Endo-beta-N-acetylglucosaminidase (ENGase) is widely distributed in various organisms. The first reported ENGase activity was detected in Diplococcus pneumoniae in 1971. The protein (Endo D) was purified and its peptide sequence was determined in 1974. Three ENGases (Endo F1-F3) were discovered in Flavobacterium meningosepticum from 1982 to 1993. After that, the activity was detected from different species of bacteria, yeast, fungal, plant, mice, human, etc. Multiple ENGases were detected in some species, such as Arabidopsis thaliana and Trichoderma atroviride. The first preliminary crystallographic analysis of ENGase was conducted in 1994. But to date, only a few ENGases structures have been obtained, and the structure of human ENGase is still missing. The currently identified ENGases were distributed in the GH18 or GH85 families in Carbohydrate-Active enZyme (CAZy) database. GH18 ENGase only has hydrolytic activity, but GH85 ENGase has both hydrolytic and transglycosylation activity. Although ENGases of the two families have similar (β/α)8-TIM barrel structures, the active sites are slightly different. ENGase is an effective tool for glycan detection andglycan editing. Biochemically, ENGase can specifically hydrolyze β‑1,4 glycosidic bond between the twoN-acetylglucosamines (GlcNAc) on core pentasaccharide presented on glycopeptides and/or glycoproteins. Different ENGases may have different substrate specificity. The hydrolysis products are oligosaccharide chains and a GlcNAc or glycopeptides or glycoproteins with a GlcNAc. Conditionally, it can use the two products to produce a new glycopeptides or glycoprotein. Although ENGase is a common presentation in cell, its biological function remains unclear. Accumulated evidences demonstrated that ENGase is a none essential gene for living and a key regulator for differentiation. No ENGase gene was detected in the genomes of Saccharomyces cerevisiae and three other yeast species. Its expression was extremely low in lung. As glycoproteins are not produced by prokaryotic cells, a role for nutrition and/or microbial-host interaction was predicted for bacterium produced enzymes. In the embryonic lethality phenotype of the Ngly1-deficient mice can be partially rescued by Engase knockout, suggesting down regulation of Engase might be a solution for stress induced adaptation. Potential impacts of ENGase regulation on health and disease were presented. Rabeprazole, a drug used for stomach pain as a proton inhibitor, was identified as an inhibitor for ENGase. ENGases have been applied in vitro to produce antibodies with a designated glycan. The two step reactions were achieved by a pair of ENGase dominated for hydrolysis of substrate glycoprotein and synthesis of new glycoprotein with a free glycan of designed structure, respectively. In addition, ENGase was also been used in cell surface glycan editing. New application scenarios and new detection methods for glycobiological engineering are quickly opened up by the two functions of ENGase, especially in antibody remodeling and antibody drug conjugates. The discovery, distribution, structure property, enzymatic characteristics and recent researches in topical model organisms of ENGase were reviewed in this paper. Possible biological functions and mechanisms of ENGase, including differentiation, digestion of glycoproteins for nutrition and stress responding were hypothesised. In addition, the role of ENGase in glycan editing and synthetic biology was discussed. We hope this paper may provide insights for ENGase research and lay a solid foundation for applied and translational glycomics.

Objective To construct a measurement tool for atrial fibrillation(AF)patients'experience of catheter ablation,in order to provide quantifiable basis for improving the patients'perioperative experience.Methods From Jun 2022 to Apr 2023,literature analysis,qualitative research,Delphi expert consultation,and analytic hierarchy process were used to determine the content and weight of various indicators of the measurement tool.Results The enthusiasm of experts in 3 rounds was 100%.The authority coefficient of experts was 0.946,0.961 and 0.976.The Kendal harmony coefficients of the 2 and 3 rounds of expert consultation was 0.130 and 0.370(P＜0.001).The final measurement tool included 46 items and 5 dimensions,including operational and technical quality experience,comfort management experience,information and communication experience,emotional support experience,service process and response experience.Conclusion The preliminary construction of measurement tool for AF patients'experience of catheter ablation,which were based on the features of specialty,could not only evaluate the patients'experience accurately,but also provide a basis for targeted improvement of medical and nursing service quality.

Coronary perforation is when a contrast agent or blood flows outside a blood vessel through a tear in a coronary artery.In this case,we reported a case of percutaneous coronary intervention for coronary calcified lesions,which led to iatrogenic coronary perforation and cardiac tamponade after the use of Shockwave balloon to treat intracoronary calcified nodules,and the management of PCI-related CAP was systematically reviewed through the literature.

Peroxisome proliferator-activated receptor gamma(PPAR-γ)is a member of the ligand-activated nuclear tran-scription factor superfamily.Activated PPAR-γ is involved in the regulation of many central nervous system(CNS)events,and is involved in cholesterol metabolism by inducing or inhibi-ting a series of gene pathways,thereby inhibiting the deposition of β-amyloid protein(Aβ).It plays an important neuroprotec-tive role in Alzheimer's disease(AD),improves memory and cognition in AD,and is a potential target for AD.Drug develop-ment aimed at restoring cholesterol homeostasis may be a poten-tial strategy to counteract AD.By analyzing the distribution and structure of PPAR-γ,focusing on the biological correlation be-tween PPAR-γ-mediated cholesterol metabolism and AD,this paper describes the mechanism regulation of PPAR-γ on key proteins,genes and their corresponding molecules,providing a new reference for the treatment of AD.

Objective: To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. Methods: A total of 2 894 lateral cephalograms were collected in Department of Orthodontics, Capital Medical University School of Stomatology from January 2015 to December 2021 to construct a data set, including 1 351 males and 1 543 females with a mean age of (26.4± 7.4) years. Firstly, 2 orthodontists (with 5 and 8 years of orthodontic experience, respectively) performed manual annotation and calculated measurement for primary classification, and then 2 senior orthodontists (with more than 20 years of orthodontic experience) verified the 8 diagnostic classifications including skeletal and dental indices. The data were randomly divided into training, validation, and test sets in the ratio of 7∶2∶1. The open source DenseNet121 was used to construct the model. The performance of the model was evaluated by classification accuracy, precision rate, sensitivity, specificity and area under the curve (AUC). Visualization of model regions of interest through class activation heatmaps. Results: The automatic classification model of lateral cephalograms was successfully established. It took 0.012 s on average to make 8 diagnoses on a lateral cephalogram. The accuracy of 5 classifications was 80%-90%, including sagittal and vertical skeletal facial pattern, mandibular growth, inclination of upper incisors, and protrusion of lower incisors. The acuracy rate of 3 classifications was 70%-80%, including maxillary growth, inclination of lower incisors and protrusion of upper incisors. The average AUC of each classification was ≥0.90. The class activation heat map of successfully classified lateral cephalograms showed that the AI model activation regions were distributed in the relevant structural regions. Conclusions: In this study, an automatic classification model for lateral cephalograms was established based on the DenseNet121 to achieve rapid classification of eight commonly used clinical diagnostic items.
Male ; Female ; Humans ; Young Adult ; Adult ; Artificial Intelligence ; Deep Learning ; Cephalometry ; Maxilla ; Mandible/diagnostic imaging*

Objective: To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. Methods: A total of 35 000 clinical orthodontic images were collected in the Department of Orthodontics, Capital Medical University School of Stomatology, from October to November 2020 and June to July 2021. The images were from 490 orthodontic patients with a male-to-female ratio of 49∶51 and the age range of 4 to 45 years. After data cleaning based on inclusion and exclusion criteria, the final image dataset included 17 453 face images (frontal, smiling, 90° right, 90° left, 45° right, and 45° left), 8 026 intraoral images [frontal occlusion, right occlusion, left occlusion, upper occlusal view (original and flipped), lower occlusal view (original and flipped) and coverage of occlusal relationship], 4 115 X-ray images [lateral skull X-ray from the left side, lateral skull X-ray from the right side, frontal skull X-ray, cone-beam CT (CBCT), and wrist bone X-ray] and 684 other non-orthodontic images. A labeling team composed of orthodontic doctoral students, associate professors, and professors used image labeling tools to classify the orthodontic images into 20 categories, including 6 face image categories, 8 intraoral image categories, 5 X-ray image categories, and other images. The data for each label were randomly divided into training, validation, and testing sets in an 8∶1∶1 ratio using the random function in the Python programming language. The improved SqueezeNet deep learning model was used for training, and 13 000 natural images from the ImageNet open-source dataset were used as additional non-orthodontic images for algorithm optimization of anomaly data processing. A multi-classification orthodontic image recognition system based on deep learning models was constructed. The accuracy of the orthodontic image classification was evaluated using precision, recall, F1 score, and confusion matrix based on the prediction results of the test set. The reliability of the model's image classification judgment logic was verified using the gradient-weighted class activation mapping (Grad-CAM) method to generate heat maps. Results: After data cleaning and labeling, a total of 30 278 orthodontic images were included in the dataset. The test set classification results showed that the precision, recall, and F1 scores of most classification labels were 100%, with only 5 misclassified images out of 3 047, resulting in a system accuracy of 99.84%(3 042/3 047). The precision of anomaly data processing was 100% (10 500/10 500). The heat map showed that the judgment basis of the SqueezeNet deep learning model in the image classification process was basically consistent with that of humans. Conclusions: This study developed a multi-classification orthodontic image recognition system for automatic classification of 20 types of orthodontic images based on the improved SqueezeNet deep learning model. The system exhibitted good accuracy in orthodontic image classification.
Humans ; Male ; Female ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Deep Learning ; Reproducibility of Results ; Radiography ; Algorithms ; Cone-Beam Computed Tomography

Objective: This cross-sectional investigation aimed to determine the incidence, clinical characteristics, prognosis, and related risk factors of olfactory and gustatory dysfunctions related to infection with the SARS-CoV-2 Omicron strain in mainland China. Methods: Data of patients with SARS-CoV-2 from December 28, 2022, to February 21, 2023, were collected through online and offline questionnaires from 45 tertiary hospitals and one center for disease control and prevention in mainland China. The questionnaire included demographic information, previous health history, smoking and alcohol drinking, SARS-CoV-2 vaccination, olfactory and gustatory function before and after infection, other symptoms after infection, as well as the duration and improvement of olfactory and gustatory dysfunction. The self-reported olfactory and gustatory functions of patients were evaluated using the Olfactory VAS scale and Gustatory VAS scale. Results: A total of 35 566 valid questionnaires were obtained, revealing a high incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain (67.75%). Females(χ2=367.013, P<0.001) and young people(χ2=120.210, P<0.001) were more likely to develop these dysfunctions. Gender(OR=1.564, 95%CI: 1.487-1.645), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), oral health status (OR=0.881, 95%CI: 0.839-0.926), smoking history (OR=1.152, 95%CI=1.080-1.229), and drinking history (OR=0.854, 95%CI: 0.785-0.928) were correlated with the occurrence of olfactory and taste dysfunctions related to SARS-CoV-2(above P<0.001). 44.62% (4 391/9 840) of the patients who had not recovered their sense of smell and taste also suffered from nasal congestion, runny nose, and 32.62% (3 210/9 840) suffered from dry mouth and sore throat. The improvement of olfactory and taste functions was correlated with the persistence of accompanying symptoms(χ2=10.873, P=0.001). The average score of olfactory and taste VAS scale was 8.41 and 8.51 respectively before SARS-CoV-2 infection, but decreased to3.69 and 4.29 respectively after SARS-CoV-2 infection, and recovered to 5.83and 6.55 respectively at the time of the survey. The median duration of olfactory and gustatory dysfunctions was 15 days and 12 days, respectively, with 0.5% (121/24 096) of patients experiencing these dysfunctions for more than 28 days. The overall self-reported improvement rate of smell and taste dysfunctions was 59.16% (14 256/24 096). Gender(OR=0.893, 95%CI: 0.839-0.951), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), history of head and facial trauma(OR=1.180, 95%CI: 1.036-1.344, P=0.013), nose (OR=1.104, 95%CI: 1.042-1.171, P=0.001) and oral (OR=1.162, 95%CI: 1.096-1.233) health status, smoking history(OR=0.765, 95%CI: 0.709-0.825), and the persistence of accompanying symptoms (OR=0.359, 95%CI: 0.332-0.388) were correlated with the recovery of olfactory and taste dysfunctions related to SARS-CoV-2 (above P<0.001 except for the indicated values). Conclusion: The incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain is high in mainland China, with females and young people more likely to develop these dysfunctions. Active and effective intervention measures may be required for cases that persist for a long time. The recovery of olfactory and taste functions is influenced by several factors, including gender, SARS-CoV-2 vaccination status, history of head and facial trauma, nasal and oral health status, smoking history, and persistence of accompanying symptoms.
Female ; Humans ; Adolescent ; SARS-CoV-2 ; Smell ; COVID-19/complications* ; Cross-Sectional Studies ; COVID-19 Vaccines ; Incidence ; Olfaction Disorders/etiology* ; Taste Disorders/etiology* ; Prognosis

Objective To analyze the genetic subtypes of human immunodeficiency virus (HIV) and the prevalence of pretreatment drug resistance in the newly reported HIV-infected men in Guangxi. Methods The stratified random sampling method was employed to select the newly reported HIV-infected men aged≥50 years old in 14 cities of Guangxi from January to June in 2020.The pol gene of HIV-1 was amplified by nested reverse transcription polymerase chain reaction and then sequenced.The mutation sites associated with drug resistance and the degree of drug resistance were then analyzed. Results A total of 615 HIV-infected men were included in the study.The genetic subtypes of CRF01_AE,CRF07_BC,and CRF08_BC accounted for 57.4% (353/615),17.1% (105/615),and 22.4% (138/615),respectively.The mutations associated with the resistance to nucleoside reverse transcriptase inhibitors (NRTI),non-nucleoside reverse transcriptase inhibitors (NNRTI),and protease inhibitors occurred in 8 (1.3%),18 (2.9%),and 0 patients,respectively.M184V (0.7%) and K103N (1.8%) were the mutations with the highest occurrence rates for the resistance to NRTIs and NNRTIs,respectively.Twenty-two (3.6%) patients were resistant to at least one type of inhibitors.Specifically,4 (0.7%),14 (2.3%),4 (0.7%),and 0 patients were resistant to NRTIs,NNRTIs,both NRTIs and NNRTIs,and protease inhibitors,respectively.The pretreatment resistance to NNRTIs had much higher frequency than that to NRTIs (2.9% vs.1.3%;χ²=3.929,P=0.047).The prevalence of pretreatment resistance to lamivudine,zidovudine,tenofovir,abacavir,rilpivirine,efavirenz,nevirapine,and lopinavir/ritonavir was 0.8%, 0.3%, 0.7%, 1.0%, 1.3%, 2.8%, 2.9%, and 0, respectively. Conclusions CRF01_AE,CRF07_BC,and CRF08_BC are the three major strains of HIV-infected men≥50 years old newly reported in Guangxi,2020,and the pretreatment drug resistance demonstrates low prevalence.
Male ; Humans ; Middle Aged ; Reverse Transcriptase Inhibitors/therapeutic use* ; HIV Infections/drug therapy* ; Drug Resistance, Viral/genetics* ; China/epidemiology* ; Mutation ; HIV-1/genetics* ; Protease Inhibitors/therapeutic use* ; Genotype

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.

Objective:To investigate the clinical characteristics of central nervous system tuberculosis in adults and the possible factors affecting the mortality and disability of the patients.Methods:The clinical data of patients diagnosed as "tuberculous meningitis" "tuberculous meningoencephalitis" "tuberculous cerebrospinal meningitis" or "tuberculous brain ubscess" in Huashan Hospital, Fudan University and Jing′an Branch, Huashan Hospital, Fudan University in Shanghai from January 1, 2010 to December 31, 2017 were collected, and a retrospective cohort was established. The clinical characteristics were analyzed, Medical Research Council (MRC) grade system was used to assess the severity of meningitis, and the modified Rankin Scale was used to assess the impairment of self-care. Survival rate and disability rate of the cohort were analyzed. Binary logistic regression was used for multivariate analysis. Kaplan-Meier survival curve was used for survival analysis.Results:A total of 161 patients with central nervous system tuberculosis were enrolled. Among the 161 patients, 55 cases (34.2%) were confirmed, 72 cases (44.7%) were highly suspected and 34 cases (21.1%) were suspected diagnosis. There were 56 cases (34.8%) with MRC grade Ⅰ, 76 cases (47.2%) with MRC grade Ⅱ and 29 cases (18.0%) patients with MRC grade Ⅲ before treatment. Up to January 1, 2019, ten (6.2%) patients died, 32 (19.9%) patients lost to follow-up, 119 (73.9%) patients survived. The five-year survival rate was 92.83%. There were 72 patients with no impact on life, 34 patients with moderate impact and 13 patients with severe impact. The disability rate was 39.5% (47/119). Binary logistic regression analysis showed that increasing age (odds ratio ( OR)=1.06, 95%confidence interval ( CI) 1.00 to 1.13, P=0.032) and deterioration of MRC grade during anti-tuberculosis treatment ( OR=89.00, 95% CI4.46 to 1 779.00, P=0.003) were independent risk factors for death. When severe disability and death were used as adverse outcomes, logistic regression analysis showed increasing age ( OR=1.07, 95% CI 1.01 to 1.13, P=0.035) and deterioration of MRC grade during anti-tuberculosis treatment ( OR=77.17, 95% CI4.45 to 1 337.00, P=0.003) were still independent risk factors for adverse outcomes. Conclusions:The mortality of central nervous system tuberculosis in adults in this cohort is relatively low, but the disability rate is still high. Increasing age and deterioration of MRC grade during anti-tuberculosis treatment are independent risk factors for death and disability.