Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

Objective To investigate the prevalence of thyroid nodules in the physical examination population in Mianyang region and analyze its association with metabolic syndrome. Methods A retrospective study was conducted on 9 978 individuals who underwent health examinations at our hospital from January 2024 to May 2025. Thyroid examinations were performed using color Doppler ultrasound to analyze the prevalence of thyroid nodules in this population. Clinical data of all subjects were collected, and logistic regression analysis was employed to assess the association between metabolic syndrome and the risk of thyroid nodule development. Results The prevalence of thyroid nodules in the physical examination population of Mianyang region was 17.98% (1 794/9 978). The logistic regression results showed that after adjusting for gender, age, BMI, occupation, consumption of non-iodized salt, staying up late, daily sleep duration, anxiety, and depression, metabolic syndrome (OR=6.593, 95% CI: 3.961-10.975) was associated with thyroid nodules (P<0.05). Conclusion The prevalence of thyroid nodules among the physical examination population in the Mianyang area is 17.98%, and metabolic syndrome remains associated with the risk of thyroid nodules after effectively controlling for confounding factors.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

BackgroundSuicide and self-injury risk in patients with depression disorder is associated with pain symptoms， but the relationships between specific pain types and their severity and distinct self-injury/suicide risk phenotypes remain controversial. ObjectiveTo explore whether somatic pain can reflect different self-injury/suicide risk phenotypes， and to provide references for the clinical identification of suicide and self-injury risk in patients with depression. MethodsBased on data from the National Survey on Symptomatology of Depression （NSSD）， 3 275 patients who met the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders， fourth edition， text revision （DSM-IV-TR） were recruited. According to previous suicidal behavior， suicidal ideation and self-injury behavior in the past two weeks， patients were divided into the no self-injury/suicide risk group， self-injury group， and high suicide-risk group. The occurrence of headache， muscle soreness， trunk pain， limb pain， and other pain symptoms was assessed using the structured symptom assessment instrument of the NSSD. With the no self-injury/suicide risk group as the reference， an ordinal Logistic regression model was used to analyze the associations between the risk groups and the occurrence frequency of pain， with demographic and clinical characteristics entered into the model as covariates for adjustment. ResultsA total of 3 211 patients （98.05%） were included in the analysis， including 1 329 cases （41.39%） in the no self-injury/suicide risk group， 415 cases （12.92%） in the self-injury group， and 1 467 cases （45.69%） in the high suicide-risk group. Compared with the no self-injury/suicide risk group， the occurrence frequencies of headache （OR=1.526， 95% CI： 1.221–1.894） and muscle soreness （OR=1.287， 95% CI： 1.034–1.597） were higher in the self-injury group， and the occurrence frequencies of headache （OR=0.583， 95% CI： 0.504–0.672）， muscle soreness （OR=0.682， 95% CI： 0.597–0.780）， trunk pain （OR=0.557， 95% CI： 0.475–0.634）， limb pain （OR=0.454， 95% CI： 0.384–0.522）， and other pain difficult to localize （OR=0.542， 95% CI： 0.472–0.631） were all lower in the high suicide-risk group. ConclusionPatients with depression disorder across different self-injury and suicide risk phenotypes exhibit distinct pain characteristics， and these differences may provide a reference for the clinical identification of suicide and self-injury risk in patients with depression disorder. ［Funded by The National Key Research and Development Program of China during the "13th Five-Year Plan" period （number， 2016YFC1307100）； Shanghai Key Clinical Specialties Construction Project］

With the rapid development of social economy and the continuous improvement of human living standard, the incidence, fatality and recurrence rates of cardiovascular disease (CVD) are increasing year by year, which seriously affects people's life and health. Conventional therapeutic drugs have limited improvement on the disability rate, so the search for new therapeutic drugs and action targets has become one of the hotspots of current research. In recent years, the therapeutic role of the natural compound rosmarinic acid (RA) in CVD has attracted much attention, which is capable of preventing CVD by modulating multiple signalling pathways and exerting physiological activities such as antioxidant, anti-apoptotic, anti-inflammatory, anti-platelet aggregation, as well as anti-coagulation and endothelial function protection. In this paper, the role of RA in the prevention of CVD is systematically sorted out, and its mechanism of action is summarised and analysed, with a view to providing a scientific basis and important support for the in-depth exploration of the prevention value of RA in CVD and its further development as a prevention drug.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Objective:To summarize the best evidence of volume management in patients with continuous renal replacement therapy, and to provid reference for clinical nursing practice.Methods:Comprehensive search clinical decisions, guidelines, expert consensus, group standards, systematic review and original study on volume management of patients with continuous renal replacement therapy in UpToDate, Cochrane Library, BMJ Best Practice, PubMed, Web of Science, CINAHL, Embase, Joanna Briggs Institute, National Guideline Clearinghouse, National Institute for Health and Clinical Excellence, Guideline International Network, Registered Nurses 'Association of Ontario, French Society of Anaesthesia and Intensive Care, International Society of Nephrology, Yimaitong, Chinese Nursing Association, China National Knowledge Infrastructure, Wanfang and other databases. The retrieval period was from the establishment of the database to April 6, 2024. Literature quality evaluation were conducted independently by researchers who had learned evidence-based nursing research, and the evidence was extracted and integrated.Results:A total of 17 articles were included, comprising 3 clinical decision-making studies, 2 guidelines, 9 expert consensus documents, 1 systematic review, 1 group standard, and 1 randomized controlled trial, and 31 pieces of evidence were summarized from six dimensions: team management, capacity assessment, capacity management objectives, process monitoring, capacity management measures and management of volume related complications.Conclusions:This study summarized the best evidence for the volume management of patients with continuous renal replacement therapy, and provided scientific and standardized basis for the guidance of volume management for clinical medical staff, suggesting that medical staff should selectively apply the best evidence according to the actual clinical situation.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.