Objective To compare the value of transvaginal ultrasound, 3.0T magnetic resonance imaging (MRI) scanning alone and in combination for diagnosis of ectopic pregnancy, so as to provide insights into early screening of ectopic pregnancy. Methods This study enrolled a total of 130 patients with suspected ectopic pregnancy admitted to Dachuan People’s Hospital in Dazhou City, Sichuan Province, China between February 2019 and December 2022. All patients underwent transvaginal ultrasound examination and 3.0T MRI scanning. The consistency of transvaginal ultrasound and 3.0T MRI with clinical diagnostic results was evaluated with surgical pathology or clinical follow-up results as the golden standards. The sensitivity, specificity, and accuracy of transvaginal ultrasound and 3.0T MRI, alone and in combination, were compared for diagnosis of ectopic pregnancy. Results Of the 130 patients with suspected ectopic pregnancy, 108 cases were confirmed with ectopic pregnancy by surgical pathology, and 22 cases were confirmed without ectopic pregnancy by clinical follow-up. The sensitivity, specificity, and accuracy of transvaginal ultrasound were 85.19% (92/108), 54.55% (12/22), and 80.00% (104/130), respectively, with 0.358 consistency with clinical diagnostic results. The sensitivity, specificity, and accuracy of 3.0T MRI were 92.59% (100/108), 81.81% (18/22), and 90.77% (118/130), respectively, with 0.694 consistency with clinical diagnostic results. The sensitivity, specificity, and accuracy of transvaginal ultrasound combined with 3.0T MRI were 98.15% (106/108), 72.73% (16/22), and 93.85% (122/130), respectively, with 0.764 consistency with clinical diagnostic results. In addition, the sensitivity and accuracy of transvaginal ultrasound combined with 3.0T MRI were significantly higher than transvaginal ultrasound alone for diagnosis of ectopic pregnancy (χ² = 11.88 and 10.96, both P < 0.01). Conclusion Transvaginal ultrasound combined with 3.0T MRI may provide more diagnostic information for ectopic pregnancy, and is highly consistent with the clinical diagnostic results. In addition, transvaginal ultrasound combined with 3.0T MRI improves the diagnostic sensitivity and accuracy for ectopic pregnancy than transvaginal ultrasound alone.

Objective To explore the potential mechanism of Babao Dan on primary liver cancer based on network pharmacology. Methods First, the diethylnitrosamine-induced hepatocellular carcinoma rat（HCC）model was used to observe the effects of Babao Dan. Then, the effective components in Babao Dan were detected by UPLC-MS, and the potential target sites of these effective components were predicted in the Swiss Target Prediction databases, etc. The corresponding target sites for HCC were screened using GeneCards, OMIM and Therapeutic Target Database, and the common target sites between Babao Dan and HCC were obtained after getting the intersection. The protein-protein interaction network was drawn by Cytoscape software and the STRING database, and the key molecules regulating HCC by Babao Dan were screened out. The effective target sites were subjected to GO analysis in the DAVID database and enrichment analysis in the Pathway’s KEGG. Finally, the clinical relevance of key molecules to liver cancer patients was verified by the TCGA database. Results Babao Dan could slow down the tumor development. 851 chemical components were detected in BaBao Dan by UPLC-MS , 9 major active components and 285 target sites were identified. 637 hepatocellular carcinoma-related targets were screened out, and 16 targets of Babao Dan regulating HCC were identified. GO enrichment analysis showed 802 biological processes, 11 cell compositions, and 43 molecular functions, while KEGG pathway enrichment analysis identified a total of 90 pathways. Correlation analysis of TCGA identified three key molecules associated with the survival of liver cancer patients. Conclusion In the primary rat liver cancer model, Babao Dan was found to significantly prolong the survival of cancer-induced rats and reduce tumor burden. The initial prediction of the mechanism by which Babao Dan regulating liver cancer was made through UPLC-MS analysis and network pharmacology methods, indicating that Babao Dan has the characteristics of multi-component, multi-pathway, and multi-target regulation of primary liver cancer, which could provide a reference for further relevant experimental research.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

International collaboration in education enables learning from advanced teaching experience and promotes the reform, optimization, and upgrading of medical education and teaching. We analyzed the difficulties and challenges in the education concept, curriculum system, and teaching language mode of infectious diseases under the condition of international cooperation in education in Chongqing Medical University. We tried to upgrade the teaching concepts, optimize the curriculum, and explore teaching language mode in the practice of teaching infectious diseases. We used the methods of deepening cooperation between departments, strengthening the communication between teachers and students, and emphasizing teacher training. We also adopted a variety of teaching methods and flexible teaching modes based on teaching content. With these methods, we explored teaching models of infectious diseases suitable in the context of international cooperation in education.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Objective:To investigate the correlation between paraspinal muscle atrophy, morphological changes of facet joints and adjacent segment disease (ASDis) after lumbar fusion operation.Methods:A retrospective study was conducted among 195 patients who underwent posterior lumbar fusion again for ASDis at this institution from January 2014 to December 2020, including 29 patients with ASDis whose initial surgical fusion segment was L 4,5. According to Roussouly's staging, there were 5 cases of type I, 9 cases of type II, 10 cases of type III, and 5 cases of type IV. Another 29 cases were selected from patients without ASDis after lumbar fusion as a control group. The control group was paired 1∶1 with the ASDis group according to gender, fusion segment, and Roussouly typing of the lumbar spine. The cross-sectional area (CSA) and fat infiltration (FI) of paravertebral muscle, facet joint angle (F-J) and pedicle facet (P-F) angle before the first (second) operation were measured and compared between the two groups. Then logistic regression analysis was used to determine the predictors of ASDis after posterior lumbar fusion. Finally, the receiver operation characteristic (ROC) curve was described, and the area under the curve (AUC) and cut-off point were calculated. At the same time, the paraspinal muscle atrophy before the second operation in ASDis group was measured. Results:The average follow-up time of 98 patients was 59.25±6.38 months (range, 49-73 months). The average body mass index (BMI) of ASDis group was 24.76±3.64 kg/m 2, which was higher than that in control group (22.24±2.92 kg/m 2) ( t=2.481, P=0.041). The average CSA and relative cross-sectional area (rCSA) of paraspinal muscle in ASDis group were 3 214.32± 421.15 mm 2 and 1.69±0.36 respectively, which were less than 3 978.91±459.87 mm 2 and 2.26±0.29 in control group ( t=10.22, P=0.012; t=9.47, P=0.038). The FI degree of paraspinal muscle in ASDis group (21.95%±5.89%) was significantly higher than that in control group (14.64%±7.11%) ( t=7.32, P=0.002). The F-J angle in ASDis group was 35.06°±3.45°, which was less than 38.39°±4.67° in control group ( t=4.76, P=0.027). The P-F angle in ASDis group was 117.39°±8.13°, which was greater than 111.32°±4.78° in control group ( t=5.25, P=0.031). Multivariate logistic regression analysis showed that higher BMI ( OR=1.34, P=0.038), smaller rCSA of paraspinal muscle ( OR=0.02, P=0.017) and higher FI of paraspinal muscle ( OR=1.58, P=0.032) were the risk factors of postoperative ASDis. The ROC curve showed that the AUC of BMI was 0.680 and the cut-off point was 22.58 kg/m 2; The AUC of the FI of paraspinal muscle was 0.716 and the cut-off point was 15.69%; The AUC of rCSA of paraspinal muscle was 0.227 and the cut-off point was 1.92. For ASDis patients, the paraspinal muscle before the second operation had a higher degree of FI (25.47%±6.59% vs. 21.95%±5.89%, t=3.99, P=0.042) and a smaller rCSA (1.52±0.28 vs. 1.69±0.36, t=3.85, P=0.038) than that before the first operation. The difference between the FI degree of paraspinal muscle before the second operation and the first operation was negatively correlated with the occurrence time of ASDis ( r=-0.53, P=0.039) , and the difference of rCSA was positively correlated with the occurrence time of ASDis ( r=0.64, P=0.043) . Conclusion:When BMI >22.58 kg/m 2, FI of paraspinal muscle >15.69%, and rCSA of paraspinal muscle <1.92, it suggests that ASDis is more likely to occur after operation. And the more obvious paraspinal muscle atrophy after the first operation, the earlier ASDis may occur. Morphological changes of facet joints cannot be used as an index to predict the occurrence of ASDis.

[Abstract] Objective: To investigate the expression of chemokine-like factor-like MARVEL transmembrane domain-containing family member 6 (CMTM6) in breast cancer tissues and its correlation with clinicopathological features and prognosis of patients. Methods:Atotal of 136 breast cancer tissue chips (purchased from Superchip Company), including 42 pairs of matched cancer and paracancerous tissues, were used for this study. The expression level of CMTM6 in cancer and paracancerous tissues was detected by immunohistochemistry. The comparison of CMTM6 expression between breast cancer and paracancerous tissues was conducted by paired χ2 test. The relationship between CMTM6 expression in breast cancer tissues and the clinicopathological characteristics of patients was analyzed by χ2 test. Kaplan-Meier and Log rank test analyses were used to analyze the relationship between CMTM6 expression and the survival of patients, and Cox model was used to evaluate the effect of different indicators on the prognosis of patients. Results: The expression of CMTM6 in breast cancer tissues was significantly higher than that in paracancerous tissues (P<0.01). The expression of CMTM6 was correlated with pathological type of breast cancer and HER2 positivity (P<0.05). The survival time of patients in CMTM6 high expression group was significantly shorter than that of patients in CMTM6 low expression group (P<0.05). Pathological type (HR=10.374, 95%CI: 3.529-30.497, P<0.01), TNM stage (HR=4.599, 95%CI: 1.784-11.856, P<0.01), triple-negative breast cancer (HR=3.370, 95%CI: 1.055-10.761, P<0.05) and high expression of CMTM6 (HR=0.195, 95%CI: 0.073-0.518, P<0.01) were independent risk factors for prognosis of breast cancer patients. Conclusion: CMTM6 is highly expressed in breast cancer tissues, which can be used as a risk factor for prognosis evaluation of breast cancer patients.

Objective: To explore the effect of enteral nutrition on tumor cell proliferation activity in rectal cancer patients with nutritional risk treated with preoperative neoadjuvant therapy. Methods: Sixty-six rectal cancer patients with nutritional risk treated with preoperative neoadjuvant therapy from January 2016 to January 2018 in the Yongchuan Hospital Affiliated to Chongqing Medical University were selected. The patients were divided into experimental group (enteral nutrition combined with neoadjuvant therapy) and control group (simple adjuvant therapy) according to the random digits table method, with 33 cases in each group. The expressions of proliferating cell nuclear antigen (PCNA) and Ki-67 antigen before and after treatment were detected by immunohistochemical method; the albumin and prealbumin before and after treatment were observed, and the nutrition risk screening 2002 (NRS2002) was evaluated. Results: There were no statistical differences in the expressions of PCNA and Ki-67 antigen before treatment between 2 groups (P>0.05); the expressions of PCNA and Ki-67 antigen after treatment in experimental group were significantly lower than those in control group, and there were statistical differences (P<0.05). There were no statistical differences in the NRS2002 score, albumin and prealbumin before treatment between 2 groups (P>0.05); the NRS2002 score after treatment in experimental group was significantly lower than that in control group: (1.58 ± 0.50) scores vs. (3.65 ± 0.72) scores, the albumin and prealbumin after treatment were significantly higher than those in control group: (35.92 ± 2.77) g/L vs. (31.12 ± 1.76) g/L and (204.58 ± 23.86) mg/L vs. (157.46 ± 18.99) mg/L, and there were statistical differences (P<0.01). Conclusions Enteral nutrition can reduce the proliferation activity of tumor cell in rectal cancer patients with nutritional risk treated with preoperative neoadjuvant therapy, and it can improve the nutritional status of patients.

The main work and achievements of clinical pathway work in China since 2009 were systematically reviewed in the paper. It analyzed the problems existing in the implementation of clinical pathway management in China, and suggested on such management in the future. The suggestions include:deeper understanding, convergence with the payment system reform, strengthened quality control, further informatization,and better performance appraisal system.

Objective: To compare the efficacy and safety of plasma exchange (PE) combined with double plasma absorption and simple PE in the treatment of acute-on-chronic liver failure. Methods: We retrospectively analyzed 251 cases of acute-on-chronic liver failure treated with artificial liver treatment since January 2015. Changes in clinical manifestations, laboratory tests, and complications of the patients before and after different modes of treatment were compared and short-term efficacy was tracked. In accordance with different data, t-test, Pearson's chi-squared test and Fisher's exact test were used for statistical analysis. Results: The effectiveness of low-volume PE combined with double plasma molecular adsorption system (DPMAS) and equal amount of PE combined with DPMAS was significantly better than simple PE (83.7%, 84.05% and 82.15 vs 55.6%, P < 0.05) in early stage of liver failure. In late-stage of liver failure, there was no significant difference in the treatment efficiency of each group (P > 0.05). Bilirubin and bile acid levels were significantly decreased in combined treatment groups than that to simple PE group (P < 0.05). PTA and albumin improvement rate of DPMAS PE groups were significantly lower than that of simple PE group (P < 0.05). There was no statistical difference in adverse reactions between each group. Conclusion PE combined with DPMAS improves the treatment efficiency of early hepatic failure and decrease dosage of plasma when compared with simple PE. A beforehand DPMAS treatment after PE treatment can improve the adverse effects of DPMAS on blood coagulation function and albumin levels.