ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

Objective To explore the effects of HPV16 E6 on genes and signaling pathways in cervical epithelial cells and to screen genes associated with oncogenic transformation.Methods HUCEC models infected with HPV16 E6 were constructed,and transcriptome sequencing was performed to screen for differentially expressed genes(DEGs),which were subjected to Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment to analyze the differential signaling pathways.RT-qPCR was used to validate major differentially down-regulated expressed genes.After predicting the major differentially expressed proteins by molecular docking analysis,the expression of major differential genes in HUCEC cell model was verified by RT-qPCR and Western blotting.In addition,RT-qPCR and Western blotting were used to further verify the expression of major differential genes in cervical cancer cell lines,SiHa and CaSki.Results A total of 55 genes with more than two-fold differential expression were screened.The results centering on down-regulated genes showed that the negatively regulated differential gene was mainly enriched in redox processes;KEGG enrichment analysis revealed that it was mainly associated with carbohydrate metabolism and cancer.RT-qPCR results showed that the down-regulated differential expression trends of the selected 10 genes were basically consistent with the sequencing results.Molecular docking analysis predicted an interaction between DHRS2 and HPV16 E6,and RT-qPCR and Western blotting confirmed that HPV16 E6 down-regulated DHRS2 mRNA(P＜0.01)and protein(P＜0.05)and ETV5 protein expression(P＜0.01).In SiHa and CaSki cells,compared with the control group,the mRNA and protein expression of DHRS2 was downregulated and positively correlated with the trend of P53 protein expression(P＜0.05).Conclusion HPV16 E6 can mediate oncogenic transformation of cervical cells and promote cervical carcinogenesis through downregulating DHRS2 expression.

Objective·To compare the performance of various deep learning methods in the segmentation and classification of colorectal polyp endoscopic images,and identify the most effective approach.Methods·Four colorectal polyp datasets were collected from three hospitals,encompassing 1 534 static images and 15 videos.All samples were pathologically validated and categorized into two types:serrated lesions and adenomatous polyps.Polygonal annotations were performed by using the LabelMe tool,and the annotated results were converted into integer mask formats.These data were utilized to train various architectures of deep neural networks,including convolutional neural network(CNN),Transformers,and their fusion,aiming to develop an effective semantic segmentation model.Multiple performance indicators for automatic diagnosis of colon polyps by different architecture models were compared,including mIoU,aAcc,mAcc,mDice,mFscore,mPrecision and mRecall.Results·Four different architectures of semantic segmentation models were developed,including two deep CNN architectures(Fast-SCNN and DeepLabV3plus),one Transformer architecture(Segformer),and one hybrid architecture(KNet).In a comprehensive performance evaluation of 291 test images,KNet achieved the highest mIoU of 84.59％,significantly surpassing Fast-SCNN(75.32％),DeepLabV3plus(78.63％),and Segformer(80.17％).Across the categories of"background","serrated lesions"and"adenomatous polyps",KNet's intersection over union(IoU)were 98.91％,74.12％,and 80.73％,respectively,all exceeding other models.Additionally,KNet performed excellently in key performance metrics,with aAcc,mAcc,mDice,mFscore,and mRecall reaching 98.59％,91.24％,91.31％,91.31％,and 91.24％,respectively,all superior to other models.Although its mPrecision of 91.46％was not the most outstanding,KNet's overall performance remained leading.In inference testing on 80 external test images,KNet maintained an mIoU of 81.53％,demonstrating strong generalization capabilities.Conclusion·The semantic segmentation model of colorectal polyp endoscopic images constructed by deep neural network based on KNet hybrid architecture,exhibits superior predictive performance,demonstrating its potential as an efficient tool for detecting colorectal polyps.

Objective To develop deep learning models for colonoscopy quality control using various deep learning architectures,and to delve into the decision-making mechanisms.Methods The colonoscopy images were selected from two datasets separately constructed by the HyperKvasir and Changshu Hospital Affiliated to Soochow University,encompassing intestines of varying degrees of cleanliness,polyps,and cecums.After image preprocessing and enhancement,transfer learning was carried out using the pre-trained models based on convolutional neural network(CNN)and Transformer.The model training adopted cross-entropy loss functions and Adam optimizer,and simultaneously implemented learning rate scheduling.To enhance model transparency,a thorough interpretability analysis was conducted using Grad-CAM,Guided Grad-CAM,and SHAP.The final model was converted to ONNX format and deployed on various equipment terminals to achieve real-time colonoscopy quality control.Results In a dataset of 3 831 colonoscopy images,EfficientNet model outperformed the other models on the test set,achieving an accuracy of 0.992 which was higher than those of the other models based on CNN(DenseNet121,ResNet50,VGG19)and Transformer(ViT,Swin,CvT),with a precision,recall rate,and F1 score of 0.991,0.989,and 0.990.On an external test set of 358 images,EfficientNet model had an average AUC,precision,and recall rate of 0.996,0.948,and 0.952,respectively.Although EfficientNet model is high-performing,some misjudgments still occurred.Interpretability analysis highlighted key image areas affecting decision-making.In addition,EfficientNet model was successfully converted to ONNX format and deployed on multiple platforms and devices,and it ensured real-time colonoscopy quality control with an inference speed of over 60 frames per second.Conclusion Among the 7 models developed for colonoscopy quality control based on CNN and Transformer,EfficientNet demonstrated exemplary performance across all categories and is deployed for real-time predictions on multiple terminals,aiming to provide patients with better medical care.

Objective To evaluate factors associated with prognosis of tonsil squamous cell carcinoma (TSCC) patients and analyze the competing risks of death in TSCC patients. Methods Data tonsil malignant tumors cases diagnosed between 1975 and 2020 were obtained from the SEER database, and records confirmed as squamous cell carcinoma were selected. A Cox proportional hazards regression model was used to investigate the relationships of gender, race, age, marital status, year of diagnosis, lesion location, pathological evidence, treatment regimen with overall survival rate as well as cause-specific mortality outcomes. The competing risks of cause-specific death outcomes among TSCC patients with different clinical characteristics were assessed. Results This study included 14, 805 TSCC patients, including 11, 650 males, accounting for 78.69%. 93.99% of TSCC cases were diagnosed after the age of 45, with the highest incidence occurring in 45 to 64 age group. Radiotherapy was the most commonly used treatment modality (81.78%), compared to surgery (49.47%) and chemotherapy (47.10%). By the end of the follow-up period, 8, 003 (54.06%) TSCC patients had died, with a median survival time of 2.33 years. Cox proportional hazards regression analysis showed that the HR (95%CI) for TSCC-related deaths among patients not receiving surgery, radiotherapy and chemotherapy were 2.101 (1.972 to 2.239), 1.829 (1.702 to 1.966) and 1.023(0.951 to 1.100), respectively, compared to those who did receive these treatments; the HR (95%CI) for deaths due to other causes were 1.630 (1.513 to 1.756), 1.438 (1.318 to 1.570) and 1.328 (1.212 to 1.456), respectively. Compared to patients < 45 years old, the HR (95%CI) for TSCC-related deaths among patients ≥65 years old were 2.218 (1.933 to 2.545), and for deaths due to other causes were 6.178 (5.133 to 7.436). Conclusion Radiotherapy, surgery and chemotherapy all contribute to improving the prognosis of TSCC patients. For elderly TSCC patients, particular attention should be paid to non-TSCC-related death risks.

Objective:To investigate the factors affecting the prognosis of stage Ⅰa2-Ⅱa2 cervical cancer after laparoscopic radical hysterectomy (LRH), and to compare the prognosis and recurrence sites of patients with different colpotomy paths.Methods:The clinical data of 965 patients with stage Ⅰa2-Ⅱa2 cervical cancer who underwent LRH in the First Affiliated Hospital of Army Medical University from January 2015 to December 2018 were collected. The median age was 47.0 years of all patients with a median follow-up of 62 months (48-74 months). Cox regression was used to perform the univariate and multivariate analysis of the clinicopathological factors associated with the prognosis that included disease-free survival (DFS) and overall survival (OS). Patients were categorized into LRH through vaginal colpotomy (VC group, n=475) and LRH through intracorporeal colpotomy (IC group, n=490) according to the colpotomic approaches. The prognosis and recurrence sites of patients in each group were compared. Results:(1) During the follow-up period, 137 cases recurred (14.2%, 137/965) and 98 cases died (10.2%, 98/965). The 5-year DFS and OS were 85.8% and 89.9%, respectively. In univariate analysis, positive vaginal margin (PVM) was significantly affected the 5-year OS of patients with cervical cancer ( P=0.023), while clinical stage, maximum diameter of tumor, degree of pathological differentiation, lymph node metastasis (LNM), depth of cervical stromal invasion, parametrium involvement, and uterine corpus invasion (UCI) were significantly associated with 5-year DFS and OS in patients with cervical cancer (all P<0.05). In multivariate analysis, clinical stage ( HR=1.882, 95% CI: 1.305-2.716), LNM ( HR=2.178, 95% CI: 1.483-3.200) and UCI ( HR=3.650, 95% CI: 1.906-6.988) were independent risk factors of 5-year DFS (all P<0.001). Clinical stage ( HR=2.500, 95% CI: 1.580-3.956), LNM ( HR=2.053, 95% CI: 1.309-3.218), UCI ( HR=3.984, 95%C I: 1.917-8.280), PVM ( HR=3.235, 95% CI: 1.021-10.244) were independent risk factors of 5-year OS (all P<0.05). (2) Different colpotomy paths did not significantly affect the 5-year DFS and OS of patients with stage Ⅰa2-Ⅱa2 cervical cancer. The 5-year DFS in VC group and IC group were 85.9% and 85.6% ( P=0.794), and the 5-year OS were 90.8% and 89.3% ( P=0.966), respectively. Recurrence patterns consisted of intraperitoneal recurrence, pelvic recurrence, vaginal stump recurrence, and lymph node and distant metastasis. The intraperitoneal recurrence rate of VC group was significantly lower than that of IC group [0.6%(3/468) vs 2.3% (11/485), P=0.037], while the rates of pelvic recurrence, vaginal stump recurrence, lymph node and distant metastasis and overall recurrence were not significantly different between two groups (all P>0.05). Subgroup analysis of patients with different clinical stages, LNM and UCI showed that statistical differences of the intraperitoneal recurrence rates between two groups were only in patients without LNM (0.5% vs 2.3%, P=0.030) or without UCI (0.7% vs 2.3%, P=0.037). Conclusions:Clinical stage, LNM, PVM and UCI are independent risk factors for the prognosis of patients with stage Ⅰa2-Ⅱa2 cervical cancer. For patients without LNM or UCI, LRH through VC could reduce the intraperitoneal recurrence rate, while it is not enough to improve 5-year DFS and OS of patients. Low proportion of intraperitoneal recurrence, intra-operative tumor cells spillage to vagina stump and pelvic cavity might be the explanation.

Objective:To evaluate the oncologic outcomes of different laparoscopic radical hysterectomy.Methods:From January 2011 to December 2014, the laparoscopic operation cases of cervical cancer at stage Ⅰb1, Ⅰb2, Ⅱa1 and Ⅱa2, including the histologic subtypes of squamous-cell carcinoma, adenocarcinoma and adenosquamous carcinoma, were collected in five clinical centers. The data were divided into two groups according to the surgical procedures, that is, modified laparoscopic-vaginal radical hysterectomy (mLVRH) and total laparoscopic radical hysterectomy (TLRH). The overall survival rate (OS), disease-free survival rate (DFS) at 5 years were retrospectively analyzed in this study.Results:There were 674 cases in total, including 377 cases of mLVRH, 297 cases of TLRH. (1) The OS at 5 years: the mLVRH was 96.1% and the TLRH was 92.0%, and the mLVRH was higher than that of TLRH （ P=0.010）. Stratify analysis， including stage of disease （Ⅰb1 and Ⅱa1）， histologic subtypes （squamous-cell carcinoma, adenocarcinoma）， lymph node metastasis， revealed that, ① Stage of disease: in stage Ⅰb1, the OS at five years of mLVRH was higher than that in TLRH group （98.6% vs 93.6%, P=0.012）. In stage Ⅱa1, there was significant difference between the two groups, the OS at five years of mLVRH and TLRH were 93.6% and 77.6% （ P=0.007）. ② Histologic subtypes: for the OS at five years of squamous-cell carcinoma, mLVRH and TLRH were 96.1% and 92.3%, and there was significant difference （ P=0.046）； for adenocarcinoma, the OS at five years were 91.0% and 88.6%， and there was no difference between two groups （ P=0.230）. ③ Lymph node metastasis： the mLVRH and TLRH with lymph node metastasis, the OS at five years were 98.6% and 96.4%; the mLVRH and TLRH without lymph node metastasis, the OS at five years were 89.3% and 80.8%. There were no significant differences between the two groups,respectively ( P=0.156， P=0.093）. (2) The DFS at 5 years: there was no significant difference between mLVRH and TLRH (94.1% vs 90.9%, P=0.220). Stratify analysis for stage of disease, the mLVRH group was higher than that in the TLRH group in stage Ⅰb1 (97.0% vs 92.8%, P=0.039). However, for stage Ⅱa1, there was no significant difference between mLVRH and TLRH group （88.2% vs 75.8%, P=0.074）. Conclusions:The results of this retrospective study indicated that different laparoscopy surgical procedures had diverse oncologic outcomes. The OS at 5 years of the mLVRH is superior to the TLRH. The DFS at 5 years in Ⅰb1 stage, the mLVRH is higher than the TLRH. Therefore, the modified laparoscopy is still an alternative surgery for early cervical cancer patients when following the principle of no-tumor-exposure.

Objective To construct genipin-crosslinked rat acellular spinal cord scaffolds and evaluate their enzymatic degradation rate,biomechanical properties and cytotoxicity.Methods Rat spinal cord scaffolds were decellularized by chemical extraction and chemically crosslinked with 5 g/L genipin solution.Micro-structure of the uncrosslinked and genipin-crosslinked acellular spinal cord scaffolds were observed by HE staining and scanning electron microscopy and properties of pore size,porosity,water ratio,and degradation rate in 2.5 g/L trypsin enzyme solution were examined.Ultimate tensile strength and elastic modulus of normal rat thoracic spinal cord,uncrosslinked and genipin-crosslinked acellular spinal cord scaffolds were determined on Instron mechanical testing instrument.Rat bone marrow mesenchymal stem cells were cultured in lixivium of uncrosslinked and genipin-crosslinked acellular spinal cord scaffolds and MTT assay for relative cell growth rate was test to evaluate the cytotoxicity of scaffolds.Results The uncrosslinked and the genipin-crosslinked acellular spinal cord scaffolds possessed a similar three-dimensional mesh-porous structure with a mean pore diameter about 30 μm and a porosity over 80％,but there was a statistical difference between the two groups(P ＞ 0.05).Water ratio of genipincrosslinked scaffolds was (229.7 ± 12.5) ％,far lower than (283.4 ± 11.2) ％ of uncrosslinked scaffolds (P ＜ O.05) ; genipin-crosslinked acellular spinal cord scaffolds had lower weight loss at each time point than the uncrosslinked acellular spinal cord scaffolds (P ＜ 0.05),but the stability in trypsin,ultimate tensile strength and elastic modulus of acellular spinal cord scaffolds were significantly enhanced by genipin-crosslinking (P ＜ 0.05).Furthermore,no obvious cytotoxicity was observed in the uncroslinked and genipin-crosslinked scaffolds.Conclusions Rat acellular spinal cord scaffolds present no obvious change in structure after genipin-crosslinking,but there is significant improvement in the biomechanical properties and ability against enzymatic degradation and no marked cytotoxicity.Hence,the genipincrosslinked scaffolds are promising in tissue engineering for spinal injury.

OBJECTIVETo construct dengue virus-specific full-length fully human antibody libraries using mammalian cell surface display technique.

METHODSTotal RNA was extracted from peripheral blood mononuclear cells (PBMCs) from convalescent patients with dengue fever. The reservoirs of the light chain and heavy chain variable regions (LCκ and VH) of the antibody genes were amplified by RT-PCR and inserted into the vector pDGB-HC-TM separately to construct the light chain and heavy chain libraries. The library DNAs were transfected into CHO cells and the expression of full-length fully human antibodies on the surface of CHO cells was analyzed by flow cytometry.

RESULTSUsing 1.2 µg of the total RNA isolated from the PBMCs as the template, the LCκ and VH were amplified and the full-length fully human antibody mammalian display libraries were constructed. The kappa light chain gene library had a size of 1.45×10(4) and the heavy chain gene library had a size of 1.8×10(5). Sequence analysis showed that 8 out of the 10 light chain clones and 7 out of the 10 heavy chain clones randomly picked up from the constructed libraries contained correct open reading frames. FACS analysis demonstrated that all the 15 clones with correct open reading frames expressed full-length antibodies, which could be detected on CHO cell surfaces. After co-transfection of the heavy chain and light chain gene libraries into CHO cells, the expression of full-length antibodies on CHO cell surfaces could be detected by FACS analysis with an expressible diversity of the antibody library reaching 1.46×10(9) [(1.45×10(4)×80%)×(1.8×10(5)×70%)].

CONCLUSIONUsing 1.2 µg of total RNA as template, the LCκ and VH full-length fully human antibody libraries against dengue virus have been successfully constructed with an expressible diversity of 10(9).

Animals ; Antibodies, Viral ; CHO Cells ; Cell Surface Display Techniques ; Cricetinae ; Cricetulus ; Dengue Virus ; immunology ; Gene Library ; Genetic Vectors ; Humans ; Immunoglobulin Heavy Chains ; immunology ; Transfection