±9)%, and 2-year EFS rate was (56±11)%. Nine cases (36%) relapsed, the time from allo-HSCT to disease relapse was 10.9 (5.5, 16.0) months. Five cases (20%) died. The hematopoietic stem cell transplantation associated mortality rate was 4% (1/25).The 2-year OS rate of patients who had partial remission prior to allo-HSCT was significant lower than those who had complete remission prior to allo-HSCT ((33±25)% vs. 100%, P=0.037). Conclusion:allo-HSCT is an effective treatment for patients with stage 4/M NB.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To investigate the value of serum lipoprotein-associated phospholipase A2(Lp-PLA2)for predicting high-risk coronary plaques in elderly males.Methods A retrospective study was conducted on 46 elderly males aged ≥60 years undergoing health check-ups and coro-nary computed tomography angiography in our hospital between May and July 2024.Their general clinical data were collected.Artificial intelligence software was used to analyze coronary calcium scores and plaque characteristics.The participants were divided into a high-risk plaque group(n=15)and a non-high-risk plaque group(n=31).The differences were compared between the two groups.Multivariate logistic regression analysis was used to identify the influencing factors for high-risk coronary plaques.ROC curve was plotted to determine the predictive value of serum Lp-PLA2 for high-risk plaques,and its AUC value was calculated.Results The high-risk plaque group had significantly larger proportions of smoking history and hyperlipidemia,and higher level of homocysteine and Lp-PLA2 than the non-high-risk plaque group(P＜0.05,P＜0.01).Multiva-riate logistic regression analysis indicated that Lp-PLA2 was an independent risk factor for high-risk coronary plaques(HR=1.030,95％CI:1.008-1.053,P＜0.05).ROC curve analysis revealed that the AUC value of Lp-PLA2 in predicting high-risk coronary plaques was 0.833(95％CI:0.694-0.927,P＜0.01),with a sensitivity of 93.3％,a specificity of 71.0％,a positive predictive value of 62.5％,and a negative predictive value of 100％.Conclusion Serum Lp-PLA2 is of signif-icant value in predicting high-risk coronary plaques in elderly men.