BACKGROUND:Exercise has a regulatory effect on intestinal flora and glucose metabolism,but the effects of high-intensity intermittent exercise on intestinal flora and glucose metabolism in patients with type 2 diabetes mellitus are unclear. OBJECTIVE:To investigate the effects of high-intensity intermittent exercise on glucose metabolism and intestinal flora in patients with type 2 diabetes mellitus. METHODS:Eleven patients with type 2 diabetes mellitus were recruited,among which,two were lost to the follow-up and nine were finally enrolled.High-intensity intermittent exercise intervention was conducted 3 times per week for 6 continuous weeks.Fasting blood and fecal samples were collected before and after the intervention.Glucose metabolism indexes were detected in the blood samples,and intestinal flora was detected in the fecal samples.Changes in glucose metabolism indexes and intestinal flora indexes of the patients with type 2 diabetes mellitus before and after the intervention were compared. RESULTS AND CONCLUSION:After 6 weeks of high-intensity intermittent exercise intervention,fasting blood glucose and glycosylated serum protein levels in patients were significantly reduced(P<0.05),and fasting insulin,although not significantly changed,was decreased compared with before intervention.Alpha diversity analysis showed that the diversity(Shannon index),richness(Chao index)and coverage(Coverage index)did not change significantly.Venn diagrams showed that the relative abundance of Bacteroidetes,Actinobacteria,Proteobacteria,and Fusobacteria in the intestinal flora of the patients increased,and the relative abundance of Firmicutes decreased,and a significant decrease was seen in Ruminococcus_torques and Ruminococcus_gnavus in the Firmicutes,which were both positively correlated with the abnormalities of the glycemic metabolism-related indicators,as well as with other disease development.All these findings indicate that high-intensity intermittent exercise intervention has an improvement effect on the glycemic metabolism-related indexes of patients with type 2 diabetes mellitus,and the abundance of beneficial flora in the intestinal tract increases,and the abundance of harmful flora decreased,enhancing the stability of the intestinal flora in patients.

OBJECTIVE To estimate the cost-effectiveness of penpulimab combined with chemotherapy versus chemotherapy alone in first-line treatment of advanced squamous non-small-cell lung cancer （sq-NSCLC）. METHODS From the perspective of Chinese health system， cost-utility analysis was used to evaluate the cost-effectiveness of penpulimab combined with chemotherapy （paclitaxel + carboplatin） versus chemotherapy （paclitaxel + carboplatin） in first-line treatment of sq-NSCLC. A three-health states Markov model was constructed with R packages， and clinical data used in the model were derived from the AK105-302 clinical trial. Costs and utilities were collected from the open-access database and published literature. The quality-adjusted life-years （QALY） was used as the utility index， and the willingness-to-pay （WTP） threshold was set at three times China’s per capita GDP in 2024， equivalent to 287 247 yuan/QALY. The cost-effectiveness of the schemes was evaluated by comparing the incremental cost- utility ratios （ICER） of the two schemes with the WTP threshold. One-way sensitivity analysis and probabilistic sensitivity analysis （PSA） were used to verify the stability of the basic analysis results. RESULTS Compared with chemotherapy， penpulimab combined with chemotherapy increased 0.73 QALY with an incremental cost of 150 681.93 yuan， and the ICER was 206 413.60 yuan/QALY. One-way sensitivity analysis showed that the utility of progression-free survival was the most sensitive factor on ICERs. At the WTP threshold of 3 times China’s per capita GDP， the economic probability of this scheme was 98.80%. At the WTP threshold of 1 times China’s per capita GDP， the probability of ICER being cost-effective was less than 0.01%. CONCLUSIONS For patients with advanced sq-NSCLC， penpulimab combined with chemotherapy is a cost-effective first-line treatment option when WTP threshold is 3 times China’s per capita GDP.

OBJECTIVE To construct the simulated traditional Chinese medicine pharmacy based on virtual simulation technology， and assist in the development of the new mode of traditional Chinese medicine dispensing education training. METHODS The field research and questionnaire surveys were conducted to identify the needs of Chinese medicine students and practitioners for the content and presentation of knowledge on the construction of simulated traditional Chinese medicine pharmacy. Taking the laws and regulations on the construction of traditional Chinese medicine pharmacy and the related teaching materials and literature on traditional Chinese medicine preparation as the knowledge source， the virtual simulation technology was applied to build a simulated traditional Chinese medicine pharmacy so as to achieve the functions of browsing the traditional Chinese medicine pharmacy， learning the knowledge of traditional Chinese medicine preparation and practical skills training. A multi-site simulated traditional Chinese medicine pharmacy evaluation scale study was conducted based on platform operational testing. RESULTS A simulated traditional Chinese medicine pharmacy was constructed， consisting of four core modules： video teaching， animation video， simulated pharmacy， and simulated experience. The overall score of evaluation scale was 93.31， with all entries scoring above 80； the ones with evaluation scales above 90 accounted for 92.31% （60/65）. CONCLUSIONS Simulated traditional Chinese medicine pharmacy based on virtual simulation technology meets the learning needs of users and enhances the teaching effect of traditional Chinese medicine dispensing technology training.

Magnetic resonance imaging(MRI)is a significant non-invasive diagnostic technique in medical imaging.Due to limitations in MRI hardware and scanning time,some MRI images have relatively low spatial resolution.The rise of deep learning technology offers a new approach to improve the resolution of MRI images.The study outlines the background of MRI super-resolution reconstruction,delves into the applications of various deep learning methods in MRI super-resolution reconstruction and offers a detailed analysis of these methods,evaluating their working principles,advantages,and performance efficiency in image reconstruction.Additionally,it also discusses the key challenges of deep learning technology in MRI super-resolution reconstruction,and provides prospects for future research trends.

Objective:To explore the diagnostic value of CT pulmonary vascular quantitative parameters in patients with chronic obstructive pulmonary disease (COPD) and high-risk groups.Methods:A retrospective study of 1 126 patients who underwent chest CT examination and pulmonary function test in Shanghai Tongji Hospital from January 2015 to August 2020. According to lung function, they were divided into COPD group (471 cases), high-risk group (454 cases), and normal control group (201 cases). Pulmonary vascular parameters on chest CT, including the total number of vessels (N total), the number cross-sectional area of vessels under 5 mm 2 (N CSA<5), lung surface area (LSA), number of pulmonary blood vessels per unit lung surface area (N total/LSA) and the total area of vessels (VA total) at a 9, 15, 21 mm depth from the pleural surface, and the total blood vessel volume (TBV), blood vessel volume under 5 mm 2 and 10 mm 2(BV5 and BV10) were measured quantitatively. Kruskal-Wallis H test was used to compare the differences of quantitative parameters of pulmonary vascular in the three groups; Spearman rank test was used to analyze the correlation between CT pulmonary vascular parameters and pulmonary function. Results:There were significant differences in N total/LSA at a 9, 15, 21 mm depth from the pleural surface among three groups ( P<0.05). There were significant differences in N CSA<5, N total at a 9 mm depth from the pleural surface among three groups ( P<0.05). There were significant differences in LSA at a 9 mm depth from the pleural surface, N CSA<5, N total, LSA, VA total at a 15, 21 mm depth from the pleural surface and TBV, BV5 and BV10 among three groups ( P<0.05). In high-risk group, there were positive correlation between N total/LSA, VA total at a 9 mm depth from the pleural surface and some pulmonary function parameters ( r=0.095-0.139, P<0.05). N CSA<5, N total, LSA, N total/LSA, TBV, BV5 and BV10 at different depth from pleural surface were negatively correlated with some pulmonary function parameters ( r=-0.110--0.215, P<0.05). In COPD group, number of vessels at a 9 mm depth from the pleural surface was positively correlated with the diffusion capacity for carbon monoxide of the lung single breath ( r=0.105, 0.103, P<0.05). In addition to N total/LSA were positively correlated with lung function parameters ( r=0.181-0.324, P<0.05), the remaining pulmonary vascular parameters were negatively correlated with some pulmonary function parameters ( r=-0.092--0.431, P<0.05). Conclusion:Quantitative chest CT imaging are able to effectively evaluate pulmonary vascular changes in COPD patients and high-risk groups, and the quantitative parameters of pulmonary vascular CT may distinguish COPD from high-risk groups, providing a novel means for early diagnosis of COPD and prediction of high-risk groups.

Objective:To assess the effectiveness of a model created using clinical features and preoperative chest CT imaging features in predicting the chronic obstructive pulmonary disease (COPD) among patients diagnosed with lung cancer.Methods:A retrospective analysis was conducted on clinical (age, gender, smoking history, smoking index, etc.) and imaging (lesion size, location, density, lobulation sign, etc.) data from 444 lung cancer patients confirmed by pathology at the Second Affiliated Hospital of Naval Medical University between June 2014 and March 2021. These patients were randomly divided into a training set (310 patients) and an internal test set (134 patients) using a 7∶3 ratio through the random function in Python. Based on the results of pulmonary function tests, the patients were further categorized into two groups: lung cancer combined with COPD and lung cancer non-COPD. Initially, univariate analysis was performed to identify statistically significant differences in clinical characteristics between the two groups. The variables showing significance were then included in the logistic regression analysis to determine the independent factors predicting lung cancer combined with COPD, thereby constructing the clinical model. The image features underwent a filtering process using the minimum absolute value convergence and selection operator. The reliability of these features was assessed through leave-P groups-out cross-validation repeated five times. Subsequently, a radiological model was developed. Finally, a combined model was established by combining the radiological signature with the clinical features. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) curves were plotted to evaluate the predictive capability and clinical applicability of the model. The area under the curve (AUC) for each model in predicting lung cancer combined with COPD was compared using the DeLong test.Results:In the training set, there were 182 cases in the lung cancer combined with COPD group and 128 cases in the lung cancer non-COPD group. The combined model demonstrated an AUC of 0.89 for predicting lung cancer combined with COPD, while the clinical model achieved an AUC of 0.82 and the radiological model had an AUC of 0.85. In the test set, there were 78 cases in the lung cancer combined with COPD group and 56 cases in the lung cancer non-COPD group. The combined model yielded an AUC of 0.85 for predicting lung cancer combined with COPD, compared to 0.77 for the clinical model and 0.83 for the radiological model. The difference in AUC between the radiological model and the clinical model was not statistically significant ( Z=1.40, P=0.163). However, there were statistically significant differences in the AUC values between the combined model and the clinical model ( Z=-4.01, P=0.010), as well as between the combined model and the radiological model ( Z=-2.57, P<0.001). DCA showed the maximum net benifit of the combined model. Conclusion:The developed synthetic diagnostic combined model, incorporating both radiological signature and clinical features, demonstrates the ability to predict COPD in patients with lung cancer.

Objective:To explore the differences of functional small airway and pulmonary vascular parameters in chronic obstructive pulmonary disease (COPD) of different imaging phenotypes.Methods:One hundred and thirty COPD patients underwent biphasic CT scanning in Shanghai Changzheng Hospital from August 2018 to August 2020 were analyzed retrospectively. The patients were classified into three phenotypes based on the presence of emphysema and bronchial wall thickening on CT images. Phenotype A: no emphysema or mild emphysema, with or without bronchial wall thickening; Phenotype E: obvious emphysema without bronchial wall thickening; phenotype M: significant emphysema and bronchial wall thickening were present. Parametric response map (PRM) and pulmonary vascular parameters were quantitatively measured at the whole lung level. PRM parameters included the volume of emphysema (PRMV Emphysema), the volume of functional small airway (PRMV fSAD), the volume of normal pulmonary parenchyma (PRMV Normal) and its volume percentage (%). Pulmonary vascular parameters included the number of vessels (N) and cross-sectional area vessels<5 mm 2 (N -CSA<5) at 6, 9, 12, 15, 18 21, 24 mm distance from the pleura. ANOVA or Kruskal-Wallis H tests were used to compare the differences for PRM and pulmonary vascular parameters among the three phenotypes, and LSD or Bonferroni tests were used for multiple comparisons. Results:There were significant differences among the three phenotypes for PRMV fSAD, PRMV Emphysema, PRMV fSAD%, PRMV Emphysema%, and PRMV Normal% at the whole lung level ( P<0.05). PRMV Emphysema, PRMV Emphysema%, PRMV Fsad, PRMV fSAD% of phenotype A were lower than those of phenotype E and M ( P<0.001), while there was no significant difference for PRMV Emphysema, PRMV Emphysema%, PRMV fSAD, PRMV fSAD% between phenotype E and phenotype M ( P>0.05). There were significant differences in N and N -CSA<5 that 6 mm distance from the pleura among the three groups( P<0.05). Among them, N and N -CSA<5 that 6 mm distance from pleura in phenotype M were significantly lower than those in phenotype A( P<0.001,0.002); No significant differences was found in N between phenotype M and phenotype E( P>0.05), while there was significant differences in N -CSA<5 between phenotype M and phenotype E( P=0.034). Conclusion:Biphasic quantitative CT analysis can reflect the heterogeneity of the functional small airways and pulmonary vascular abnormality in COPD with different phenotypes, and provide objective evidence for individualized diagnosis and treatment.

Objective:To explore the predictive value of random forest regression model for pulmonary function test.Methods:From August 2018 to December 2019, 615 subjects who underwent screening for three major chest diseases in Shanghai Changzheng Hospital were analyzed retrospectively. According to the ratio of forced expiratory volume in the first second to forced vital capacity (FEV 1/FVC) and the percentage of forced expiratory volume in the first second to the predicted value (FEV 1%), the subjects were divided into normal group, high risk group and chronic obstructive pulmonary disease (COPD) group. The CT quantitative parameter of small airway was parameter response mapping (PRM) parameters, including lung volume, the volume of functional small airways disease (PRMV fSAD), the volume of emphysema (PRMV Emph), the volume of normal lung tissue (PRMV Normal), the volume of uncategorized lung tissue (PRMV Uncategorized) and the percentage of the latter four volumes to the whole lung (%). ANOVA or Kruskal Wallis H was used to test the differences of basic clinical characteristics (age, sex, height, body mass), pulmonary function parameters and small airway CT quantitative parameters among the three groups; Spearman test was used to evaluate the correlation between PRM parameters and pulmonary function parameters. Finally, a random forest regression model based on PRM combined with four basic clinical characteristics was constructed to predict lung function. Results:There were significant differences in the parameters of whole lung PRM among the three groups ( P<0.001). Quantitative CT parameters PRMV Emph, PRMV Emph%, and PRMV Normal% showed a moderate correlation with FEV 1/FVC ( P<0.001). Whole lung volume, PRMV Normal,PRMV Uncategorized and PRMV Uncategorized% were strongly or moderately positively correlated with FVC ( P<0.001), other PRM parameters were weakly or very weakly correlated with pulmonary function parameters. Based on the above parameters, a random forest model for predicting FEV 1/FVC and a random forest model for predicting FEV 1% were established. The random forest model for predicting FEV 1/FVC predicted FEV 1/FVC and actual value was R 2=0.864 in the training set and R 2=0.749 in the validation set. The random forest model for predicting FEV 1% predicted FEV 1% and the actual value in the training set was R 2=0.888, and the validation set was R 2=0.792. The sensitivity, specificity and accuracy of predicting FEV 1% random forest model for the classification of normal group from high-risk group were 0.85(34/40), 0.90(65/72) and 0.88(99/112), respectively; and the sensitivity, specificity and accuracy of predicting FEV 1/FVC random forest model for differentiating non COPD group from COPD group were 0.89(8/9), 1.00 (112/112) and 0.99(120/121), respectively. While the accuracy of two models combination for subclassification of COPD [global initiative for chronic obstructive lung disease (GOLD) Ⅰ, GOLDⅡ and GOLD Ⅲ+Ⅳ] was only 0.44. Conclusions:Small airway CT quantitative parameter PRM can distinguish the normal population, high-risk and COPD population. The comprehensive regression prediction model combined with clinical characteristics based on PRM parameter show good performance differentiating normal group from high risk group, and differentiating non-COPD group from COPD group. Therefore, one-stop CT scan can evaluate the functional small airway and PFT simultaneously.

This paper reports 3 cases of acute hepatitis of unknown cause in children who met the case definition of WHO. Human adenovirus group C was detected in case 3, and the quantity of viral DNA was relatively high, which may be related to the liver function damage in the patient, but its role in pathogenesis needs further study to confirm.

Objective To get well-informed of the current status of emergency training in primary hospitals in Sichuan Province and to find weaknesses in the system in order to provide scientific basis for emergency knowledge and skills training.Methods A stratified random cluster sampling method as adopted and an anonymous questionnaire survey method was conducted to investigate the basic circumstances of the current training and the training needs of 1 000 emergency medical staff in 9 regions throughout Sichuan Province.Results The scope of the survey covered emergency doctors,nurses and technicians in hospitals of Grade Ⅱ,Grade Ⅲ and below.A total of 1 000 surveys were sent out and 983 were recovered.The questionnaire completion rate was 98.3％.The respondents mainly worked for more than 10 years,most of which with Bachelor degree,junior and intermediate titles.Results of the survey showed,63.1％ Most respondents have only one or two training opportunities per year.The training methods are mainly continuing education (59.0％,580 trips),training organized within the unit (58.5％,575 trips),and training organized by health administrative units (39.3％,386 trips).The main contents of the training are:basic professional skills learning (66.7％,655 trips),basic professional theoretical study (59.2％,582 trips),and new emergency technology (42.5％,418 trips),only 32.0％ of the respondents believe that these methods meet the practical needs.The main factors that influence participation in the training were:not be arranged by employer (36.2％,356 trips);the training was different from actual work (31.6％,311 trips);no replacement for work so they couldn't join training (29.8％,293 trips).The survey showed that the most desirable way of training is:practical application (60.1％,591 trips) and the most desirable training content is:emergency first aid knowledge (73.7％,724 trips).There were significant differences in case discussion,technical observation,academic lectures,special study trainingand learning methods in hospitals of different levels (P＜0.05),but there was no significant difference in the choice of professional practice methods (P＞0.05),and the selection of training contents was in emergency first aid knowledge,general medical knowledge and prevention and treatment of chronic diseases.There was no statistical difference in the selection of training contents of knowledge,infectious disease knowledge and department management knowledge (P＞0.05).There were significant differences in the choice of nursing knowledge training (P＜0.05).Conclusion The current situation showed a lack of first-aid knowledge and skills training for emergency personnel in Sichuan Province.The present situation of skill training can't satisfy the need of their desire to participate in training.It is urgent to develop a standardized,systematic and scientific training mode to improve the emergency first aid ability of primary medical and emergency personnel.