OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

ObjectiveTo observe the effects of Yangjing Zhongyutang （YJZYT） on mitochondrial biogenesis and oxidative stress damage mediated by the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor gamma coactivator-1alpha （PGC-1α） signaling pathway in cyclophosphamide （CTX）-induced rats with diminished ovarian reserve （DOR）， and to explore its mechanism in improving ovarian reserve function and follicular development. MethodsForty-two 8-week-old female SD rats with normal estrous cycles were randomly divided into a blank control group （n=7） and a model group （n=35）. Rats in the model group received a single intraperitoneal injection of CTX （90 mg·kg^-1） to establish the DOR model. After modeling， estrous cycles were monitored for 7 consecutive days， and model success was confirmed based on criteria for estrous cycle disruption. After successful modeling， rats were divided into groups for intervention： estradiol valerate group （0.09 mg·kg^-1）， and YJZYT high-， medium-， and low-dose groups （19.98， 9.99， 5.00 g·kg^-1）. The blank control group and model group were given an equal volume of distilled water by gavage. All groups received daily gavage once for 4 consecutive weeks. The general state， body weight， and ovarian wet weight of rats were observed and recorded， and the ovarian organ index was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， anti-Müllerian hormone （AMH）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px）. Hematoxylin-eosin （HE） staining was performed to observe ovarian histomorphological changes and follicular development status. Immunofluorescence was used to detect reactive oxygen species （ROS） expression levels. Colorimetric assays were employed to measure adenosine triphosphate （ATP） and malondialdehyde （MDA） content in ovarian tissues. Quantitative Real-time polymerase chain reaction （Real-time PCR） was used to detect mitochondrial DNA （mtDNA） copy number and the mRNA expression levels of key genes including SIRT1， PGC-1α， nuclear respiratory factor 1 （NRF1）， and mitochondrial transcription factor A （TFAM）. Western blot was performed to detect the protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM. ResultsCompared with the blank group， rats in the model group exhibited disrupted estrous cycles， obviously reduced body weight， and decreased ovarian index （P<0.05）. Ovarian histopathology revealed cortical thinning， loose structure， and a significant reduction in both primordial and growing follicles （P<0.01）. Serum FSH and LH levels were significantly elevated （P<0.01）， while E₂ and AMH levels were obviously reduced （P<0.05， P<0.01）. ATP content and mtDNA copy number decreased in ovarian tissue （P<0.01）， ROS expression increased， MDA levels rose， while SOD and GSH-Px activities obviously decreased （P<0.05， P<0.01）， mRNA and protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM were obviously downregulated （P<0.05， P<0.01）. After treatment， compared with the model group， body weight and ovarian index obviously recovered in rats administered various doses of YJZYT （P<0.05）， serum E₂ and AMH levels increased， while FSH and LH levels obviously decreased （P<0.05， P<0.01）， ovarian tissue ATP content and mtDNA copy number were up-regulated， ROS and MDA levels decreased， and antioxidant enzymes SOD and GSH-Px activity obviously increased （P<0.05， P<0.01）， Gene and protein expression levels related to the SIRT1/PGC-1α /NRF1/TFAM signaling pathway were obviously up-regulated compared to the model group （P<0.05， P<0.01）， HE staining revealed that ovarian structure gradually recovered to integrity in all treatment groups， with a obviously increase in the number of primordial and growing follicles （P<0.05， P<0.01）. Granulosa cells were neatly arranged， indicating marked improvement in ovarian function. ConclusionYJZYT may improve ovarian function and follicular development in rats with diminished ovarian reserve by activating the SIRT1/PGC-1α signaling pathway， promoting mitochondrial biogenesis， enhancing mitochondrial function， and alleviating oxidative stress damage.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Objective To explore the biological functions of pyroptosis-related genes in pneumonic plague using bioinformatics methods,and to evaluate their potential applicability as diagnostic markers.Methods The pneumonic plague-related dataset GSE220123 was retrieved from the Gene Expression Omnibus(GEO)database and screened for differentially expressed pyroptosis-related genes(DE-PRGs).The functions of DE-PRGs were studied via Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses,and immune infiltration analysis.The hub genes were identified via protein-protein interaction(PPI)network analysis,and further screened for key genes with sustained high expression characteristics based on differential expression analysis.The relative expression levels of the key genes were verified using the reverse transcription real-time quantitative PCR(qPCR)method.Results A total of 17 DE-PRGs were screened,and PPI network analysis revealed 7 Hub genes.Among them,Casp4 continued to be up-regulated during the course of pneumonic plague.The results of reverse transcription qPCR were consistent with the those of bioinformatic analyses.Conclusion DE-PRGs play a crucial role in the immune response of pneumonic plague,especially Casp4,which has significant applications as a diagnostic biomarker and potential therapeutic target for pneumonic plague.

OBJECTIVE T o compare the biological characteristics,drug resistance and pathogenicity between two strains of mucoid Pseudomonas aeruginosa and the standard strain PAO1.METHODS The strains were identified,and biofilms were detected by 96-well plates method.The bacterial drug resistance was detected by fully automatic drug susceptibility analysis system,the expression levels of RNA of virulence factors were detected by real-time fluorescent quantitative polymerase chain reaction(RT-PCR);the models of rats with pneumonia infection were established through liquid aerosol lung delivery method,the survival status of the rats was observed,and the lev-els of cytokines in bronchoalveolar lavage fluid(BALF)were detected.RESULTS NY4593,NY4605 and PAO1 strains were successfully isolated and identified.NY4593 and NY4605 showed high-yield biofilms,while PAO1 showed low-yield biofilms.The drug resistance rates of NY4593 and NY4605 were remarkably higher than those of the PAO1.The expression levels of exoT and exoY gene RNA of the NY4593 and NY4605 strains were higher than those of the PAO1 strains(P＜0.05);the expression level of exoS gene RNA of the NY4605 was lower than that of the PAO1(P＜0.05).Under the same infection dose,the PAO1 showed more powerful pathogenicity,and the secretion volumes of inflammatory factors interleukin-6(IL-6),interleuki-1β(IL-1β)and interleukin-17A(IL-17A)of the PAO1 were(2858.00±150.30)pg/ml,(7821.00±761.20)pg/ml and(1079.00±225.40)pg/ml respectively,remarkably higher than those of the NY4593 and NY4605(P＜0.05).CONCLUSION The clini-cal mucoid NY4593 and NY4605 remarkably differ from PAO1 in biology and pathogenicity.The study may facilitate deep understanding of the mechanisms of PA infection and provide guidance for clinical treatment,prevention and control.

Objective:To evaluate the clinical efficacy and safety of dupilumab in the treatment of pediatric prurigo nodularis (PN), and to explore factors associated with the treatment response.Methods:A retrospective analysis was conducted on clinical data from 26 children with PN who received dupilumab treatment at the Institute of Dermatology and Venereology, Sichuan Provincial People's Hospital between December 2022 and January 2025. Primary efficacy endpoints were the proportion of patients achieving investigator's global assessment-activity (IGA PN-A) and stage (IGA PN-S) scores of 0/1 at week 8; secondary efficacy endpoints included the proportion of patients achieving a ≥ 4-point reduction in the pruritus numerical rating scale (NRS) and changes in laboratory parameters. Paired t tests or Wilcoxon signed-rank tests were used for pre- and post-treatment comparisons; generalized estimating equation models were applied to evaluate changes in eczema area and severity index (EASI) scores over time; univariate logistic regression analysis was performed to calculate odds ratios ( ORs) and 95% confidence intervals ( CIs) to analyze factors influencing efficacy. Results:Among the 26 children with PN, 14 (53.8%) were males and 12 (46.2%) were females, with ages ( M[ Q1, Q3]) of 4.50 (3.00, 9.25) years and disease duration of 1.00 (0.48, 2.25) years. Twenty-four (92.3%) patients had comorbid atopic diseases, including 17 with allergic rhinitis and 15 with atopic dermatitis (AD). At week 8, IGA PN-A scores decreased from 3.27 ± 0.53 points at baseline to 1.31 ± 0.84 points ( t = 10.44, P < 0.001), with 16 (61.5%) patients achieving IGA PN-A 0/1; IGA PN-S scores decreased from 3.15 ± 0.46 points at baseline to 1.73 ± 0.78 points ( t = 10.33, P < 0.001), with 10 (38.5%) patients achieving IGA PN-S 0/1; pruritus NRS scores decreased from 5.00 (5.00, 6.00) points at baseline to 2.00 (1.00, 3.00) points ( Z = -3.82, P < 0.001), with 10 (38.5%) patients achieving a ≥ 4-point reduction in NRS scores. At week 40, 7 patients who continued treatment achieved complete remission. Univariate logistic regression showed that head/face involvement ( OR = 7.000, 95% CI: 1.200 - 40.829) and disease duration of < 1 year ( OR = 7.000, 95% CI: 1.200 - 40.829) were associated with better treatment response, while baseline IGA scores of 4 points predicted poorer outcomes ( OR = 0.114, 95% CI: 0.017 - 0.742). During treatment, conjunctivitis and local infection occurred in 2 cases without discontinuation, and no serious adverse events occurred in any of the cases. Conclusions:Dupilumab demonstrated rapid and sustained efficacy in pediatric PN with a favorable safety profile. Head/face involvement, shorter disease duration, and lower baseline severity were associated with better treatment response.

Artificial intelligence （AI） and population pharmacokinetics （PPK） technologies have demonstrated significant potential in the personalized medication of immunosuppressants after organ transplantation, enabling precise prediction of drug dosages. This article provides a comprehensive review of the application status of AI and PPK in the individualized administration of immunosuppressants after organ transplantation， focuses on monitoring blood drug concentration， predicting efficacy/adverse reactions， and establishing individualized dosing models for organ transplant recipients after immunosuppressant administration， and analyzes and compares the application characteristics of different methods in different organ transplant patients as well as the integration and future development of AI and PPK technologies. AI and PPK technologies can not only significantly reduce the dependence on human resources， but also greatly improve the level of individualized treatment of immunosuppressants after organ transplantation， and reduce the discomfort and burden caused by frequent blood concentration monitoring to patients.

Glucagon-like peptide-1 （GLP-1） receptor agonists are a novel class of antidiabetic drugs that also possess lipid- lowering and cardiovascular protective effects， with liraglutide and semaglutide being their representative medications. Based on a systematic literature search， this review summarizes the lipid-lowering mechanisms by which liraglutide and semaglutide exert direct effects on the liver and kidney （regulating autophagy， key lipid metabolism pathways， reverse cholesterol transport， etc.）， direct actions on adipose tissue （affecting adipocyte proliferation and differentiation， expression of lipid metabolism proteins， and gene transcription）， activation of sympathetic pathways through the central nervous system， and modulation of the gut microbiota. Additionally， it summarizes the clinical evidence of their lipid-lowering effects in populations with type 2 diabetes mellitus， overweight individuals， and others. These findings indicate that GLP-1 receptor agonists exert lipid-lowering effects by acting on multiple tissues or systems， providing crucial evidence for further elucidating the molecular mechanisms of these drugs in lipid regulation and exploring potential new ideas for their clinical applications.

OBJECTIVE T o compare the biological characteristics,drug resistance and pathogenicity between two strains of mucoid Pseudomonas aeruginosa and the standard strain PAO1.METHODS The strains were identified,and biofilms were detected by 96-well plates method.The bacterial drug resistance was detected by fully automatic drug susceptibility analysis system,the expression levels of RNA of virulence factors were detected by real-time fluorescent quantitative polymerase chain reaction(RT-PCR);the models of rats with pneumonia infection were established through liquid aerosol lung delivery method,the survival status of the rats was observed,and the lev-els of cytokines in bronchoalveolar lavage fluid(BALF)were detected.RESULTS NY4593,NY4605 and PAO1 strains were successfully isolated and identified.NY4593 and NY4605 showed high-yield biofilms,while PAO1 showed low-yield biofilms.The drug resistance rates of NY4593 and NY4605 were remarkably higher than those of the PAO1.The expression levels of exoT and exoY gene RNA of the NY4593 and NY4605 strains were higher than those of the PAO1 strains(P＜0.05);the expression level of exoS gene RNA of the NY4605 was lower than that of the PAO1(P＜0.05).Under the same infection dose,the PAO1 showed more powerful pathogenicity,and the secretion volumes of inflammatory factors interleukin-6(IL-6),interleuki-1β(IL-1β)and interleukin-17A(IL-17A)of the PAO1 were(2858.00±150.30)pg/ml,(7821.00±761.20)pg/ml and(1079.00±225.40)pg/ml respectively,remarkably higher than those of the NY4593 and NY4605(P＜0.05).CONCLUSION The clini-cal mucoid NY4593 and NY4605 remarkably differ from PAO1 in biology and pathogenicity.The study may facilitate deep understanding of the mechanisms of PA infection and provide guidance for clinical treatment,prevention and control.