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.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To explore the role of secreted phosphoprotein 1(SPP1)and myeloid differentiation primary response 88(MYD88)in morphine-induced cardiomyocyte apoptosis.Methods A morphine addiction model was established in Sprague-Dawley(SD)rats.Twelve SD rats were randomly assigned to the normal saline(NS)group or the morphine-dependent(DAM)group.Histopathological analysis was employed to observe and compare myocardial tissue morphology between the two groups.Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL)staining was performed to assess the number of apoptotic cells in each group.The expression levels of SPP1 and MYD88 were evaluated using immunohistochemistry.Quantitative real-time poly merase chain reaction(RT-qPCR)and Western blot were used to detect the mRNA and protein expression of SPP1,MYD88,Bax,Bcl2,Caspase-3,and Caspase-9.Simultaneously,Western blot analysis was used to detected the expression of Cleaved Caspase-3 and Cleaved Caspase-9 proteins.In vitro,SPP1 expression was knocked down in primary neonatal rat cardiomyocytes(NRCMs),and cells were divided into three groups:control(CON),morphine treated(DA),and shSPP1#3+DA.Cell viability was assessed using the CCK-8 assay,and apoptosis rates were determined by flow cytometry.Results HE and TUNEL staining of myocardial tissues from morphine-addicted SD rats revealed that,compared with the NS group,myofibrils in the DAM group exhibited partial disruption and a significant increase in apoptotic cells(P<0.05).Western blot and RT-qPCR analyses demonstrated that,relative to the NS group,the mRNA and protein levels of SPP1,MYD88,Bax,Caspase-3,and Caspase-9 were significantly upregulated in the DAM group(P<0.05),whereas Bcl2 expression was significantly downregulated at both mRNA and protein levels(P<0.05),and the protein expression levels of Cleaved Caspase-3 and Cleaved Caspase-9 were also increased.with all differences being statistically significant.In NRCMs following morphine intervention,cell viability in the DA group was markedly reduced compared to the CON group(P<0.05),accompanied by a signifi-cant increase in apoptosis rate(P<0.05).Consistently,Western blot and RT-qPCR results showed elevated mRNA and protein expression of SPP1,MYD88,Bax,Caspase-3,and Caspase-9 in the DA group(P<0.05),along with decreased Bcl2 expression(P<0.05).The protein expression levels of Cleaved Caspase-3 and Cleaved Caspase-9 were elevated simultaneously.In contrast,the shSPP1#3+DA group exhibited opposing trends compared to the DA group,with statistically sig nificant differences(P<0.05).Conclusion SPP1 and MYD88 play critical roles in mediating morphine-induced cardiomyocyte apoptosis,and silencing SPP1 has been shown to significantly reduce the extent of cardiomyocyte apoptosis following morphine exposure.

Aim To explore the mechanism of Lycium barbarum glycopeptide(LbGP)improving aging in rat primary ovarian granulosa cells.Methods This study divided the cells into a normal group,a DOX group,and four different LbGP concentration treatment groups post-DOX intervention.Results Cell proliferation was assessed using CCK-8,EDU,and Ki67 assays,while aging markers and mitochondrial function-related fac-tors were detected using immunofluorescence and West-ern blotting.The results showed that,compared to the DOX group,LbGP treatment significantly increased cell viability(P＜0.05)and promoted proliferation(P＜0.05).Post LbGP treatment,the β-galactosidase-posi-tive area in cells was significantly reduced compared to the DOX group(P＜0.05).Immunofluorescence re-sults indicated that,compared to the DOX group,levels of p21 and γH2AX significantly decreased(P＜0.05),while pRB increased(P＜0.05)after LbGP treatment.Western blot results showed that,compared to the DOX group,the aging phenotype proteins p21 and p53 significantly decreased(P＜0.05),and pRB notably increased(P＜0.05)in the LbGP treatment group.The release of cytC into the cytoplasm and the activated caspase-9 significantly decreased(P＜0.05);levels of CAMKK2,pAMPK,and mitochondrial calcium homeostasis regulator MCU increased(P＜0.05);nuclear energy metabolism-related proteins SirT1,PGC1α/β and ATP5A1 significantly increased(P＜0.05);compared to the DOX group,ROS levels significantly decreased after LbGP treatment(P＜0.05).Conclusions The results suggest that LbGP can ameliorate DOX-induced aging in rat primary ovar-ian granulosa cells,potentially through the upregulation of the CAMKKβ/AMPK signaling pathway,thereby im-proving mitochondrial calcium homeostasis and increas-ing the expression levels of cell energy metabolism-re-lated regulatory proteins.This provides an experimen-tal basis for LbGP's potential role in supporting the im-provement of ovarian function.

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

Objective To explore the efficacy differences between 3 Tesla magnetic resonance imaging with zero echo time(3T MRI ZTE)and high resolution computed tomography(HRCT)in the detection of pulmonary nodules and the classification diagnosis of the lung imaging reporting and data system(Lung-RADS)in sub-health populations.Methods Clinical and imaging data of 93 patients with pulmonary nodules(126 nodules in total)admitted to some hospital from July to December 2023 were retrospectively analyzed.The 126 nodules were categorized into a benign nodule group(n=51)and a malignant nodule group(n=75)using pathological findings as the gold standard.All the patients underwent examinations by 3T MRI ZTE and HRCT to compare the detection rates of the two measures for pulmonary nodules;the missed and misdiagnosis rates of 3T MRI ZTE,HRCT and Lung-RADS grading were contrasted with the postoperative pathological diagnosis results as the gold standard;comparison analyses of 3T MRI ZTE signs and HRCT signs were performed between the two groups and the patients with different Lung-RADS grades;3T MRI ZTE,HRCT and Lung-RADS grading were compared with the receiver operating characteristic(ROC)curve in terms of diagnosis efficacy for pulmonary nodules,and the consistency analysis was carried out.Results No discernible statistical variation was observed in the detection rates of pulmonary nodules between 3T MRI ZTE and HRCT(P>0.05).Lung-RADS grading had the highest rates of missed diagnosis and misdiagnosis,and 3T MRI ZTE and HRCT had similar detection rates.The malignant nodule group was different from the benign nodule group in the 3T MRI ZTE and HRCT signs in terms of lesion size,spiculation sign,lobulation sign,calcifica-tion,pleural indentation sign,cavity sign,boundary and bronchial cut-off sign,with the differences being statistically signi-ficant(all P<0.05).For the patients of Lung-RADS grade 3,the 3T MRI ZTE and HRCT signs had significant differences in terms of lesion size,spiculation sign,lobulation sign,calcification,pleural indentation sign,cavity sign and bronchial cut-off sign(all P<0.05).For the patients of Lung-RADS grade 4A,the 3T MRI ZTE and HRCT signs had significant differen-ces in terms of lesion size,calcification,boundary and bronchial cut-off sign(all P<0.05).For the patients of Lung-RADS grade 4B,the 3T MRI ZTE and HRCT signs had significant differences in terms of lesion size and calcification(all P<0.05).For the patients of Lung-RADS grade 4X,there were no significant differences found between the 3T MRI ZTE and HRCT signs(all P>0.05).HRCT had the highest sensitivity,specificity,accuracy,AUC value,predictive values and Kappa value for benign and malignant nodules,3T MRI ZTE had the values slightly lower than those of HRCT,and Lung-RADS grading had the lowest values when compared with HRCT and 3T MRI ZTE.Conclusion HRCT and 3T MRI ZTE are complementary for the evaluation of pulmonary nodules,and the differences in imaging signs between them show graded dependence.3T MRI ZTE and HRCT have no significant differences in the detection rate of pulmonary nodules,while HRCT gains advanta-ges in differentiating benign and malignant pulmonary nodules,and references are provided for the screening and clinical early diagnosis of pulmonary nodules.[Chinese Medical Equipment Journal,2025,46(9):52-59]

AIM To investigate the effects of Wuzi Yanzong Pills on subacute aging-induced testicular trauma and AMPK/mTOR pathway in rats.METHODS Rat models of subacute aging were induced by 8-week subcutaneous injection of D-gal(200 mg/kg)into the rat neck,followed by their random assignment into the model group,the metformin group(0.3 g/kg)and the low-dose and high-dose Wuzi Yanzong Pills groups(0.54,2.16 g/kg),with 9 rats in each group,in contrast to the 8 intact rats of the normal group.And the corresponding drug was given by gavage for 4 weeks after modeling,after which the rats had their levels of serum T,FSH,SOD,LH,8-OHdG and MDA detected by ELISA;their pathological changes of testes observed by HE and β-galactosidase staining;and their expressions of aging-related proteins(p16,p21,p53),testicle secretory function-related proteins(CYP11A1,HSD17B3,STAR),autophagy-related proteins(p62,ATG5,Beclin-1,LC3B)and AMPK/mTOR pathway-related protein detected by Western blot and immunohistochemistry.RESULTS Compared with the normal group,the model group displayed morphologically smaller testes and body surface;dry hair;overall atrophic testicular tissue structure;increased testicular protein expressions of γ-H2AX,p16,p21 andβ-galactosidase(P＜0.05,P＜0.01);and decreased p53 protein expression(P＜0.05);suggesting the modeling success.Compared with the model group,the high-dose Wuzi Yanzong Pills group shared decreased levels of serum 8-OHdG,MDA,FSH and LH(P＜0.01);increased levels of SOD and T(P＜0.01);improved sperm damage and almost morphologically normal testicular tissue;decreased testicular protein expressions of p16,p21,p53,p62 and p-mTOR(P＜0.01);and increased protein expressions of CYP11A1,HSD17B3,STAR,ATG5,Beclin-1,LC3B and p-AMPK(P＜0.01).CONCLUSION Wuzi Yanzong Pills can improve the subacute aging-induced testicular injury and testicular function in rats by reducing their oxidative stress through improving their autophagy level and testicle antioxidant capacity.