OBJECTIVE:Neuromuscular exercise is a new comprehensive rehabilitation therapy in recent years,but its effect on knee osteoarthritis is still controversial.The purpose of this paper is to systematically evaluate the efficacy of neuromuscular exercise on knee osteoarthritis pain and function. METHODS:The randomized controlled trials addressing neuromuscular exercise in the treatment of knee osteoarthritis pain and function were retrieved from PubMed,Cochrane Library,Embase,EBSCO,CNKI,Web of Science,China Biomedical Database(CBM),VIP,and WanFang Database.The retrieval time ranged from database inception to October 2023.The neuromuscular training group(experimental group)was given neuromuscular training or neuromuscular training as the main intervention;the control group was a blank group or given conventional rehabilitation.Outcome indicators included the Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC)score,walking time,knee stability,and the maximum number of knee flexion in 30 seconds.The risk of bias was evaluated by the Cochrane Collaboration tool and the Physiotherapy Evidence Database.Meta-analysis was performed using RevMan 5.4 software. RESULTS:A total of 11 randomized controlled trials were included,and 628 samples were extracted.The results of Meta-analysis showed that the experimental group was superior to the control group in terms of WOMAC pain score[standardized mean difference(SMD)=0.38,95%confidence interval(CI):0.08-0.69,P=0.01],knee stability(SMD=0.57,95%CI:0.23-0.92,P=0.001),the maximum number of knee joint flexion in 30 seconds(SMD=0.35,95%CI:0.05-0.65,P=0.02),and WOMAC physical function score(SMD=-0.79,95%CI:-1.30 to-0.28,P=0.002).In both groups,walking speed was increased and walking ability was improved in patients with knee osteoarthritis,but there was no significant difference(walking time:SMD=-0.22,95%CI:-0.48-0.03,P=0.09). CONCLUSION:Neuromuscular exercise can effectively improve knee joint pain,enhance the stability of the knee joint,and promote functional recovery in patients with knee osteoarthritis.However,more high-quality randomized controlled trials are still needed to further confirm the research.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

Objective To investigate the diagnostic value of contrast-enhanced ultrasound(CEUS)combined with serum Smad ubiquitin regulatory factor 1(SMURF1)detection for thyroid cancer.Methods A total of 144 suspected thyroid cancer patients admitted to Lishui branch of Zhongda Hospital Affiliated to Southeast University from February 2019 to February 2020 were selected as the study subjects.Based on the histopathological results,they were divided into the thyroid cancer group(76 cases)and the benign group(68 cases).All patients underwent contrast-enhanced ultrasound examination and serum SMURF1 level detection;the diagnostic value of contrast-enhanced ultrasound parameters,serum SMURF1 detection alone,and the combination of the two methods for thyroid cancer were analyzed.Results Contrast-enhanced ultrasound parameters peak intensity(PI),mean perfusion intensity(SImean)and maximum perfusion intensity(SImax)in the thyroid cancer group were lower than those in the benign group,and the level of SMURF1 mRNA was higher than that in the benign group(P<0.05).The sensitivity of contrast-enhanced ultrasound parameter SImax in the diagnosis of thyroid cancer was 82.89%,the specificity was 72.06%,the accuracy was 77.78%,and the Kappa value was 0.552.The sensitivity of serum SMURF1 in the diagnosis of thyroid cancer was 65.79%,the specificity was 94.12%,the accuracy was 79.17%,and the Kappa value was 0.589.The sensitivity,specificity,accuracy and Kappa value of SImax combined with serum SMURF1 in the diagnosis of thyroid cancer were 97.37%,85.29%,91.67%and 0.832,respectively,which were higher than those of SImax and SMURF1 alone(P<0.05),the AUC of the combination of the two methods was 0.927,which was significantly higher than that of the two methods alone(Zcombined vs.SImax=3.999,P<0.001;Zcombined vs.SMURF1=3.270,P=0.001).Conclusion Contrast-enhanced ultrasound combined with serum SMURF1 detection can improve the diagnostic efficiency of thyroid cancer,which may avoid the over-diagnosis on the premise of ensuring the effective diagnosis of thyroid cancer patients.

Objective To investigate the risk factors for pediatric acute perforation appendicitis,and to construct a nomogram predictive model and conduct the verification.Methods A total of 426 children patients with appendectomy in this hospital from June 30,2020 to June 30,2022 were selected as the study subjects 340 children with acute appendicitis admitted to the hospital from 30 June 2020 to 28 February 2022 were the training set and 86 children patients with appendicitis hospitalized in this hospital from March 1,2022 to June 30,2022 conducted the external validation(verification set).The univariate and multivariate logistic regression models were employed to analyze the independent risk factors of pediatric acute perforation appendicitis.The nomograms predictive model was constructed.The receiver operating characteristic(ROC)curve and calibra-tion curve were used to evaluate the predictive efficiency of the model.The decision curve analysis(DCA)was used to evaluate the application value of the model.Results Of the 426 children,198 were perforated and 228 were not perforated.The univariate and multivariate logistic regression analyses revealed that elevated C-reac-tive protein(CRP),presence of stercorolith in appendiceal cavity,time of onset to visiting hospital ≥2 d and body temperature ≥37.3 ℃ were the independent risk factors for pediatric acute perforation appendicitis(P＜0.05).The Hosmer-Lemeshow test demonstrated that the nomogram predictive model had good fitting(P=0.869),and the area under the curve(AUC)for the training and validation sets were 0.808 and 0.860 respectively,showing the good predictive ability of the model.The calibration curve closely approach the ideal diagonal.The model showed good discrimination,consistency and accuracy.The DC A revealed that the curve was far away from oblique and horizontal lines,and the model had good clinical practicability.Conclusion The constructed nomogram model of pediatric acute perforation appendicitis has good predictive ability and may help clinic to identify as early as possible.

Objective To investigate the acupoint selection rules of obesity complicated with type 2 diabetes mellitus(T2DM)through R language data mining technology.Methods CNKI,Wanfang,VIP,CBM,PubMed,Embase,Cochrane Library,web of science and other major databases were searched by computer.From the establishment of the database to January 2024,the clinical research literature on acupuncture and moxibustion for the treatment of obesity with T2DM was included.Microsoft Excel 2021 was used to establish a database of acupoint prescriptions.R 4.3.2 and Rstudio software were used to analyze the frequency,meridian tropism,specific acupoints,correlation analysis,association rules and cluster analysis of acupoints.Results A total of 81 articles were included,and 117 prescriptions were extracted.It involves 82 acupoints,and the total frequency of acupoint usage is 1 072 times.The top five acupoints with the highest frequency were Zusanli(ST36),Zhongwan(RN12),Weiwanxiashu(EX-B3),Pishu(BL20),Tianshu(ST25).The meridian selection is mainly based on the stomach meridian of foot yangming,ren meridian,foot taiyang bladder meridian and foot taiyin spleen meridian.The five-shu points are the specific points with the highest frequency of use.Correlation analysis showed that there were three groups of strongly related acupoint groups.The core acupoints were obtained by association rule analysis.Cluster analysis and machine voting were performed on acupoints with frequency ≥ 10 by function,and a total of four cluster acupoint groups were obtained.Conclusion Through R language data analysis,the principle of acupoint selection for acupuncture and moxibustion in the treatment of obesity complicated with T2DM is mainly based on abdominal local acupoints,combined with visceral syndrome differentiation and empirical point selection,which provides effective treatment ideas for acupuncture and moxibustion in the treatment of obesity complicated with T2DM.

Tinnitus is a clinically refractory disease with a high incidence.LAI's Tongyuan acupuncture method believes that tinnitus is nothing more than the two ends of deficiency and excess.The deficiency is closely related to original spirit,and the excess is related to the pathological factors such as externally-contracted six pathogenic factors,phlegm-damp and blood stasis,and qi stagnation and yang constraint.The Tongyuan acupuncture method is based on original spirit,takes the two vessels of conception vessel(CV)and governor vessel(GV)as the general outline,takes the regulation of yin and yang as the main method,pays attention to the combination of local and overall,and emphasizes the application of tonification and purgation,and has the clinical effect of reinforcing healthy qi and dispelling pathogen,cultivating the vital essence.In clinical application,the method of'unblocking governor vessel and nourishing spirit'is used to play the role of heart and brain nourishing spirit and warming and supporting yang qi.The method of'conducting qi back to its source'has the effect of cultivating the vital essence and regulating qi movement.The treatments should be cooperated according to the syndromes,so that the pathogens can be expelled and healthy qi can be settled.Qi and blood have origins of generation and transformation and normally nourishing in the ear,so as to effectively alleviate the patient's tinnitus symptoms.This paper summarizes and analyzes Professor LAI Xin-Sheng's Experience in the diagnosis and treatment of tinnitus by Tongyuan acupuncture method,and provides a new acupuncture treatment plan for clinical application.

Crawling is a significant sign of gross motor development in infants,and also an important means of rehabilitation training for patients with motor disorders.The accurate measurement of the motion state during human crawling is essential for evaluating the gross motor developmental process in infants and the rehabilitation outcome of patients with motor disorders.In recent years,many studies have attempted to quantitatively evaluate the motion state by detecting physiological signals during human crawling,but there is a lack of overview on human crawling motion signal acquisition and processing.Herein the detection and processing methods for motion signals during human crawling and relevant researches are reviewed.The mainstream methods for detecting motion signals during human crawling are introduced from the perspectives of inertial sensors,pressure sensors,and surface electromyography.Then,the signal processing and analysis such as periodic segmentation,kinematic analysis,and dynamic analysis in human crawling are summarized.Based on the theory of motion coordination,the research advances in joint synergy and muscle synergy during human crawling are elaborated.Finally,the current problems and future development directions of motion analysis for human crawling are discussed.

Purpose To analyze the multimodal imaging manifestations of phosphaturic mesenchymal tumor.Materials and Methods A retrospective analysis was performed on ten patients with phosphaturic mesenchymal tumor confirmed by pathology and molecular imaging from November 2012 to June 2022 in Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology.The imaging features of CT in four cases,of MRI in seven cases,and of nuclear medicine in ten cases were reviewed,along with the clinical characteristics of all patients.Results The main clinical symptoms of ten patients,eight cases had pain,four cases had weakness,and nine cases had multiple fractures.Laboratory tests results:ten cases showed decreased blood phosphorus,six cases showed decreased blood 25-hydroxyvitamin D and ten cases showed elevated blood alkaline phosphatase.The lesions were heterogeneous in four cases on CT scans and in six cases on MRI scans.Calcification was common,and some had cysts and fatty components.After enhancement,seven cases showed moderate to obvious uneven enhancement.99Tcm-MDP SPECT showed increased uptake of multiple bones and joints in eight cases,18F-FDG PET/CT showed no or slight increase in lesion metabolism in eight cases,68Ga-DOTATATE PET/CT showed significantly high uptake at the lesion site in ten cases.Conclusion Phosphaturic mesenchymal tumor patients typically present with pain,fractures and hypophosphatemia.The conventional imaging features are characterized by small and concealed lesions and complex components.Particularly,68Ga-DOTATATE PET/CT imaging exhibits high sensitivity for the tumor detection.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.