Objective:To explore the effect of intervention model based on comprehensive nutrition management on glucose and lipid metabolism and pregnancy outcome in patients with gestational diabetes mellitus (GDM).Methods:104 GDM patients admitted to Shanxi Bethune Hospital from February 2022 to March 2023 were randomly divided into control group and experimental group, with 52 cases in each group. The control group implemented routine management measures and nutrition guidance, while the experimental group implemented an intervention model based on comprehensive nutrition management on the basis of routine management. The indexes of glucose and lipid metabolism (glycosylated hemoglobin, fasting blood glucose, 2 h postprandial blood glucose, total cholesterol, triglyceride and low density lipoprotein cholesterol), pregnancy outcome, self-management ability and self-efficacy were compared between the two groups before and after intervention.Results:Before the intervention, there was no significant difference in general situation, glucose and lipid metabolism index, self-management ability and self-efficacy between the two groups ( P>0.05). After the intervention, the level of glucose and lipid metabolism index in the experimental group was significantly lower than that in the control group, with statistical significance ( P<0.05). The incidence of adverse pregnancy outcome in the experimental group was significantly lower than that in the control group, with statistical significance ( P<0.05). The scores of self-management ability and self-efficacy in the experimental group were significantly higher than those in the control group, with statistical significance ( P<0.05). Conclusion:The intervention model based on comprehensive nutrition management can effectively improve the glucose and lipid metabolism index and pregnancy outcome of GDM patients, and significantly improve their self-management ability and self-efficacy related to nutrition management, which has high clinical application and promotion value.

Objective:To evaluate the clinical relevant effect of hospital-wide blood glucose management in perioperative cholelithiasis patients with type 2 diabetes.Methods:The subjects of the study were patients with type 2 diabetes mellitus complicated with cholelithiasis who were treated at the Baiqiu'en Hospital in Shanxi from September 2022 to October 2023. The patients were divided into hospital-wide blood sugar management group and conventional treatment group, according to different blood glucose management they received. The differences in preoperative blood glucose control, length of stay, postoperative complications, and hospitalization expenses between the two groups were compared.Results:Compare based on the median (quartiles) of the observed indicators, patients with cholelithiasis who underwent hospital-wide blood glucose management based on insulin pumps had a higher proportion of time in range [72.00(70.21, 82.90)% vs. 64.80 (61.55,70.50)%, P<0.001)], lower average blood glucose level [9.00 (8.55, 10.44) mmol/L vs. 11.50 (10.50, 12.50) mmol/L, P<0.001], and shorter hospital stay [8.00 (7.00,13.00) days vs. 10.00 (8.00, 12.00) ) days, P<0.05]. Moreover, the incidence of postoperative complications was lower [5(11.11)% vs. 15(33.33)%, P<0.05], and hospitalization expenses were lower [16 535.34 (14 271.44, 29 569.23) yuan vs. 18 633.85 (17 482.66) yuan , 22 855.02) yuan, P<0.05] in patients who received hospital-wide blood glucose management. Conclusion:Hospital-wide blood glucose management based on insulin pumps showed favorable effects in the perioperative clinical application in cholelithiasis patients with type 2 diabetes, and could contribute to shortening the average length of stay, reducing hospitalization costs, and reducing postoperative complications.

Objective:To assess the diagnostic efficacy of upper gastrointestinal endoscopic image assisted diagnosis system (ENDOANGEL-LD) based on artificial intelligence (AI) for detecting gastric lesions and neoplastic lesions under white light endoscopy.Methods:The diagnostic efficacy of ENDOANGEL-LD was tested using image testing dataset and video testing dataset, respectively. The image testing dataset included 300 images of gastric neoplastic lesions, 505 images of non-neoplastic lesions and 990 images of normal stomach of 191 patients in Renmin Hospital of Wuhan University from June 2019 to September 2019. Video testing dataset was from 83 videos (38 gastric neoplastic lesions and 45 non-neoplastic lesions) of 78 patients in Renmin Hospital of Wuhan University from November 2020 to April 2021. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD for image testing dataset were calculated. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD in video testing dataset for gastric neoplastic lesions were compared with those of four senior endoscopists.Results:In the image testing dataset, the accuracy, the sensitivity, the specificity of ENDOANGEL-LD for gastric lesions were 93.9% (1 685/1 795), 98.0% (789/805) and 90.5% (896/990) respectively; while the accuracy, the sensitivity and the specificity of ENDOANGEL-LD for gastric neoplastic lesions were 88.7% (714/805), 91.0% (273/300) and 87.3% (441/505) respectively. In the video testing dataset, the sensitivity [100.0% (38/38) VS 85.5% (130/152), χ2=6.220, P=0.013] of ENDOANGEL-LD was higher than that of four senior endoscopists. The accuracy [81.9% (68/83) VS 72.0% (239/332), χ2=3.408, P=0.065] and the specificity [ 66.7% (30/45) VS 60.6% (109/180), χ2=0.569, P=0.451] of ENDOANGEL-LD were comparable with those of four senior endoscopists. Conclusion:The ENDOANGEL-LD can accurately detect gastric lesions and further diagnose neoplastic lesions to help endoscopists in clinical work.

Objective:To construct a real-time artificial intelligence (AI)-assisted endoscepic diagnosis system based on YOLO v3 algorithm, and to evaluate its ability of detecting focal gastric lesions in gastroscopy.Methods:A total of 5 488 white light gastroscopic images (2 733 images with gastric focal lesions and 2 755 images without gastric focal lesions) from June to November 2019 and videos of 92 cases (288 168 clear stomach frames) from May to June 2020 at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University were retrospectively collected for AI System test. A total of 3 997 prospective consecutive patients undergoing gastroscopy at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University from July 6, 2020 to November 27, 2020 and May 6, 2021 to August 2, 2021 were enrolled to assess the clinical applicability of AI System. When AI System recognized an abnormal lesion, it marked the lesion with a blue box as a warning. The ability to identify focal gastric lesions and the frequency and causes of false positives and false negatives of AI System were statistically analyzed.Results:In the image test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 92.3% (5 064/5 488), 95.0% (2 597/2 733), 89.5% (2 467/ 2 755), 90.0% (2 597/2 885) and 94.8% (2 467/2 603), respectively. In the video test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 95.4% (274 792/288 168), 95.2% (109 727/115 287), 95.5% (165 065/172 881), 93.4% (109 727/117 543) and 96.7% (165 065/170 625), respectively. In clinical application, the detection rate of local gastric lesions by AI System was 93.0% (6 830/7 344). A total of 514 focal gastric lesions were missed by AI System. The main reasons were punctate erosions (48.8%, 251/514), diminutive xanthomas (22.8%, 117/514) and diminutive polyps (21.4%, 110/514). The mean number of false positives per gastroscopy was 2 (1, 4), most of which were due to normal mucosa folds (50.2%, 5 635/11 225), bubbles and mucus (35.0%, 3 928/11 225), and liquid deposited in the fundus (9.1%, 1 021/11 225).Conclusion:The application of AI System can increase the detection rate of focal gastric lesions.

ABSTRACT OBJECTIVE To explore the pharmacological mechanism of trace elements in preterm low birth weight infants through network pharmacology. METHODS Targets associated with trace elements were obtained from Drugbank database and TTD database. Genes related to preterm low birth weight infants were collected from GeneCards database and DisGeNET database. Two groups of data were intersected to get mapping targets. Protein-protein interaction network of mapping targets were constructed by STRING database. Candidate targets were screened by Cytoscape 3.6.1 and ranked to obtain key targets. The major trace elements were defined by establishing network of “trace elements-candidate targets”. Kyoto Encyclopedia of Genes and Genomes(KEGG) and Gene Ontology(GO) term enrichment analysis was performed via g:Profiler software to predict the molecular mechanisms and related pathways of trace elements on preterm low birth weight infants. RESULTS A sum of 211 targets of trace elements in preterm low birth weight infants were screened, including 26 candidate targets and three key targets: albumin(ALB), glyceraldehyde-3-phosphate dehydrogenase(GAPDH) and fibronectin 1(FN1). The major trace elements were copper(Cu) and zinc(Zn), regulating 22 and 19 targets respectively. KEGG pathway enrichment analysis predicted that three major pathways were complement and coagulation cascades, cholesterol metabolism as well as lipid and atherosclerosis. CONCLUSION The major trace elements Cu and Zn may cause neuronal damage and reduce the risk of oxidative stress-related diseases in premature infants through the regulation of GAPDH, ceruloplasmin(CP), superoxide dismutase 1(SOD1), etc. The appropriate levels of Cu and Zn for preterm infants may regulate cholesterol metabolism and other signaling pathways and therefore reduce the risk of cardiovascular diseases in premature infants and adult. Further investigation of the pharmacological mechanism of trace elements in preterm infants is necessary to provide a more sufficient theoretical basis for the good growth and development of preterm infants.

Objective:To analyze and compare the effects of conventional treatment and the dynamic 3C therapy, continuous glucose monitoring system, and on outcomes, length of hospital stay and medical costs in patients with type 2 diabetes mellitus.Methods:A total of 122 type 2 diabetes mellitus patients who visited the Department of Endocrinology of Shanxi Baiqiu'en Hospital between June 2022 and December 2022 were selected and randomized at 1:1 into the control group and the experimental group using the randomized numerical table method. The t-test and non-parametric test were used as appropriate to compare the glycemic control, length of hospital stay and medical costs of the two groups.Results:Before treatment, there was no significant difference in the indicators for blood glucose levels and fluctuations between the two groups ( P>0.05). After treatment, the glycosylated hemoglobin, fasting plasma glucose, and 2-hour postprandial blood glucose decreased in both groups. Moreover, the glycosylated hemoglobin, fasting plasma glucose, and 2-hour postprandial blood glucose showed more significant decreases in the experimental group compared with the control group after treatment. The glycemic variability indicators, including the time out of range, standard deviation of blood glucose, and the largest amplitude of glycemic excursion, decreased after treatment in both groups. The time in range increased after treatment. After treatment, the standard deviation of blood glucose and the largest amplitude of glycemic excursion in the experimental group were lower than those in the control group, and the length of hospital stay in the experimental group was shortened (all P<0.05). Conclusion:3C therapy contributes to better glycemic control and shorter hospital stay in patients with type 2 diabetes mellitus.

Objective:To explore the effects of different blood glucose management modes on self-management ability and glucose and lipid metabolism in patients with type 2 diabetes mellitus (T2DM) based on the WeChat platform.Methods:240 patients with T2DM were selected in Taiyuan Central Hospital from January to June 2020 for the study. They were randomly divided into general management groups, medical care management groups, peer management groups, and medical care and peer co-management groups using random number table, with 60 cases in each group. The general management group received routine outpatient follow-up. The medical care management group, peer management group, and medical care and peer management group established WeChat groups for management, respectively. Each group′s self-management ability and glucose and lipid metabolism indexes were compared before and after six months of intervention. t-test or nonparametric tests were used to compare. Results:After the intervention, self-management abilities such as diet, exercise, blood glucose monitoring, medication compliance, foot care, smoking and fasting blood glucose (FBG), and glycosylated hemoglobin (HbA 1c) were improved in the four groups (all P<0.05). The medical care management, peer management, and medical care and peer co-management groups were further improved than the general group (all P<0.05). Except for smoking, the above medical care and peer co-management group indicators were statistically different from those of the separate medical care management and peer management group (all P<0.05). Triacylglycerol (TG) of the four groups were improved compared with the previous [1.9(1.2, 2.7) compared with 2.3(1.6, 3.5)mmol/L, 1.4(1.2, 2.1) compared with 2.2(1.6, 3.2)mmol/L, 1.6(1.1, 2.0) compared with 2.2(1.4, 3.2)mmol/L, 1.5(1.0, 2.1) compared with 2.4(1.3, 3.1)mmol/L] (all P<0.05), and after the intervention, the total cholesterol (TC) of the four groups was also improved compared with that before the intervention [(4.7±0.9) compared with (5.1±1.2)mmol/L, (4.2±1.1) compared with (5.2±1.2)mmol/L, (4.3±1.1) compared with (5.4±1.3)mmol/L, (4.2±1.1) compared with (5.0±1.4)mmol/L] (all P<0.05), and TG and TC of the medical care management, peer management, and medical care and peer co-management groups were lower than those of the general group (all P<0.05). Conclusion:Based on the WeChat platform, the management mode of medical care and peer co-management is conducive to T2DM patients′ better self-management and blood glucose control.

Objective:To construct a deep learning-based diagnostic system for gastrointestinal submucosal tumor (SMT) under endoscopic ultrasonography (EUS), so as to help endoscopists diagnose SMT.Methods:From January 1, 2019 to December 15, 2021, at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University, 245 patients with SMT confirmed by pathological diagnosis who underwent EUS and endoscopic submucosal dissection were enrolled. A total of 3 400 EUS images were collected. Among the images, 2 722 EUS images were used for training of lesion segmentation model, while 2 209 EUS images were used for training of stromal tumor and leiomyoma classification model; 283 and 191 images were selected as independent test sets to evaluate lesion segmentation model and classification model, respectively. Thirty images were selected as an independent data set for human-machine competition to compare the lesion classification accuracy between lesion classification models and 6 endoscopists. The performance of the segmentation model was evaluated by indexes such as Intersection-over-Union and Dice coefficient. The performance of the classification model was evaluated by accuracy. Chi-square test was used for statistical analysis.Results:The average Intersection-over-Union and Dice coefficient of lesion segmentation model were 0.754 and 0.835, respectively, and the accuracy, recall and F1 score were 95.2%, 98.9% and 97.0%, respectively. Based on the lesion segmentation, the accuracy of classification model increased from 70.2% to 92.1%. The results of human-machine competition showed that the accuracy of classification model in differential diagnosis of stromal tumor and leiomyoma was 86.7% (26/30), which was superior to that of 4 out of the 6 endoscopists(56.7%, 17/30; 56.7%, 17/30; 53.3%, 16/30; 60.0%, 18/30; respectively), and the differences were statistically significant( χ2=7.11, 7.36, 8.10, 6.13; all P<0.05). There was no significant difference between the accuracy of the other 2 endoscopists(76.7%, 23/30; 73.3%, 22/30; respectively) and model(both P<0.05). Conclusion:This system could be used for the auxiliary diagnosis of SMT under ultrasonic endoscope in the future, and to provide a powerful evidence for the selection of subsequent treatment decisions.

Objective:To develop an artificial intelligence-based system for measuring the size of gastrointestinal lesions under white light endoscopy in real time.Methods:The system consisted of 3 models. Model 1 was used to identify the biopsy forceps and mark the contour of the forceps in continuous pictures of the video. The results of model 1 were submitted to model 2 and classified into open and closed forceps. And model 3 was used to identify the lesions and mark the boundary of lesions in real time. Then the length of the lesions was compared with the contour of the forceps to calculate the size of lesions. Dataset 1 consisted of 4 835 images collected retrospectively from January 1, 2017 to November 30, 2019 in Renmin Hospital of Wuhan University, which were used for model training and validation. Dataset 2 consisted of images collected prospectively from December 1, 2019 to June 4, 2020 at the Endoscopy Center of Renmin Hospital of Wuhan University, which were used to test the ability of the model to segment the boundary of the biopsy forceps and lesions. Dataset 3 consisted of 302 images of 151 simulated lesions, each of which included one image of a larger tilt angle (45° from the vertical line of the lesion) and one image of a smaller tilt angle (10° from the vertical line of the lesion) to test the ability of the model to measure the lesion size with the biopsy forceps in different states. Dataset 4 was a video test set, which consisted of prospectively collected videos taken from the Endoscopy Center of Renmin Hospital of Wuhan University from August 5, 2019 to September 4, 2020. The accuracy of model 1 in identifying the presence or absence of biopsy forceps, model 2 in classifying the status of biopsy forceps (open or closed) and model 3 in identifying the presence or absence of lesions were observed with the results of endoscopist review or endoscopic surgery pathology as the gold standard. Intersection over union (IoU) was used to evaluate the segmentation effect of biopsy forceps in model 1 and lesion segmentation effect in model 3, and the absolute error and relative error were used to evaluate the ability of the system to measure lesion size.Results:(1)A total of 1 252 images were included in dataset 2, including 821 images of forceps (401 images of open forceps and 420 images of closed forceps), 431 images of non-forceps, 640 images of lesions and 612 images of non-lesions. Model 1 judged 433 images of non-forceps (430 images were accurate) and 819 images of forceps (818 images were accurate), and the accuracy was 99.68% (1 248/1 252). Based on the data of 818 images of forceps to evaluate the accuracy of model 1 on judging the segmentation effect of biopsy forceps lobe, the mean IoU was 0.91 (95% CI: 0.90-0.92). The classification accuracy of model 2 was evaluated by using 818 forceps pictures accurately judged by model 1. Model 2 judged 384 open forceps pictures (382 accurate) and 434 closed forceps pictures (416 accurate), and the classification accuracy of model 2 was 97.56% (798/818). Model 3 judged 654 images containing lesions (626 images were accurate) and 598 images of non-lesions (584 images were accurate), and the accuracy was 96.65% (1 210/1 252). Based on 626 images of lesions accurately judged by model 3, the mean IoU was 0.86 (95% CI: 0.85-0.87). (2) In dataset 3, the mean absolute error of systematic lesion size measurement was 0.17 mm (95% CI: 0.08-0.28 mm) and the mean relative error was 3.77% (95% CI: 0.00%-10.85%) when the tilt angle of biopsy forceps was small. The mean absolute error of systematic lesion size measurement was 0.17 mm (95% CI: 0.09-0.26 mm) and the mean relative error was 4.02% (95% CI: 2.90%-5.14%) when the biopsy forceps was tilted at a large angle. (3) In dataset 4, a total of 780 images of 59 endoscopic examination videos of 59 patients were included. The mean absolute error of systematic lesion size measurement was 0.24 mm (95% CI: 0.00-0.67 mm), and the mean relative error was 9.74% (95% CI: 0.00%-29.83%). Conclusion:The system could measure the size of endoscopic gastrointestinal lesions accurately and may improve the accuracy of endoscopists.

Background: Granular cell tumor (GCT) is an uncommon tumor, and gastrointestinal tract GCT is even more rare. Aims: To investigate the clinicopathological characteristics, treatment and prognosis of gastrointestinal tract GCT. Methods: Nine cases of gastrointestinal tract GCT from January 2017 to June 2021 at the 903rd Hospital of Joint Logistics Support Force, PLA and Jinhua Municipal Central Hospital Medical Group were retrieved. The clinical data, histopathological characteristics, treatment, and prognosis were retrospectively analyzed. Results: In the 9 patients with gastrointestinal tract GCT, ratio of male to female was 2:1, age at diagnosis was 19-60 years, with a median age of 52 years. Six GCT were found in esophagus, 2 in colorectum and 1 in anus. Endoscopic results showed submucosal protrusion or sessile polyps ranging in size from 2-12 mm with a median of 5 mm. Histology results showed that tumors were located in mucosa and/or submucosa, arranged in solid sheets or nests, with an infiltrative margin and inflammatory infiltrates. Tumor cells were mainly plump and polygonal with abundant cytoplasm and eosinophilic granules. Nuclei were small, the nuclear-cytoplasmic ratio was very low. Mitotic figure was rare. Immunohistochemistry results showed that S100 and CD68 proteins were positive in all patients, SOX10, CD56, Calretinin and Syn were positive in some patients, and CKp, Desmin, SMA, CD117, CD34, Dog1, and α-inhibin were negative in all patients. Esophageal and colorectal GCT patients received endoscopic mucosal resection (EMR) or endoscopic submucosal dissection (ESD). The anal GCT patient underwent local resection. Recurrence or metastasis were not observed during 9-53 months of follow-up. Conclusions: Gastrointestinal tract GCT is rare with non-specific clinical symptoms and submucosal protrusion or sessile polyps under endoscopy. Gastrointestinal tract GCT has special pathomorphology and immunophenotype. EMR or ESD is recommended for small and superficial lesions. Long-term follow-up should be performed.