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:Systematic evaluation and integration of the exercise experience of HIV infected/AIDS patients.Methods:Databases including Web of science, PubMed, Embase, Cochrane Library, CINAHL, PsycINFO, Wangfang Database, CNKI, SinoMed and Vip were searched, from their inception to January 31, 2024, to collect qualitative studies on HIV infected/AIDS patients′ experience of exercise. The quality of included studies was evaluated according to JBI Critical Appraisal Tool for qualitative studies in Australia. The results were integrated by integrating methods.Results:A total of 20 studies were included. 87 complete findings were grouped according to similarities to form 10 new categories.These categories resulted in 4 synthesized findings: perceived benefits of exercise in HIV infected/AIDS patients; motivation of exercise in HIV infected/AIDS patients; obstructive factors of exercise in HIV infected/AIDS patients; the needs and expectations of HIV infected/AIDS for exercise.Conclusions:Exercise is a supportive nursing choice for HIV infected/AIDS patients during the treatment process, and nursing staff should pay attention to the patients′perception of exercise and guide their perception of benefits. Focus on the patients′ positive psychology and provide support from multiple perspectives. Pay attention to the factors that hinder patient movement and provide personalized care. Targeting patient needs and optimizing home exercise intervention methods.

Objective:To systematically evaluate the qualitative study on HIV pre-exposure prophylaxis (PrEP) medication experience among men who have sex with men (MSM) .Methods:China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Web of Science, Embase, CINAHL, Cochrane Library, and PsycINFO were searched. The search period was from database establishment to February 1, 2024. The methodological quality of the included literature was evaluated according to the quality evaluation criteria for qualitative research of the Joanna Briggs Institute Evidence-Based Health Care Center. The integrative synthesis was used to integrate the findings.Results:A total of 11 articles were included, and 36 findings were distilled into eight new categories, which were synthesized to form three integrated findings (perceived PrEP medication benefits by MSM, perceived barriers to PrEP medication by MSM, and multidimensional adaptations to enhance the PrEP medication experience in MSM) .Conclusions:Healthcare providers should pay close attention to the PrEP medication experience of MSM, identify medication challenges promptly, and focus on assisting them with self-adaptation to improve the PrEP medication experience and increase PrEP medication adherence in MSM.

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:Systematic evaluation and integration of the exercise experience of HIV infected/AIDS patients.Methods:Databases including Web of science, PubMed, Embase, Cochrane Library, CINAHL, PsycINFO, Wangfang Database, CNKI, SinoMed and Vip were searched, from their inception to January 31, 2024, to collect qualitative studies on HIV infected/AIDS patients′ experience of exercise. The quality of included studies was evaluated according to JBI Critical Appraisal Tool for qualitative studies in Australia. The results were integrated by integrating methods.Results:A total of 20 studies were included. 87 complete findings were grouped according to similarities to form 10 new categories.These categories resulted in 4 synthesized findings: perceived benefits of exercise in HIV infected/AIDS patients; motivation of exercise in HIV infected/AIDS patients; obstructive factors of exercise in HIV infected/AIDS patients; the needs and expectations of HIV infected/AIDS for exercise.Conclusions:Exercise is a supportive nursing choice for HIV infected/AIDS patients during the treatment process, and nursing staff should pay attention to the patients′perception of exercise and guide their perception of benefits. Focus on the patients′ positive psychology and provide support from multiple perspectives. Pay attention to the factors that hinder patient movement and provide personalized care. Targeting patient needs and optimizing home exercise intervention methods.

Objective:To systematically evaluate the qualitative study on HIV pre-exposure prophylaxis (PrEP) medication experience among men who have sex with men (MSM) .Methods:China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Web of Science, Embase, CINAHL, Cochrane Library, and PsycINFO were searched. The search period was from database establishment to February 1, 2024. The methodological quality of the included literature was evaluated according to the quality evaluation criteria for qualitative research of the Joanna Briggs Institute Evidence-Based Health Care Center. The integrative synthesis was used to integrate the findings.Results:A total of 11 articles were included, and 36 findings were distilled into eight new categories, which were synthesized to form three integrated findings (perceived PrEP medication benefits by MSM, perceived barriers to PrEP medication by MSM, and multidimensional adaptations to enhance the PrEP medication experience in MSM) .Conclusions:Healthcare providers should pay close attention to the PrEP medication experience of MSM, identify medication challenges promptly, and focus on assisting them with self-adaptation to improve the PrEP medication experience and increase PrEP medication adherence in MSM.

Objective Meta-analysis was used to evaluate the effect of the solution-focused brief therapy on im-proving the anxiety and depression status of patients with HIV/AIDS.Methods Computer search of PubMed,Embase,Web of Science,Cochrane Library,CINAHL,PsycINFO,Chinese Biomedical Literature Database,China Na-tional Knowledge Infrastructure,Wanfang Database,CQVIP were conducted,and the search time frame was from the establishment of databases until April 9,2023.There were 2 investigators who independently screened the literature according to inclusion and exclusion criteria,extracted data and performed quality evaluation,and performed Meta-analysis using RevMan 5.4 software.Results A total of 11 publications were included,including 9 randomized controlled trials and 2 quasi-experimental studies,with a total of 1 219 patients with HIV/AIDS.Meta-analysis re-sults showed that solution-focused brief therapy reduced anxiety scores(SMD=-1.89;95%CI:-2.79～-0.99,P＜0.001),depression scores(SMD=-2.45;95%CI:-3.51～-1.39,P＜0.001).Subgroup analysis showed that improved anxiety(SMD=-4.16;95%CI:-7.97～-0.35,P＜0.001),depression(SMD=-5.69;95%CI:-11.20～-0.19,P＜0.001)in pregnant HIV/AIDS patients was significantly better than that in ordinary patients.Conclusion Solution-focused brief therapy is effective in improving anxiety and depression levels in patients with HIV/AIDS,and the application of this model in pregnant patients with HIV/AIDS has a more significant improvement effect,but high-quality,multicenter,large-sample clinical trial studies are needed to further confirm this conclusion in the future.

Unnatural amino acid orthogonal translation machinery can insert unnatural amino acids at desired sites of protein through stop codon by means of foreign orthogonal translation system composed of aminoacyl-tRNA synthetase and orthogonal tRNA genes. This new genetic engineering technology is not only a new tool for biochemical researches of proteins, but also an epoch-making technology for the development of new-type live viral vaccines. The mutated virus containing premature termination codon in genes necessary for replication can be propagated in transgenic cells harboring unnatural amino acid orthogonal translation machinery in media with corresponding unnatural amino acid, but it cannot replicate in conventional host cells. This replication-deficient virus is a new-type of live viral vaccine that possesses advantages of high efficacy of traditional attenuated vaccine and high safety of killed vaccine. This article reviews the application and prospect of unnatural amino acid orthogonal translation machinery in the development of novel replication-deficient virus vaccines.
Amino Acids ; genetics ; Amino Acyl-tRNA Synthetases ; Genetic Engineering ; Protein Engineering ; RNA, Transfer ; Viral Vaccines