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

COVID-19 has been prevalent for three years. The virulence of SARS-CoV-2 is weaken as it mutates continuously. However, elderly patients, especially those with underlying diseases, are still at high risk of developing severe infections. With the continuous study of the molecular structure and pathogenic mechanism of SARS-CoV-2, antiviral drugs for COVID-19 have been successively marketed, and these anti-SARS-CoV-2 drugs can effectively reduce the severe rate and mortality of elderly patients. This article reviews the mechanism, clinical medication regimens, drug interactions and adverse reactions of five small molecule antiviral drugs currently approved for marketing in China, so as to provide advice for the clinical rational use of anti-SARS-CoV-2 in the elderly.

Intestinal flora is the largest microbial community in human body， which consists of more than 1 000 species. Its structure and metabolites change dynamically with the age， diet and intestinal environment of the host. Study shows that the intestinal microbes play a pivotal role in regulating human physiological and pathological processes， and intestinal flora imbalance may be the key factors affecting the occurrence and development of bone and joint diseases， including osteoporosis， osteoarthritis， rheumatoid arthritis and gouty arthritis. At present， calcitonin， estrogen， nonsteroidal anti-inflammatory drugs， immunosuppressants， xanthine oxidase inhibitors and other western drugs are mostly used to treat the above diseases. However， long-term use of western drugs leads to poor compliance and obvious gastrointestinal adverse reactions among patients. Traditional Chinese medicine （TCM） predominates in the treatment of bone and joint diseases due to its low price， high efficacy and slight side effects， with the advantages of multi-targets， multi-mechanism and multi-levels. In recent years， many scholars have carried out experiments and clinical studies on the treatment of bone and joint diseases by TCMs on the basis of the liver and kidney theory such as "tonifying liver and kidney and strengthening muscles and bones". Gratifying results have been achieved. However， the mechanism of action has not been fully clarified. Intestinal flora becomes a hot spot in medical research， and a close relationship between intestinal flora and bone and joint diseases has been unveiled. Relevant literature in China and abroad showed that TCM has a significant effect on the treatment of bone and joint diseases by regulating intestinal flora. In this paper， the relationship between intestinal flora and bone and joint diseases was summarized and the intervention of TCM active ingredients and compounds on intestinal flora was reviewed to facilitate the prevention and treatment of bone and joint diseases by TCM.

Charcot-Marie-Tooth Disease/genetics* ; DNA-Binding Proteins/genetics* ; Humans ; Mutation ; Transcription Factors/genetics*

OBJECTIVE: To evaluate the efficacy of decitabine combined with low-dose CEG regimen (DCEG) and decitabine combined with low-dose CAG regimen (DCAG) in the treatment of elderly patients with MDS and MDS-transformed acute myeloid leukemia (AML). METHODS: A prospective study was conducted in 7 medical centers, 45 patients with MDS (≥ 60 years old) and MDS-transformed AML from October 2016 to January 2019 were enrolled, with the median age of 68.5 years old. The risk stratification of patients was poor or very poor, according to IPSS-R score. The treament results of decitabine combined with CEG and decitabine combined with CAG were compared. RESULTS: The comparison of the two regiem showed that the DCEG regimen had advantages on total effective rate (ORR, 86.4% vs 47.8%, respectively), overall survival time (OS) (10.0 months vs 6.0 months, respectively) and progression-free survival time (PFS) (9.0 months vs 3.0 months, respectively). About 50% of MDS patients treated by DCEG regimen achieved PR or CR, with a median OS of 31 months. Multivariate analysis showed that patients with PR or CR after induction therapy and DCEG regimen had longer survival time (31months). The incidence of bone marrow suppression, infection and treatment-related mortality rate were similar between the two groups. CONCLUSION Decitabine combined with CEG regimen could improve the survival of patients with high-risk MDS and MDS-transformed AML. The conclusion of the reaserch needs to be validated by a larger prospective randomized clinical trial.
Aclarubicin ; Aged ; Antineoplastic Combined Chemotherapy Protocols ; Azacitidine/therapeutic use* ; Cytarabine/therapeutic use* ; Decitabine/therapeutic use* ; Granulocyte Colony-Stimulating Factor ; Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Myelodysplastic Syndromes/drug therapy* ; Patients ; Prospective Studies ; Treatment Outcome

Humans ; Immunoglobulin D ; Multiple Myeloma ; Rupture, Spontaneous ; Spleen

To introduce the application status of network Meta-analysis( NMA) in the field of traditional Chinese medicine,and to discuss the application value of NMA in the field of traditional Chinese medicine,this study comprehensively reviewed the systematic reviews with application of NMA in the field of traditional Chinese medicine. CNKI,Wan Fang,Sino Med,VIP,Embase,PubMed and Cochrane Library and the reference list of previous studies were searched. The AMSTAR scale was used to evaluate the quality of literature methodology,and PRISMA-NMA checklist was used to measure the degree of report specification. Overall,122 articles were included,including 80 in Chinese and 42 in English. The included studies centered on cancer,bone and joint disease,cardiovascular disease,respiratory disease,mental disease and digestive disease. Additionally,the intervention can be categorized into three groups,traditional Chinese medicine injection,oral Chinese medicine or prescription,and traditional physical therapy including acupuncture.Nearly one-third of the researches' intervention program is aimed at comparing the effect of Chinese and Western combined therapy and monotherapy. The overall methodology quality grade is medium and the report quality is average,with methodology reporting and result reporting especially need to be improved. The subgroup analysis shows that the methodology quality of the English literatures is evidently higher than Chinese literatures,and the quality of the literatures published after 2015 is higher than those published in or before 2015.This study indicates that the NMA can compare multiple treatments simultaneously,which accords with characteristics of the clinical practice in traditional Chinese medicine that is complex and individual. NMA in the field of traditional Chinese medicine is still in the process of development. With higher level of quality control and reporting as well as the improvement of the statistical methodology and the accumulation of original researches,NMA application in the field of traditional Chinese medicine will be promising.
Administration, Oral ; Humans ; Injections ; Medicine, Chinese Traditional ; Network Meta-Analysis ; Physical Therapy Modalities ; Quality Control ; Research Design/standards* ; Systematic Reviews as Topic

OBJECTIVETo investigate the prognostic value of morphology and Hans classification in diffuse large B cell lymphoma（DLBCL）.

METHODSClinical data of 249 patients diagnosed with DLBCL in our hospital and Hangzhou Xixi hospital during Jan 2006 to Dec 2016 were analyzed retrospectively. These patients were classified into 3 groups: immunoblastic variant（IB） group, centroblastic variant（CB） group and others group according to the cell morphology. And DLBCL was also divided into GCB（germinal center B-cell-like）or non-GCB（non-germinal center B-cell-like） group by analyzing the expression of CD10, BCL6 and MUM1 (GCB: CD10 ,BCL6,MUM1/CD10,BCL6,MUM1；non-GCB：CD10,BCL6,MUM1/CD10,BCL6,MUM1).

RESULTSThe univariate analysis displayed that the age，LDH level，IPI，IB，non-GCB，B-symptoms and rituximab all could influence the OS and EFS, the CR rate of CB subtype patients was significantly higher than that of the patients with IB subtype （68.3% vs 38.9%)(P=0.02）. IB subtype was the in dependent prognostic factor for both EFS and OS in the whole study. In multivariate analysis, IPI and IB were the independent prognostic factors for OS and EFS. IB subtype was also an independent prognostic factor in EFS and OS with or without rituximab. The expression of BCL2 and BCL6 was related with prognosis in R-CHOP, but not in CHOP treated patients. Other markers (CD5, CD10, IRF4/MUM1, HLA-DR and Ki-67 proliferation index) were not of the significant prognostic value for DLBCL. When accepted rituximab, the GCB and non-GCB were not different significantly for prognosis. However, the non-GCB group showed a poor prognosis without using rituximab （EFS P=0.020；OS P=0.020）. Multivariate Cox models showed that OS and EFS were not significantly different between GCB and non-GCB group, however, the IB subtype had a very significantly poor prognosis in OS and EFS (P=0.001, P=0.002). When the analysis was restricted to DLBCL with CB morphology only, no prognostic value was observed in Hans classification.

CONCLUSIONThe subtype of immunoblast is a major risk factor in patients treated with CHOP or R-CHOP. There is a significant association between the Hans classification and the morphologic subclassification. Results of this study have supplemented the data for the prognostic factor of DLBCL and demonstrated that the cytomorphologic diagnosis can be reproducible.

Antineoplastic Combined Chemotherapy Protocols ; Cyclophosphamide ; Doxorubicin ; Humans ; Immunohistochemistry ; Lymphoma, Large B-Cell, Diffuse ; Prognosis ; Proportional Hazards Models ; Retrospective Studies ; Rituximab

Objective: To investigate the current status of antithrombotic strategy for elderly patients with atrial fibrillation (AF) and acute coronary syndrome (ACS) after stent implantation in Beijing area and to study the safety and efficacy of different therapeutic strategy. Methods: A total of 467 relevant patients were enrolled by re-travelling electronic medical records from 12 hospitals in Beijing area. The patients' mean age was (78.70±3.32) years and they were divided into 2 groups by antithrombotic therapy condition: Triple therapy group, n=17 (3.64％), Double therapy group, n=450 (96.36％). The incidence of major adverse cardiac and cerebral events (MACCE) including all-caused death, non-fatal myocardial infarction, stent thrombosis, target vessel revascularization (TVR), stoke and bleeding was compared between Triple therapy group and Double therapy group.Results: The medication in Double therapy group included aspirin+ticagrelor, aspirin+clopidogrel, clopidogrel+warfarin and cilostazol+clopidogrel; in Triple therapy group was aspirin+clopidogrel+warfarin. Patient with HAS-BLED score≥3 was defined as high risk of bleeding and they were all treated by double therapy; HAS-BLED<3 was defined as low risk of bleeding, only 5.03％ patients were treated by triple therapy. 3 patients in Triple therapy group and 33 in Double therapy group suffered from gastrointestinal bleeding, P=0.338; 6 patients in Triple therapy group and 128 in Double therapy group had MACCE, P=0.589; 3 and 80 patients died in Triple therapy group and Double therapy group, P=0.766. Conclusion: Triple therapy was rarely used in elderly AF and ACS patients after stent implantation, double therapy was the main strategy; the incidence of MACCE and mortality were similar between triple and double therapies; patients with triple therapy had the higher incidence of gastrointestinal bleeding.