BACKGROUND:Periprosthetic joint infection is the most common cause of early failure after total knee replacement.The current methods of preventing periprosthetic joint infection by improving the surface of the prosthesis have limitations to varying degrees.OBJECTIVE:To construct a coating material that can stably improve the surface of the implant,prevent the initial floating bacterial infection of periprosthetic infection,and regulate the bone transfer function around the implant.METHODS:(1)Material preparation:YGF polypeptide(which promotes bone formation),LL-37 polypeptide(with antibacterial properties)and YGF+LL-37 composite peptide were prepared by Fmoc solid phase peptide synthesis technology.The titanium-based materials were immersed in the three polypeptide solutions for 2 hours to obtain YGF coating,LL-37 coating and composite peptide coating coated titanium sheets.(2)In vitro experiment:Uncoated titanium sheets and coated titanium sheets were co-cultured with Escherichia coli(or Staphylococcus aureus)and the colonies were counted by plate method.MC3T3 cells were inoculated on the surface of uncoated titanium sheet and coated titanium sheet,respectively.Alizarin red staining was used to observe the calcium salt deposition on the surface of the material.Western blot assay was used to detect the protein expression of RUNX2,osteocalcin,osteopontin,and bone morphogenetic protein 2.(3)Animal experiment:24 SD rats were randomly divided into three groups:the blank group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal;the control group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension;the experimental group(n=8)was implanted with composite peptide coated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension.After 5 weeks of implantation,micro-CT examination,hematoxylin-eosin staining and immunohistochemical staining of femur specimens were performed.RESULTS AND CONCLUSION:(1)In vitro experiment:Compared with uncoated titanium sheet and YGF coated titanium sheet,LL-37 coated and composite peptide coated titanium sheet could significantly inhibit the growth and reproduction of Escherichia coli and Staphylococcus aureus.Compared with uncoated titanium sheets and LL-37-coated titanium sheets,YGF-coated and composite peptide-coated titanium sheets could promote calcium salt deposition in osteoblasts and increase the protein expression of RUNX2,osteocalcin,osteopontin and bone morphogenetic protein 2.(2)Animal experiment:Micro-CT test showed that the control group had less bone mass than the blank group and the experimental group.Hematoxylin-eosin staining showed that there was a large amount of fibrous tissue around the nail channel in the control group,only a small amount of tissue fibrosis around the nail channel in the blank group,and only a small amount of tissue fibrosis around the nail channel in the experimental group.Immunohistochemical staining showed that the protein expression of interleukin 1β and tumor necrosis factor α in the control group was higher than that in the blank group and the experimental group,and the expression of osteocalcin,RUNX2 and osteopontin in the experimental group was higher than that in the blank group and the control group.(3)The results show that the titanium-based material coated with YGF+LL-37 composite peptide coating has good antibacterial ability and can promote bone transfer around the implant.

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.

BACKGROUND:Periprosthetic joint infection is the most common cause of early failure after total knee replacement.The current methods of preventing periprosthetic joint infection by improving the surface of the prosthesis have limitations to varying degrees.OBJECTIVE:To construct a coating material that can stably improve the surface of the implant,prevent the initial floating bacterial infection of periprosthetic infection,and regulate the bone transfer function around the implant.METHODS:(1)Material preparation:YGF polypeptide(which promotes bone formation),LL-37 polypeptide(with antibacterial properties)and YGF+LL-37 composite peptide were prepared by Fmoc solid phase peptide synthesis technology.The titanium-based materials were immersed in the three polypeptide solutions for 2 hours to obtain YGF coating,LL-37 coating and composite peptide coating coated titanium sheets.(2)In vitro experiment:Uncoated titanium sheets and coated titanium sheets were co-cultured with Escherichia coli(or Staphylococcus aureus)and the colonies were counted by plate method.MC3T3 cells were inoculated on the surface of uncoated titanium sheet and coated titanium sheet,respectively.Alizarin red staining was used to observe the calcium salt deposition on the surface of the material.Western blot assay was used to detect the protein expression of RUNX2,osteocalcin,osteopontin,and bone morphogenetic protein 2.(3)Animal experiment:24 SD rats were randomly divided into three groups:the blank group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal;the control group(n=8)was implanted with uncoated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension;the experimental group(n=8)was implanted with composite peptide coated titanium nails in the femoral medullary canal+intra-articular injection of Staphylococcus aureus suspension.After 5 weeks of implantation,micro-CT examination,hematoxylin-eosin staining and immunohistochemical staining of femur specimens were performed.RESULTS AND CONCLUSION:(1)In vitro experiment:Compared with uncoated titanium sheet and YGF coated titanium sheet,LL-37 coated and composite peptide coated titanium sheet could significantly inhibit the growth and reproduction of Escherichia coli and Staphylococcus aureus.Compared with uncoated titanium sheets and LL-37-coated titanium sheets,YGF-coated and composite peptide-coated titanium sheets could promote calcium salt deposition in osteoblasts and increase the protein expression of RUNX2,osteocalcin,osteopontin and bone morphogenetic protein 2.(2)Animal experiment:Micro-CT test showed that the control group had less bone mass than the blank group and the experimental group.Hematoxylin-eosin staining showed that there was a large amount of fibrous tissue around the nail channel in the control group,only a small amount of tissue fibrosis around the nail channel in the blank group,and only a small amount of tissue fibrosis around the nail channel in the experimental group.Immunohistochemical staining showed that the protein expression of interleukin 1β and tumor necrosis factor α in the control group was higher than that in the blank group and the experimental group,and the expression of osteocalcin,RUNX2 and osteopontin in the experimental group was higher than that in the blank group and the control group.(3)The results show that the titanium-based material coated with YGF+LL-37 composite peptide coating has good antibacterial ability and can promote bone transfer around the implant.

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.

ObjectiveTo explore the potential mechanism of Weicanqing Formula （微残清方， WF） combined with chemotherapy in treating acute myeloid leukemia （AML） based on malic enzyme 2 （ME2）-mediated bone marrow immune-metabolic homeostasis and . MethodsSixty-five male C57BL/6N mice were randomly divided into control group， model group， WF group， chemotherapy group， and the combination group （WF plus chemotherapy）， with 13 mice per group. Except for the control group， mice were injected with C1498 cells （appro-ximately 1×10⁶ cells per mouse） via the tail vein on day 1 to establish an AML model. Starting from day 8， mice in the chemotherapy group and the combination group were administered with cytarabine at 30 mg/（kg·d） via subcutaneous injection， once daily for 3 consecutive days； WF group and the combination group received WF at 7.54 g/（kg·d） by gavage， once daily for 21 consecutive days. On days 1， 7， 14， 21 and 28， hemoglobin （Hb） and white blood cell （WBC） levels were determined in each group. On day 28， Giemsa staining was used to observe morphological changes in bone marrow cells. Flow cytometry was employed to detect the expression levels of bone marrow T lympthocyte subsets， including CD8⁺， CD4⁺， and regulatory T lymphocytes （Treg）. The contents of glutamine （Gln）， nicotinamide adenine dinucleotide phosphate （NADP⁺）， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） in bone marrow were determined using visible spectrophotometry. Adenosine triphosphate （ATP） concentration in bone marrow was measured by chemiluminescence assay. The mRNA expression of malic enzyme 2 （ME2） in bone marrow was detected by RT-qPCR， and the protein expression level of ME2 was determined by Western blotting. ResultsCompared to the control group， the model group showed decreased Hb levels on day 14， 21， and 28， and increased WBC levels on day 7， 14， 21， and 28 （P＜0.05）. On day 28， bone marrow CD8⁺ and CD8⁺/CD4⁺ levels decreased， while Treg cells， ATP， Gln， NADP⁺， NADPH， ME2 mRNA， and their corresponding protein levels increased （P＜0.05）. Compared to the model group， the chemotherapy group and the combination group both exhibited reduced Hb level on day 14， 21 and 28， as well as the increased WBC level； the combination group showed increased CD8⁺ level， decreased Treg， ATP， Gln， and NADPH content， as well as reduced ME2 mRNA expression and protein levels （P＜0.05）. Compared to the chemotherapy group， the combination group showed significantly increased Hb level on days 21 and 28， and increased WBC level on day 28 （P＜0.05）. Bone marrow smear pathology revealed that， in the model group， myeloid blast cells exhibited cytoplasmic vacuoles indicative of abnormal metabolic activity. In contrast， both the chemotherapy group and the combination group showed large numbers of metamyelocytes and band neutrophils， with only a few immature granulocytic blast cells observed. ConclusionWF may improve the prognosis of AML when used as an adjunct to chemotherapy by modulating ME2 expression， inhibiting metabolic energy competition within the bone marrow microenvironment， and reshaping the distribution of T lymphocyte subsets in the bone marrow.

ObjectiveTo evaluate the effects of Tongnaoyin on the blood-brain barrier status and neurological impairment in acute ischemic stroke （AIS） patients with the syndrome of phlegm-stasis blocking collaterals by dynamic contrast-enhanced magnetic resonance imaging （DCE-MRI）. MethodsA total of 63 patients diagnosed with AIS in the Jiangsu Province Hospital of Chinese Medicine from October 2022 to December 2023 were enrolled in this study. According to random number table method，the patients were assigned into a control group （32 cases） and an observation group （31 cases）. The control group received conventional Western medical treatment，and the observation group took 200 mL Tongnaoyin after meals，twice a day from day 2 of admission on the basis of the treatment in the control group. After 7 days of treatment，the patients were examined by DCE-MRI. The baseline data for two groups of patients before treatment were compared. The National Institute of Health Stroke Scale （NIHSS） score and modified Rankin Scale （mRS） score were recorded before treatment and after 90 days of treatment for both groups. The rKtrans，rKep，and rVe values were obtained from the region of interest （ROI） of the infarct zone/mirror area and compared between the two groups. ResultsThere was no significant difference in the NIHSS or mRS score between the two groups before treatment. After 90 days of treatment，the NIHSS and mRS scores declined in both groups，and the observation group had lower scores than the control group （P<0.05）. After treatment，the rKtrans and rVe in the observation group were lower than those in the control group （P<0.01）. ConclusionCompared with conventional Western medical treatment alone，conventional Western medical treatment combined with Tongnaoyin accelerates the repair of the blood-brain barrier in AIS patients，thereby ameliorating neurological impairment after AIS to improve the prognosis.

Objective To investigate the role and primary mechanism of a novel fusion gene RELCH-RET in driving the malignant transformation of normal human bronchial epithelial(HBE)cells.Methods Based on retrospective clinical data from 456 non-small cell lung cancer(NSCLC)patients admitted in the Second Affiliated Hospital of Army Medical University from January 2019 to June 2022,a fusion gene,RELCH-RET,was identified as a research target.Three cell models were established:negative control(HBE VC,transfected with empty lentiviral vector),RET control(HBE RET,transfected with lentiviral overexpression vector of Flag-RET),and experimental group(HBE RELCH-RET,transfected with lentiviral overexpression vector of Flag-RELCH-RET).MTS assay and Transwell assay were used to detect cell proliferation and migratory and invasive abilities.In vivo tumorigenicity of the 3 cell models was assessed in 15 female non-obese diabetic/severe combined immunodeficiency(NOD/SCID)mice(SPF grade,4 weeks old,weighing 15.1±0.4 g)via subcutaneous xenograft experiments,with 5 animals in each group.Western blotting was employed to detect the autophosphorylation of RET(Y905)and the phosphorylation of downstream signaling proteins ERK1/2,EGFR(Y845)and STAT3(Y705).Dimerization and multimerization status of RELCH-RET were analyzed by chemical cross-linking(DTME treatment)in combination with Western blotting,with the reversibility being confirmed through de-cross-linking experiments.Results There were 3 cases carrying RELCH-RET fusion gene screened out from the 469 NSCLC patients.Compared with the HBE VC and HBE RET groups,the HBE RELCH-RET group exhibited significantly enhanced cell proliferation(P<0.01),and acquired migratory and invasive abilities(P<0.01),while the control groups did not demonstrate the abilities.In the mouse xenograft tumor model,HBE cells stably expressing RELCH-RET developed significant tumor nodules(P<0.001),whereas the control groups(empty vector and wild-type RET)failed to exhibit detectable tumor growth.Western blotting revealed that RELCH-RET could induce the autophosphorylation of the RET tyrosine residue(Y905)and significantly up-regulate the phosphorylation levels of ERK1/2,EGFR(Y845),and STAT3(Y705)proteins.Chemical cross-linking combined with Western blot analysis demonstrated that RELCH-RET formed a dimer(～170 kDa)in HBE cells,which is reversibly dissociated into monomers upon decross-linking treatment.Conclusion The novel fusion gene RELCH-RET,promotes ligand-independent dimerization/oligomerization,thereby mediating RET autophosphorylation,subsequently activates the downstream typical RET signaling pathway and ultimately drives the malignant transformation of normal HBE cells.

Objective To explore the effect of rotenone exposure on the metabolic homeostasis of nicotinamide adenine dinucleotide(NAD+)in dopaminergic neurons of the rat mid-brain striatum,and investigate the effect of exogenous NAD+intervention on the cellular damage response of dopaminergic neurons induced by rotenone.Methods Male SD rats(8 weeks old,200～250 g)were divided into a control group using a table of random numbers,a rotenone exposure group,an NAD+-intervention group,and an NAD+group.An intoxication model was established in the rotenone exposure group.NAD+(250 mg/kg)was administered simultaneously with rotenone exposure in the NAD+-intervention group.The NAD+group was only given NAD+,while the control group received no intervention.After modeling,open field test was performed to evaluate behavioral changes.After scarification,serum samples and mid-brain striatal tissues were collected.HE staining was used to observe the morphology of dopaminergic neurons in the striatum.The NAD+content in the tissues was detected with NAD+/NADH kit.Western blotting was employed to determine the contents of tyrosine hydroxylase(TH),nicotinamide phosphoribosyltransferase(NAMPT),nicotinamide mononucleotide adenylyltransferase(NMNAT),and solute carrier family 25 member A51(SLC25A51).ELISA was utilized to measure the content of dopamine in the striatal tissues.Immunohistochemical staining was applied to observe the distribution and contents of TH proteins in the striatal tissues of each group.Results Rotenone exposure significantly affected the vital signs and motor abilities of rats,induced disorderly-arranged,atrophy and deformed neurons in the striatal tissue,decreased the content of TH,rate-limiting enzyme for dopamine synthesis,by approximately 29%(P<0.01),the content of dopamine by about 42%,and that of NAD+by almost 50%(P<0.01),while increased the NADH/NAD+ratio(P<0.01).After exposure,the content of NAMPT,an enzyme related to NAD+synthesis,was decreased by 26%(P<0.05),the contents of NMNAT1-3 and SLC25A51,mitochondrial transporters of NAD+by approximately 21%,38%,43%,and 21%,respectively(P<0.01).Exogenous NAD+intervention improved the motor function of exposure rats and the morphology of dopaminergic neurons in the mid-brain striatal tissue,and restored the content of TH in the striatal tissue significantly by 12.8%(P<0.05),and the content of dopamine by 20.9%(P<0.05).Conclusion Rotenone disrupts the NAD+homeostasis in dopaminergic neurons by inhibiting the NAD+synthesis and transport pathways in the mid-brain striatal tissues,while exogenous NAD+intervention can effectively alleviate the dopaminergic neuron damage induced by rotenone exposure.

Objective To elucidate the effects of miR-616 on the malignant biological processes of osteosarcoma and to preliminarily explore its potential mechanisms.Methods In situ hybridization(ISH)was employed to analyze miR-616 expression in 11 paraffin-embedded osteosarcoma specimens collected in our department during January 2018 to December 2019.Quantitative real-time PCR(qRT-PCR)was used to compare the mRNA expression level of miR-616 in the osteoblast cell line hFOB1.19 and osteosarcoma cell lines 143B and HOS.Stable cell lines with miR-616 knockdown or overexpression were established via lentiviral transfection in 143B and HOS cells.Cell proliferation and apoptosis were detected by flow cytometry,while cell invasion and migration were assessed using Transwell and colony formation assays,respectively.To evaluate the effect of miR-616 on tumor growth in vivo,10 female nude mice(4 weeks old,weighing 18～20 g)were randomized into a control group and a miR-616 overexpression group.After the xenograft tumor model was constructed,the growth of subcutaneous tumors was monitored.Finally,next-generation sequencing and a dual-luciferase reporter assay were performed to identify the target genes of miR-616.Results ISH results showed that miR-616 expression was up-regulated in osteosarcoma tissues than adjacent tissues,and primarily localized in the cytoplasm.qRT-PCR confirmed that miR-616 level was significantly higher in 143B and HOS cells than hFOB1.19 cells(P<0.05).In vitro experiments revealed that miR-616 overexpression enhanced the proliferation,migration and invasion,while suppressing apoptosis in 143B and HOS cells(P<0.01).Conversely,miR-616 knockdown weakened these malignant phenotypes(P<0.05),with miR-616-3p showing a stronger effect on apoptosis than miR-616-5p.Animal experiments demonstrated that the tumor weight in the miR-616 overexpression group was significantly greater than that of the control group(98.00±17.22 vs 33.60±8.08 mg,P<0.01).Furthermore,KLF2 was identified and confirmed as a direct target of miR-616.Conclusion MiR-616 promotes malignant biological behaviors in osteosarcoma,and its expression level indicates that it may serve as a potential therapeutic target.

BACKGROUND:The plantarflexor weakness is a common muscle defect in patients with spastic cerebral palsy and Charcot-Marie-Tooth,which clinically manifests abnormal gaits,and the relationship between plantarflexor weakness and abnormal gaits is unclear. OBJECTIVE:To explore the biomechanical behavior of the lower limb under the action of a single factor of plantarflexor weakness to reveal the mechanism of abnormal gait induced by plantarflexor weakness and to provide guidance for the rehabilitation training of patients with plantarflexor weakness. METHODS:A predictive framework of musculoskeletal multibody dynamics in the sagittal plane was established based on OpenSim Moco to predict lower limb joint angles and muscle activation changes during walking in normal subjects.The validity of the framework was verified by combining the inverse kinematics and electromyogram activation time of the experimental data.Reduced isometric muscle forces were used to model plantarflexor weakness and to compare predicted lower extremity joint angles,joint moments,and muscle energy expenditure with normal subjects to analyze the effects of plantarflexor weakness on lower extremity biomechanics. RESULTS AND CONCLUSION:(1)The Moco-based prediction framework realistically predicted the biomechanical changes of the lower limbs during walking in normal subjects(joint angles:normalized correlation coefficient≥0.73,root mean square error≤7.10°).(2)The musculoskeletal model used a small stride support phase to increase the"heel-walking"gait during plantarflexor weakness.When the plantarflexor weakness reached 80%,the muscle energy expenditure was 5.691 4 J/kg/m,and the maximum activation levels of the gastrocnemius and soleus muscles were 0.72 and 0.53,which might cause the plantarflexor weakness patients to be more prone to fatigue when walking.(3)Muscle energy expenditure was significantly higher when the weakness of plantarflexors exceeded 40%,and the joint angles and moments of the lower limbs deteriorated significantly when the weakness of plantarflexors exceeded 60%,suggesting that there may be a"threshold"for the effect of plantarflexor weakness on gait,which may correspond to the point at which health care professionals should intervene in the clinical setting.