Background::Histological healing is closely associated with improved long-term clinical outcomes and lowered relapses in patients with ulcerative colitis (UC). Here, we developed a novel diagnostic criterion for assessing histological healing in UC patients.Methods::We conducted a retrospective cohort study in UC patients, whose treatment was iteratively optimized to achieve mucosal healing at Shanghai Tenth People’s Hospital of Tongji University from January 2017 to May 2022. We identified an inflammatory cell enumeration index (ICEI) for assessing histological healing based on the proportions of eosinophils, CD177 + neutrophils, and CD40L + T cells in the colonic lamina propria under high power field (HPF), and the outcomes (risks of symptomatic relapses) of achieving histological remission vs. persistent histological inflammation using Kaplan-Meier curves. Intrareader reliability and inter-reader reliability were evaluated by each reader. The relationships to the changes in the Nancy index and the Geboes score were also assessed for responsiveness. The ICEI was further validated in a new cohort of UC patients from other nine university hospitals. Results::We developed an ICEI for clinical diagnosis of histological healing, i.e., Y = 1.701X 1 + 0.758X 2 + 1.347X 3 - 7.745 (X 1, X 2, and X 3 represent the proportions of CD177 + neutrophils, eosinophils, and CD40L + T cells, respectively, in the colonic lamina propria under HPF). The receiver operating characteristics curve (ROC) analysis revealed that Y <-0.391 was the cutoff value for the diagnosis of histological healing and that an area under the curve (AUC) was 0.942 (95% confidence interval [CI]: 0.905-0.979) with a sensitivity of 92.5% and a specificity of 83.6% ( P <0.001). The intraclass correlation coefficient (ICC) for the intrareader reliability was 0.855 (95% CI: 0.781-0.909), and ICEI had good inter-reader reliability of 0.832 (95% CI: 0.748-0.894). During an 18-month follow-up, patients with histological healing had a substantially better outcome compared with those with unachieved histological healing ( P <0.001) using ICEI. During a 12-month follow-up from other nine hospitals, patients with histological healing also had a lower risk of relapse than patients with unachieved histological healing. Conclusions::ICEI can be used to predict histological healing and identify patients with a risk of relapse 12 months and 18 months after clinical therapy. Therefore, ICEI provides a promising, simplified approach to monitor histological healing and to predict the prognosis of UC.Registration::Chinese Clinical Trial Registry, No. ChiCTR2300077792.

Objective:To investigate the characteristics of gut microbiota in patients with type 2 diabetes (T2DM) complicated by nonalcoholic fatty liver disease (NAFLD).Methods:A total of 74 patients first diagnosed with T2DM at the Endocrinology Department of Peking Union Medical College Hospital from April 2021 to October 2023 were included. Among them, 28 patients had concurrent NAFLD while 46 patients did not. Additionally, 51 healthy controls were matched (HC group). Clinical laboratory parameters were collected, and 16S rRNA sequencing with fecal samples was conducted to compare the differences in gut microbiota across the groups.Results:Compared to the group with T2DM, patients with concurrent T2DM and NAFLD were younger, had higher level of insulin resistance as assessed by the homeostatic model assessment of insulin resistance, higher body mass index (BMI), and higher triglyceride levels. There was no difference in α-diversity across the three groups ( P>0.05), while there was a significant difference in β-diversity ( P=0.03). The Eubacterium coprostanoligenes, Fusicatenibacter, Parasutterella and Tyzzerella 3 were enriched in the group with concurrent T2DM and NAFLD as shown by the relative abundance, while the relative abundance of Flavonifractor was decreased in this group. Tyzzerella 3 abundance was positively correlated with triglyceride and albumin levels and negatively correlated with high-density lipoprotein cholesterol (HDL-C) levels. Conclusion:Patients with T2DM complicated by NAFLD exhibit dysbiosis in gut microbiota composition and specific genera abundance, with Flavonifractor identified as a potential protective factor for T2DM complicated by NAFLD.

Objective:To investigate the predictive performance of triglyceride and triglyceride glucose (TyG) index in the first trimester for the onset of gestational diabetes mellitus (GDM).Methods:Pregnant women who visited Beijing Chaoyang Maternal and Child Health Care Hospital and Beijing Haidian Maternal and Child Health Care Hospital from 2019 to 2022 were prospectively included. Concurrently, 78 healthy non-pregnant women who visited the Department of Endocrinology of Peking Union Medical College Hospital were included. The clinical characteristics and laboratory biomarkers including fasting blood glucose and blood lipid profiles were collected at the first visit in early pregnancy. Oral glucose tolerance test (OGTT) was performed at 24-28 weeks of gestation for GDM screening. Multivariate Logistic regression analysis was used to determine the association between biomarkers in early pregnancy and the risk of GDM. The receiver operating characteristic curve was used to evaluate the predictive performance and to identify the optimal cut-off value of triglyceride and TyG index in the first trimester for the risk of GDM.Results:A total of 1 677 pregnant women were included in this study, and the prevalence of GDM in our cohort was 19.6%. Compared with women who did not develop GDM, women with GDM showed an older maternal age, higher pre-pregnancy body mass index, and increased levels of laboratory biomarkers including fasting blood glucose, fasting insulin, total cholesterol, triglyceride, low-density lipoprotein cholesterol, TyG index, and Homeostasis Model Assessment of Insulin Resistance ( P<0.001). Logistic regression analysis showed that both triglyceride and TyG index in the first trimester were independent risk factors for GDM. The optimal cut-off values of triglyceride and TyG index for predicting the risk of GDM were 0.93 mmol/L and 8.10, respectively. The predictive performance can be further improved if maternal age and pre-pregnancy BMI are included. Conclusion:Triglyceride and TyG index in early pregnancy are closely associated with the risk of GDM, and can be used as early predictors of GDM.

Objective:Overweight and obesity prevalence has increased in low-income countries.This study systematically reviewed the obesity trend,disparities,and prevention and control efforts in Nepal. Methods:We searched PubMed and Google Scholar for articles and reports published between January 1,2004 and December 31,2022.Additional information on National policies and programs related to obesity prevention was retrieved from governmental websites and consultation with relevant experts.Overweight and obesity were defined using the World Health Organization body mass index cut points.Thirty-two studies and reports were included. Results:Overall,overweight and obesity rates increased in all groups in Nepal although nationally representative data remained limited.The combined overweight and obesity(OW/OB)and obesity rates in women aged 15-49 years increased from 8.5％to 22.2％and from 0.9％to 5.1％between 2006 and 2016,respectively.OW/OB and obesity rates in men were 17.1％and 2.5％based on data from the 2016 Demographic and Health Survey.OW/OB rate in under-five children increased from 0.6％to 2.8％between 2006 and 2016.Obesity rates for school-age(5-9 years)boys and girls in 2016 were 2.4％and 2.8％,respectively,and were 1.1％and 1.4％for male and female adolescents aged 10-19 years,respectively.OW/OB prevalence was much higher among women,residents in urban areas and central provinces,and in higher socioeconomic status groups.Projected prevalence of OW/OB and obesity for 2030 in adults aged 15-49 was 44.7％and 8.3％,respectively,while it was 2.2％for OW/OB in preschool children.Policies and direct interventions that specifically focused on obesity prevention and control are limited. Conclusions:OW/OB prevalence in Nepal has increased during the past 1.8 decades,disproportionately affecting population groups.Existing interventions mostly focused on undernutrition with some indirect implications for obesity prevention.In the future,Nepal needs to develop population-based programs for obesity prevention.

Objective To evaluate the agreement of four common HEp-2 indirect immunofluorescence assay(IFA)kits in the patients with antinuclear antibody(ANA)-associated rheumatic immune diseases(AARD)and the patients with non-autoimmune diseases(NAD).Methods The experiment in this study included two stages.In stage 1,the serum samples were randomly selected from 134 patients,and ANAs were detected by IFA at Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from Janu-ary to June 2023.All of the samples were tested using four kinds of HEp-2 IFA kits,and the consistency of qualitative results was eval-uated by statistical analysis.The kit exhibited highest positive rate was defined as Kit X.In the stageⅡ,a total of 554 serum samples(from 218 AARD and 336 NAD patients)with positive results detected by initial screening of reagent X were selected during the same period,and then the samples were tested by the other three HEp-2 IFA kits.The patterns and titers of ANA were recorded,and a semi-quantitative evaluation system was established.The reproducibility of different patterns of ANA and the consistency of the results among varying clinical characteristics,fluorescence reaction intensities and positive reaction sites in nucleus was statistically analyzed.Results There were no significant differences of qualitative results among the results from four kits(P＞0.05).The highest positive rate ap-peared in the kit m(45.86%)which was deemed as the initial screening kit X.Significant differences in the consistency of ANA pat-terns were observed.The reproducibility scores of centromeric pattern and granular pattern were higher than those of homogeneous pat-tern,dense fine speckled pattern,nuclear cytoplasmic mixed pattern and other mixed pattern with significant difference(P＜0.05).The reproducibility score of simple pattern was higher than that of mixed patterns(P＜0.05).In the nucleoplasmic region,the consistency score of the AARD group was higher than that of NAD group(P＜0.01).The consistency scores of each reaction site increased with the rise of the intensity of reaction.In the three reaction parts(nucleoplasm,nucleolus and equatorial plate),the scores between the weak and strong fluorescence reaction intensity groups showed significant differences(P＜0.001).The lowest consistency score occurred in cytoplasmic region.Conclusion The clinical interpretation for IFA ANA reports should be more cautious for the results showing weak fluorescence intensity,mixed patterns,and staining positive cytoplasmic sites.For the choice for reagents,the clinical laboratories should be also mindful of the impacts of fluorescent secondary antibodies of anti-human immunoglobulin on the test results.The develop-ment of standardized official guidelines for the manufacture of HEp-2 IFA kits should be crucial initiative for enhancing the consistency of ANA detection and promoting mutual recognition for the results between laboratories.

Objective:The decline in nutritional status in patients with severe pneumonia may contribute to an increase in in-hospital mortality. Enteral nutrition support can improve the nutritional status of patients, and is relatively easy to manage, with low cost and fewer serious complications. On the other hand, adverse reactions such as gastric retention and gastric microbiota translocation may increase the incidence of nosocomial pneumonia and increase the uncertainty of patient prognosis. There is no predictive model for in-hospital death in severe pneumonia patients receiving enteral nutrition support. The objective of this study was to investigate the risk factors of in-hospital death in patients with severe pneumonia receiving enteral nutrition support and to establish a prognostic model for such patients.Methods:This was a single-center retrospective study. Patients with severe pneumonia who were hospitalized in Peking Union Medical College Hospital and received enteral nutrition support were included from January 1, 2015 to December 31, 2020. The primary endpoints were in-hospital mortality rate and unordered discharge rate. The independent risk factors were determined using univariate and multifactorial logistic regression analysis, the nomogram scoring model was constructed, and the decision curve analysis (DCA) was performed.Results:A total of 632 severe pneumonia patients who received enteral nutrition support were included. Patients were divided into death and survival groups according to the presence or absence of in-hospital death, and 24 parameters were found with significant differences between groups. Nine parameters were independent predictors of mortality, namely the duration of ventilator use, the presence of malignant hyperplasia diseases, the maximal levels of platelet and prothrombin during hospitalization, and the nadir levels of alanine aminotransferase, serum albumin, sodium, potassium, and blood glucose. Based on these variables, a risk prediction scoring model was established (ROC = 0.782; 95% CI: 0.744 to 0.819, concordance index: 0.772). Calibration curves, DCA, and clinical impact curve were plotted to evaluate the goodness of function, accuracy, and applicability of the predictive nomogram, using the training and test sets. Conclusion:This study summarized the clinical characteristics of patients with severe pneumonia receiving enteral nutrition support and developed a scoring model to identify risk factors and establish prognostic models.

Objective:To develop a prototype artificial intelligence immunofluorescence image recognition system for classification of antinuclear antibodies in order to meet the growing clinical requirements for an automatic readout and classification of immunof luorescence patterns for antinuclear antibody (ANA) images.Methods:Immunofluorescence images with positive results of ANA in Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 2020 to December 2021 were collected. Three senior technicians independently and in parallel interpreted the Immunofluorescence images to determine the ANA results. Then the images were labeled according to the ANA International Consensus on Fluorescence Patterns (ICAP) classification criteria. There were 7 labeled groups: Fine speckled, Coarse speckled, Homogeneous, nucleolar, Centromere, Nuclear dots and Nuclear envelope. Each group was randomly divided into training dataset and validation dataset at a ratio of 9∶1 by using random number table. On the deep learning framework PyTORCH 1.7, the convolutional neural network (CNN) training platform was constructed based on ResNet-34 image classification network, and the automatic ANA recognition system was established. After the model was established, the test set was set up separately, the judgment results of the model were output by ranking the prediction probability, with the results of the 2 senior technicians was taken as "golden standard". Parameters such as accuracy, precision, recall and F1-score were used as indicators to evaluate the performance of the model.Results:A total of 23138 immunofluorescence images were obtained after segmentation and annotation. A total of 7 models were trained, and the effects of different algorithms, image processing and enhancement methods on the model were compared. The ResNet-34 model with the highest accuracy andswas selected as the final model, with the classification accuracy of 93.31%, precision rate of 91%, and recall rate of 90% and F1-score of 91% in the test set. The overall coincidence rate between the model and manual interpretation was 90.05%, and the accuracy of recognition of nucleolus was the highest, with the coincidence rate reaching 100% in the test set.Conclusion:The current AI system developed based on deep learning of the ANA immunofluorescence images in the present study showed the ability to recognize ANA pattern, especially in the common, typical, simple pattern.

Objective:To explore the intention of exclusive breastfeeding and its influencing factors within six months after delivery of pregnant women in the third trimester of pregnancy in Xi'an.Methods:From January to February 2019, convenience sampling was used to select 2 671 pregnant women in the third trimester of pregnancy who underwent regular obstetric examinations in Obstetrics Clinic of five hospitals in Xi'an for a cross-sectional survey. Pregnant women were surveyed by means of a field survey using a self-designed Exclusive Breastfeeding Intention of Pregnant Women in the Third Trimester Questionnaire. Multivariate Logistic regression was used to analyze the influencing factors of the intention of exclusive breastfeeding among pregnant women in the third trimester. A total of 2 671 questionnaires were distributed, 2 479 valid questionnaires were recovered, and the valid recovery rate was 92.8% (2 479/2 671) .Results:A total of 60.8% (1 507/2 479) of pregnant women planned to exclusively breastfeed within 6 months of delivery. Pregnant women in the third trimester of pregnancy whose husbands ( OR=2.950, 95% CI: 2.097-4.066) and family members ( OR=2.171, 95% CI: 1.571-3.000) supported exclusive breastfeeding had high intention to exclusively breastfeed, and those who participated in breastfeeding courses had a high intention to exclusively breastfeed ( OR=1.436, 95% CI: 1.199-1.719) . Conclusions:More than half of third-trimester women plan to exclusively breastfeed within six months postpartum. Husband and family support and enrolment in breastfeeding classes increase the intention of pregnant women to exclusively breastfeed. Prenatal breastfeeding courses should be carried out to raise the awareness of pregnant women and family members about exclusive breastfeeding, and focus on the support of husbands and family members for exclusive breastfeeding, so as to increase the exclusive breastfeeding rate within six months after delivery.

Objective:To explore effects of mindfulness training on the psychological resilience, subjective well-being and blood glucose metabolism indexes of middle-aged and young diabetic patients.Methods:From April to September 2019, convenience sampling was used to select 100 inpatient diabetic patients admitted to the Endocrinology Department of a provincial hospital in Hebei Province. The patients were divided into the control group and the observation group with the random number table method, each with 50 cases. The control group was given routine nursing, and the observation group was given mindfulness training on the basis of routine nursing. The psychological resilience, subjective well-being and blood glucose metabolism indexes of the two groups of patients were evaluated before the intervention and 6 months after the intervention.Results:Before the intervention, there was no statistically significant difference in the psychological resilience, subjective well-being scores, and blood glucose metabolism indexes of patients between two groups ( P>0.05) . After the intervention, the scores of psychological resilience and subjective well-being of observation group were (63.04±3.19) and (71.67±5.40) respectively, higher than those [ (50.68±3.50) and (53.83±6.06) ] of the control group, and the fasting blood glucose, 2 hours postprandial blood glucose, and glycosylated hemoglobin of the observation group were lower than those of the control group, and the differences were statistically significant ( P<0.05) . Conclusions:Mindfulness training can improve the psychological resilience, subjective well-being, and blood glucose control of young and middle-aged diabetic patients.

Chromatin accessibility is a highly informative structural feature for understanding gene transcription regulation,because it indicates the degree to which nuclear macromolecules such as proteins and RNAs can access chromosomal DNA.Studies have shown that chromatin accessibility is highly dynamic during stress response,stimulus response,and developmental transition.More-over,physical access to chromosomal DNA in eukaryotes is highly cell-specific.Therefore,current technologies such as DNase-seq,ATAC-seq,and FAIRE-seq reveal only a portion of the open chro-matin regions(OCRs)present in a given species.Thus,the genome-wide distribution of OCRs remains unknown.In this study,we developed a bioinformatics tool called CharPlant for the de novo prediction of OCRs in plant genomes.To develop this tool,we constructed a three-layer con-volutional neural network(CNN)and subsequently trained the CNN using DNase-seq and ATAC-seq datasets of four plant species.The model simultaneously learns the sequence motifs and regu-latory logics,which are jointly used to determine DNA accessibility.All of these steps are integrated into CharPlant,which can be run using a simple command line.The results of data analysis using CharPlant in this study demonstrate its prediction power and computational efficiency.To our knowledge,CharPlant is the first de novo prediction tool that can identify potential OCRs in the whole genome.The source code of CharPlant and supporting files are freely available from https://github.com/Yin-Shen/CharPlant.