Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Objective:To investigate the safety and efficacy of total pelvic exenteration (TPE) for treating late complications of radiation-induced pelvic injury.Methods:This was a descriptive case series study. The inclusion criteria were as follows: (1) confirmed radiation-induced pelvic injury after radiotherapy for pelvic malignancies; (2) late complications of radiation-induced pelvic injury, such as bleeding, perforation, fistula, and obstruction, involving multiple pelvic organs; (3) TPE recommended by a multidisciplinary team; (4) patient in good preoperative condition and considered fit enough to tolerate TPE; and (5) patient extremely willing to undergo the procedure and accept the associated risks. The exclusion criteria were as follows: (1) preoperative or intraoperative diagnosis of tumor recurrence or metastasis; (2) had only undergone diversion or bypass surgery after laparoscopic exploration; and (3) incomplete medical records. Clinical and follow-up data of patients who had undergone TPE for late complications of radiation-induced pelvic injury between March 2020 and September 2022 at the Sixth Affiliated Hospital of Sun Yat-sen University were analyzed. Perioperative recovery, postoperative complications, perioperative deaths, and quality of life 1 year postoperatively were recorded.Results:The study cohort comprised 14 women, nine of whom had recto-vagino-vesical fistulas, two vesicovaginal fistulas, one ileo-vesical fistula and rectal necrosis, one ileo-vesical and rectovaginal fistulas, and one rectal ulcer and bilateral ureteral stenosis. The mean duration of surgery was 592.1±167.6 minutes and the median blood loss 550 (100–6000) mL. Ten patients underwent intestinal reconstruction, and four the Hartmann procedure. Ten patients underwent urinary reconstruction using Bricker's procedure and 7 underwent pelvic floor reconstruction. The mean postoperative hospital stay was 23.6±14.9 days. Seven patients (7/14) had serious postoperative complications (Clavien-Dindo IIIa to IVb), including surgical site infections in eight, abdominopelvic abscesses in five, pulmonary infections in five, intestinal obstruction in four, and urinary leakage in two. Empty pelvis syndrome (EPS) was diagnosed in five patients, none of whom had undergone pelvic floor reconstruction. Five of the seven patients who had not undergone pelvic floor reconstruction developed EPS, compared with none of those who had undergone pelvic floor reconstruction. One patient with EPS underwent reoperation because of a pelvic abscess, pelvic hemorrhage, and intestinal obstruction. There were no perioperative deaths. During 18.9±10.1 months of follow-up, three patients died, two of renal failure, which was a preoperative comorbidity, and one of COVID-19. The remaining patients had gradual and significant relief of symptoms during follow-up. QLQ-C30 assessment of postoperative quality of life showed gradual improvement in all functional domains and general health at 1, 3, and 6 months postoperatively (all P<0.05). Conclusions:TPE is a feasible procedure for treating late complications of radiation-induced pelvic injury combined with complex pelvic fistulas. TPE is effective in alleviating symptoms and improving quality of life. However, the indications for this procedure should be strictly controlled and the surgery carried out only by experienced surgeons.

Objective:To investigate the safety and efficacy of total pelvic exenteration (TPE) for treating late complications of radiation-induced pelvic injury.Methods:This was a descriptive case series study. The inclusion criteria were as follows: (1) confirmed radiation-induced pelvic injury after radiotherapy for pelvic malignancies; (2) late complications of radiation-induced pelvic injury, such as bleeding, perforation, fistula, and obstruction, involving multiple pelvic organs; (3) TPE recommended by a multidisciplinary team; (4) patient in good preoperative condition and considered fit enough to tolerate TPE; and (5) patient extremely willing to undergo the procedure and accept the associated risks. The exclusion criteria were as follows: (1) preoperative or intraoperative diagnosis of tumor recurrence or metastasis; (2) had only undergone diversion or bypass surgery after laparoscopic exploration; and (3) incomplete medical records. Clinical and follow-up data of patients who had undergone TPE for late complications of radiation-induced pelvic injury between March 2020 and September 2022 at the Sixth Affiliated Hospital of Sun Yat-sen University were analyzed. Perioperative recovery, postoperative complications, perioperative deaths, and quality of life 1 year postoperatively were recorded.Results:The study cohort comprised 14 women, nine of whom had recto-vagino-vesical fistulas, two vesicovaginal fistulas, one ileo-vesical fistula and rectal necrosis, one ileo-vesical and rectovaginal fistulas, and one rectal ulcer and bilateral ureteral stenosis. The mean duration of surgery was 592.1±167.6 minutes and the median blood loss 550 (100–6000) mL. Ten patients underwent intestinal reconstruction, and four the Hartmann procedure. Ten patients underwent urinary reconstruction using Bricker's procedure and 7 underwent pelvic floor reconstruction. The mean postoperative hospital stay was 23.6±14.9 days. Seven patients (7/14) had serious postoperative complications (Clavien-Dindo IIIa to IVb), including surgical site infections in eight, abdominopelvic abscesses in five, pulmonary infections in five, intestinal obstruction in four, and urinary leakage in two. Empty pelvis syndrome (EPS) was diagnosed in five patients, none of whom had undergone pelvic floor reconstruction. Five of the seven patients who had not undergone pelvic floor reconstruction developed EPS, compared with none of those who had undergone pelvic floor reconstruction. One patient with EPS underwent reoperation because of a pelvic abscess, pelvic hemorrhage, and intestinal obstruction. There were no perioperative deaths. During 18.9±10.1 months of follow-up, three patients died, two of renal failure, which was a preoperative comorbidity, and one of COVID-19. The remaining patients had gradual and significant relief of symptoms during follow-up. QLQ-C30 assessment of postoperative quality of life showed gradual improvement in all functional domains and general health at 1, 3, and 6 months postoperatively (all P<0.05). Conclusions:TPE is a feasible procedure for treating late complications of radiation-induced pelvic injury combined with complex pelvic fistulas. TPE is effective in alleviating symptoms and improving quality of life. However, the indications for this procedure should be strictly controlled and the surgery carried out only by experienced surgeons.

Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis; however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis, including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids, omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathway-related reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.

Objective To investigate the expression of stathmin and evaluate its influence to anti-microtubule adjuvant chemotherapy in non-small-cell lung cancer(NSCLC).Methods The clinical data and survival status of 78 NSCLC patients were collected,and their paraffin-embedded tissue were detected immunohistochemically with a rabbit anti-human stathmin polyclonal antibody.The clinical significance of stathmin expression and its influence to overall survival rate were analyzed statistically between patients who received paclitaxel or vinblastine adjuvant chemotherapy.Results The positive expression of stathmin could only be observed in the cytoplasm of cancer cells.Among 78 patients,40 (51.3 ％ ) patients were stained stathmin-positive.The positive rate of stathmin was significantly higher in male than female,in central type than peripheral type,in pleura-involved than non-involved,and in dead patients than survival patients ( P ＜ 0.05 ),but showed no significant differences in patients with different age,differentiated grade,pathological type,clinical stage,or lymph-node metastasis status.The expression of stathmin had a significant influence to overall survival rate(x2 =4.348,P ＜0.05 ),and those stathmin-negative patients showed a longer survival time.In stathmin-negative patients,those who received adjuvant chemotherapy with vinblastine exhibited a shorter survival time than those with paclitaxel,but the P =0.06.In stathmin-positive patients,the survival rate or time showed no difference between groups with paclitaxel and vinblastine.The differentiated grade,metastasis to lymph node and expression of stathmin were independent risk factors influencing survival rate.The positive expression of stathmin could only be observed in the cytoplasm of cancer cells.Among 78 patients,40 (51.3 ％ )patients were stained stathminpositive.The positive rate of stathmin was significantly higher in male than female,in central type than peripheral type,in pleura-involved than non-involved,and in dead patients than survival patients ( P ＜ 0.05 ),but showed no significant differences in patients with different age,differentiated grade,pathological type,clinical stage,or lymph-node metastasis status.The expression of stathmin had a significant influence to overall survival rate(x2 =4.348,P ＜ 0.05 ),and those stathmin-negative patients showed a longer survival time.In stathmin-negative patients,those who received adjuvant chemotherapy with vinblastine exhibited a shorter survival time than those with paclitaxel,but the P =0.06.In stathmin-positive patients,the survival rate or time showed no difference between groups with paclitaxel and vinblastine.The differentiated grade,metastasis to lymph node and expression of stathmin were independent risk factors influencing survival rate.Conclusion Our study suggested that the detection of stathmin in resected NSCLC tumor tissues may be helpful for prediction of prognosis,but helpless for making a choice between paclitaxel and vinblastine.NSCLC patients with stathmin-negative,no metastasis to lymph node or good-differentiated grade may have a better prognosis.

Objective To investigate the prevalence and pattern of androgenetic alopecia (AGA) in Shanghai through a community-based survey. Methods A cluster sampling survey was done among the residents in Beixinjing Community, Changning District, Shanghai. All the subjects were asked to fill a questionnaire to provide their general information, including sex, age, native place, physical status, life habit, family history, etc. The diagnosis of AGA was made by dermatologists. To determine the pattern of hair loss,Norwood-Hamilton classification system and Ludwig classification system were used for male AGA and female AGA, respectively. All the data were statistically analyzed by EpiData and SPSS11.5 software. Results Totally, 7056 subjects completed the questionnaire, including 3519 males and 3537 females, and the response rate was 72.5%. AGA was diagnosed in 809 patients, consisting of 701 males aging from 19 to 91 years (mean 64.16±11.9 years) and 108 females aging from 35 to 91 years (mean 70.46±18.89 years). The standardized prevalence (SP) was 9.47% in total, 15.73% in males and 2.73% in females; the difference was significant between males and females (χ2=356.00, P<0.001). A family history of AGA was observed in 52.7% of all subjects including 391 (55.78%) males and 35 (32.41%) females. Type Ⅲ vertex involvement was the most common type in men aging from 20 to 70 years old, and type Ⅵ in those over 70 years old. Grade Ⅰ and Ⅱ predominated in female AGA. Conclusions The results of this survey indicate that the prevalence of AGA is remarkably higher in men than that in women. Furthermore, the prevalence is steadily increased with advancing age in Shanghai.