AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

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.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

In 2023, new diagnostic criteria were proposed to distinguish myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) from other inflammatory diseases of the central nervous system.With typical clinical presentation and neuroimaging features, the seropositive status of anti-myelin oligodendrocyte glycoprotein-IgG (MOG-IgG) is essential for the diagnosis of MOGAD.Advances in cell transfection immunofluorescence assays have improved diagnostic accuracy in the last few years, but there are differences in the positive predictive value of serum MOG-IgG titers in the context of different MOGAD prevalence.Therefore, alternative diagnostic methods need to be further explored, and the clinical significance of low MOG-IgG titers should be carefully interpreted.In this review, the main clinical features, current understanding and challenges of MOGAD were discussed, including uncertainties about the specificity and pathogenicity of myelin oligodendrocyte glycoprotein autoantibodies and the need to identify immunopathological targets for future therapies.Moreover, it is necessary to search for and validate biomarkers that can help diagnose and detect disease activity, and it is important to identify MOGAD patients who need long-term immunotherapy.

Varicella, often referred to as chickenpox, is a widespread acute infectious condition triggered by the varicella-zoster virus (VZV). It manifests with systemic symptoms and distinct skin and mucosal eruptions, including macules, papules, and vesicles. Although it mainly affects children, the disease is typically more severe in teenagers and adults. Following the adoption of vaccine-based control measures in China, there has been a noticeable trend of varicella affecting older demographics, leading to an uptick in cases among teenagers and adults. This review synthesizes the latest research on the clinical symptoms, epidemiological trends, and immunization strategies for varicella in these age groups, both domestic and aboard. The goal is to enhance strategies for prevention and control, support the development of tailored immunization policies, and underscore the critical role of the varicella vaccine in comprehensive health management across all ages.

To evaluate the effectiveness of the modified post anesthesia care unit (PACU) discharge assessment tool in the field of bone oncology, in order to prevent and reduce postoperative adverse events in patients undergoing bone tumor surgery. This is a prospective controlled study. 81 bone tumor patients who underwent general anesthesia surgery in the PACU from January to December 2023 were prospectively selected as the study subjects. They were randomly divided into a control group and an intervention group using a random number table method, with 43 and 38 cases, respectively. The control group and intervention group respectively used the fast track scoring system and the improved fast track scoring system as exit assessment tools. Independent sample t-test was used to compare the duration of PACU stay, mean arterial pressure (MAP) at PACU exit, heart rate, and blood oxygen saturation (SpO 2) between two groups of patients. Chi square test was used to compare the occurrence of adverse events between the two groups. The results showed that there was no statistically significant difference between the intervention group and the control group in terms of PACU dwell time [(55.58±23.83) min vs. (46.14±21.87) min], MAP at PACU [(88.23±11.52) mmHg vs. (86.25±10.62) mmHg], heart rate [(86.25±10.62) beats/min vs. (72.93±18.86) beats/min], and SpO 2 [(99.84±0.68)% vs. (99.86±0.91)%] ( t=1.859, 0.805, 1.003, 0.101,all P>0.05). The total incidence of adverse events in the intervention group was significantly lower than the control group (68.42% vs. 90.70%, χ2=4.988, P<0.05). In conclusion, the modified fast-tracking criteria can significantly reduce the incidence of adverse events in PACU patients undergoing bone tumor surgery, but does not affect PACU dwell time and patient circulatory status.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

AIM To evaluate the chemical constituent consistency in formula granules and traditional decoctions of Gouteng Jiangya Formula.METHODS HPLC characteristic chromatograms were established,the analysis was performed on a 30 ℃ thermostatic YMC-Triart C18 column(4.6 mm× 250 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.Puerarin was used as an internal standard to calculate the relative correction factors of 3'-methoxy puerarin,puerarin apioside,magnolflorine,paeoniflora,daidzin,baicalin,palmatine,berberine,wogonoside and benzoylpaeoniflorin,after which the content detemination was made by quantitative analysis of multi-components by single-marker(QAMS).RESULTS The characteristic chromatograms of 9 batches of formula granules and 15 bacthes of traditional decoctions demonstrated the similarities of more than 0.90 at the detection wavelengths of 192,210,240,260,280,300,320,360 nm,along with similar total peak areas.Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 97.27％-101.64％with the RSDs of 0.36％-1.11％,the result obtained by QAMS and external standard method demonstrated no significant differences(P＞0.05).The contents of various constituents in the formula granules approximated those in the traditional decoctions.CONCLUSION The consistent kinds and contents of various constituents are obversable in formula granules and traditional decoctions of Gouteng Jiangya Formula,which can provide a reference for the reasonable clinical application of this formula.

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

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.