BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.

Investigated the mechanisms by which baicalein regulates nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)to ameliorate lipopolysaccharide(LPS)-induced sepsis-asso-ciated acute kidney injury(AKI)in mice.Sixty male C57BL/6 mice were randomly divided into six groups:control,model,low-dose baicalein(50 mg/kg),medium-dose baicalein(100 mg/kg),high-dose baicalein(200 mg/kg),and high-dose baicalein+brusatol(4 mg/kg).Baicalein was adminis-tered orally for 7 days as a preventative measure.Sepsis was induced via intraperitoneal injection of LPS.Murine sepsis score(MSS)was assessed within 12 hours post-induction.Serum creatinine(Scr),blood urea nitrogen(BUN),tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and interleukin-6(IL-6)were measured using an automatic biochemical analyzer and enzyme-linked immunosorbent assays(ELISA),respectively.Histopathological changes in kidney tissues were ob-served via hematoxylin-eosin(HE)staining.Western blot analysis was employed to determine the protein expression levels of Nrf2,HO-1,caspase-8,TNF-α,IL-1β,and IL-6 in kidney tissues.Additionally,total superoxide dismutase(SOD)activity in kidney tissues was assessed using com-mercially available kits.Compared to the model group,baicalein treatment significantly improved renal histopathological changes,alleviated cellular damage,and reduced the levels of inflammatory cytokines(TNF-α,IL-1βand IL-6)(P＜0.01)and kidney injury markers(Scr and BUN)(P＜0.01).Moreover,baicalein treatment significantly increased the protein expression levels of Nrf2 and HO-1(P＜0.01)and enhanced antioxidant enzyme activity.In conclusion,baicalein may pro-tect against LPS-induced sepsis-associated AK1 in mice by modulating the Nrf2/HO-1 signaling pathway,thereby attenuating oxidative stress,reducing inflammation,and disrupting the vicious cycle between inflammation and oxidative stress.

Investigated the mechanisms by which baicalein regulates nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)to ameliorate lipopolysaccharide(LPS)-induced sepsis-asso-ciated acute kidney injury(AKI)in mice.Sixty male C57BL/6 mice were randomly divided into six groups:control,model,low-dose baicalein(50 mg/kg),medium-dose baicalein(100 mg/kg),high-dose baicalein(200 mg/kg),and high-dose baicalein+brusatol(4 mg/kg).Baicalein was adminis-tered orally for 7 days as a preventative measure.Sepsis was induced via intraperitoneal injection of LPS.Murine sepsis score(MSS)was assessed within 12 hours post-induction.Serum creatinine(Scr),blood urea nitrogen(BUN),tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and interleukin-6(IL-6)were measured using an automatic biochemical analyzer and enzyme-linked immunosorbent assays(ELISA),respectively.Histopathological changes in kidney tissues were ob-served via hematoxylin-eosin(HE)staining.Western blot analysis was employed to determine the protein expression levels of Nrf2,HO-1,caspase-8,TNF-α,IL-1β,and IL-6 in kidney tissues.Additionally,total superoxide dismutase(SOD)activity in kidney tissues was assessed using com-mercially available kits.Compared to the model group,baicalein treatment significantly improved renal histopathological changes,alleviated cellular damage,and reduced the levels of inflammatory cytokines(TNF-α,IL-1βand IL-6)(P＜0.01)and kidney injury markers(Scr and BUN)(P＜0.01).Moreover,baicalein treatment significantly increased the protein expression levels of Nrf2 and HO-1(P＜0.01)and enhanced antioxidant enzyme activity.In conclusion,baicalein may pro-tect against LPS-induced sepsis-associated AK1 in mice by modulating the Nrf2/HO-1 signaling pathway,thereby attenuating oxidative stress,reducing inflammation,and disrupting the vicious cycle between inflammation and oxidative stress.

Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.

Objective To explore an epileptic seizure prediction method for patients with refractory epilepsy to improve the classification and prediction efficiency of epileptic electroencephalogram(EEG)signals.Methods The study used the long-term EEG database of patients with intractable epilepsy from Children's Hospital Boston(CHB-MIT).The EEG features of epileptic seizures and preictal periods were extracted from multiple dimensions such as EEG synchronization,complexity,and energy distribution,and then these features were input into the artificial neural network model for classification and identification,thereby achieving accurate prediction of epilepsy.The performance were optimized by adjusting the model parameters,and a comparative evaluation was conducted with existing deep learning models.Results The model proposed in this study showed an accuracy rate of 99.29％,a precision of 91.44％,a sensitivity of 96.46％,and a specificity of 99.46％.Compared with current epilepsy seizure prediction studies based on machine learning or deep learning frameworks,the model in this study improved its classification prediction capabilities and demonstrated higher prediction accuracy.Conclusion An effective prediction of epileptic seizures was achieved by manually extracting epileptic EEG features and constructing an artificial neural network model.The model demonstrated high accuracy and stability,providing reliable technique to support clinical treatment and prevention of epilepsy.

Objective To explore an epileptic seizure prediction method for patients with refractory epilepsy to improve the classification and prediction efficiency of epileptic electroencephalogram(EEG)signals.Methods The study used the long-term EEG database of patients with intractable epilepsy from Children's Hospital Boston(CHB-MIT).The EEG features of epileptic seizures and preictal periods were extracted from multiple dimensions such as EEG synchronization,complexity,and energy distribution,and then these features were input into the artificial neural network model for classification and identification,thereby achieving accurate prediction of epilepsy.The performance were optimized by adjusting the model parameters,and a comparative evaluation was conducted with existing deep learning models.Results The model proposed in this study showed an accuracy rate of 99.29％,a precision of 91.44％,a sensitivity of 96.46％,and a specificity of 99.46％.Compared with current epilepsy seizure prediction studies based on machine learning or deep learning frameworks,the model in this study improved its classification prediction capabilities and demonstrated higher prediction accuracy.Conclusion An effective prediction of epileptic seizures was achieved by manually extracting epileptic EEG features and constructing an artificial neural network model.The model demonstrated high accuracy and stability,providing reliable technique to support clinical treatment and prevention of epilepsy.