AIM: To construct signal peptide-canstatin expression vector pEGFP-C1-SP-Can and express secretable mouse canstatin fusion protein in Eca-109 cells.METHODS: Site-directed mutagenesis was used in amplifying the signal peptide of murine plasminogen to construct the plasmid pEGFP-C1-SP.The cDNA of mouse canstatin,obtained from a cloning vector pMD18T-Can by PCR,was inserted into pEGFP-C1-SP to construct a secretable expression vector pEGFP-C1-SP-Can.Constructed plasmid pEGFP-C1-SP-Can was transiently transfected into Eca-109 cells via lipofectamine,and subsequently its secretable expression in the medium of cultured Eca-109 was observed by Western blotting.RESULTS: DNA sequencing and restriction enzyme analysis attested the validity of the constructed plasmids pEGFP-C1-SP and pEGFP-C1-SP-Can.EGFPcanstatin fusion protein was proved to be secretably expressed in Eca-109 by Western blotting.CONCLUSION: It is concluded that the constructed vector pEGFP-C1-SP-Can is valid and capable of expression in Eca-109,these findings provide a basis for testing the function of mouse canstatin and its application in gene therapy.

Purpose: This study aimed to investigate the changes in microRNA-130a (miR-130a) and its correlation with cardiotoxicity during epirubicin/cyclophosphamide followed by docetaxel plus trastuzumab (EC-D+T) adjuvant chemotherapy in human epidermal growth factor receptor-2-positive (HER2+) breast cancer patients. Methods: A total of 72 HER2+ breast cancer patients who underwent resection and were scheduled to receive EC-D+T adjuvant therapy were consecutively enrolled. The expression of miR-130a and cardiotoxicity (defined as any of the following situations: 1) absolute decline of left ventricular ejection fraction (LVEF) ≥ 10% and LVEF < 53%; 2) heart failure; 3) acute coronary artery syndromes; and 4) fatal arrhythmia) were assessed every 3 months throughout the 15-month EC-D+T treatment. Results: The accumulating cardiotoxicity rate was 12 (16.7%), of which the incidence of heart failure, acute coronary syndrome, life-threatening arrhythmias, ΔLVEF ≥ 10%, and LVEF < 53% was 0 (0.0%), 1 (1.4%), 0 (0.0%), and 12 (16.7%), respectively. Baseline miR-130a expression was negatively correlated with LVEF (%) and positively correlated with cardiac troponin I. The expression of miR-130a gradually increased in both cardiotoxicity and noncardiotoxicity patients during EC-D+T treatment, while the increment of miR-130a was more obvious in cardiotoxicity patients compared with non-cardiotoxicity patients. Further logistic regression and receiver operating characteristic curve analysis indicated that miR-130a was an independent predictive factor for increased cardiotoxicity risk. Conclusion MiR-130a increases constantly and predicts high cardiotoxicity risk during ECD+T adjuvant chemotherapy in HER2+ breast cancer patients.

Purpose: This study aimed to investigate the changes in microRNA-130a (miR-130a) and its correlation with cardiotoxicity during epirubicin/cyclophosphamide followed by docetaxel plus trastuzumab (EC-D+T) adjuvant chemotherapy in human epidermal growth factor receptor-2-positive (HER2+) breast cancer patients. Methods: A total of 72 HER2+ breast cancer patients who underwent resection and were scheduled to receive EC-D+T adjuvant therapy were consecutively enrolled. The expression of miR-130a and cardiotoxicity (defined as any of the following situations: 1) absolute decline of left ventricular ejection fraction (LVEF) ≥ 10% and LVEF < 53%; 2) heart failure; 3) acute coronary artery syndromes; and 4) fatal arrhythmia) were assessed every 3 months throughout the 15-month EC-D+T treatment. Results: The accumulating cardiotoxicity rate was 12 (16.7%), of which the incidence of heart failure, acute coronary syndrome, life-threatening arrhythmias, ΔLVEF ≥ 10%, and LVEF < 53% was 0 (0.0%), 1 (1.4%), 0 (0.0%), and 12 (16.7%), respectively. Baseline miR-130a expression was negatively correlated with LVEF (%) and positively correlated with cardiac troponin I. The expression of miR-130a gradually increased in both cardiotoxicity and noncardiotoxicity patients during EC-D+T treatment, while the increment of miR-130a was more obvious in cardiotoxicity patients compared with non-cardiotoxicity patients. Further logistic regression and receiver operating characteristic curve analysis indicated that miR-130a was an independent predictive factor for increased cardiotoxicity risk. Conclusion MiR-130a increases constantly and predicts high cardiotoxicity risk during ECD+T adjuvant chemotherapy in HER2+ breast cancer patients.

Objective:To investigate the influencing factors for celiac lymph node metastasis in thoracic esophageal squamous cell carcinoma (TE-SCC), construct a prediction model of celiac lymph node metastasis in TE-SCC, and stratify the probability of celiac lymph node metastasis.Methods:The retrospective case-control study was conducted. The clinicopathological data of 443 patients with TE-SCC who underwent thoracoscopic and laparoscopic esophagectomy with systematic lymph node dissection in the First Affiliated Hospital of Zhengzhou University between March 2015 and April 2019 were collected. There were 259 males and 184 females, aged from 41 to 81 years, with a median age of 64 years. The nomogram prediction model was constructed based on the results of multivariate analysis of influencing factors for celiac lymph node metastasis in TE-SCC, of which calibration curve and decision curve were drawed. The predictive performance was evaluated using the concordance index. The score for celiac lymph node metastasis in TE-SCC predicted by nomogram model was used for further recursive partitioning analysis, and patients were stratified into risk subgroups using the decision-making tree model. Observation indicators: (1) celiac lymph node metastasis in TE-SCC; (2) analysis of influencing factors for celiac lymph node metastasis in TE-SCC; (3) construction of nomogram prediction model of celiac lymph node metastasis in TE-SCC; (4) construction of decision-making tree model of celiac lymph node metastasis in TE-SCC and risk subgroup analysis of celiac lymph node metastasis probability. Measurement data with skewed distribution were represented as M (range). Count data were represented as absolute numbers and percentages, and comparison between groups was analyzed using the chi-square test. Comparison of ordinal data between groups was analyzed using the nonparametric rank sum test. Multivariate analysis was performed using the Logistic regression model. Based on Logistic regression model multivariate analysis, a new nomogram model was constructed using the RStudio 3.4 software. Results:(1) Celiac lymph node metastasis in TE-SCC: celiac lymph node metastasis was found in 89 of the 443 patients, with a celiac lymph node metastasis rate of 20.09%(89/443). (2) Analysis of influencing factors for celiac lymph node metastasis in TE-SCC. Results of univariate analysis showed that tumor location, tumor length, tumor differentiation degree, pathological T staging, nerve invasion, vessel invasion, and thoracic lymph node metastasis were related factors for celiac lymph node metastasis in TE-SCC ( χ2=12.177, Z=-2.754, -4.218, -4.254, χ2=3.908, 33.025, 30.387, P<0.05). Results of multivariate analysis showed that tumor location, vessel invasion, and thoracic lymph node metastasis were independent influencing factors for celiac lymph node metastasis in TE-SCC ( odds ratio=2.165, 3.442, 2.876, 95% confidence interval: 1.380-3.396, 1.787-6.633, 1.631-5.071, P<0.05). (3) Construction of nomogram prediction model of celiac lymph node metastasis in TE-SCC: based on the factors screened by multivariate analysis, including tumor location, vessel invasion, and thoracic lymph node metastasis, the nomogram prediction model of celiac lymph node metastasis in TE-SCC was established, with the concordance index of 0.846. The calibration curve showed a high consistency between the celiac lymph node metastasis probability estimated by the prediction model and the actual rate of celiac lymph node metastasis. The decision curve showed that the nomogram prediction model of celiac lymph node metastasis in TE-SCC had a good prediction value when the probability threshold was 0.001-0.819.(4) Construction of decision-making tree model of celiac lymph node metastasis in TE-SCC and risk subgroup analysis of celiac lymph node metastasis probability: patients were stratified into six risk subgroups using the decision-making tree model based on the celiac lymph node metastasis probability. The group A included patients with no vessel invasion+negative thoracic lymph node, group B included patients with no vessel invasion+the number of positive thoracic lymph nodes of 1-3, group C included patients with no vessel invasion+the number of positive thoracic lymph nodes of ≥4, group D included patients with vessel invasion+the number of positive thoracic lymph nodes of 0-2+upper or middle thoracic esophageal carcinoma, group E included patients with vessel invasion+the number of positive thoracic lymph nodes of 0-2+lower thoracic esophageal carcinoma, group F included patients with vessel invasion+the number of positive thoracic lymph nodes of ≥3. The group A was low-risk group with the celiac lymph node metastasis probability of 11%, group B and D were intermediate low-risk groups with the celiac lymph node metastasis probability of 27% and 21%, group C and E were the intermediate high-risk groups with the celiac lymph node metastasis probability of 56% and 55%, and group F was high-risk group with the celiac lymph node metastasis probability of 80%. Conclusions:The tumor location, vessel invasion, and thoracic lymph node metastasis are independent influencing factors for celiac lymph node metastasis in TE-SCC. Vessel invasion has the dominant influence on celiac lymph node metastasis, followed by the number of positive thoracic lymph nodes, and then the tumor location. Patients can be stratified into six risk subgroups based on the nomogram prediction model and decision-making tree model of celiac lymph node metastasis in TE-SCC.

Objective:To establish and verify a dynamic web-based nomogram for predicting futile recanalization after thrombectomy in acute ischemic stroke.Methods:Three hundred and four acute ischemic stroke patients admitted to the Second Affiliated Hospital of Soochow University from May 2017 to April 2021 were retrospectively enrolled. All these patients underwent mechanical thrombectomy and obtained successful recanalization. The eligible patients were randomly divided into training group ( n=216) and test group ( n=88) by 7∶3. The nomogram was established and internally validated with the data of the training group, and externally validated with the data of the test group. For the training group, multivariate Logistic regression analysis was performed by including all variables with P<0.05 in univariate analysis, and the independent predictors of futile recanalization were screened out to construct a nomogram. In the training group and the test group, the performance of the nomogram was verified by C-index, calibration chart and decision curve analysis respectively. Results:No significant difference was detected between the training group and the test group in futile recanalization [134/216 (62.0%) vs 56/88 (63.6%), χ 2=0.07, P=0.794]. Multivariate Logistic regression analysis showed that age ( OR=1.04,95% CI 1.00-1.08, P=0.033), National Institutes of Health Stroke Scale (NIHSS) score on admission ( OR=1.11,95% CI 1.04-1.19, P=0.001), neutrophil to lymphocyte ratio ( OR=1.19,95% CI 1.07-1.32, P=0.001), glycated hemoglobins ( OR=2.02,95% CI 1.34-3.05, P<0.001), poor collateral status ( OR=10.87,95% CI 4.08-29.01, P<0.001), postoperative high density ( OR=11.38,95% CI 4.56-28.40, P<0.001) were independent risk factors for futile recanalization. The C-index of this nomogram in the training group and the test group was 0.92 (95% CI 0.877-0.954, P<0.001) and 0.93 (95% CI 0.87-0.98, P<0.001), respectively. Conclusion:This web-based nomogram, including age, NIHSS score on admission, neutrophil to lymphocyte ratio, glycated hemoglobin, poor collateral status and postoperative high density, predicted individual probability of futile recanalization after mechanical thrombectomy with good discrimination and clinical utility.

A method was proposed to detect pulmonary nodules in low-dose computed tomography (CT) images by two-dimensional convolutional neural network under the condition of fine image preprocessing. Firstly, CT image preprocessing was carried out by image clipping, normalization and other algorithms. Then the positive samples were expanded to balance the number of positive and negative samples in convolutional neural network. Finally, the model with the best performance was obtained by training two-dimensional convolutional neural network and constantly optimizing network parameters. The model was evaluated in Lung Nodule Analysis 2016(LUNA16) dataset by means of five-fold cross validation, and each group's average model experiment results were obtained with the final accuracy of 92.3%, sensitivity of 92.1% and specificity of 92.6%.Compared with other existing automatic detection and classification methods for pulmonary nodules, all indexes were improved. Subsequently, the model perturbation experiment was carried out on this basis. The experimental results showed that the model is stable and has certain anti-interference ability, which could effectively identify pulmonary nodules and provide auxiliary diagnostic advice for early screening of lung cancer.
Algorithms ; Humans ; Lung Neoplasms ; Multiple Pulmonary Nodules ; Neural Networks, Computer ; Radiographic Image Interpretation, Computer-Assisted ; Tomography, X-Ray Computed