Based on the theory of blood collateral， postoperative recurrence and metastasis of bladder cancer are considered to arise primarily from the binding of stasis and toxin， which accumulate and hide within the blood collaterals. Accordingly， treatment should focus on clearing and resolving the deeply concealed stasis toxin retained in the blood collaterals. The paired use of insect and vine medicinals may exert synergistic effects by simultaneously searching out and eliminating pathogenic factors， guiding the action of herbs to the channels， and unblocking the collaterals. Drawing on clinical practice， the stasis-toxin pathogenesis of postoperative recurrence and metastasis of bladder cancer can be divided into four stages including stagnation and astringent of collateral qi， formation of fixed stasis nests， transformation of persistent stasis into toxin， and deficiency of healthy qi with lingering toxin. Accordingly， four herb pairs are proposed for each stage based on conventional treatment， which are Dilong （Pheretima）-Daxueteng （Caulis Sargentodoxae）， Shuizhi （Hirudo）-Jixueteng （Caulis Spatholobi）， Wugong （Scolopendra）-Luoshiteng （Caulis Trachelospermi）， and Quanxie （Scorpio）-Qianjinteng （stephania）. Their potential modern pharmacological mechanisms are further discussed.

Objective:To investigate the value of MRI radiomics model in evaluating the pathological complete response (pCR) status of human epidermal growth factor receptor 2(HER-2) positive breast cancer after neoadjuvant therapy.Methods:The study was a cross-sectional study. The clinical, pathological, and MRI data of 243 HER-2 positive breast cancer patients who received neoadjuvant therapy in Shanxi Province Cancer Hospital from January 2021 to June 2023 were retrospectively analyzed. All patients were female, aged 26?75 years. All patients were randomly divided into training set (146 cases) and validation set (97 cases) at a ratio of 6∶4 according to the simple random sampling method. Univariate and multivariate logistic regression were used to screen independent predictors of pCR. Radiomics features were extracted from the early-phase (the 2nd phase) images of breast dynamic contrast-enhanced-MRI after neoadjuvant therapy.The four-step procedure was adopted for feature screening. The radiomics model was constructed by logistic regression. A combined model was constructed by integrating radiomics features and independent predictors. Two radiologists (Reader 1 with 10 years experience and Reader 2 with 13 years experience) who major in breast MRI visually evaluated the pCR status of breast cancer after neoadjuvant therapy. The receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the efficacy of Reader 1, Reader 2, the radiomics model, and the combined model in predicting pCR status. The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the calibration of the model.Results:Among 243 HER-2 positive breast cancer patients, totally 118 achieved pCR. In clinical and pathological features, HER-2 3+ was an independent predictor of pCR ( OR=2.71, 95% CI 1.03?7.12, P=0.043). In the training set and validation set, the AUCs of the radiomics model in predicting pCR status were 0.899 and 0.853, respectively.The AUCs of the combined model were 0.917 and 0.890, respectively. In the validation set, the AUC value of the radiomics model in predicting pCR status was higher than that of Reader 1 and Reader 2. Hosmer-Lemeshow goodness-of-fit test showed that there was no significant difference between the prediction of pCR status by the combined model and radiomics model and the actual results in the training set and validation set, and the fitting was good ( P>0.05). Conclusion:The MRI-based radiomics model can be used to predict pCR status in HER-2 positive breast cancer and outperforms the visual qualitative assessments of radiologists.

Objective:This study aimed to analyze the genetic subtypes and drug resistance transmission characteristics of HIV-1 among the preoperative population in Ningxia from 2018 to 2023, to provide a scientific basis for the prevention and control of the AIDS epidemic.Methods:Plasma samples and demographic information of HIV/AIDS patients receiving antiviral treatment in Ningxia from 2018 to 2023 were collected. Blood samples with a viral loads >200 copies/ml from preoperative testing were amplified, sequenced, and subjected to genotypic resistance testing to analyze their genetic subtypes and drug resistance characteristics. The TN93 model in MEGA11 software was used to calculate the genetic distance between each pair of all sequences, and a molecular transmission network was constructed in Cytoscape 3.10.0 with 1.9% as the genetic threshold.Results:Among 101 preoperative HIV/AIDS patients, CRF07_BC and CRF01_AE were the predominant subtypes. The majority were male (85.15%, 86/101), aged 41-60 years (45.54%, 46/101), residing in Yinchuan city (61.39%, 62/101), and infected via heterosexual transmission (71.29%, 72/101), with most cases being late-detected. Of 39 drug-resistant sequences, resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) alone (18.81%, 19/101) and dual resistance to nucleoside reverse transcriptase inhibitors (NRTIs)-NNRTIs (13.86%, 14/101) were most common. Among 44 sequences forming 13 transmission clusters, nine clusters harbored drug-resistant mutations. Four subtypes entered the molecular network, primarily involving heterosexual transmission, individuals with junior high school education or below, and men aged≥50 years.Conclusions:From 2018 to 2023, the preoperative HIV/AIDS patients had diversified genetic subtypes, with higher rates of overall drug resistance and late detection, stronger drug resistance and higher mortality rate. Strengthening molecular epidemiological research and developing targeted screening strategies are critical to improve early detection and reduce transmission risks.

Objective:To analyze risk factors for immune checkpoint inhibitor-related pneumonitis (CIP) in non-small cell lung cancer (NSCLC) patients based on clinical and radiological characteristics, and to develop and validate a nomogram model for predicting the risk of CIP.Methods:A retrospective case-controlled study was conducted. The clinical data of 159 patients diagnosed with NSCLC in Shanxi Province Cancer Hospital between January 2020 and December 2023 who received immune checkpoint inhibitor (ICI) therapy were retrospectively analyzed. Based on the development of CIP after immunotherapy, the patients were divided into the CIP group (30 cases) and the control group (129 cases). The clinical data of NSCLC patients, hematological indicators and the data of imaging characteristics before their first ICI treatment were collected. Quantitative assessments were performed on pretreatment chest CT images, including lung total tumor volume, number of involved lung segments, and pulmonary infection index. Logistic regression analysis was used to screen out the factors influencing the development of CIP. R 4.3.0 statistical software was used to construct a nomogram model for predicting CIP based on the statistically significant risk factors identified in the multivariate logistic regression analysis. The predictive performance of the model was evaluated by using receiver operating characteristic (ROC) curves and the area under the curve (AUC). Calibration curves and decision curve analysis (DCA) were employed to assess the model's consistency and clinical benefit.Results:There were statistically significant differences in the proportions of patients with a history of chest radiotherapy and those receiving different immunotherapy regimens between the control group and the CIP group (both P < 0.001). The difference in the lactate dehydrogenase (LDH) [ M ( IQR)] between the both groups was statistically significant [211.00 U/L (57.00 U/L) vs. 276.00 U/L (136.00 U/L), Z = -3.41, P < 0.001]; additionally, the difference in lung status score between the 2 groups was statistically significant ( P < 0.001). Multivariate logistic regression analysis revealed that a history of chest radiotherapy (with vs. without: OR = 4.200, 95% CI: 1.466-12.036), the combination of immunotherapy (monotherapy vs. the combined therapy: OR = 0.106, 95% CI: 0.022-0.509), LDH ≥ 255.5 U/L (< 255.5 U/L vs. ≥ 255.5 U/L: OR = 0.988, 95% CI: 0.981-0.995), and severe lung status score(mild vs. moderate vs. severe: OR = 0.187, 95% CI: 0.059-0.593) were independent risk factors for CIP development in NSCLC patients after immunotherapy (all P < 0.05). A nomogram model for predicting CIP occurrence was constructed based on chest radiotherapy history, immunotherapy regimen, LDH, and lung status score. ROC curve analysis showed the AUC was 0.878 (95% CI: 0.813-0.942). The calibration curve demonstrated the good consistency between the predicted risk probability of CIP and the observed outcomes; DCA indicated that the model had favorable clinical benefits. Conclusions:The constructed nomogram prediction model shows a good predictive performance.

To perform the phylogenetic characterization of an isolated porcine rotavirus(PoRV)and investigate its pathogenicity in suckling mice and piglets.A G4P[23]genotype PoRV strain JSJR2023 was successfully isolated from the diarrheic piglet feces through propagation in MA104 cells.The viral proliferation kinetics were analyzed using TCID50 assays,followed by complete genome sequencing through Sanger sequencing platforms.Comprehensive genotyping and phylogenetic reconstruction were conducted using MEGA7.0 with maximum likelihood algorithms.Pathogenicity was assessed in the following animal models:5-day-old C57BL/6 mice and 3-day-old piglets.Multidimensional evaluation included clinical monitoring(diarrhea scoring,growth parameters),virological detection,and histopathological analysis of intestinal tissues.The virus strain JSJR2023 could replicate efficiently in MA104 cells,achieving peak titers of 107.5 TCID50/mL.Whole genome genotype analysis showed that the strain belonged to G4-P[23]-I5-R1-C1-M1-A8-N1-T1-E1-H1.Phylogenetic analysis indicated that the VP3 and NSP4 genes of JSJR2023 strain were most closedrelated to human species rotaviruses,suggesting genetic reassortment between human and porcine RV strains.The animal experiments in suckling mice showed that the JSJR2023 strain infection caused diarrhea symptoms,intestinal edema and congestion,and shedding of intestinal villus epithelial cells.The pathogenicity experiments in piglets showed that compared with the control group,the challenged group of pig-lets had severe diarrhea symptoms,accompanied by reduced appetite and listlessness.Post-mortem examination revealed that the intes-tines were significantly thinner,congested,and filled with yellow watery contents.The challenged piglets showed typical pathological changes such as thinning of the intestinal wall and shortening and shedding of intestinal villi.In conclusion,this study successfully iso-lated a human-porcine recombinant G4P[23]PoRV strain and established the infection models in suckling mice and piglets,providing important tools for investigating the pathogenic mechanism of PoRV,evaluating vaccines and developing antiviral drug.

To perform the phylogenetic characterization of an isolated porcine rotavirus(PoRV)and investigate its pathogenicity in suckling mice and piglets.A G4P[23]genotype PoRV strain JSJR2023 was successfully isolated from the diarrheic piglet feces through propagation in MA104 cells.The viral proliferation kinetics were analyzed using TCID50 assays,followed by complete genome sequencing through Sanger sequencing platforms.Comprehensive genotyping and phylogenetic reconstruction were conducted using MEGA7.0 with maximum likelihood algorithms.Pathogenicity was assessed in the following animal models:5-day-old C57BL/6 mice and 3-day-old piglets.Multidimensional evaluation included clinical monitoring(diarrhea scoring,growth parameters),virological detection,and histopathological analysis of intestinal tissues.The virus strain JSJR2023 could replicate efficiently in MA104 cells,achieving peak titers of 107.5 TCID50/mL.Whole genome genotype analysis showed that the strain belonged to G4-P[23]-I5-R1-C1-M1-A8-N1-T1-E1-H1.Phylogenetic analysis indicated that the VP3 and NSP4 genes of JSJR2023 strain were most closedrelated to human species rotaviruses,suggesting genetic reassortment between human and porcine RV strains.The animal experiments in suckling mice showed that the JSJR2023 strain infection caused diarrhea symptoms,intestinal edema and congestion,and shedding of intestinal villus epithelial cells.The pathogenicity experiments in piglets showed that compared with the control group,the challenged group of pig-lets had severe diarrhea symptoms,accompanied by reduced appetite and listlessness.Post-mortem examination revealed that the intes-tines were significantly thinner,congested,and filled with yellow watery contents.The challenged piglets showed typical pathological changes such as thinning of the intestinal wall and shortening and shedding of intestinal villi.In conclusion,this study successfully iso-lated a human-porcine recombinant G4P[23]PoRV strain and established the infection models in suckling mice and piglets,providing important tools for investigating the pathogenic mechanism of PoRV,evaluating vaccines and developing antiviral drug.

Objective:To investigate the value of MRI radiomics model in evaluating the pathological complete response (pCR) status of human epidermal growth factor receptor 2(HER-2) positive breast cancer after neoadjuvant therapy.Methods:The study was a cross-sectional study. The clinical, pathological, and MRI data of 243 HER-2 positive breast cancer patients who received neoadjuvant therapy in Shanxi Province Cancer Hospital from January 2021 to June 2023 were retrospectively analyzed. All patients were female, aged 26?75 years. All patients were randomly divided into training set (146 cases) and validation set (97 cases) at a ratio of 6∶4 according to the simple random sampling method. Univariate and multivariate logistic regression were used to screen independent predictors of pCR. Radiomics features were extracted from the early-phase (the 2nd phase) images of breast dynamic contrast-enhanced-MRI after neoadjuvant therapy.The four-step procedure was adopted for feature screening. The radiomics model was constructed by logistic regression. A combined model was constructed by integrating radiomics features and independent predictors. Two radiologists (Reader 1 with 10 years experience and Reader 2 with 13 years experience) who major in breast MRI visually evaluated the pCR status of breast cancer after neoadjuvant therapy. The receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the efficacy of Reader 1, Reader 2, the radiomics model, and the combined model in predicting pCR status. The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the calibration of the model.Results:Among 243 HER-2 positive breast cancer patients, totally 118 achieved pCR. In clinical and pathological features, HER-2 3+ was an independent predictor of pCR ( OR=2.71, 95% CI 1.03?7.12, P=0.043). In the training set and validation set, the AUCs of the radiomics model in predicting pCR status were 0.899 and 0.853, respectively.The AUCs of the combined model were 0.917 and 0.890, respectively. In the validation set, the AUC value of the radiomics model in predicting pCR status was higher than that of Reader 1 and Reader 2. Hosmer-Lemeshow goodness-of-fit test showed that there was no significant difference between the prediction of pCR status by the combined model and radiomics model and the actual results in the training set and validation set, and the fitting was good ( P>0.05). Conclusion:The MRI-based radiomics model can be used to predict pCR status in HER-2 positive breast cancer and outperforms the visual qualitative assessments of radiologists.

Objective:This study aimed to analyze the genetic subtypes and drug resistance transmission characteristics of HIV-1 among the preoperative population in Ningxia from 2018 to 2023, to provide a scientific basis for the prevention and control of the AIDS epidemic.Methods:Plasma samples and demographic information of HIV/AIDS patients receiving antiviral treatment in Ningxia from 2018 to 2023 were collected. Blood samples with a viral loads >200 copies/ml from preoperative testing were amplified, sequenced, and subjected to genotypic resistance testing to analyze their genetic subtypes and drug resistance characteristics. The TN93 model in MEGA11 software was used to calculate the genetic distance between each pair of all sequences, and a molecular transmission network was constructed in Cytoscape 3.10.0 with 1.9% as the genetic threshold.Results:Among 101 preoperative HIV/AIDS patients, CRF07_BC and CRF01_AE were the predominant subtypes. The majority were male (85.15%, 86/101), aged 41-60 years (45.54%, 46/101), residing in Yinchuan city (61.39%, 62/101), and infected via heterosexual transmission (71.29%, 72/101), with most cases being late-detected. Of 39 drug-resistant sequences, resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) alone (18.81%, 19/101) and dual resistance to nucleoside reverse transcriptase inhibitors (NRTIs)-NNRTIs (13.86%, 14/101) were most common. Among 44 sequences forming 13 transmission clusters, nine clusters harbored drug-resistant mutations. Four subtypes entered the molecular network, primarily involving heterosexual transmission, individuals with junior high school education or below, and men aged≥50 years.Conclusions:From 2018 to 2023, the preoperative HIV/AIDS patients had diversified genetic subtypes, with higher rates of overall drug resistance and late detection, stronger drug resistance and higher mortality rate. Strengthening molecular epidemiological research and developing targeted screening strategies are critical to improve early detection and reduce transmission risks.

Objective:To analyze risk factors for immune checkpoint inhibitor-related pneumonitis (CIP) in non-small cell lung cancer (NSCLC) patients based on clinical and radiological characteristics, and to develop and validate a nomogram model for predicting the risk of CIP.Methods:A retrospective case-controlled study was conducted. The clinical data of 159 patients diagnosed with NSCLC in Shanxi Province Cancer Hospital between January 2020 and December 2023 who received immune checkpoint inhibitor (ICI) therapy were retrospectively analyzed. Based on the development of CIP after immunotherapy, the patients were divided into the CIP group (30 cases) and the control group (129 cases). The clinical data of NSCLC patients, hematological indicators and the data of imaging characteristics before their first ICI treatment were collected. Quantitative assessments were performed on pretreatment chest CT images, including lung total tumor volume, number of involved lung segments, and pulmonary infection index. Logistic regression analysis was used to screen out the factors influencing the development of CIP. R 4.3.0 statistical software was used to construct a nomogram model for predicting CIP based on the statistically significant risk factors identified in the multivariate logistic regression analysis. The predictive performance of the model was evaluated by using receiver operating characteristic (ROC) curves and the area under the curve (AUC). Calibration curves and decision curve analysis (DCA) were employed to assess the model's consistency and clinical benefit.Results:There were statistically significant differences in the proportions of patients with a history of chest radiotherapy and those receiving different immunotherapy regimens between the control group and the CIP group (both P < 0.001). The difference in the lactate dehydrogenase (LDH) [ M ( IQR)] between the both groups was statistically significant [211.00 U/L (57.00 U/L) vs. 276.00 U/L (136.00 U/L), Z = -3.41, P < 0.001]; additionally, the difference in lung status score between the 2 groups was statistically significant ( P < 0.001). Multivariate logistic regression analysis revealed that a history of chest radiotherapy (with vs. without: OR = 4.200, 95% CI: 1.466-12.036), the combination of immunotherapy (monotherapy vs. the combined therapy: OR = 0.106, 95% CI: 0.022-0.509), LDH ≥ 255.5 U/L (< 255.5 U/L vs. ≥ 255.5 U/L: OR = 0.988, 95% CI: 0.981-0.995), and severe lung status score(mild vs. moderate vs. severe: OR = 0.187, 95% CI: 0.059-0.593) were independent risk factors for CIP development in NSCLC patients after immunotherapy (all P < 0.05). A nomogram model for predicting CIP occurrence was constructed based on chest radiotherapy history, immunotherapy regimen, LDH, and lung status score. ROC curve analysis showed the AUC was 0.878 (95% CI: 0.813-0.942). The calibration curve demonstrated the good consistency between the predicted risk probability of CIP and the observed outcomes; DCA indicated that the model had favorable clinical benefits. Conclusions:The constructed nomogram prediction model shows a good predictive performance.