OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

ObjectiveBased on the clinical characteristics of chronic gouty arthritis （CGA） in both traditional Chinese and western medicine， this study aims to systematically evaluate the clinical concordance of existing CGA animal models， providing recommendations for establishing animal models that align with the pathological characteristics of CGA and the manifestations of traditional Chinese medicine syndromes. MethodsBy comprehensively retrieving Chinese and international databases such as China National Knowledge Infrastructure， Wanfang， VIP Chinese Science and Technology Periodical Database （VIP）， and PubMed， all relevant literature on CGA animal models was collected. Based on the guidelines， the diagnostic criteria of both traditional Chinese and western medicine were summarized and organized. The evaluation indicators for the CGA model were constructed with reference to existing evaluation modes， and the CGA animal models were analyzed to systematically evaluate the clinical concordance of existing models. ResultsThe current methods used to construct CGA animal models mainly include monosodium urate crystal induction， high-protein diet induction （poultry lack urate oxidase）， and high-fat diet combined with urate oxidase inhibitors and joint injection. Based on 11 pieces of included literature， the traditional Chinese and western medicine scoring data of each model were extracted， and the average scoring values of all models were ultimately calculated. The results show that the average clinical concordances of existing CGA animal models in both traditional Chinese and western medicine are 43.33% and 64.44%， respectively. Among them， the model with the highest clinical concordance rate is the one with a high-fat diet combined with potassium oxonate to induce hyperuricemia plus joint injection， achieving 83.33% clinical concordance in western medicine and 60% in traditional Chinese medicine. This model aligns well with the pathogenic characteristics and pathological changes of clinical CGA. ConclusionAlthough current CGA animal models can simulate some pathological characteristics of CGA， they struggle to comprehensively reflect the complex pathological processes of CGA and the characteristics of traditional Chinese medicine syndromes. Therefore， in the future， it is necessary to establish the CGA animal models that incorporate the clinical disease and syndrome characteristics of traditional Chinese and western medicine and formulate the uniform model evaluation criteria， providing more precise tools for CGA mechanism research and the development of traditional Chinese medicine.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Aim To investigate the protective effect of liraglutide(LIRA)on acetaminophen(APAP)-in-duced hepatotoxicity at the in vivo level and to reveal the underlying mechanism.Methods Forty SPF grade male C57BL/6J mice were randomly divided into the Control,LIRA(200 μg·kg-1),APAP(500 mg·kg-1),LIRA+APAP,LIRA+APAP+3-methylade-nine(3-MA,30 mg·kg-1)groups,with eight mice in each group.The mice were administered for three con-secutive days,and the materials were taken after 24 h.The general condition and body weight of mice in each group were recorded,and liver morphology was ob-served.Serum ALT and AST levels,as well as SOD ac-tivity,MDA,and GSH content in liver homogenates,were measured using biochemical assay kits.The levels of inflammatory cytokines IL-6,TNF-α,and IL-1β in serum were detected by ELISA.Liver pathological changes were assessed by HE staining,while mitochon-drial and autophagosome structures in liver tissues were observed using transmission electron microscopy.The number of PCNA-positive cells in liver tissues was e-valuated using immunohistochemical staining.The pro-tein expression levels of LC3Ⅱ,p62,Bax,Bcl-2,PC-NA,and CyclinD1 in liver tissues were determined by Western blot.Results LIRA pretreatment can im-prove the general condition of mice with acetamino-phen-induced liver injury(AILI),reduce serum ALT and AST levels,and effectively ameliorate the appear-ance and morphology of the liver as well as the patho-logical damage to liver tissue.Simultaneously,the lev-els of inflammatory cytokines IL-6,TNF-α,and IL-1βare significantly decreased;SOD activity and GSH con-tent are significantly increased,while MDA content is significantly reduced.Transmission electron microsco-py observations reveal the presence of numerous auto-phagosomes in the cytoplasm of liver tissue.Immuno-histochemical staining results indicate a significant in-crease in the number of PCNA-positive cells.Further-more,the expression of LC3Ⅱ,Bcl-2,PCNA,and Cy-clinD1 proteins in liver tissue is significantly upregulat-ed,while the expression of p62 and Bax proteins is significantly downregulated.However,after interven-tion with the autophagy inhibitor 3-MA,the aforemen-tioned protective effects of LIRA are significantly.Conclusions LIRA pretreatment can significantly im-prove liver injury in AILI mice.Its protective mecha-nism may be related to enhancing autophagy in hepato-cytes,thereby reducing oxidative stress,inflammatory response and apoptosis in liver of AILI mice.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To investigate the effect of individual pretreatment of preoperative medical multi-dimensional carbohydrates on intraoperative body temperature in elderly patients with hip replacement under general anesthesia. Methods A total of 81 elderly patients who underwent unilateral hip replacement in Yancheng Third People's Hospital from January 2022 to June 2024 were selected as the study subjects,and they were randomly divided into the conventional group and the pretreatment group. Both groups of patients were given routine fasting and drinking restriction before operation,and patients in the pretreatment group were given individual pretreatment of 5 mL/kg medical multi-dimensional carbohydrates 2 hours before anesthesia. The perioperative related indicators,body temperature,intraoperative hypothermia,adverse reactions during the recovery period,and pre-anesthesia gastric antral ultrasound examination results of patients in the two groups were compared. Results There was no statistically significant difference in the surgical time or intraoperative intravenous fluid infusion between the two groups (P>0.05). The anesthesia recovery time,tracheal extubation time and intraoperative bleeding volume of patients in the pretreatment group were significantly shorter/less than those in the conventional group (P<0.05). At 30 minutes,60 minutes and the end of the surgery,the body temperature of patients in the pretreatment group was significantly higher than that in the conventional group (P<0.05),and the incidences of intraoperative hypothermia and shivering in the pretreatment group were significantly lower than those in the conventional group (P<0.05). There was no statistically significant difference in the cross-sectional area (CSA) of gastric antrum,gastric volume (GV) or ratio of gastric volume/weight (GV/W) between the two groups of patients (P>0.05). Conclusion The individual pretreatment of 5 mL/kg medical multi-dimensional carbohydrates before surgery can significantly reduce the incidence of intraoperative hypothermia in elderly patients with hip replacement under general anesthesia,promote anesthesia recovery,reduce intraoperative bleeding volume and adverse reactions,and not increase the risk of reflux aspiration.

BACKGROUND: Modern acupuncture anesthesia is a combination of Chinese and Western medicine that integrates the theories of acupuncture with anesthesia. However, some clinical studies of acupuncture anesthesia lack specific descriptions of randomization, allocation concealment, and blinding processes, with subsequent systematic reviews indicating a risk of bias. OBJECTIVE: Clinical trial registration is essential for the enhancement of the quality of clinical trials. This study aims to summarize the status of clinical trial registrations for acupuncture anesthesia listed on the World Health Organization International Clinical Trials Registry Platform (ICTRP). SEARCH STRATEGY: We searched the ICTRP for clinical trials related to acupuncture anesthesia registered between January 1, 2001 and May 31, 2023. Additionally, related publications were retrieved from PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Data. Registrations and publications were analyzed for consistency in trial design characteristics. INCLUSION CRITERIA: Clinical trials that utilized one of several acupuncture-related therapies in combination with pharmacological anesthesia during the perioperative period were eligible for this review. DATA EXTRACTION AND ANALYSIS: Data extracted from articles included type of surgical procedure, perioperative symptoms, study methodology, type of intervention, trial recruitment information, and publication information related to clinical enrollment. RESULTS: A total of 166 trials related to acupuncture anesthesia from 21 countries were included in the analysis. The commonly reported symptoms in the included studies were postoperative nausea and vomiting (19.9%) and postoperative pain (13.3%). The concordance between the publications and the trial protocols in the clinical registry records was poor, with only 31.7% of the studies being fully compatible. Inconsistency rates were high for sample size (39.0%, 16/41), blinding (36.6%, 15/41), and secondary outcome indicators (24.4%, 10/41). CONCLUSION The volume of acupuncture anesthesia clinical trials registered in international trial registries over the last 20 years is low, with insufficient disclosure of results. Postoperative nausea and vomiting as well as postoperative pain, are the most investigated for acupuncture intervention. Please cite this article as: Li Y, Liu YN, Guo Z, Gu ME, Wang WJ, Zhu Y, Zhuang XJ, Chen LM, Zhou J, Li J. Current situation of clinical trial registration in acupuncture anesthesia: A scoping review. J Integr Med. 2025; 23(3): 256-263.
Humans ; Acupuncture Analgesia ; Acupuncture Therapy ; Anesthesia ; Clinical Trials as Topic ; Registries

Osteoporosis is a prevalent skeletal condition characterized by reduced bone mass and strength, leading to increased fragility. Buqi-Tongluo (BQTL) decoction, a traditional Chinese medicine (TCM) prescription, has yet to be fully evaluated for its potential in treating bone diseases such as osteoporosis. To investigate the mechanism by which BQTL decoction inhibits osteoclast differentiation in vitro and validate these findings through in vivo experiments. We employed MTS assays to assess the potential proliferative or toxic effects of BQTL on bone marrow macrophages (BMMs) at various concentrations. TRAcP experiments were conducted to examine BQTL's impact on osteoclast differentiation. RT-PCR and Western blot analyses were utilized to evaluate the relative expression levels of osteoclast-specific genes and proteins under BQTL stimulation. Finally, in vivo experiments were performed using an osteoporosis model to further validate the in vitro findings. This study revealed that BQTL suppressed receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and osteoclast resorption activity in vitro in a dose-dependent manner without observable cytotoxicity. The inhibitory effects of BQTL on osteoclast formation and function were attributed to the downregulation of NFATc1 and c-fos activity, primarily through attenuation of the MAPK, NF-κB, and Calcineurin signaling pathways. BQTL's inhibitory capacity was further examined in vivo using an ovariectomized (OVX) rat model, demonstrating a strong protective effect against bone loss. BQTL may serve as an effective therapeutic TCM for the treatment of postmenopausal osteoporosis and the alleviation of bone loss induced by estrogen deficiency and related conditions.
Animals ; NFATC Transcription Factors/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Ovariectomy ; Osteoclasts/metabolism* ; Female ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; NF-kappa B/genetics* ; Osteoporosis/genetics* ; Signal Transduction/drug effects* ; Bone Resorption/genetics* ; Cell Differentiation/drug effects* ; Humans ; RANK Ligand/metabolism* ; Mitogen-Activated Protein Kinases/genetics* ; Transcription Factors

BACKGROUND:Hemivertebra deformity should be treated surgically at an early age,but the risk factors for progression of deformity after hemivertebral resection have not been established.OBJECTIVE:To investigate the curative effect of one-stage posterior hemivertebrae resection and pedicle screw fixation in the treatment of congenital scoliosis,and to further explore the risk factors causing the progression of postoperative deformity.METHODS:The medical records of patients who underwent pedicle screw-rod fixation for unilateral hemivertebral deformity from January 2012 to February 2020 and were followed up for at least 2 years were retrospectively analyzed,and a total of 116 patients met the inclusion criteria.All patients were treated with standing anterior and lateral spinal radiographs taken before,after and at each follow-up time point.The segment Cobb angle,the total scoliosis Cobb angle,the proximal complementary Cobb angle,the distal complementary Cobb angle,and the coronal balance distance,apical vertebra distance,upper instrumented vertebra tilt,upper instrumented vertebra disc angle,lower instrumented vertebra tilt,lower instrumented vertebra disc angle,segmental kyphosis/lordosis,thoracic kyphosis,lumbar lordosis and sagittal vertical axis were measured.The progression of deformity and complications were also recorded.RESULTS AND CONCLUSION:(1)Segment Cobb,total scoliosis Cobb,segmental kyphosis,proximal complementary Cobb,and distal complementary Cobb were significantly corrected after operation(P＜0.05),and remained corrected at the last follow-up.Thoracic kyphosis,lumbar lordosis,coronal balance distance,and sagittal vertical axis were all in the normal range pre-operation,after operation and at the last follow-up.(2)During follow-up,10 patients developed coronary decompensation,which was characterized by abnormal progression.(3)Independent sample t-test showed that preoperative total scoliosis Cobb,preoperative apical vertebra distance,age,Risser sign,postoperative upper instrument vertebra tilt and postoperative lowest instrumented vertebra tilt were correlated with postoperative malformation progression(P＜0.05).(4)Multivariate Logistic regression analysis showed that postoperative lowest instrumented vertebra tilt was an independent risk factor for postoperative malformation progression(P=0.002,OR=1.526).(5)Receiver operating characteristic curve analysis showed that a postoperative lowest instrumented vertebra tilt of 8.14° was the optimal threshold for deformity progression after hemivertebrae resection and pedicle rod fixation(sensitivity 0.900,specificity 0.906,area under curve:0.926).(6)It is indicated that the treatment of congenital scoliosis with one-stage posterior hemivertebrae resection and pedicle nail fixation can achieve satisfactory orthopedic effect.Postoperative lowest instrumented vertebra tilt greater than 8.14° was an independent risk factor for postoperative coronal decompensation.