Objective To investigate and analyze the status quo of professional identity of nursing students with different educational backgrounds.Methods With stratified-cluster random sampling,635 students were surveyed using the nursing students' professional identity questionnaire.Results The total score of professional identity of junior college nursing students was significantly higher than that of undergraduate students.Junior college nursing students had a higher score in professional knowledge dimension than undergraduate and graduate students,while the score of nursing undergraduate students was higher than that of graduate students.Junior college nursing students had a higher score in professional will dimension than undergraduate and graduate students.Nursing graduate students had a higher score in professional expectation dimension than junior college and undergraduate students,while the score of undergraduate students was higher than that of junior college students.Whatever the educational background,professional skill and professional expectation were the top two dimensions,while professional knowledge and professional emotion were the last two dimensions.The difference was statistically significant between the answers of nursing students with different educational backgrounds to the following questions,such as which is the most probable factor affecting your learning enthusiasm,who has the greatest impact on your professional thought about nursing and which nursing field are you most willing to go in for.There was significant difference in professional identity score between different grades of junior college and undergraduate nursing students,while there is no significant grade difference in graduate students.Conclusions There were some differences of professional identity of nursing students with different educational backgrounds.Nursing educators should carry out the professional education according to the student's educational backgrounds.

OBJECTIVE:To establish derivative spectrophotometry for the determination of the main component of Captopril tablets.METHODS:Under the alkaline condition of sodium hydroxide,2,4-dinitrofluorobenzene was used as derivatization reagent to react with captopril at 40 ℃ in the water bath.Then UV spectrophotometry was adopted to detect the content of captopril with detection wavelength set at 342 nm.RESULTS:The linear range of captopril was 1.0～14.0 ?g?mL-1(r=0.999 9) with an average recovery of 99.61%(RSD=1.27%,n=9).The RSD of intra-day and inter-day both were less than 2%.CONCLUSION:This method is stable,reliable,rapid and simple for the determination of the main components of Captopril tablets.

OBJECTIVE Tostudytheeffectofmetforminonglucolipidmetabolicdisorderscaused byolanzapineorquetiapineinrats.METHODS Olanzapine1mg·kg-1·d-1wasgivenigorquetiapine 20 mg·kg -1·d -1 was given ig for 4 d,and the dose increased to 40 mg·kg -1·d -1 from the 5th day.Met-formin 100 mg·kg -1·d -1 was given ig from the 15th day.The treatment lasted 8 weeks.Body mass, fasting blood sugar (FBS)and postprandial 2 hours blood glucose (2hPBG)were measured at base-line,3 d,1 week,2 week,4 week,6 week and 8 week.At the end of the 8th week,serum cholesterol (TC),triglyceride (TG),low density lipoprotein (LDL-C),high density lipoprotein (HDL-C),fruc-tosamine(FA)andinsulin(IRS)weremeasured.RESULTS Therewasnosignificantstatisticaldiffer-ence between normal control group and metformin 1 00 mg·kg -1·d -1 group.At the end of the 6th week, compared with normal control group,the body mass and 2hPBG were significantly increased in olanzap-ine 1 mg·kg -1·d -1 group and quetiapine 40 mg·kg -1·d -1 group (P<0.05),respectively.At the end of the 8th week,body mass,2hPBG,INS,FA,TC,TG,LDL-C were significantly increased (P<0.05), and HDL-C decreased in olanzapine group and quetiapine group(P<0.05),respectively.FBS was increased only in olanzapine group(P<0.05).Compared with olanzapine group or quetiapine group, body mass,FBS,2hPBG,INS,FA,TC,TG,LDL-C were significantly decreased by metformin admin-istration(P<0.05).CONCLUSION Metformincaneffectivelypreventandtreatweightgainand glucolipid metabolic disorder caused by olanzapine or quetiapine.

OBJECTIVE: To establish a technical process for the separation and purification of total flavones from Licorice. METHODS: The static absorption capacity of macroreticular adsorptive resins D101、Hz-806、AB-83 for total flavones from licorice were compared. The macroreticular adsorptive resin columns on the Licorice extractives were eluted respectively with different concentrations of ethanol, then the content, the weight of residue and purity coefficient of flavones from Licorice in the eluant were detected. RESULTS: The optimal technological conditions were found in AB-8 as follows: flow rate=3ml/min, sample concentration=1.5 mg/ml, pH=5 and 80% ethanol was used as eluting agent. CONCLUSIONS: AB-8 macroreticular adsorptive resin can effectively separate and purify total flavones from licorice, the purity coefficient thus obtained being over 50%, which meets the requirement of the study of effective components of herbal medicine.

Objective To investigate the diagnostic value of Bcl-2, miR-451 and Th17 cells in esophageal cancer and their relation with recurrence. Methods We selected 101 patients with esophageal cancer as the experimental group and 95 healthy patients as the control group. The correlation between the clinicopathological characteristics and the level of each peripheral blood index was analyzed. The ROC curve was used to analyze the diagnostic value of each peripheral blood index. Multiple linear regression analysis was used to analyze the relation between each index and tumor recurrence. Results Peripheral blood Bcl-2, miR-451 and Th17 cells in the experimental group were higher than those in the control group (all P < 0.05); differentiation degree, clinical stage, tumor diameter and lymph node metastasis were positively correlated with the levels of Bcl-2, miR-451, and Th17 cells (all P < 0.05). Bcl-2, miR-451 and Th17 cells in relapsed patients were higher than those in non-relapsed patients (all P < 0.05); after controlling other factors such as differentiation degree, clinical stage, tumor size and lymph node metastasis, the levels of Bcl-2, miR-451 and Th17 cells were significantly correlated with recurrence (all P < 0.05). Conclusion Bcl-2, miR-451 and Th17 cells in peripheral blood of esophageal cancer patients are abnormally expressed and their expression are closely related to differentiation degree, clinical stage and recurrence. The combined detection could provide an objective basis for clinical diagnosis and prognosis assessment.

Objective:To compare the cost-effectiveness before and after using an artificial intelligence gastroscopy-assisted system for early gastric cancer screening.Methods:The gastroscopy cases before (non-AI group) and after (AI group) the use of artificial intelligence gastroscopy-assisted system were retrospectively collected in Renmin Hospital of Wuhan University from January 1, 2017 to February 28, 2022. The proportion of early gastric cancer among all gastric cancer was analyzed. Costs were estimated based on the standards of Renmin Hospital of Wuhan University and the 2021 edition of Wuhan Disease Diagnosis-related Group Payment Standards. Cost-effectiveness analysis was conducted per 100 thousand cases with and without the system. And the incremental cost-effectiveness ratio was calculated.Results:For the non-AI group, the proportion of early gastric cancer among all gastric cancer was 28.81% (70/243). The cost of gastroscopy screening per 100 thousand was 54 598.0 thousand yuan, early gastric treatment cost was 221.8 thousand yuan, and a total cost was 54 819.8 thousand yuan. The direct effectiveness was 894.2 thousand yuan, the indirect effectiveness was 1 828.2 thousand yuan and the total effectiveness was 2 722.4 thousand yuan per 100 thousand cases. For the AI group, the early gastric cancer diagnositic rate was 36.56%(366/1 001), where gastroscopy cost was 53 440.0 thousand yuan, early gastric treatment cost 315.8 thousand yuan, the total cost 53 755.8 thousand yuan. The direct effectiveness was 1 273.5 thousand yuan, indirect effectiveness 2 603.1 thousand yuan and the total effectiveness 3 876.6 thousand yuan per 100 thousand cases. The use of the system reduced the cost of early gastric cancer screening by 1 064.0 thousand yuan, and increased the benefit by 1 154.2 thousand yuan per 100 thousand cases. The incremental cost-effectiveness ratio was -0.92.Conclusion:The use of artificial intelligence gastroscopy-assisted system for gastric early cancer screening can reduce medical costs as well as improve the efficiency of screening, and it is recommended for gastroscopy screening .

Type 2 Diabetes Mellitus(T2DM)is a chronic metabolic disease characterized by disorders of insulin and glucose.As a disease closely related to our daily diet,the molecular mechanism of its pathogenesis is still unclear.Sweet taste receptors are a kind of G protein-coupled receptors with 7 times transmembrane.Although the research on the pathogenesis of T2DM has been gradually deepened,there are few studies on the mechanism of sweet taste damage in the state of disease.Therefore,in-depth study of the pathological mechanism of T2DM sweet taste receptor damage is of great significance to further understand the molecular characteristics of sweet taste receptors and explore new targets of traditional Chinese medicine in the treatment of T2DM.In this paper,the biological characteristics of sweet taste receptors,signal transduction mechanism of sweet taste receptors,sweet taste receptors and T2DM,sweet taste receptors and"spleen is sweet"are reviewed in order to provide the latest opinions for the targeted prevention and treatment of this kind of diseases by traditional Chinese medicine and the elucidation of related pathological mechanism.

Remodeling of the mitochondrial network is an important process in the maintenance of cellular homeostasis and is closely related to mitochondrial function. Interactions between the biogenesis of new mitochondria and the clearance of damaged mitochondria (mitophagy) is an important manifestation of mitochondrial network remodeling. Mitochondrial fission and fusion act as a bridge between biogenesis and mitophagy. In recent years, the importance of these processes has been described in a variety of tissues and cell types and under a variety of conditions. For example, robust remodeling of the mitochondrial network has been reported during the polarization and effector function of macrophages. Previous studies have also revealed the important role of mitochondrial morphological structure and metabolic changes in regulating the function of macrophages. Therefore, the processes that regulate remodeling of the mitochondrial network also play a crucial role in the immune response of macrophages. In this paper, we focus on the molecular mechanisms of mitochondrial regeneration, fission, fusion, and mitophagy in the process of mitochondrial network remodeling, and integrate these mechanisms to investigate their biological roles in macrophage polarization, inflammasome activation, and efferocytosis.
Mitochondria ; Mitophagy ; Homeostasis/physiology* ; Phagocytosis ; Macrophages/metabolism*

Objective:To construct a real-time monitoring system based on computer vision for monitoring withdrawal speed of colonoscopy and to validate its feasibility and performance.Methods:A total of 35 938 images and 63 videos of colonoscopy were collected in endoscopic database of Renmin Hospital of Wuhan University from May to October 2018. The images were divided into two datasets, one dataset included in vitro, in vivo and unqualified colonoscopy images, and another dataset included ileocecal and non-cecal area images. And then 3 594 and 2 000 images were selected respectively from the two datasets for testing the deep learning model, and the remaining images were used to train the model. Three colonoscopy videos were selected to evaluate the feasibility of real-time monitoring system, and 60 colonoscopy videos were used to evaluate its performance.Results:The accuracy rate of the deep learning model for classification for in vitro, in vivo, and unqualified colonoscopy images was 90.79% (897/988), 99.92% (1 300/1 301), and 99.08% (1 293/1 305), respectively, and the overall accuracy rate was 97.11% (3 490/3 594). The accuracy rate of identifying ileocecal and non-cecal area was 96.70% (967/1 000) and 94.90% (949/1 000), respectively, and the overall accuracy rate was 95.80% (1 916/2 000). In terms of feasibility evaluation, 3 colonoscopy videos data showed a linear relationship between the retraction speed and the image processing interval, which indicated that the real-time monitoring system automatically monitored the retraction speed during the colonoscopy withdrawal process. In terms of performance evaluation, the real-time monitoring system correctly predicted entry time and withdrawal time of all 60 examinations, and the results showed that the withdrawal speed and withdrawal time was significantly negative-related ( R=-0.661, P<0.001). The 95% confidence interval of withdrawal speed for the colonoscopy with withdrawal time of less than 5 min, 5-6 min, and more than 6 min was 43.90-49.74, 40.19-45.43, and 34.89-39.11 respectively. Therefore, 39.11 was set as the safe withdrawal speed and 45.43 as the alarm withdrawal speed. Conclusion:The real-time monitoring system we constructed can be used to monitor real-time withdrawal speed of colonoscopy and improve the quality of endoscopy.

Objective:To establish a deep convolutional neural network (DCNN) model based on YOLO and ResNet algorithm for automatic detection of colorectal polyps and to test its function.Methods:Colonoscopy images and videos collected from the database of Digestive Endoscopy Center of Renmin Hospital of Wuhan University from January 2018 to March 2019 were divided into three databases (database 1, 3, 4). The public database CVC-ClinicDB (composed of 612 polyp images extracted from 29 colonoscopy videos provided by Barcelona Hospital, Spain) was used as the database 2. Database 1 (4 700 colonoscopy images from January 2018 to November 2018, including 3 700 intestinal polyp images and 1 000 non-polyp images) was used for establishing training and verifying the DCNN model. Database 2 (CVC-ClinicDB) and database 3 (720 colonoscopy images from January 2019 to March 2019, including 320 intestinal polyp images and 400 non-polyp images) were used for testing the DCNN model on image detection. Database 4 (15 colonoscopy videos in December 2019, containing 33 polyps) was used for testing the DCNN model on video detection. The sensitivity, specificity, accuracy and false positive rate of the DCNN model for detecting intestinal polyps were calculated.Results:The sensitivity of the DCNN model for detecting intestinal polyps in database 2 was 93.19% (602/646). In database 3, the DCNN model showed the accuracy of 95.00% (684/720), sensitivity of 98.13% (314/320), specificity of 92.50% (370/400), and false positive rate of 7.50% (30/400) for detecting intestinal polyps. In database 4, the DCNN model achieved a per-polyp-sensitivity of 100.00% (33/33), a per-image-accuracy of 96.29% (133 840/138 998), a per-image-sensitivity of 90.24% (4 066/4 506), a per-image-specificity of 96.49% (129 774/134 492), and a per-image-false positive rate of 3.51% (4 718/134 492).Conclusion:The DCNN model constructed in the study has a high sensitivity and specificity for automatic detection of colorectal polyps both in the colonoscopy images and videos, has a low false positive rate in the videos, and has the potential to assist endoscopists in diagnosis of colorectal polyps.