Objective: To observe the immediate effect of small-angle Tui-Pushing and An-Pressing anti-rotation bone-setting manipulation in improving the correction of braces for adolescent idiopathic scoliosis. Methods: A total of 50 cases of adolescent idiopathic scoliosis were selected and given brace correction first. The whole spine anteroposterior and lateral radiographs were taken, the Cobb angle was measured, and the visual analog scale (VAS) score of pain caused by brace wearing was recorded. After removal of the brace, small-angle Tui-Pushing and An-Pressing anti-rotation bone-setting manipulation was performed once. After treatment, the same brace was put on again to take a whole spine anteroposterior radiograph, the Cobb angle was measured, and the VAS score was recorded. The changes in Cobb angle and VAS score after manipulation were compared, and the immediate efficacy was evaluated. Results: After the manipulation, the Cobb angle was significantly smaller than that before treatment (P<0.01) and the VAS score was significantly lower than that before treatment (P<0.01). Conclusion: Small-angle Tui-Pushing and An-Pressing anti-rotation bone-setting manipulation can improve the immediate efficacy of brace in treating adolescent idiopathic scoliosis and relieve the pain caused by brace wearing at the same time.

Objective: To explore the correlation between the expression status of human epidermal growth factor receptor 2 (HER-2) and the characteristics of conventional ultrasound, shear wave elastography(SWE) and contrast enhanced ultrasound(CEUS) images in breast cancer patients with negative expression of estrogen receptor (ER). Methods: In this study, 117 patients with 117 lesions were selected from the Second Hospital of Harbin Medical University Hospital, who had definite pathology and ER negative expression, including 62 patients with positive HER-2 (group Ⅰ) and 55 patients with negative HER-2(group Ⅱ). Conventional ultrasound images and SWE were collected preoperatively, and CEUS images were collected in 62 patients to analyze the correlation between the expression of HER-2 and the ultrasonic characteristics of the three ultrasonic modes. Results: ①Conventional ultrasound: the groupⅠwas characterized by irregular shape, unclear boundary, mainly with spicule edges, microcalcification, axillary lymph node metastasis and higher histological grading. The groupⅡhad no such characteristics (all P<0.05). ②SWE: the Emax, Emean and Eratio of group Ⅰ were higher than group Ⅱ(all P<0.05). ③CEUS: the peak time of group Ⅰ was earlier than group Ⅱ, the slope of ascending branch and the area under the curve were larger, and the characteristics of perforating vessels were easier to be observed, while perfusion defects were more likely to occur in groupⅡ(all P<0.05). Conclusions In the case of ER negative expression, there are obvious differences in multimodal sonograms of different breast cancer HER-2 expression conditions. The analysis of the above sonograms will play an important guiding role in the selection of clinical treatment plans.

Syphilis can not be cultured in vitro.So far, serologic testing is still regarded as the mainstay for diagnosing syphilis and for monitoring the efficacy of subsequent antibiotic treatment.However, single serological tests have limitations in sensitivity or specificity.Detective algorithms with two or more serological methods will help to improve the effectiveness of syphilis diagnosis, and decrease missed diagnosis and misdiagnosis.This article will review advances on etiological examination, serological tests, and detective algorithms for syphilis.In particular, it specially introduces the merits and demerits of three detective algorithms for syphilis,so as to explore suitable screening methods,and provide basis for relevant administrative departments to formulate related laws, regulations and guidelines for syphilis.

Objective To observe the clinical effect of traditional Chinese medicine bone-setting technique using spinal,pelvi-lower extremity line to treat patients with knee osteoarthritis(KOA).Methods 426 patients with KOA were all from the First Affiliated Hospital of Hebei University of Traditional Chinese Medicine.They were randomly divided into experimental group(384 cases,57 cases of elimination,shedding and termination)by computer generated sequence.Traditional Chinese bone setting techniques were applied with spinal-pelvic-lower limb force line(divided into three parts:lumbar fixed point reduction method,hip joint push-pull and extension method and knee peripheral tendon recovery method every 3 days.2 weeks)treatment;The control group was the waiting treatment group(48 cases,6 cases were eliminated,abscission,termination),which was only used for clinical observation for 2 weeks.The main outcome index was WOMAC pain score.Secondary outcome measures were WOMAC stiffness score,functional score,standardized score and quality of life score(SF-12).The test time points were baseline,2 weeks after enrollment,and follow-up(14 weeks after enrollment).The control group was at baseline and 2 weeks after enrollment.Results Compared with baseline,WOMAC pain score,stiffness score,functional score and standardized score were all decreased in 2 groups 2 weeks after enrollment(P<0.05),but the experimental group was significantly decreased compared with the control group(P<0.001).SF-12 quality of life scores were all higher than before(P<0.001),but the experimental group was significantly higher than the control group(P<0.001).At follow-up,compared with 2 weeks after enrollment,WOMAC pain scores were increased(P<0.001),WOMAC stiffness,joint function and standardized scores were decreased(P<0.001),and SF-12 scores were increased(P<0.001).Conclusion The use of spinal-pelvi-lower extremity line of traditional Chinese medicine bone-setting technique in the treatment of KOA is effective in improving the knee joint function and improving the quality of life of patients,but the short-term effect of pain relief is good,and the long-term effect is not good.Its safety is good,and it can be considered in clinical application for KOA patients with joint dysfunction as the main manifestation.

Objective:To develop a machine learning algorithm based on habitat imaging(HI),which can be used in the grading of gliomas by using multimodal magnetic resonance imaging(MRI),so as to construct the model of support vector machine(SVM)and the visualized heterogeneous regions of gliomas.Methods:A total of 335 glioma patients were collected from the 2019 brain tumor segmentation(BraTS)challenge competition of World Health Organization(WHO),which included 259 cases with high-grade gliomas(HGG)and 76 cases with low-grade gliomas(LGG).Subregions were divided based on HI technology.The PyRadiomics open-source package was used to extract the image features of region of interest(ROI),and to screen the features that stronger correlated with the high and low-grade gliomas.An SVM model was used to classify and predict the screened feature data.The heterogeneity of gliomas in images was analyzed through visualized characterization.The efficacy of glioma grading was assessed by using the area under curve(AUC)of the receiver operating characteristic(ROC)curve.Results:The AUC of test set exceeded 90%.The average accuracy of the performance indicators of test set was(92.74±2.88)%,and the average sensitivity was(93.90±2.10)%,and the average specificity was(90.36±4.59)%,and the average F1 score was(95.24±0.66)%when the tumors were divided into six habitat regions.The SVM model could showed important sub-regions in glioma grading in three-dimensional space.Conclusion:The study method based on HI has significant advantages in glioma grading,which can effectively realize visualized heterogeneity of tumor and construct model of the heterogeneity of tumor.

BACKGROUND:Based on different algorithms of machine learning,how to carry out clinical research on lumbar disc herniation with the help of various algorithmic models has become a trend and hot spot in the development of intelligent medicine at present. OBJECTIVE:To review the characteristics of different algorithmic models of machine learning in the diagnosis and treatment of lumbar disc herniation,and summarize the respective advantages and application strategies of algorithmic models for the same purpose. METHODS:The computer searched PubMed,Web of Science,EMBASE,CNKI,WanFang,VIP and China Biomedical(CBM)databases to extract the relevant articles on machine learning in the diagnosis and treatment of lumbar disc herniation.Finally,96 articles were included for analysis. RESULTS AND CONCLUSION:(1)Different algorithm models of machine learning provide intelligent and accurate application strategies for clinical diagnosis and treatment of lumbar disc herniation.(2)Traditional statistical methods and decision trees in supervised learning are simple and efficient in exploring risk factors and establishing diagnostic and prognostic models.Support vector machine is suitable for small data sets with high-dimensional features.As a nonlinear classifier,it can be applied to the recognition,segmentation and classification of normal or degenerative intervertebral discs,and to establish diagnostic and prognostic models.Ensemble learning can make up for the shortcomings of a single model.It has the ability to deal with high-dimensional data and improve the precision and accuracy of clinical prediction models.Artificial neural network improves the learning ability of the model,and can be applied to intervertebral disc recognition,classification and making clinical prediction models.On the basis of the above uses,deep learning can also optimize images and assist surgical operations.It is the most widely used model with the best performance in the diagnosis and treatment of lumbar disc herniation.The clustering algorithm in unsupervised learning is mainly used for disc segmentation and classification of different herniated segments.However,the clinical application of semi-supervised learning is relatively less.(3)At present,machine learning has certain clinical advantages in the identification and segmentation of lumbar intervertebral discs,classification and grading of the degenerative intervertebral discs,automatic clinical diagnosis and classification,construction of the clinical predictive model and auxiliary operation.(4)In recent years,the research strategy of machine learning has changed to the neural network and deep learning,and the deep learning algorithm with stronger learning ability will be the key to realizing intelligent medical treatment in the future.

BACKGROUND:In recent years,epidemiological studies have shown that sleep patterns are risk factors for osteoarthritis,but the causal relationship between sleep characteristics and osteoarthritis remains unknown. OBJECTIVE:To investigate the causal relationship between seven sleep phenotypes and osteoarthritis,thereby providing a theoretical foundation for clinical prevention and intervention of osteoarthritis. METHODS:Seven sleep-related features,namely sleep duration,wake-up time,daytime napping,morning/evening preference,snoring,insomnia,and hypersomnia,were selected from published genome-wide association studies.Instrumental variables for these sleep-related features were extracted.Instrumental variables for knee osteoarthritis and hip osteoarthritis were obtained from publicly available genome-wide association studies.Causal relationships between sleep characteristics and outcome risks were evaluated using two-sample and multivariable Mendelian randomization analyses.The inverse variance weighted method was employed as the primary Mendelian randomization approach.Various methods,including weighted median,weighted mode,Mendelian randomization-Egger regression,Mendelian randomization pleiotropy-residual sum and outlier,were utilized to detect and correct for the presence of pleiotropy. RESULTS AND CONCLUSION:The results of the inverse variance-weighted method in the two-sample Mendelian randomization study revealed a detrimental causal association between the duration of sleep and the incidence risk of knee osteoarthritis[odds ratio(OR)=0.621,95%confidence interval(CI):0.470-0.822,P=0.001].Concurrently,insomnia displayed a positive causal connection with hip osteoarthritis risk(OR=2.016,95%CI:1.249-3.254,P=0.005).Sensitivity analysis affirmed the robustness of these causal relationships,and Mendelian randomization-Egger intercept analysis found no evidence of potential horizontal pleiotropy(knee osteoarthritis:P=0.468,hip osteoarthritis:P=0.551).Moreover,the results from the multivariable Mendelian randomization analysis showed that the causal association between insomnia and hip osteoarthritis lacked statistical significance(P=0.715).In contrast,sleep duration exhibited a direct negative causal relationship with the incidence risk of knee osteoarthritis(OR=0.526,95%CI:0.336-0.824,P=0.005).Reverse Mendelian randomization analysis indicated that knee osteoarthritis did not influence sleep duration(P=0.757).These findings indicate a negative correlation between sleep duration and incidence risk of knee osteoarthritis,suggesting that correcting insufficient sleep might mitigate the incidence risk of knee osteoarthritis.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease of natural infectious focus caused by Hantavirus (HV) with clinical characteristics as fever, hemorrhage, hyperemia, hypotensive shock and renal damage. Through contacting the excreta or secretion of infected rats, human may get infected. The epidemiological characteristics of HFRS are significantly different in terms of population differences, geographical heterogeneity and seasonal variation, which are all closely related to the habitat of host animals and human productive activities. The reported number of HFRS is about 150 000 to 200 000 each year worldwide, and China accounted for 70 %-90 % of the total reported cases standing the most seriously infected country. In this study, we reviewed the epidemiological characteristics and the influencing factors of HFRS as well as the models and methods used in relevant ecological studies, in order to understand the distribution of time, regional and population and potential influencing factors on the transmission of HFRS better, so as to improve the strategies on investigation, monitoring, prevention and control of the diseases.

Objective To analyze the radiation exposure of medical personnel, and to provide real-time radiation dose monitoring data for medical personnel in interventional surgeries. Methods A total of 96 person-times who participated in cardiac surgeries in interventional operating rooms from September 2019 to March 2022 were selected as subjects. The subjects were divided into two groups according to the time progress, with 43 person-times in intervention group and 53 person-times in control group. The subjects in the intervention group were provided with radiation dose monitoring data during surgeries, while the subjects in the control group performed surgeries with routine procedures. The average intraoperative radiation dose rates of the two groups were compared. Results The median radiation dose rate was significantly lower in the intervention group than in the control group (88.80 μSv/h vs 188.40 μSv/h, U = 637.000, P = 0.000). Conclusion Providing real-time radiation dose monitoring data for medical personnel in interventional surgeries can effectively reduce their occupational radiation exposure and improve their occupational radiation protection.

Enzymes are widely used in chemical and pharmaceutical industries because of their advantages of high efficiency and specificity. However， the shortcomings of the free enzymes， such as poor stability and difficulty in recycling， limit their application. Therefore， the immobilization and application of enzymes have become one of the research hotspots. The selection of the immobilization carriers is a critical step in the process of enzyme immobilization. Metal-organic frameworks（MOFs）， a kind of porous materials， are formed by the coordination of metal ions or metal clusters with organic ligands. As an emerging immobilization carrier， its advantages such as high porosity， strong stability， and surface modifiability make it ideal for immobilized enzyme carriers. By immobilizing the free enzyme on MOFs， the above mentioned deficiencies of the free enzymes can be effectively solved， which greatly broaden the applicable condition. Ligand fishing is a method to find receptor-specific ligands from complex components， which has the advantages of high efficiency， simple sample pretreatment and high specificity. The MOF-enzyme complex formed by enzyme immobilization can act as a "fishing rod" for ligand fishing， which can screen out the targets from the complex system of components. The complex chemical composition and various active ingredients of traditional Chinese medicine（TCM） make the ligand fishing technology to play a big role in the screening of enzyme inhibitors from TCM. And the screened enzyme inhibitors are expected to be further developed into the lead compounds with good efficacy and low adverse effects， so the immobilized enzymes of MOFs have a wide application in the screening of active ingredients from TCM. Based on this， this paper summarized the methods of immobilized enzymes of MOFs in recent years， analyzed the characteristics， advantages and disadvantages of each method， and summarized the laws of preparation conditions and mechanisms. Meanwhile， the application and future development of immobilized enzymes of MOFs in the field of enzyme inhibitor screening from TCM were also summarized and prospected， with a view to providing a reference for the development of natural ingredients and the modernization of TCM.