ObjectiveTo establish a highly specific and sensitive triplex TaqMan quantitative PCR method for the detection of mouse hepatitis virus (MHV), mouse parvovirus (MPV), and reovirus type 3 (Reo-3) in laboratory mice. MethodsRecombinant plasmid standards were constructed using conserved genomic regions of the three target viruses. Specific primers and probes were designed, and a triplex TaqMan quantitative PCR (qPCR) system was optimized through preliminary experiments. Sensitivity was evaluated using 10-fold serial dilutions (10¹-10⁷ copies/μL). Intra- and inter-assay repeatability were assessed via reproducibility experiments. ResultsA strong linear correlation (R ²>0.99) was observed between copy number and Ct value at template concentrations of 10²-10⁷ copies/μL. Intra-assay and inter-assay coefficients of variation (CV) were both below 5%. No cross-reactivity was observed with mouse cytomegalovirus (MCMV), vesicular stomatitis virus (VSV), Sendai virus (SeV), or pneumonia virus of mice (PVM). ConclusionThe triplex TaqMan quantitative PCR method established in this study has high sensitivity, good repeatability, and strong specificity. It enables the rapid, specific, and sensitive detection of MHV, MPV, and Reo-3, allows the simultaneous detection of multiple pathogens in a single tube, and can be applied to the detection of clinical samples from laboratory animals and to epidemiological investigations, thereby providing effective scientific and technological support for the prevention and control of viral infection and the interruption of transmission.

ObjectiveTo investigate the mechanism by which Wumeiwan suppresses the development and progression of colorectal cancer（CRC） through the regulation of fatty acid metabolic reprogramming， thereby providing new experimental evidence for the prevention and treatment of CRC. MethodsA total of 120 C57BL/6 mice were randomly divided into the blank group， model group， Wumeiwan high-， medium-， and low-dose groups（54， 27， 13.5 g·kg^-1）， and the mesalazine group（0.01 g·kg^-1）， with 20 mice in each group. Except for the blank group， all mice were subjected to azoxymethane（AOM）/dextran sulfate sodium（DSS） treatment to establish an inflammation-associated CRC model. One week after AOM injection， mice in the treatment groups received intragastric administration of the designated drugs， while the blank and model groups received an equal volume of purified water， continuing until 20 d after the intervention endpoint. Hematoxylin-eosin（HE） staining was used to observe colonic histopathological alterations， and immunohistochemistry for vascular endothelial growth factor（VEGF） was performed to evaluate neovascularization and tumor invasion. Metabolomics combined with Kyoto Encyclopedia of Genes and Genomes（KEGG） and metabolite set enrichment analysis（MSEA） was applied to identify key CRC-related metabolic pathways， which were further validated by transcriptomic Gene Ontology（GO） enrichment and gene heatmap analysis. Subsequently， Western blot was performed to determine the expression levels of core proteins in these pathways， and immunofluorescence was used to analyze their localization and co-expression patterns in tissues， thereby elucidating the mechanism of Wumeiwan from multiple biological dimensions. ResultsCompared with the blank group， mice in the model group exhibited a significant decrease in body weight and a significant increase in the disease activity index（DAI） score（P<0.05）， with pronounced colonic mucosal damage accompanied by aggravated tumor invasion. Compared with the model group， Wumeiwan intervention markedly improved body weight loss and reduced DAI score， attenuated mucosal injury， and significantly decreased VEGF expression level（P<0.05）. Multi-omics analysis revealed that differential metabolites and genes across groups were commonly enriched in fatty acid metabolism， fatty acid biosynthesis， and other lipid-related pathways. Relative to the blank group， the model group showed significant upregulation levels of fatty acid synthesis-related genes， including sterol regulatory element-binding protein 1（SREBP1）， fatty acid synthase（FASN）， stearoyl-CoA desaturase 1（SCD1）， as well as saturated fatty acids（P<0.05）. Compared with the model group， treatment with Wumeiwan significantly reduced the expression of key genes involved in fatty acid metabolic pathways， including SREBP1， FASN， and SCD1（P<0.05）. Western blot results further confirmed that proteins in this pathway were significantly elevated in the model group， whereas they were markedly downregulated following Wumeiwan treatment（P<0.05）. Immunofluorescence analysis demonstrated enhanced co-localization of SREBP1 with the cancer-associated fibroblast（CAF） marker α-smooth muscle actin（SMA） in the model group， whereas this co-localization signal was attenuated after Wumeiwan intervention（P<0.05）. ConclusionWumeiwan can improve survival outcomes and alleviate colonic pathological damage in CRC mice， its therapeutic mechanism may be closely associated with the regulation of fatty acid metabolic reprogramming mediated by the SREBP1/FASN/SCD1 signaling pathway.

ObjectiveTo investigate the effects of Huanglian Jiedutang （HLJDT） on cognitive function in mice with ischemic stroke （IS） and to elucidate whether its neuroprotective effects are mediated by inhibition of the nuclear factor-κB （NF-κB） signaling pathway and subsequent suppression of NF-κB-regulated neuronal apoptosis. MethodsAn IS model was established using middle cerebral artery occlusion （MCAO）. Sixty C57BL/6J mice were randomly assigned to five groups （n =12 per group）， i.e.， sham operation， model， HLJDT low-dose （3.9 g·kg^-1·d^-1）， HLJDT high-dose （7.8 g·kg^-1·d^-1）， and Ginkgo biloba extract （GBE， 31.2 mg·kg^-1·d^-1）. Post-operatively， neurological deficit scores （Longa score）， cerebral infarct volume assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining， and brain water content were evaluated. Learning and memory were assessed using new object recognition （NOR） and fear conditioning （FC） tests. Hippocampal pathology was examined via hematoxylin and eosin （HE） staining. Immunofluorescence detected expression of glial fibrillary acidic protein （GFAP， astrocyte marker）， cellular oncogene Fos （c-Fos， neuronal activation marker）， and glutamate decarboxylase 65 （GAD65）. Western blot measured nuclear factor-κB inhibitor protein α （IκBα）， phosphorylated IκBα （p-IκBα）， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， ionic calcium binding adapter molecule 1 （Iba-1）， tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and apoptosis-related proteins， such as cleaved cysteinyl aspartate-specific protease 3 （Caspase-3）， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Real-time quantitative PCR （Real-time PCR） was used to assess mRNA levels of Iba-1， TNF-α， IL-1β， NF-κB p65， cleaved Caspase-3， Bax， and Bcl-2. ResultsCompared with the sham group， the model group exhibited significantly increased neurological deficit scores， brain water content， and cerebral infarct volume （P<0.01）. Hippocampal CA1 neurons were disorganized， showing nuclear pyknosis and karyolysis. NOR exploration time and FC freezing time were significantly reduced （P<0.01）. GFAP and c-Fos expression were increased， while GAD65 expression was decreased （P<0.01）. Cleaved Caspase-3 and Bax were upregulated， Bcl-2 was downregulated， and the Bax/Bcl-2 ratio was elevated （P<0.01）. Expression levels of p-IκBα， p-NF-κB p65， IL-1β， TNF-α， and Iba-1 were significantly increased （P<0.01）. Compared with the model group， HLJDT high-dose， low-dose， and GBE groups showed significant improvements in all parameters （P<0.01）. Among them， the HLJDT high-dose group showed the most pronounced neuronal structural recovery and superior performance in NOR and FC tests （P<0.01）. In this group， GFAP and c-Fos decreased， GAD65 increased （P<0.01）， apoptosis-related protein expression was reversed， and NF-κB signaling and related inflammatory factor expression were suppressed （P<0.01）. ConclusionHLJDT ameliorates cognitive dysfunction in mice after IS， potentially by inhibiting the NF-κB signaling pathway， thereby reducing neuroinflammation and hippocampal neuronal apoptosis.

Objective To explore a method for rapid and differential diagnosis of rejection after kidney transplantation through urine hyperspectral imaging technology. Methods Hyperspectral data information from urine samples of 118 recipients after kidney transplantation was collected, and a deep learning model was constructed to diagnose and classify the types of rejection. Results A deep learning diagnostic model based on the 34-layer residual network (ResNet-34) was constructed, and 118 patients were included and divided into the training set and the test set. Based on the pathological results of the transplanted kidney puncture, the urine samples of the patients were classified into five groups: the non-rejection group, the T-cell-mediated rejection group, the antibody-mediated rejection group, the mixed rejection group and the nephropathy recurrence group. The results showed that the diagnostic sensitivities of the model for the above five groups were 0.960, 0.980, 0.930, 0.940 and 0.943 respectively, and the diagnostic specificities were 0.983, 0.993, 0.997, 0.989 and 0.989 respectively. The overall diagnostic accuracy rate reached 95.7%. Conclusions The study provides a non-invasive, rapid and accurate auxiliary diagnostic method for the differential diagnosis of rejection after kidney transplantation.

Background: s/Aims: The patatin-like phospholipase domain-containing protein 3 (PNPLA3) I148M variant has been implicated in metabolic dysfunction-associated steatotic liver disease (MASLD), but its role in hepatocellular carcinoma (HCC) development is unclear. This study examines the association between the PNPLA3 I148M variant and HCC occurrence. Methods: A total of 562 MASLD patients, with and without HCC, were prospectively and consecutively enrolled at two universityaffiliated hospital between June 2024 and June 2025. Genomic DNA was extracted from buccal swabs or liver biopsy samples, and single nucleotide polymorphism genotyping was performed to determine the rs738409 genotype at codon 148 of PNPLA3. The histological grade of HCC was assessed using the Edmondson-Steiner (ES) grading system in patients who underwent core-needle liver biopsy. Results: Among 474 non-HCC patients, the GG genotype was found in 39.9%, GC in 37.1%, and CC in 23.0%. In 88 HCC patients, these frequencies were 45.5%, 36.4%, and 18.2%, respectively. No significant differences in GG genotype distribution were observed between HCC and non-HCC groups (P=0.509), nor in subgroups by sex, age, obesity status, cirrhosis status, fibrosis-4 index, or liver stiffness measurement. However, among HCC patients with histological grading, the GG genotype was significantly associated with higher ES grades (P=0.0076). Conclusions The PNPLA3 I148M GG genotype was not significantly associated with increased HCC occurrence in Korean MASLD patients within the present cohort. Although the GG genotype is known to play a role in development and progression of MASLD, further studies are warranted to clarify its contribution to tumor initiation and dedifferentiation.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

Objective: To identify the latent classes of acceptance and striving and their associated factors among nursing students, and to examine the mediating role of positive acceptance and striving in the association between self transcendence and subjective well being, so as to provide evidence for targeted interventions to improve subjective well being among nursing students. Methods: From July to October 2025, a convenience sample of 861 nursing students was recruited from five schools in Sichuan and Chongqing, China. Participants were surveyed using the Self transcendence Scale, the Positive Acceptance and Striving Scale, and the General Well being Scale. Latent profile analysis was conducted to identify profiles of positive acceptance and striving. Logistic regression analysis was used to examine associated factors, and relative mediation analysis was performed to assess differences in the mediating effect across latent profiles. Results: Three latent classes of acceptance and striving were identified: the low acceptance-low striving profile (46.34%, n =399), the moderate acceptance-moderate striving profile (40.88%, n =352), and the high acceptance-high striving profile (12.78%, n =110). Multivariable Logistic regression analysis showed that, with the low acceptance-low striving profile as the reference, nursing students with higher self transcendence scores ( OR =151.85) and those who studied nursing because of personal preference ( OR =14.72) or parental expectations ( OR =11.16) were more likely to be classified into the high acceptance-high striving profile (all P <0.05). Male students ( OR =0.19), those perceiving nurses social status as average ( OR =0.35), and those receiving moderate teacher support ( OR =0.23) were less likely to be classified into the high acceptance-high striving profile (all P <0.05). Positive acceptance and striving partially mediated the association between self transcendence and subjective well being, with a total effect of β =0.97 and a mediating effect of β =0.48; the mediating effect accounted for 49.34% of the total effect. Relative mediation analysis showed that the mediating effect was statistically significant only in the low acceptance-low striving profile ( β =0.21), whereas the direct effects were stronger in the moderate acceptance-moderate striving and high acceptance-high striving profiles ( β =0.39, 1.06)(all P <0.05). Conclusions Positive acceptance and striving among nursing students exhibit substantial heterogeneity. Its predictive effect on subjective well being and the underlying mediating mechanism vary across latent profiles. Profile specific interventions should therefore be implemented to improve subjective well being among nursing students.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective:To investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Blonanserin,a second-generation atypical antipsychotic agent,acts as an antagonist for dopamine D2,D3,and serotonin 5-HT2A receptors.Clinical studies have demonstrated that blonanserin is non-inferior to other antipsychotics,such as haloperidol and risperidone,in alleviating the symptoms of schizophrenia.Moreover,it exhib-its beneficial effects on cognitive symptoms and social functioning,with a favorable safety profile,making it one of the key treatment options for schizophrenia.With extensive clinical experience accumulated in China,this expert consensus aims to provide psychiatrists with updated and localized guidance on the optimal use of blonan-serin.Based on a systematic review of the latest evidence-particularly studies in Chinese population,this paper pres-ents the updated Chinese expert recommendations for the clinical use of blonanserin in 2024.