Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

Objective:To investigate the association between peripheral immune function status and lung cancer metastasis,and to identify peripheral blood immune biomarkers for'Deficiency of Vital Qi'assessment in lung cancer metastasis.Methods:A retrospective analysis was conducted on peripheral blood immune markers collected before treatment from lung cancer patients admitted into Shanghai Municipal Hospital of Traditional Chinese Medicine,affiliated to Shanghai University of Traditional Chinese Medicine,between March 2023 and April 2025.Patients were categorized into the non-metastatic and the metastatic groups based on the presence of distant metastasis,and the differences in the expressions of immune cells and cytokines between groups were compared.Peripheral blood immune markers with P<0.05 in univariate analysis were incorporated into a multivariate binary logistic regression model to identify independent predictors of lung cancer metastasis.Results:A total of 193 lung cancer patients were included(101 in the non-metastatic group and 92 in the metastatic group).There were no statistically significant differences between the two groups in terms of gender,age,smoking history,drinking history,or pathological type(all P>0.05).Univariate analysis revealed significant differences in multiple immune markers between the non-metastatic and metastatic groups(all P<0.05),including:lymphocyte count,CD3+,CD4+,and CD8+T,CD19+B cells,absolute counts of CD3-CD16+CD56+NK cells,percentages of Treg cells,CD8+CD28+Treg cells,G-MDSC,and CD3-CD16+CD56+dim NK cells,and levels of cytokine IL-1β,IL-6,and IL-10.Binary logistic regression analysis of differential indicators suggested that the percentage of Treg cells and CD8+CD28+Treg cells in peripheral blood were independent predictors of distant metastasis in lung cancer(OR=1.193,95%CI[1.047,1.36],P<0.01;OR=0.978,95%CI[0.957,0.999],P<0.05).Conclusion:Peripheral blood immune dysfunction is the biological basis for'qi deficiency'in lung cancer metastasis.This study quantitatively demonstrates the correlation between peripheral immune function status and lung cancer metastasis,providing empirical evidence for the theories of'qi deficiency and hidden toxicity'and'metastatic state of tumors'.

Objective To observe the value of multi-sequence magnetic resonance imaging(MRI)radiomics in predicting the efficacy of concurrent chemoradiotherapy(CCRT)in locally advanced cervical squamous cell carcinoma(CSCC)patients.Methods Clinical data of 100 CSCC patients underwent CCRT treatment were selected.In order to better validate the performance of the model,patients were randomly divided into the training set(70 cases)and the validation set(30 cases)in a 7∶3 ratio.According to the efficacy criteria for solid tumors,patients were divided into the complete response(CR)group(n=16)and the partial response(PR)group(n=14).Examination images of cross-sectional DWI,T2WI and enhanced T1WI were collected from all patients before treatment.ITK-SNAP software package combined with three sequences were used to outline ROI,and the open source software PyRadiomics was used to extract image omics features.For MRI omics features,the minimum redundancy maximum correlation(mRMR)algorithm was used to analyze and screen out the first 30 main features,and then the minimum absolute contraction and selection method(Lasso)based on 10-fold cross-validation was used to reduce dimensionality to screen the non-zero coefficient features.According to the weighting coefficient of Lasso-Logistic regression model in the training set,patient omics labels were calculated.Logistic regression analysis was used to construct a prediction model based on DWI,T2WI and T1WI sequence prediction models and multiple sequenomics labels.Receiver operating characteristic(ROC)curves evaluated the predictive value of each omics model for CCRT treatment in patients with locally advanced CSCC.Results There were 38 cases in the CR group and 32 cases in the PR group in the training set.There were 16 cases in the CR group and 14 cases in the PR group in the validation set.There were no significant differences in patient age,FIGO stage,differentiation degree,maximum lesion diameter and menstrual status between the CR group and the PR group in the training and validation sets.A total of 851 imaging features were extracted from the ROI target area.After the first 30 features were retained by mRMR algorithm,3 CR-related features were selected from the 851 imaging omics features of each individual sequence by Lasso algorithm and 10-fold cross-validation.Eight CR related features were selected from 2 553 features after the combination of the three sequences.ROC curve results showed that in the training set and validation set,the AUC of multiple sequences combined to predict the therapeutic effect of CCRT in patients with locally advanced CSCC was 0.971 and 0.946,respectively,which was higher than that of T1WI,T2WI and DWI single sequence prediction(training set Z=2.683,2.046,2.817,P＜0.05;verification set Z=2.075,2.117,2.005,P＜0.05).Conclusion The multi sequence MRI radiomics model has high predictive value for the efficacy of CCRT treatment in locally advanced CSCC patients.

Lung cancer is the malignant tumor with the highest morbidity and mortality. The tumor-node-metastasis (TNM) staging has gradually shown its limitations in the accurate prediction of lung cancer, so it is urgent to construct a new clinical predictive model to guide the prevention and treatment of lung cancer. In recent years, as a comprehensive evaluation system based on peripheral immune related parameters, the value of peripheral immunoscore in the construction of predictive model has gradually become prominent. By quantifying the quantity and proportion of immune components in peripheral blood, the score can dynamically reflect the overall immune function and tumor microenvironment characteristics of the body. This paper systematically summarizes the latest research progress of peripheral immunoscore in early diagnosis, drug efficacy prediction, early warning of adverse reactions and prognosis evaluation of lung cancer, aiming to tap its potential clinical application value and provide some ideas and directions for developing new lung cancer-related predictive models.
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Humans ; Lung Neoplasms/drug therapy* ; Tumor Microenvironment ; Prognosis

Objective To observe the value of multi-sequence magnetic resonance imaging(MRI)radiomics in predicting the efficacy of concurrent chemoradiotherapy(CCRT)in locally advanced cervical squamous cell carcinoma(CSCC)patients.Methods Clinical data of 100 CSCC patients underwent CCRT treatment were selected.In order to better validate the performance of the model,patients were randomly divided into the training set(70 cases)and the validation set(30 cases)in a 7∶3 ratio.According to the efficacy criteria for solid tumors,patients were divided into the complete response(CR)group(n=16)and the partial response(PR)group(n=14).Examination images of cross-sectional DWI,T2WI and enhanced T1WI were collected from all patients before treatment.ITK-SNAP software package combined with three sequences were used to outline ROI,and the open source software PyRadiomics was used to extract image omics features.For MRI omics features,the minimum redundancy maximum correlation(mRMR)algorithm was used to analyze and screen out the first 30 main features,and then the minimum absolute contraction and selection method(Lasso)based on 10-fold cross-validation was used to reduce dimensionality to screen the non-zero coefficient features.According to the weighting coefficient of Lasso-Logistic regression model in the training set,patient omics labels were calculated.Logistic regression analysis was used to construct a prediction model based on DWI,T2WI and T1WI sequence prediction models and multiple sequenomics labels.Receiver operating characteristic(ROC)curves evaluated the predictive value of each omics model for CCRT treatment in patients with locally advanced CSCC.Results There were 38 cases in the CR group and 32 cases in the PR group in the training set.There were 16 cases in the CR group and 14 cases in the PR group in the validation set.There were no significant differences in patient age,FIGO stage,differentiation degree,maximum lesion diameter and menstrual status between the CR group and the PR group in the training and validation sets.A total of 851 imaging features were extracted from the ROI target area.After the first 30 features were retained by mRMR algorithm,3 CR-related features were selected from the 851 imaging omics features of each individual sequence by Lasso algorithm and 10-fold cross-validation.Eight CR related features were selected from 2 553 features after the combination of the three sequences.ROC curve results showed that in the training set and validation set,the AUC of multiple sequences combined to predict the therapeutic effect of CCRT in patients with locally advanced CSCC was 0.971 and 0.946,respectively,which was higher than that of T1WI,T2WI and DWI single sequence prediction(training set Z=2.683,2.046,2.817,P＜0.05;verification set Z=2.075,2.117,2.005,P＜0.05).Conclusion The multi sequence MRI radiomics model has high predictive value for the efficacy of CCRT treatment in locally advanced CSCC patients.

In order to study whether there is a direct interaction between the key variant gene(AP-PV-YN-Mut)protein of atypical porcine pestivirus(APPV)Yunnan strain and the host protein signal sequence receptor subunit 4(SSR4),the physical and chemical properties,spatial structure and subcellular localization of SSR4 protein were analyzed and predicted using online software such as ProtParam,PredictProtein and TMHMM.The recombinant vectors pCMV-Tag4A-SSR4 and pET-GST-Mut were constructed for GST pull-down test in vitro.The recombinant vectors pBiFC-VN173-SSR4 and pBiFC-VC155-Mut were constructed and the bimolecular fluorescence comple-mentary test(BiFC)was performed in cells to verify whether there was direct interaction between APPV-YN-Mut and host protein SSR4 in vitro and in cells.The results showed that SSR4 protein was a hydrophobic stable protein with no transmembrane structure and signal peptide.The second-ary structure was mainly irregular curl,and the tertiary structure was stable,mainly located in the endoplasmic reticulum.GST pull-down and BiFC experiments showed that APPV-YN-Mut interac-ted directly with host protein SSR4 in vitro and in cells.

In order to study whether there is a direct interaction between the key variant gene(AP-PV-YN-Mut)protein of atypical porcine pestivirus(APPV)Yunnan strain and the host protein signal sequence receptor subunit 4(SSR4),the physical and chemical properties,spatial structure and subcellular localization of SSR4 protein were analyzed and predicted using online software such as ProtParam,PredictProtein and TMHMM.The recombinant vectors pCMV-Tag4A-SSR4 and pET-GST-Mut were constructed for GST pull-down test in vitro.The recombinant vectors pBiFC-VN173-SSR4 and pBiFC-VC155-Mut were constructed and the bimolecular fluorescence comple-mentary test(BiFC)was performed in cells to verify whether there was direct interaction between APPV-YN-Mut and host protein SSR4 in vitro and in cells.The results showed that SSR4 protein was a hydrophobic stable protein with no transmembrane structure and signal peptide.The second-ary structure was mainly irregular curl,and the tertiary structure was stable,mainly located in the endoplasmic reticulum.GST pull-down and BiFC experiments showed that APPV-YN-Mut interac-ted directly with host protein SSR4 in vitro and in cells.

Porcine reproductive and respiratory syndrome is caused by the PRRS virus(PRRSV), which has six structural proteins(GP2, GP3, GP4, GP5, M and N). GP5 and N protein are important targets for serological detection by enzyme-linked immunosorbent assay(ELISA)and other methods. Toward this goal, we developed an indirect ELISA with recombinant GP5 antigens and this method was validated by comparison to the LSI PRRSV-Ab ELISA kit. The results indicated that the optimal concentration of coated recombinant antigen was 0.2 μg/well for a serum dilution of 1:40. The rate of agreement with the LSI PRRSV-Ab kit was 88.7%(266/300). These results support the potential use of recombinant GP5 as an antigen for indirect ELISA to detect PRRSV antibodies in pigs.

In this study,a panel of monoclonal antibodies (mAbs) against Porcine reproductive and respiratory syndrome virus(PRRSV),named as 8C9 and4B4,were produced by fusing SP2/0 myeloma cells and spleen cells of BALB/c mice immunized with the PRRSV (TCID50=5.5),screened by the indirect ELISA and subjected to several limiting dilutions.mAbs were then identified by biological characterization.Among the two fusion cell strains,8C9 belonged to the IgG1 subclass and 4B4 belonged to the IgG2a subclass.The titers in cell culture supernatant and abdomen liquor reached to 1:104and 1:105,respectively.The specificity test indicated that the two cells had specific reactions for the PRRSV and GP5 protein respectively,and no reaction with Classical swine fever virus (CSFV) or Swine vesicular disease virus (SVDV).The molecular weights of the heavy chain and light chain were about 45.0 kDa and 25.0 kDa,respectively.In neutralization activity tests,the results showed that the prepared mAb 4B4 can protect 50% of cells with no CPE in dilution up to 1:512,but mAB 8C9 has no neutralization activities to PRRSV.

VP1, a capsid protein of swine vesicular disease virus, was cloned from the SVDV HK/70 strain and inserted into retroviral vector pBABE puro, and expressed in PK15 cells by an retroviral expression system. The ability of the VP1 protein to induce an immune response was then evaluated in guinea pigs. Western blot and ELISA results indicated that the VP1 protein can be recognized by SVDV positive serum, Furthermore,anti-SVDV specific antibodies and lymphocyte proliferation were elicited and increased by VP1 protein after vaccination. These results encourage further work towards the development of a vaccine against SVDV infection.