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.

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding

This study investigates the mechanism by which Xintong Granules improve myocardial ischemia-reperfusion injury(MIRI) through the regulation of gut microbiota and their metabolites, specifically short-chain fatty acids(SCFAs). Rats were randomly divided based on body weight into the sham operation group, model group, low-dose Xintong Granules group(1.43 g·kg~(-1)·d~(-1)), medium-dose Xintong Granules group(2.86 g·kg~(-1)·d~(-1)), high-dose Xintong Granules group(5.72 g·kg~(-1)·d~(-1)), and metoprolol group(10 mg·kg~(-1)·d~(-1)). After 14 days of pre-administration, the MIRI rat model was established by ligating the left anterior descending coronary artery. The myocardial infarction area was assessed using the 2,3,5-triphenyltetrazolium chloride(TTC) staining method. Apoptosis in tissue cells was detected by the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL) assay. Pathological changes in myocardial cells and colonic tissue were observed using hematoxylin-eosin(HE) staining. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6), creatine kinase MB isoenzyme(CK-MB), and cardiac troponin T(cTnT) in rat serum were quantitatively measured using enzyme-linked immunosorbent assay(ELISA) kits. The activities of lactate dehydrogenase(LDH), creatine kinase(CK), and superoxide dismutase(SOD) in myocardial tissue, as well as the level of malondialdehyde(MDA), were determined using colorimetric assays. Gut microbiota composition was analyzed by 16S rDNA sequencing, and fecal SCFAs were quantified using gas chromatography-mass spectrometry(GC-MS). The results show that Xintong Granules significantly reduced the myocardial infarction area, suppressed cardiomyocyte apoptosis, and decreased serum levels of pro-inflammatory cytokines(TNF-α, IL-1β, and IL-6), myocardial injury markers(CK-MB, cTnT, LDH, and CK), and oxidative stress marker MDA. Additionally, Xintong Granules significantly improved intestinal inflammation in MIRI rats, regulated gut microbiota composition and diversity, and increased the levels of SCFAs(acetate, propionate, isobutyrate, etc.). In summary, Xintong Granules effectively alleviate MIRI symptoms. This study preliminarily confirms that Xintong Granules exert their inhibitory effects on MIRI by regulating gut microbiota imbalance and increasing SCFA levels.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Myocardial Reperfusion Injury/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Apoptosis/drug effects* ; Humans ; Tumor Necrosis Factor-alpha/metabolism* ; Interleukin-6/genetics* ; Malondialdehyde/metabolism*

The efficacy mechanism of the alcoholic extract of Gnaphalium affine was investigated by observing its influence on oxidative stress and intestinal flora in rats modeled for chronic obstructive pulmonary disease(COPD). UPLC-MS was used to evaluate the quality of the alcoholic extract of G. affine, and 72 rats were randomly divided into six groups, with COPD models established in five groups by cigarette smoke combined with airway drip lipopolysaccharide, and the rats were given the positive drug of Danlong Oral Solution, as well as low-, medium-, and high-doses alcoholic extract of G. affine, respectively. After two weeks of continuous gastric gavage, the body weights and general morphology observations were performed; HE staining and Masson staining were used to verify the effects of the alcoholic extract of G. affine on alveolar inflammation and collagen deposition area in COPD rats; the oxidative stress indexes CAT and GSH in serum and SOD and MDA in lung tissue of the rats were measured, and the mRNA expression of HO-1, Nrf2, and NQO1 were determined by qRT-PCR. The protein expressions of HO-1, Nrf2, and NQO1 were determined by the Western blot method, and the mechanism by which the alcoholic extract of G. affine affected oxidative stress in COPD rats was explored. Finally, the influence of G. affine on the changes in intestinal flora caused by COPD was studied by 16S rRNA sequencing. The results showed that a total of 121 chemical components were identified by UPLC-MS, including 70 positive and 51 negative ion modes. In animal experiments, it was found that the alcoholic extracts of G. affine were able to reduce the percentage of collagen deposition, affect the oxidative stress indexes such as CAT, GSH, SOD, MDA, as well as the mRNA and protein expression of Nrf2, HO-1, and NQO1. The 16S rRNA sequencing results showed an increase in the level of Lactobacillales and a decrease in the level of Desulfovibrio and Desulfovibrionales, suggesting that the alcoholic extracts of G. affine could reverse the changes in intestinal flora caused by COPD. In conclusion, the alcoholic extracts of G. affine may exert anti-COPD effects by affecting the oxidative stress pathway and modulating the changes in intestinal flora.
Animals ; Oxidative Stress/drug effects* ; Pulmonary Disease, Chronic Obstructive/genetics* ; Rats ; Male ; Gastrointestinal Microbiome/drug effects* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; NF-E2-Related Factor 2/metabolism* ; Humans ; Lung/metabolism*

OBJECTIVE: To explore the corrective strategies and effectiveness of osteotomy surgery for severe lower limb deformities in hypophosphatemic rickets. METHODS: A retrospective analysis was conducted on 29 patients with severe lower limb deformities of hypophosphatemic rickets who underwent surgical treatment between February 2012 and August 2024. There were 9 males and 20 females. The age ranged from 13 to 53 years, with an average of 24.6 years. All patients were deformities of both lower limbs, presenting as 24 cases of O-shaped legs, 2 cases of wind-blown deformities, and 3 cases of X-shaped legs. Based on the full-length films of both lower limbs in the standing position before operation, the osteotomy planes of the femur, tibia, and fibula were designed. Among them, if both the same-sided thigh and leg were deformed, staged surgeries of both lower limbs were selected. If only the thigh or leg were deformed, simultaneous surgeries of both lower limbs were selected. The femur deformity was corrected immediately after osteotomy at the deformed plane; the osteotomy fragment was temporarily controlled with an external fixator, which was removed after perform internal fixation with a steel plate. After fibular osteotomy, the Ilizarov frame or Taylor frame was installed on the tibia and fibula. The threaded rods were removed and then tibial osteotomy was performed on the deformed plane. Patients using the Taylor frame did not undergo deformity correction during operation. The external fixators were adjusted starting 7 days after operation to correct the varus, valgus, and rotational deformities of the lower limb. Patients using the Ilizarov frame corrected the rotational deformity of the tibia during operation. The external fixator was adjusted starting 7 days after operation to correct the varus and valgus deformities of the lower limb. During the treatment period, the patient could walk with partial weight-bearing on the operated limb with crutches. The external fixator was removed after the bone healed. Before operation and at last follow-up, the medial proximal tibial angle (MPTA), lateral distal tibial angle (LDTA), posterior proximal tibial angle (PPTA), anterior distal tibial angle (ADTA), anatomic lateral distal femoral angle (aLDFA), posterior distal femoral angle (PDFA), and mechanical axis deviation (MAD), lower limb rotation, limb length discrepancy (LLD) were measured. The self-made scoring criteria were adopted to evaluate the degree of lower limb deformity of the patients. RESULTS: All operations were successfully completed, and no complications such as nerve or vascular injury occurred. The adjustment time of the external fixator of the lower limb after operation was 28-46 days, with an average of 37.4 days. The wearing time of the external fixator ranged from 134 to 398 days, with an average of 181.5 days. Mild pin tract infections occurred in 2 limbs. The osteofascial compartment syndrome occurred in 1 limb after operation. No complications related to orthopedic adjustment of the external fixator occurred in other patients. All patients were followed up 6-56 months, with an average of 28.2 months. At last follow-up, full-length films of both lower limbs in the standing position showed that the coronal mechanical axes of the lower limbs of all patients returned to the normal. At last follow-up, MPTA, LDTA, PPTA, aLDFA, PDFA, MAD, lower limb rotation, LLD, and the score of lower limb deformity significantly improved when compared with those before operation ( P<0.05). There was no significant difference in ADTA between pre- and post-operation ( P>0.05). The degree of lower limb deformity were rated as moderate in 2 cases and poor in 27 cases before operation and as excellent in 7 cases, good in 18 cases, and moderate in 4 cases at last follow-up, with an excellent and good rate of 86.2%. CONCLUSION For severe lower limb deformities in hypophosphatemic rickets, immediate correction of deformities with femoral osteotomy and internal plate fixation, as well as gradually correction of deformities with tibiofibular osteotomy and circular external fixation (Ilizarov frame or Taylor frame), have satisfactory therapeutic effects.
Humans ; Male ; Osteotomy/instrumentation* ; Female ; Adult ; Retrospective Studies ; Tibia/abnormalities* ; Adolescent ; Femur/abnormalities* ; Middle Aged ; Fibula/surgery* ; Rickets, Hypophosphatemic/complications* ; Young Adult ; Treatment Outcome ; External Fixators ; Bone Plates ; Lower Extremity Deformities, Congenital/etiology*

Objective To explore the effects of Shuanglu Tongnao Formula on neuroinflammation in ischemic stroke (IS) rats via the P2X purinoceptor 7 receptor (P2X7R)/NLR family pyrin domain-containing 3 (NLRP3) pathway. Methods The rats were divided into five groups: the IS group, control group, Shuanglu Tongnao Formula group, P2X7R inhibitor brilliant blue G (BBG) group, and Shuanglu Tongnao Formula combined with P2X7R activator adenosine triphosphate (ATP) group, with 18 rats in each group. Except for the control group, rats in all other groups were used to construct an IS model using the suture method. After successful modeling, the drug was given once a day for 2 weeks. Neurological function scores and cerebral infarction volume ratios were measured in rats. Pathological examination of the ischemic penumbra brain tissue was performed. Immunofluorescence staining was used to quantify the proportions of microglia co-expressing both inducible nitric oxide synthase (iNOS) and ionized calcium-binding adapter molecule 1 (Iba1), as well as arginase 1 (Arg1) and Iba1, in the ischemic penumbra brain tissue. ELISA was used to detect tumor necrosis factor-alpha (TNF-α), transforming growth factor-beta (TGF-β), interleukin 6 (IL-6) and IL-10 in the ischemic penumbra brain tissue. Western blotting was used to measure P2X7R, NLRP3, and IL-1β proteins in the ischemic penumbra brain tissue. Results Compared with the control group, the IS group showed disordered neuronal arrangement, nuclear condensation, and obvious infiltration of inflammatory cells in the ischemic penumbra; significantly elevated neurological function scores, cerebral infarction volume ratios, proportions of microglia co-expressing iNOS and Iba1, and levels of TNF-α, IL-6, and P2X7R, NLRP3, IL-1β proteins; along with reduced proportions of microglia co-expressing Arg1 and Iba1 and levels of TGF-β and IL-10. Compared with the IS group, the Zhuang medicine Shuanglu Tongnao Formula and BBG groups demonstrated alleviated brain tissue damage; reduced neurological function scores, cerebral infarction volume ratios, proportions of microglia co-expressing iNOS and Iba1, and levels of TNF-α, IL-6, and P2X7R, NLRP3, IL-1β proteins; along with increased proportions of microglia co-expressing Arg1 and Iba1 and levels of TGF-β and IL-10. ATP reversed the effects of Zhuang medicine Shuanglu Tongnao Formula on microglial polarization and neuroinflammation in IS rats. Conclusion Zhuang medicine Shuanglu Tongnao Formula may promote the transformation of microglia from M1 type to M2 type by inhibiting the P2X7R/NLRP3 pathway, thereby improving neuroinflammation in IS rats.
Animals ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Receptors, Purinergic P2X7/metabolism* ; Male ; Drugs, Chinese Herbal/pharmacology* ; Rats ; Ischemic Stroke/pathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Signal Transduction/drug effects* ; Neuroinflammatory Diseases/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; Interleukin-10/metabolism* ; Brain Ischemia/drug therapy* ; Microglia/metabolism*

OBJECTIVES: To explore the factors related to prognosis and treatment failure in children with acute lymphoblastic leukemia (ALL). METHODS: A retrospective study was conducted to collect and analyze clinical data of ALL children admitted to the Department of Pediatric Hematology at Tongji Hospital, Huazhong University of Science and Technology, from January 2012 to December 2019, with follow-up until June 2024. RESULTS: A total of 341 children with ALL were included. Among the 69 children with treatment failure, 55 (80%) experienced relapse, while 14 (20%) had non-relapse-related deaths, and no secondary tumors were observed. Initial WBC count ≥50×10⁹/L, positive minimal residual disease, and severe adverse events were identified as independent risk factors for treatment failure (P<0.05). Among the 55 relapsed patients, early relapses were predominant (36%), and the primary site of relapse was the bone marrow (56%). Immunophenotyping (P=0.009), initial WBC count (P=0.011), and fusion genes (P=0.040) were associated with the timing of relapse. High-risk status, T-cell ALL, relapse, and severe adverse events were independent risk factors affecting long-term survival (P<0.05). CONCLUSIONS The prognosis of children with ALL is related to risk stratification, immunophenotyping, relapse status, and occurrence of severe adverse events. Among these factors, relapse is the primary cause of treatment failure. Actively preventing relapse may reduce the treatment failure rate and improve long-term survival.
Humans ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/therapy* ; Male ; Female ; Child ; Child, Preschool ; Retrospective Studies ; Prognosis ; Treatment Failure ; Adolescent ; Infant ; Risk Factors

A retrospective analysis was conducted on the clinical course of two children with PICALM-MLLT10-positive acute leukemia treated at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, between July 2021 and July 2023. The patients were diagnosed with acute T-lymphoblastic leukemia with central nervous system involvement and high-risk acute myeloid leukemia, respectively. Both achieved bone marrow complete remission after conventional chemotherapy combined with venetoclax. Following conversion to molecular negativity, they underwent sequential allogeneic hematopoietic stem cell transplantation. At the latest follow-up, both patients were alive and in good clinical condition. These observations suggest that proceeding to hematopoietic stem cell transplantation after venetoclax-based chemotherapy may improve the long-term survival of children with PICALM-MLLT10-positive leukemia.
Humans ; Hematopoietic Stem Cell Transplantation ; Male ; Female ; Child, Preschool ; Transplantation, Homologous ; Child ; Leukemia, Myeloid, Acute/genetics* ; Oncogene Proteins, Fusion/genetics*

A 91-year-old male patient was admitted with a history of mitral valve prolapse diagnosed by physical examination ten years prior and recent onset of exertional chest discomfort persisting for over one month. Transthoracic echocardiography showed that the anterior leaflet of mitral valve was thickened and prolapsed with severe regurgitation, and transesophageal echocardiography further confirmed that the anterior and posterior leaflets of mitral valve were prolapsed with massive regurgitation (A1, A2, A3, P1 and P2 were all prolapsed). Thus, the diagnosis of Barlow syndrome was considered. Transcatheter edge-to-edge mitral repair was performed with two MitraClip^TM G4 XTWs. After a 10 months follow-up, the patient's cardiac function was significantly improved, and the degree of mitral regurgitation was mild.
Humans ; Male ; Aged, 80 and over ; Mitral Valve Insufficiency/surgery* ; Mitral Valve Prolapse/diagnostic imaging* ; Cardiac Catheterization/methods* ; Mitral Valve/surgery* ; Heart Valve Prosthesis Implantation/methods*