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.

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.

Objective To investigate the clinical effect of dapagliflozin combined with sacubitril-valsar-tan in the treatment of non-reduced ejection fraction type heart failure(non-HFrEF).Methods A total of 120 patients with non-HFrEF diagnosed and treated in this hospital from January to December 2022 were selected as the study subjects and divided into the observation group and control group by the random number method,60 cases in each group.The both groups were treated with conventional treatments such as β-receptor blockers and diuretics,the patients in the control group were treated with sacubitril-valsartan(Noxinto),and the pa-tients in the observation group were treated with dapagliflozin on the basis of the control group for 6 months.The clinical efficacy,serum N-terminal B-type natriuretic peptide precursor(NT-proBNP),hypersensitivity-C-reactive protein(hs-CRP),serum creatinine(SCr),serum potassium,cardiac color Doppler ultrasound param-eters,6 min walk test(6MWT)distance before treatment and in 6 months after treatment,and the occurrence of major adverse cardiovascular events(MACE)during treatment were compared between the two groups.Re-sults After 6 months of treatment,the total effective rate in the observation group was 93.3%,which was higher than 80%in the control group,and the difference was statistically significant(P=0.032).After 6 months of treatment,the levels of NT-proBNP and hs-CRP in the two groups were significantly decreased compared with those before treatment,moreover the observation group was lower than the control group,and the difference was statistically significant(P<0.05).After 6 months of treatment,LVEF and 6MWT dis-tance in the two groups were increased compared with those before treatment,LVEDV and LVESV were de-creased compared with those before treatment,moreover the change amplitude of the above indexes in the ob-servation group were greater than those in the control group,and the differences were statistically significant(P<0.05).The incidence rate of MACE in the observation group was lower than that in the control group(16.7%vs.5.0%),and the difference was statistically significant(P<0.05).Conclusion Dapagliflozin combined with sacubitril-valsartan in the treatment of non-HFrEF could significantly reduce the levels of NT-proBNP and hs-CRP,improve the cardiac function,increase the exercise tolerance,decrease the incidence rate of MACE and improve the prognosis.

BACKGROUND:The pelvis has abundant trabecular bone content,but the ability of conventional sacroiliac percutaneous fixation to control trabecular bone is limited,leading to fixation failure.Therefore,the development of devices that can more effectively control trabecular bone tension is of significant importance.OBJECTIVE:The mechanical properties of a novel sacroiliac tension screw were investigated using biomechanical testing and numerical modeling analysis,along with an assessment of the reliability of the pull-out force numerical model.METHODS:A mechanical model was established based on the working principle of the novel sacroiliac tension screw.Numerical methods were employed to analyze its pull-out performance,validated through mechanical testing with polyurethane material to assess the reliability of the pull-out force numerical model.Using pelvic specimens,the mechanical effectiveness of the novel sacroiliac tension screw in repairing sacroiliac joint injuries was analyzed under normal standing posture,along with an evaluation of the load stiffness of different pelvic models in the standing position.RESULTS AND CONCLUSION:(1)The average error between the computed values of the numerical model and the measured values was 13.19％,indicating a certain level of validity for the numerical model.(2)The damage to the polyurethane material after the extraction of the screw was less pronounced in the novel screw group.(3)The average effective holding displacement for the novel screw was approximately(9.24±0.27)mm,significantly greater than the average displacement of(1.71±0.57)mm observed with the lag screws.However,the maximum resistance to pullout for the lag screws was significantly higher than that for the novel screws.(4)The novel screw effectively repaired sacroiliac joint injuries.(5)The stiffness after repair of sacroiliac joint injuries was equivalent when using a single novel screw compared to using two lag screws.(6)These results prove that the theoretical model for the maximum resistance to pullout of the screws established in this study has a certain level of validity and can guide the design of them with improved mechanical performance.The novel sacroiliac spiral blade screw can effectively hold trabecular bone and has practical clinical utility.

Objective To investigate the effects of Qizhi Zhoufei Granules on endoplasmic reticulum stress in rats with chronic obstructive pulmonary disease(COPD);To explore its mechanism.Methods COPD rat model was induced by lipopolysaccharide tracheal instillation and smoking.Totally 60 Wistar rats were divided into control group,model group,Bufei Huoxue Capsules group and Qizhi Zhoufei Granules low-,medium-and high-dosage groups using random number table method,with 10 rats in each group.Drug gavage intervention was carried out for the treatment group since the 29th day of modeling,and normal saline was given to the control group and model group for 28 d.Lung function tests were performed,HE staining was used to detect morphology of lung tissue,TUNEL staining was used to detect the degree of apoptosis in lung tissue,RT-qPCR and Western blot were used to detect the endoplasmic reticulum stress and apoptosis related molecular mRNA and protein expression in lung tissue.Results Compared with the control group,the lung function indexes of peak inspiratory flow(PIF),peak expiratory flow(PEF)and minute volume(MV)significantly decreased,and frequency of breathing(F)significantly increased in the model group(P＜0.05);the structural damage of the lung tissue was obvious,the lung injury score and apoptosis rate significantly increased(P＜0.05),the expressions of glucose regulated protein 78(GRP78),protein kinase R-like ER kinase(PERK),C/EBP-homologous protein(CHOP),Caspase-3 and Caspase-9 mRNA were increased(P＜0.05),the protein expressions of GRP78,p-PERK,activating transcription factor 4(ATF4),CHOP,Caspase-3 and Caspase-9 were significantly increased(P＜0.05).Compared with the model group,PIF,PEF and MV significantly increased in Qizhi Zhoufei Granules medium-and high-dosage groups and Bufei Huoxue Capsules group,and F significantly decreased(P＜0.05);the damage in lung tissue was improved,and the lung injury score and cell apoptosis rate significantly decreased(P＜0.05),the mRNA expressions of GRP78,PERK,CHOP,Caspase-3 and Caspase-9 in lung tissue decreased(P＜0.05),and the protein expressions of GRP78,p-PERK,ATF4,CHOP,Caspase-3 and Caspase-9 decreased(P＜0.05).Conclusion Qizhi Zhoufei Granules can prevent cell apoptosis and excessive damage by inhibiting the expression of endoplasmic reticulum stress related factors in COPD rats,thereby promoting unfolded protein response and improving endoplasmic reticulum folding ability,constraining endoplasmic reticulum stress state,and assisting in its regulation.