Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

ObjectiveTo investigate the potential machanism of Xiaozhong Zhitong Mixture （消肿止痛合剂， XZM） in the treatment of diabetes foot ulcer （DFU）. MethodsFifty SD rats were randomly divided into blank group， model group， XZM group， inhibitor group， XZM plus inhibitor group （combination group）， with 10 rats in each group. Except for the blank group， rats were fed with high-sugar， high-fat， high-cholesterol diet， intraperitoneally injected with streptozotocin， and subjected to skin defect to establish DFU model. After successful modeling， the XZM group and the combination group were given 1 ml/（100 g·d）of XZM by gavage， while the blank group， model group， and inhibitor group were all given an equal volume of 0.9% sodium chloride injection by gavage. Thirty minutes later， the inhibitor group and the combination group were intraperitoneally injected with 5 mg/（kg·d） of Notch1 inhibitor DAPT. All groups were treated once a day. After 14 days of administration， the skin tissue from the dorsal foot of the blank group rats and wound tissue from the other groups were collected. The pathological changes of granulation tissue in the wound were detected using hematoxylin eosin （HE） staining. The microvascular density （MVD） in wounds was detected through immunohistochemical staining. Real time fluorescence quantitative polymerase chain reaction （RT-PCR） and western blotting were used to detect the mRNA and protein levels of Notch1 homolog （Notch1）， Delta-like ligand 4 （Dll4）， Delta-like ligand 4 （VEGF）， and angiopoietin 2 （Ang-2）， respectively. ResultsHistological results showed that the epidermal structure in the dorsal foot skin tissue of the rats in the blank group was intact. In the wound tissue of the model group， the epidermis exhibited excessive keratinization， vacuolar cytoplasm， and a large number of inflammatory cells infiltrating the tissue， while in the XZM group， a large amount of scab formation was observed in the epidermis， with no significant inflammatory cell infiltration and a noticeable increase in fibroblasts. In the combination group and the inhibitor group， partial epidermal scab formation was observed in the wound tissue with a small amount of inflammatory cell infiltration. Compared to those in the blank group， the MVD in the wound tissue increased in the model group， as well as the mRNA expression and protein levels of Notch1 and Dll4， while VEGFA and Ang-2 mRNA expression and protein levels significantly decreased （P＜0.05 or P＜0.01）. Compared to those in the model group， the MVD in the wound tissue of all medication groups significantly increased， and the mRNA and protein levels of Notch1 and Dll4 decreased， while VEGFA and Ang-2 mRNA expression and protein levels increased （P＜0.05 or P＜0.01）. Compared to the XZM group， the inhibitor group and the combination group showed decreased MVD in wound tissue， increased Notch1 and Dll4 mRNA and protein levels， and decreased expression of VEGFA and Ang-2 mRNA and proteins （P＜0.05 or P＜0.01）. ConclusionXZM can effectively promote wound healing in DFU rats， and its mechanism of action may be related to the inhibition of Dll4/Notch1 signaling pathway in the wound tissue， therey promoting angiogenesis.

Fifty whitespotted bamboo sharks (Chiloscyllium playgiosum) of both sexes were used to establish a large capacity variable domain of the new antigen receptor (VNAR) library with a total capacity of over 10⁹ colony-forming units (CFU). It was applied to screen VNARs against human serum albumin (HSA) and human transcription factor EB (TFEB), respectively. Meanwhile, VNAR libraries specific to HSA and TFEB with capacities above 10⁸ CFU were obtained following conventional immunization. These two approaches were systematically studied in terms of VNAR yield and composition. By comparing the VNAR sequences obtained from naïve and antigen-immunized libraries, we found that the complementary-determining region 3 (CDR3) of the former differs in composition from that of the latter. It shares a higher degree of homology with the naïve library. Meanwhile, the binding efficiency assessed by ELISA is also different between the naïve and antigen-immunized libraries. The binding of VNARs from the TFEB-immunized library appeared to surpass that observed with the naïve libraries, whereas the performance of VNARs from the HSA-immunized library indicated that both the immunized and naïve libraries for HSA had positive binding responses in polyclonal and monoclonal ELISA. The results are useful to develop novel diagnostic and therapeutic products based on shark VNARs.

Objective Hepatitis C is a kind of infectious disease with great harm and strong concealment.Accurate trend prediction is an important measure to ensure accurate intervention.This paper aims to confirm the effectiveness of multivariate time series prediction method and Internet data and provide a better data and method basis for hepatitis C prediction.Methods The data of the monthly incidence of hepatitis C in Chongqing from 2011 to 2018 were included,including infectious disease incidence data and Internet prediction data.To screen important features,this paper introduces the theoretical basis of feature entropy,and proposes an adaptive correlation entropy weight method(ACEW)for feature selection through the steps of collinearity removal,directional evaluation and information content evaluation.After that,this paper constructed a multivariate time series model(CNN-BILLSTM-Attention)and carried out the characteristic performance test(including prospective evaluation and posterior evaluation)and model efficiency exploration.Results Prospective evaluation revealed that the variables selected by ACEW had low consistency with each other,and the weight distribution calculated by each variable was relatively equal.The posterior evaluation revealed that the feature set screened by ACEW could obtain the best prediction information in each model.In the exploration of model effectiveness,the overall performance of multivariate time series prediction model is significantly better than that of univariate model.When ACEW and CNN-BILSTM-Attention are combined,the MSE,MAE,RMSE,MAPE and R2 on the test set are 0.0223,0.0649,0.0771,5.9285 and 0.9156,respectively.Conclusion In the study of predicting the incidence of hepatitis C,data fusion and method improvement are studied in this paper.The improved feature selection method(ACEW)can provide an opportunity for the regulation of hepatitis C,and the multivariate time series prediction model can improve the performance of hepatitis C trend prediction,to effectively control and prevent hepatitis C,which has better public health prevention and control significance.

Objective To investigate the predictive value of integrating clinical pathological characteristics with genetic testing for occult lymph node metastasis(OLNM)in patients with papillary thyroid microcarcinoma(PTMC).Methods A total of 104 PTMC patients admitted to our hospital between May 2023 and May 2025 were included in the study.All patients showed no evidence of suspicious lymph node metastasis on preoperative imaging and underwent standard thyroidectomy with central lymph node dissection.Based on postoperative pathological con-firmation of central lymph node metastasis status,patients were classified into an OLNM-positive group(n=53)and an OLNM-negative group(n=51).Baseline characteristics,clinicopathological features,BRAFV600E gene mutation status,and TERT promoter mutation status were compared between the two groups.To identify factors independently associated with OLNM in PTMC patients,multivariate logistic regression analysis was conducted.The area under the receiver operating characteristic curve(AUC)was utilized to assess the predictive performance of a combined model incorporating clinical,pathological,and genetic features for OLNM.Results Compared with the OLNM-negative group,the OLNM-positive group exhibited significantly higher preoperative thyroid-stimulating hormone(TSH)levels(P<0.05).Moreover,the OLNM-positive group demonstrated significantly greater proportions of tumors with diameter>0.5 cm,multifocality,microcalcifications,capsule invasion,extrathyroidal extension,T3 stage,BRAFV600E mutation,and TERT promoter mutation(all P<0.05).Multivariate logistic regression analysis identified preoperative TSH level,tumor diameter>0.5 cm,multifocal lesions,capsule invasion,extrathyroidal extension,T stage,BRAFV600E mutation,and TERT promoter mutation as independent risk factors for OLNM in patients with PTMC(all P<0.05).ROC curve analysis demonstrated that the integrated model combining clinical pathological features-including tumor diameter,number of lesions,microcalcification,capsule invasion,extrathy-roidal extension,and T stage-with genetic markers(BRAFV600E and TERT promoter mutations)exhibited the highest predictive performance,yielding an AUC of 0.940.This was significantly higher than the model based solely on clinical pathological features(AUC=0.736)or those relying exclusively on genetic testing(BRAFV600E:AUC=0.860;TERT:AUC=0.882),with all comparisons reaching statistical significance(P<0.05).Conclusions The integration of clinical pathological features with genetic testing significantly improved the predictive accuracy of OLNM in PTMC patients,surpassing models based solely on individual clinical pathological characteristics or genetic tests alone.This multimodal strategy offers a robust,evidence-based foundation for personalized surgical planning and enhances the precision of clinical decision-making in the management of PTMC.

Objective:To investigate the association of regulatory T cell (Treg) levels in peripheral blood with bronchopulmonary dysplasia (BPD) in preterm infants and its predictive value for BPD.Methods:In this case-control study, a total of 102 infants with gestational age ≤32 weeks who were hospitalized in the Neonatal Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical University from April 2022 to April 2024 were included.They were divided into a BPD group (31 cases) and a non-BPD group (71 cases) based on the diagnostic criteria of BPD.Peripheral blood samples were collected on 0 day, 7 days, 14 days, 21 days and 28 days after birth.Differences in Treg levels between the 2 groups and the relationship between Treg levels and BPD were analyzed.The independent sample t test or χ2 test was used to analyze differences between the 2 groups.One-Way ANOVA was used to compare data between groups.Multivariate Logistic regression was used to analyze the risk factors of BPD.The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of Treg levels on 7 days after birth for early diagnosis of BPD. Results:Gestational age[(28.1±1.4) weeks vs.(30.9±1.0) weeks], birth weight[(1 024±243) g vs.(1 301±188) g], Apgar score at 1 minute after birth[(4.3±1.9) points vs.(7.8±1.9) points], Apgar score at 5 minutes after birth[(7.2±1.7) points vs.(9.1±1.3) points], proportion of invasive mechanical ventilation time ≥7 days [87.1%(27/31) vs.45.1%(32/71)] and oxygen inhalation time[(45.1±11.7) days vs.(19.7±7.3) days] were statistically significantly different between BPD and non-BPD groups (all P<0.05).The Treg level in the peripheral blood of preterm infants increased first and then decreased after birth, with the peak observed on 7 days after birth.On 7 days after birth, the BPD group had a significantly higher Treg level than the non-BPD group[(10.4±1.2)% vs.(8.7±1.7)%] ( P<0.05).The multivariate Logistic regression analysis showed increased Treg levels in peripheral blood on 7 days after birth ( OR=3.320, 95% CI: 1.057-10.427, P=0.040), gestational age ( OR=0.040, 95% CI: 0.003-0.446, P=0.009), invasive mechanical ventilation time ≥7 days ( OR=4.126, 95% CI: 1.301-14.125, P=0.002), and oxygen inhalation time ( OR=1.716, 95% CI: 1.317-3.933, P=0.041) were risk factors of BPD in preterm infants.The ROC curve analysis showed that the area under the curve of Treg levels on 7 days after birth for BPD prediction was 0.794, the best cut-off value was 9.35%, the sensitivity was 90.3%, and the specificity was 66.2%. Conclusions:Treg levels in the peripheral blood of preterm infants increase first and then decrease in the early stage after birth, peaking at 7 days after birth.Elevated Treg levels at 7 days after birth may have early predictive value for the occurrence of BPD in preterm infants.

Objective Hepatitis C is a kind of infectious disease with great harm and strong concealment.Accurate trend prediction is an important measure to ensure accurate intervention.This paper aims to confirm the effectiveness of multivariate time series prediction method and Internet data and provide a better data and method basis for hepatitis C prediction.Methods The data of the monthly incidence of hepatitis C in Chongqing from 2011 to 2018 were included,including infectious disease incidence data and Internet prediction data.To screen important features,this paper introduces the theoretical basis of feature entropy,and proposes an adaptive correlation entropy weight method(ACEW)for feature selection through the steps of collinearity removal,directional evaluation and information content evaluation.After that,this paper constructed a multivariate time series model(CNN-BILLSTM-Attention)and carried out the characteristic performance test(including prospective evaluation and posterior evaluation)and model efficiency exploration.Results Prospective evaluation revealed that the variables selected by ACEW had low consistency with each other,and the weight distribution calculated by each variable was relatively equal.The posterior evaluation revealed that the feature set screened by ACEW could obtain the best prediction information in each model.In the exploration of model effectiveness,the overall performance of multivariate time series prediction model is significantly better than that of univariate model.When ACEW and CNN-BILSTM-Attention are combined,the MSE,MAE,RMSE,MAPE and R2 on the test set are 0.0223,0.0649,0.0771,5.9285 and 0.9156,respectively.Conclusion In the study of predicting the incidence of hepatitis C,data fusion and method improvement are studied in this paper.The improved feature selection method(ACEW)can provide an opportunity for the regulation of hepatitis C,and the multivariate time series prediction model can improve the performance of hepatitis C trend prediction,to effectively control and prevent hepatitis C,which has better public health prevention and control significance.

Objective To investigate the predictive value of integrating clinical pathological characteristics with genetic testing for occult lymph node metastasis(OLNM)in patients with papillary thyroid microcarcinoma(PTMC).Methods A total of 104 PTMC patients admitted to our hospital between May 2023 and May 2025 were included in the study.All patients showed no evidence of suspicious lymph node metastasis on preoperative imaging and underwent standard thyroidectomy with central lymph node dissection.Based on postoperative pathological con-firmation of central lymph node metastasis status,patients were classified into an OLNM-positive group(n=53)and an OLNM-negative group(n=51).Baseline characteristics,clinicopathological features,BRAFV600E gene mutation status,and TERT promoter mutation status were compared between the two groups.To identify factors independently associated with OLNM in PTMC patients,multivariate logistic regression analysis was conducted.The area under the receiver operating characteristic curve(AUC)was utilized to assess the predictive performance of a combined model incorporating clinical,pathological,and genetic features for OLNM.Results Compared with the OLNM-negative group,the OLNM-positive group exhibited significantly higher preoperative thyroid-stimulating hormone(TSH)levels(P<0.05).Moreover,the OLNM-positive group demonstrated significantly greater proportions of tumors with diameter>0.5 cm,multifocality,microcalcifications,capsule invasion,extrathyroidal extension,T3 stage,BRAFV600E mutation,and TERT promoter mutation(all P<0.05).Multivariate logistic regression analysis identified preoperative TSH level,tumor diameter>0.5 cm,multifocal lesions,capsule invasion,extrathyroidal extension,T stage,BRAFV600E mutation,and TERT promoter mutation as independent risk factors for OLNM in patients with PTMC(all P<0.05).ROC curve analysis demonstrated that the integrated model combining clinical pathological features-including tumor diameter,number of lesions,microcalcification,capsule invasion,extrathy-roidal extension,and T stage-with genetic markers(BRAFV600E and TERT promoter mutations)exhibited the highest predictive performance,yielding an AUC of 0.940.This was significantly higher than the model based solely on clinical pathological features(AUC=0.736)or those relying exclusively on genetic testing(BRAFV600E:AUC=0.860;TERT:AUC=0.882),with all comparisons reaching statistical significance(P<0.05).Conclusions The integration of clinical pathological features with genetic testing significantly improved the predictive accuracy of OLNM in PTMC patients,surpassing models based solely on individual clinical pathological characteristics or genetic tests alone.This multimodal strategy offers a robust,evidence-based foundation for personalized surgical planning and enhances the precision of clinical decision-making in the management of PTMC.

Objective:To investigate the association of regulatory T cell (Treg) levels in peripheral blood with bronchopulmonary dysplasia (BPD) in preterm infants and its predictive value for BPD.Methods:In this case-control study, a total of 102 infants with gestational age ≤32 weeks who were hospitalized in the Neonatal Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical University from April 2022 to April 2024 were included.They were divided into a BPD group (31 cases) and a non-BPD group (71 cases) based on the diagnostic criteria of BPD.Peripheral blood samples were collected on 0 day, 7 days, 14 days, 21 days and 28 days after birth.Differences in Treg levels between the 2 groups and the relationship between Treg levels and BPD were analyzed.The independent sample t test or χ2 test was used to analyze differences between the 2 groups.One-Way ANOVA was used to compare data between groups.Multivariate Logistic regression was used to analyze the risk factors of BPD.The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of Treg levels on 7 days after birth for early diagnosis of BPD. Results:Gestational age[(28.1±1.4) weeks vs.(30.9±1.0) weeks], birth weight[(1 024±243) g vs.(1 301±188) g], Apgar score at 1 minute after birth[(4.3±1.9) points vs.(7.8±1.9) points], Apgar score at 5 minutes after birth[(7.2±1.7) points vs.(9.1±1.3) points], proportion of invasive mechanical ventilation time ≥7 days [87.1%(27/31) vs.45.1%(32/71)] and oxygen inhalation time[(45.1±11.7) days vs.(19.7±7.3) days] were statistically significantly different between BPD and non-BPD groups (all P<0.05).The Treg level in the peripheral blood of preterm infants increased first and then decreased after birth, with the peak observed on 7 days after birth.On 7 days after birth, the BPD group had a significantly higher Treg level than the non-BPD group[(10.4±1.2)% vs.(8.7±1.7)%] ( P<0.05).The multivariate Logistic regression analysis showed increased Treg levels in peripheral blood on 7 days after birth ( OR=3.320, 95% CI: 1.057-10.427, P=0.040), gestational age ( OR=0.040, 95% CI: 0.003-0.446, P=0.009), invasive mechanical ventilation time ≥7 days ( OR=4.126, 95% CI: 1.301-14.125, P=0.002), and oxygen inhalation time ( OR=1.716, 95% CI: 1.317-3.933, P=0.041) were risk factors of BPD in preterm infants.The ROC curve analysis showed that the area under the curve of Treg levels on 7 days after birth for BPD prediction was 0.794, the best cut-off value was 9.35%, the sensitivity was 90.3%, and the specificity was 66.2%. Conclusions:Treg levels in the peripheral blood of preterm infants increase first and then decrease in the early stage after birth, peaking at 7 days after birth.Elevated Treg levels at 7 days after birth may have early predictive value for the occurrence of BPD in preterm infants.