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: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.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

OBJECTIVE: To explore the clinical efficacy of orthopedic manipulation combined with daoyin exercises in the treatment of chronic lumbar disc herniation under the guidance of the theory of "equal emphasis on muscles and bones". METHODS: A total of 60 patients with single-segment, unilateral chronic lumbar disc herniation from January 2023 to January 2024 were randomly divided into the traditional physical therapy group and the manipulation treatment group, with 30 cases in each group. Among them, 3 cases were lost to follow-up in the traditional physical therapy group and 2 cases in the manipulation treatment group. There were 27 cases in the traditional physical therapy group, including 15 males and 12 females, aged 25 to 65 years old with an average of (51.96±14.42) years;the course of disease ranged from 3 to 15 months with an average of (9.89±3.32) months;11 cases were on the left side and 16 cases on the right side;15 cases were at the L4, 5 segment and 12 cases at the L5S1 segment. They were treated with lumbar traction, medium-frequency electrical stimulation and ultrasonic therapy. There were 28 cases in the manipulation treatment group, including 14 males and 14 females, aged 24 to 68 years old with an average of (49.82±14.85) years old;the course of disease ranged from 3 to 14 months with an average of (9.61±3.05) months;15 cases were on the left side and 13 cases on the right side;17 cases were at the L4, 5 segment and 11 cases at the L5S1 segment. They were treated with orthopedic manipulation combined with daoyin exercises. The visual analogue scale (VAS), Oswestry disability index (ODI) and bilateral erector spinae muscle tone were compared between the two groups before treatment, after 2 weeks and 4 weeks of treatment. RESULTS: The two groups of patients were followed up and evaluated before treatment, 2 weeks and 4 weeks after treatment. The VAS of the manipulation treatment group and the traditional physical therapy group decreased from (5.46±0.99) and (5.41±1.05) points before treatment to (1.75±0.79) and (2.29±0.82) points after 4 weeks of treatment, respectively. Both groups were significantly improved after treatment compared with before treatment, and the differences were statistically significant (P<0.05);and the manipulation treatment group was better than the traditional physical therapy group at 4 weeks of treatment, with a statistically significant difference (P<0.05). The ODI of the manipulation treatment group and the traditional physical therapy group before treatment was (20.25±2.72) and (18.96±2.52) points, respectively, which decreased to (15.46±1.88) and (16.56±2.01) points after 2 weeks of treatment, and to (11.54±1.23) and (12.85±1.72) points after 4 weeks of treatment. Both groups were significantly improved after treatment compared with before treatment, and the differences were statistically significant (P<0.05), and the ODI in the manipulation treatment group was better than that in the traditional physical therapy group after treatment (P<0.05). There was no significant statistical difference in the displacement of erector spinae muscle tone between the healthy side and the affected side in both the manipulation treatment group and the traditional physical therapy group before treatment (P>0.05). After 2 weeks of treatment, the displacement values of erector spinae muscle tone on the healthy side in the manipulation treatment group and the traditional physical therapy group were (6.68±0.81) mm and (6.45±0.65) mm, respectively, and those on the affected side were (5.87±0.82) mm and (5.61±0.84) mm, respectively. After 4 weeks of treatment, the displacement values of erector spinae muscle tone on the healthy side in the manipulation treatment group and the traditional physical therapy group were (7.51±0.75) mm and (7.04±0.63) mm, respectively, and those on the affected side were (6.87±0.78) mm and (6.33±0.82) mm, respectively. The displacement values of erector spinae muscle tone on both the healthy and affected sides in both groups were significantly higher than those before treatment, and the differences were statistically significant (P<0.05);the displacement of erector spinae muscle tone in the manipulation treatment group after 4 weeks of treatment was better than that in the traditional physical therapy group, with a statistically significant difference (P<0.05). CONCLUSION Orthopedic manipulation combined with daoyin exercises can effectively improve the symptoms and lumbar function of patients with chronic lumbar disc herniation, and has more advantages in improving the tone of the erector spinae muscle.
Humans ; Male ; Female ; Middle Aged ; Adult ; Intervertebral Disc Displacement/physiopathology* ; Aged ; Lumbar Vertebrae/injuries* ; Exercise Therapy ; Chronic Disease/therapy* ; Manipulation, Orthopedic ; Combined Modality Therapy

The connection between tendons and bones is called the tendon bone connection. With the continuous improvement of national sports awareness, excessive exercises and the related intensity are prone to damage the tendon bone connection. Tendon bone healing is a complex repair and healing process involving multiple factors, and good tendon bone healing is a prerequisite for its physiological function. The complexity of tendon bone structure also poses great challenges to the repair of tendon bone injuries. In recent years, researches have found that stem cells, growth factors, macrophages, and other factors are closely related to the healing process of tendon bone injuries, among which macrophages play an important role in the healing process. The authors reviewed relevant research literature in recent years and summarized the role of macrophages in tendon bone healing, in order to provide new ideas and directions for treatment strategies to promote tendon bone healing.
Humans ; Macrophages/metabolism* ; Wound Healing ; Animals ; Tendons/physiology* ; Bone and Bones/injuries* ; Tendon Injuries

PURPOSE: To methodically assess the effectiveness of augmentative plating (AP) and exchange nailing (EN) in managing nonunion following intramedullary nailing for long bone fractures of the lower extremity. METHODS: PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to gather clinical studies regarding the use of AP and EN techniques in the treatment of nonunion following intramedullary nailing of lower extremity long bones. The search was conducted up until May 2023. The original studies underwent an independent assessment of their quality, a process conducted utilizing the Newcastle-Ottawa scale. Data were retrieved from these studies, and meta-analysis was executed utilizing Review Manager 5.3. RESULTS: This meta-analysis included 8 studies involving 661 participants, with 305 in the AP group and 356 in the EN group. The results of the meta-analysis demonstrated that the AP group exhibited a higher rate of union (odds ratio: 8.61, 95% confidence intervals (CI): 4.12 - 17.99, p < 0.001), shorter union time (standardized mean difference (SMD): -1.08, 95% CI: -1.79 - -0.37, p = 0.003), reduced duration of the surgical procedure (SMD: -0.56, 95% CI: -0.93 - -0.19, p = 0.003), less bleeding (SMD: -1.5, 95% CI: -2.81 - -0.18, p = 0.03), and a lower incidence of complications (relative risk: -0.17, 95% CI: -0.27 - -0.06, p = 0.001). In the subgroup analysis, the time for union in the AP group in nonisthmal and isthmal nonunion of lower extremity long bones was shorter compared to the EN group (nonisthmal SMD: -1.94, 95% CI: -3.28 - -0.61, p < 0.001; isthmal SMD: -1.08, 95% CI: -1.64 - -0.52, p = 0.002). CONCLUSION In the treatment of nonunion in diaphyseal fractures of the long bones in the lower extremity, the AP approach is superior to EN, both intraoperatively (with reduced duration of the surgical procedure and diminished blood loss) and postoperatively (with an elevated union rate, shorter union time, and lower incidence of complications). Specifically, in the management of nonunion of lower extremity long bones with non-isthmal and isthmal intramedullary nails, AP demonstrated shorter union time in comparison to EN.
Humans ; Bone Nails/adverse effects* ; Bone Plates/adverse effects* ; Femoral Fractures/surgery* ; Fracture Fixation, Intramedullary/methods* ; Fractures, Ununited/surgery* ; Lower Extremity/injuries*

OBJECTIVES: To analyze the potential causal relationship between gut microbiota and food allergy (FA) using two-sample Mendelian randomization (MR) methods. METHODS: Data from genome-wide association studies on gut microbiota and FA were utilized. MR analysis was conducted employing inverse variance weighting, MR-Egger regression, and weighted median methods to assess the causal relationship between gut microbiota and FA. Cochrane's Q test was used to evaluate heterogeneity of instrumental variables, MR-PRESSO analysis was conducted to test for outliers and pleiotropy, and MR-Egger regression was employed to assess horizontal pleiotropy. The "leave-one-out" method was used to evaluate the impact of removing individual single nucleotide polymorphisms on the causal relationship. RESULTS: Inverse variance weighting analysis revealed that the phylum Verrucomicrobia, family Verrucomicrobiaceae, order Verrucomicrobiales, genus Ruminococcaceae UCG013, and genus Akkermansia were negatively associated with FA (P<0.05). Sensitivity analyses confirmed the reliability of the findings, indicating no heterogeneity or pleiotropy present. CONCLUSIONS There is a causal relationship between gut microbiota and FA, with Verrucomicrobia, Verrucomicrobiaceae, Verrucomicrobiales, Ruminococcaceae UCG013, and Akkermansia potentially reducing the risk of developing FA. These findings provide potential targets for the treatment and prevention of FA; however, further research is needed to explore the specific mechanisms by which the microbiota influence FA.
Humans ; Mendelian Randomization Analysis ; Gastrointestinal Microbiome ; Food Hypersensitivity/microbiology* ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide

OBJECTIVES: To investigate the molecular epidemiology of children with phenylketonuria (PKU) in Gansu, China, providing foundational data for intervention strategies. METHODS: A retrospective analysis was conducted on 1 159 PKU families who attended Gansu Provincial Maternity and Child Care Hospital from January 2012 to December 2024. Sanger sequencing, multiplex ligation-dependent probe amplification, whole exome sequencing, and deep intronic variant analysis were used to analyze the PAH gene. RESULTS: For the 1 159 children with PKU, 2 295 variants were identified in 2 318 alleles, resulting in a detection rate of 99.01%. The detection rates were 100% (914/914) in 457 classic PKU families, 99.45% (907/912) in 456 mild PKU families, and 96.34% (474/492) in 246 mild hyperphenylalaninemia families. The 2 295 variants detected comprised 208 distinct mutation types, among which c.728G>A (14.95%, 343/2 295) had the highest frequency, followed by c.611A>G (4.88%, 112/2 295) and c.721C>T (4.79%, 110/2 295). The cumulative frequency of the top 23 hotspot variants reached 70.28% (1 613/2 295), and most variant alleles were detected in exon 7 (29.19%, 670/2 295). CONCLUSIONS Deep intronic variant analysis of the PAH gene can improve the genetic diagnostic rate of PKU. The development of targeted detection kits for PAH hotspot variants may enable precision screening programs and enhance preventive strategies for PKU.
Humans ; Phenylketonurias/epidemiology* ; Female ; Male ; Retrospective Studies ; Phenylalanine Hydroxylase/genetics* ; Mutation ; Child, Preschool ; China/epidemiology* ; Child ; Infant