OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

OBJECTIVE: To provide the experience and demonstration for the transformation of acupuncture-moxibustion techniques standards from Chinese national standards to international standards. METHODS: Questionnaire research, literature research, semi-structured interviews and expert consultation were used. RESULTS: The safety of acupuncture-moxibustion techniques was evaluated through literature research, and based on the results of the questionnaire survey, expert interviews, and expert consultation, 11 main bodies and structure of the former Chinese national standard, Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting, were adjusted and optimized in accordance with the requirements of international standard (including the language, normative references, purpose, scope, applicable environment, target population, work team, terms and definitions, general principles and basic requirements, structural elements and text structure, and compilation process); and the first international standard, World Federation of Acupuncture-Moxibustion Societis (WFAS) Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting was formulated to specify the general rules for drafting. CONCLUSION The 3 key questions, "international compatibility", "technical operability" and "safety" should be solved technically on the basis of explicit international requirements. It is the core technical issue during transforming the national standards of technical benchmark of acupuncture and moxibustion into international standards.
Moxibustion/methods* ; Acupuncture Therapy/methods* ; Humans ; Translational Research, Biomedical/standards* ; Surveys and Questionnaires ; China ; Benchmarking/standards*

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective:To discuss the regulatory effect of physiological tensile stress on the differentiation of chondrocytes,and to clarify the associated signaling pathway mechanism.Methods:The ATDC5 chondrocytes were cultured in vitro and subjected to physiological tensile stress by four-point bending cell mechanical loading device.Initially,the cells were divided into control group and tensile stress group(2 000 μstrain/2 h group),and further divided into different stress magnitudes(1 000,2 000,and 3 000 μstrain)for 2 h,and 2 000 μstrain for different duration time(1,2,and 4 h)groups;the cells without tensile stress were used as control group.Real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the expression levels of type Ⅱ collagen(Col-Ⅱ),type Ⅹ collagen(Col-Ⅹ),aggregated proteoglycom(Aggrecan),sex-determining region Y-box protein 9(SOX9),vascular endothelial growth factor(VEGF),proliferating cell nuclear antigen(PCNA),Nel-like molecule tyep 1(Nell-1),Runt-related transcription factor 2(Runx2),Indian hedgehog(Ihh),patched homolog 1(Ptch-1),GLI family zinc finger protein 1(Gli-1),and hedgehog interacting protein 1(Hhip-1)mRNA in the cells in various groups;Western blotting method was used to detect the expression levels of Nell-1,Runx2,and Ihh proteins in the cells in various groups.The ATDC5 cells were divided into control group,cyclopamine group,tensile stress group,and cyclopamine + tensile stress group.RT-qPCR method was used to detect the expression levels of Nell-1,Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA in the cells in various groups;Western blotting method was used to detect the expression levels of Nell-1 and Ihh proteins in the cells in various groups.Results:Compared with control group,the expression levels of Col-Ⅱ,Col-Ⅹ,Aggrecan,SOX9,VEGF,and PCNA mRNA in the cells in 2 000 μstrain/2 h group were significantly increased(P<0.01);after treated with 2 000 μstrain tensile stress for different duration time(1,2,and 4 h)or different tensile stresses(1 000,2 000,and 3 000 μstrain)for 2 h,compared with control group,the expression levels of Runx2 mRNA in the cells in other groups were increased with the prolongation of time or the increasing of tensile stress(P<0.01),and the expression levels of Nell-1,Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA were gradually increased(P<0.01),the expression levels reached the peaking at 2 000 μstrain/2 h,and then decreased but remained significantly higher than that in control group(P<0.01).The Western blotting results showed that the expression levels of Nell-1,Runx2,and Ihh proteins in the cells were consistent with the change trend of mRNA expression levels.After pre-treated with cyclopamine,compared with control group,the expression levels of Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA in the cells in cyclopamine group were significantly decreased(P<0.01),and the expression levels of Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA in the cells in tensile stress and cyclopamine+tensile stress groups were significantly increased(P<0.01);compared with cyclopamine group,the expression levels of Nell-1,Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA in the cells in cyclopamine+tensile stress group were significantly increased(P<0.01);compared with tensile stress group,the expression levels of Ihh,Ptch-1,Gli-1,and Hhip-1 mRNA in the cells in cyclopamine + tensile stress group were significantly decreased(P<0.01).Compared with control group,the expression level of Ihh protein in the cells in cyclopamine group was significantly decreased(P<0.01),but there was no significant difference in expression level of Nell-1 protein in the cells between control group and cyclopamine group(P>0.05),while the expression levels of Nell-1 and Ihh proteins in the cells in tensile stress group and cyclopamine + tensile stress group were significantly increased(P<0.01);compared with cyclopamine group,the expression levels of Nell-1 and Ihh proteins in the cells in tensile stress group and cyclopamine + tensile stress group were significantly increased(P<0.01);compared with tensile stress group,in the expression levels of Nell-1 and Ihh proteins in the cells in cyclopamine + tensile stress group had no significant differences(P>0.05).Conclusion:After stimulated with physiological tensile stress,Nell-1 can activate the Ihh signaling pathway upstream,and regulate the differentiation of the ATDC5 chondrocytes.

Objective:To systematically summarize and comparatively analyze the development, establishment and usage of oncology drugs speedy review approaches in China and in the United States between 2012 and 2021.Methods:Based on National Medical Products Administration (NMPA) and Food and Drug Administration (FDA) websites, the development and current status of the speedy review approaches were consulted and summarized. Approved oncology drugs in China and in the United States (87 in China, 118 in the United States) over the past decade were analyzed using chi-square test for group comparison.Results:Five speedy approaches have been established in China and in the United States, three of which are the same, priority review, conditional approval or accelerated approval and breakthrough therapy. The rest two are special review and approval, special examination and approval in China, and fast track and real-time oncology review in the United States. Compared to the United States, speedy review approaches in China set up late (1992 vs. 2005). The overall utilization rates of the oncology drugs speedy review approaches were similar between the China and United States (90.8% vs. 92.4%, P=0.800) in the previous 10 years, and priority review have highest utilization rates in both China and the United States without significant group difference (77.0% vs. 82.2%, P=0.381); relatively low utilization rates of conditional approval (31.0% vs. 44.9%, P=0.041) and breakthrough therapy (2.3% vs. 50.0%, P＜0.001) were seen in China. 52.9% of new drugs applied for special examination and approval in China and 40.7% of new drugs applied for fast track in the United States. Overall, the priority review both in China and the United States are stable, with a similar average annual utilization rate (84.8% vs. 83.7%); accelerated approval and breakthrough therapies in the United States fluctuate wildly, but the situation is tending towards stability in the last 3 years. Conclusions:Both China and the United States have established a relatively complete accelerated review system, with an overall utilization rate over 90%; China's accelerated review started late, although the overall utilization rate is close to that of the United States. The utilization rates of conditional approval and breakthrough therapy are still relatively low. Flexible usage of speedy review approaches, gaining regulatory recognition to use alternative endpoints, achieving real-time review and guidance are keys to accelerate new drug development in China.

Objective:To systematically summarize and comparatively analyze the development, establishment and usage of oncology drugs speedy review approaches in China and in the United States between 2012 and 2021.Methods:Based on National Medical Products Administration (NMPA) and Food and Drug Administration (FDA) websites, the development and current status of the speedy review approaches were consulted and summarized. Approved oncology drugs in China and in the United States (87 in China, 118 in the United States) over the past decade were analyzed using chi-square test for group comparison.Results:Five speedy approaches have been established in China and in the United States, three of which are the same, priority review, conditional approval or accelerated approval and breakthrough therapy. The rest two are special review and approval, special examination and approval in China, and fast track and real-time oncology review in the United States. Compared to the United States, speedy review approaches in China set up late (1992 vs. 2005). The overall utilization rates of the oncology drugs speedy review approaches were similar between the China and United States (90.8% vs. 92.4%, P=0.800) in the previous 10 years, and priority review have highest utilization rates in both China and the United States without significant group difference (77.0% vs. 82.2%, P=0.381); relatively low utilization rates of conditional approval (31.0% vs. 44.9%, P=0.041) and breakthrough therapy (2.3% vs. 50.0%, P＜0.001) were seen in China. 52.9% of new drugs applied for special examination and approval in China and 40.7% of new drugs applied for fast track in the United States. Overall, the priority review both in China and the United States are stable, with a similar average annual utilization rate (84.8% vs. 83.7%); accelerated approval and breakthrough therapies in the United States fluctuate wildly, but the situation is tending towards stability in the last 3 years. Conclusions:Both China and the United States have established a relatively complete accelerated review system, with an overall utilization rate over 90%; China's accelerated review started late, although the overall utilization rate is close to that of the United States. The utilization rates of conditional approval and breakthrough therapy are still relatively low. Flexible usage of speedy review approaches, gaining regulatory recognition to use alternative endpoints, achieving real-time review and guidance are keys to accelerate new drug development in China.

Objective To explore the impact of prolonged sitting on lumbar disc degeneration using MRI T1ρ and T2 mapping.Methods A total of 25 taxi drivers(prolonged sitting group)and 24 age-matched non-prolonged sitting volunteers(control group)underwent routine lumbar MRI,T1ρ,and T2 mapping.The differences of T1ρ and T2 values for different Pfirrmann grades of anterior annulus fibrosus(AAF),nucleus pulposus(NP),and posterior annulus fibrosus(PAF)were analyzed using Variance analysis,Spearman correlation test,and receiver operating characteristic(ROC)curve was drawn,with independent t-tests was used for between-group com-parisons.Results Statistically significant differences were observed in T1ρ and T2 values for all Pfirrmann Ⅰ-Ⅱ grades NP and Pfirrmann Ⅱ-Ⅳgrades AAF,NP,and PAF in both groups(P＜0.05).Both T1ρ and T2 values were negatively correlated with Pfirrmann grades.The area under the curve(AUC)of T1ρ values for NP at each Pfirrmann grade were 0.928,0.987,and 0.968,respectively,while the AUC of T2 values for NP were 0.777,0.966,and 0.975,respectively.The T1ρ and T2 values of L4/L5 NP and L5/S1 AAF,NP,and PAF were lower in the prolonged sitting group compared to the control group(P＜0.05).Conclusion T1ρ is superior to T2 mapping in detecting lumbar disc degeneration.Prolonged sitting is more likely to cause degeneration of L4/L5 and L5/S1 inter-vertebral discs.

Objective:To investigate regulatory effect and mechanism of protein kinase C(PKC)δ/θ-dual functional oxidase 1(Duox1)-reactive oxygen species(ROS)signaling pathway on human airway mucin(MUC)5AC,to provide a new target for treatment of high secretion of airway mucus.Methods:Human airway epithelial cells 16HBE were pretreated with PKC and its subunit PKCδ/θ inhibitor,Duox1 inhibitor or free radical scavenger DMTU,respectively,and then human neutrophil elastase(HNE)stimulation to establish an in vitro airway inflammatory cell model.Generation level of ROS in each group of cells was determined by kit,mRNA levels of Duox1 and MUC5AC were detected by real-time fluorescent quantitative PCR,influence of interfering factors of each group of cells on Duox1 protein level was determined by Western blot,and protein expression of MUC5AC in each group of cells was detected by ELISA and immunofluorescence.Results:Compared with control group,ROS production in HNE group was increased significantly,expressions of Duox1 and MUC5AC mRNA and protein were also increased(P<0.05).After administration of Duox1 inhibitors,free radical scavengers or PKC inhibitors and PKCδ/θ inhibitors,ROS production was significantly inhibited,Duox1 and MUC5AC mRNA and protein expressions were decreased(P<0.05),while after giving PKCα/β,ROS generation,Duox1 and MUC5AC mRNA and pro-tein expressions were not significantly changed compared with HNE group(P>0.05).Conclusion:HNE can mediate high expression of MUC5AC through PKCδ/θ-Duox1-ROS,which plays an important role in development of high secretion of airway mucus in vitro cell model experiment.

Objective To observe the correlation between apparent diffusion coefficient(ADC)of sacroiliac joint and spondyloarthritis research consortium of Canada(SPARCC)score in ankylosing spondylitis(AS)patients with different grade sacroiliac joint inflammation.Methods MR examinations of sacroiliac joint were prospectively performed in 35 AS patients(AS group)and 30 healthy controls(HC group).The grade of sacroiliac joint inflammation and SPARCC score in AS group were evaluated according to MRI findings,and the patients were then further divided into bone marrow oedema(BMO)subgroup(n=19)and non-BMO subgroup(n=16)according to whether BMO presented under articular surface or not,and ADC of sacroiliac joint(ADCsacroiliac)were measured.Receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy of ADCsacroiliac for assessing AS sacroiliac joint inflammation grade.Pearson correlation analysis was performed to analyze the correlation between ADCsacroiliac and SPARCC score in AS patients with different grade sacroiliac joint inflammation.Results ADCsacroiliac in BMO subgroup and non-BMO subgroup was(4.85±1.44)×10-4 and(4.30±0.64)×10-4 mm2/s,respectively,being not significantly different(P＞0.05)but both higher than that in HC group([3.32±1.36]×10-4 mm2/s,both P＜0.05).The sensitivity of ADCsacroiliac for assessing grade of sacroiliac joint inflammation in AS patients was 49.44％,51.94％,73.06％and 60.50％,with specificity of 75.00％,78.92％,83.33％and 66.67％,respectively,and AUC of 0.613,0.712,0.837 and 0.645,respectively.ADCsacroiliac was moderately-highly positively correlated with SPARCC score of AS patients with Ⅱ and Ⅲgrade sacroiliac joint inflammation(r=0.580,0.933,both P＜0.05),but no obvious correlation was detected between ADCsacroiliac and SPARCC score of AS patients with Ⅰ or Ⅳ grade sacroiliac joint inflammation(both P＞0.05).Conclusion ADCsacroiliac was positively correlated with SPARCC scores of AS patients with Ⅱ and Ⅲ grade sacroiliac joint inflammation,which could be regarded as a reliable quantitative parameter for monitoring sacroiliac joint BMO.

Objective To develop an evidence-based practice program for ICU eye care and evaluate its application effect using Stetler model of research utilization.Methods The systematic search was carried out in domestic and foreign guid elines,systematic reviews,evidence summaries,expert consensuses on eye care for ICU patients.The quality of the included literature was evaluated and the evidence was summarized.The evidence based on expert advice,clinical context and stakeholder opinions was screened.According to Stetler model of research utilization,the evidence translation/application was formulated from 3 aspects,including method,level and type of evidence application,and the evidence translation was implemented using a stepwise trial design.Five ICUs in a tertiary hospital in Zhejiang Province were selected,and the order of enrollment of each ICU was determined by computer-generated random numbers from April to september,2022.In the first month,all ICUs were in pre-evidence-based practice period,and in the second month,an ICU was trained and entered the evidence-based practice period.Until the 6th month,all ICUs entered the evidence-based practice period.Then the rate of ocular symptoms and implementation rate of eye care measures were compared before and after EBP.Results A total of 1 540 patients were included.With regard to the implementation rate of eye care measures,the rate of lubricant use and suspected ocular infection management in patients at high risk for ocular complications in evidence-based practice period was significantly higher compared with pre-evidence-based practice period(P＜0.001),and no statistically significant difference was found in the rate of eyelid closure.The incidence of conjunctival exposure,subconjunctival hemorrhage,conjunctival congestion,and ocular discharge in non-neurology critical care patients decreased compared with pre-evidence-based practice period(P＜0.05),and the incidence of conjunctival edema and conjunctival congestion in NICU patients decreased compared with pre-evidence-based practice period as the intervention continued(P＜0.001).Conclusion Evidence-based practice in eye care for ICU patients using Stetler model of research utilization can standardize the practice of eye care for ICU patients and improve the quality of care.