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.

This article provides a systematic interpretation and review of the Society of Critical Care Medicine 2024 Guidelines on Adult ICU Design. Developed based on the Grading of Recommendations Assessment, Development and Evaluation methodology, the guideline address five core themes: ICU layout, room design, infection control, infrastructure, and staff spaces, and put forward 17 evidence-based recommendations, including 5 good practice statements. This article briefly introduces the guideline development methods and evidence characteristics, and focuses on summarizing key recommendations, including high-visibility layouts, single-bed ward settings, natural lighting and noise reduction strategies, integrated infection prevention and control design, remote monitoring, and flexible capacity expansion capabilities. Furthermore, it delves into the applicability and localized implementation pathways within China's healthcare environment, analyzing limitations in terms of evidence quality, specialty applicability, and cost-effectiveness. Furthermore, by integrating the Chinese Guidelines for the Construction and Development of Critical Care Medicine (2025 Edition) and current domestic practices, the article proposes tiered and phased implementation recommendations. This article aims to provide domestic healthcare institutions with a scientific reference that balances international cutting-edge concepts with China's real-world conditions for the construction and renovation of ICUs, thereby promoting the development of intensive care environments centered on patient safety, healthcare worker well-being, and infection control.

ObjectiveTo explore the application of virtual reality biofeedback training combined with oral localization therapy in dysphagia after oral cancer surgery. MethodsFrom May, 2023 to July, 2024, 86 patients with dysphagia after oral cancer surgery in Zhejiang Provincial People's Hospital were randomly divided into control group (n = 43) and experimental group (n = 43). The control group received conventional swallowing function training, while the experimental group added virtual reality biofeedback training combined with oral positioning therapy, for four weeks. The Standardized Swallowing Function Assessment Scale (SSA), Functional Oral Intake Scale (FOIS) and M.D.Anderson Dysphagia Inventory (MDADI) were used for evaluation before intervention, and two weeks, four weeks and eight weeks after intervention. ResultsFor scores of SSA , the main effects of group (F = 150.190, P < 0.001, η²_p = 0.641) and time (F = 230.870, P < 0.001, η²_p = 0.733), as well as the interaction effect (F = 16.910, P < 0.001, η²_p = 0.168) were all significant. For scores of FOIS, the main effects of group (F = 59.601, P < 0.001, η²_p = 0.415) and time (F = 89.464, P < 0.001, η²_p = 0.516), as well as the interaction effect (F = 7.990, P < 0.001, η²_p = 0.087) were all significant. For scores of MDADI, the main effects of group (F = 33.133, P < 0.001, η²_p = 0.283) and time (F = 49.650, P < 0.001, η²_p = 0.371), as well as the interaction effect (F = 3.224, P = 0.023, η²_p = 0.037) were all significant. ConclusionVirtual reality biofeedback training combined with oral localization therapy could improve the swallowing function, oral feeding ability and overall quality of life of patients with dysphagia after oral cancer surgery.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

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.

This study identified the types and pathogen carrying status of fleas on the surface of sheep in some areas of southern Xinjiang,and analyzed the genetic evolution differences with respect to related pathogens.The aim was to provide a reference for the local prevention and control of fleas and insect borne infectious diseases.A total of 1 586 fleas were collected from agricultural and pas-toral areas of Tumushuke City and Hotan Prefecture.Flea species were identified on the basis of morphology and the Pulex irritans mi-tochondrial COII gene.Flea DNA was extracted,and PCR was conducted to amplify the Bartonella gltA gene;Arsenophonus,Ana-plasma,Ehrlichia,and Wolbachia 16S rRNA genes;RickettsiaOmpA,17kDa,16S rRNA genes,and Yersinia pestis 16S rDNA gene.The amplified products were sequenced,and the homology of the genes of the three detected pathogens(gltA gene of Bartonella,16S rRNA gene of Wolbachia,and Anaplasma phagocytophilum)with respect to known corresponding genes of the same pathogen in Gen-Bank was analyzed.Phylogenetic trees were constructed with the adjacency method in MEGA 11.0.According to morphological and mo-lecular biology identification results,all fleas collected in this study were Pulex irritans.PCR indicated that the target gene fragments had been added to the mitochondrial COII,BartonellagltA,Wolbachia,and autophagosomal 16S rRNA genes of human fleas,all of which were consistent with the expected fragment sizes.Target bands were not amplified from Ehrlichia,Arsenophonus,spotted fever group Rickettsia,and Yersinia pestis.According to homology and genetic evolution analysis of human flea mitochondrial COII and the corresponding genes of the above-described pathogens,the COX2 gene(ON455234.1)of human fleas in Tumushuke city and Iran ob-tained in this study showed the highest homology(99.84%).The COII gene(NC_063709.1)of human fleas in Hetan City and Hunan region showed the highest homology(100%).Our findings further confirmed that the flea species was Pulex irritans.The PCR amplifi-cation results indicated that the collected Pulex irritans carried multiple pathogens,among which Bartonella and Wolbachia had the highest infection rates,and the infection rate with Anaplasma phagocytophilum was relatively low.This study is the first to discover flea species on the surface of sheep in some areas of southern Xinjiang.Our findings preliminarily confirmed that Bartonella,Wolba-chia,and Anaplasma phagocytophilum are the main Pulex irritans pathogens.

Atherosclerosis(As)is a chronic inflammatory vascular disease and serves as the pathological basis for various cardiovascular diseases.Epigallocatechin-3-O-gallate(EGCG)is the most abundant and biologically active com-pound in green tea,possessing multiple pharmacological effects such as anti-inflammatory,antiviral,and antioxidative stress properties.In recent years,studies have found that EGCG can regulate lipid metabolism,improve vascular endo-thelial function,and enhance plaque stability,demonstrating its potential value in combating As.This article provides a systematic review of the mechanisms underlying EGCG's anti-As effects,aiming to offer multi-faceted theoretical support for its further research and clinical application in the prevention and treatment of As.

Objective:To discern the association between autism-like behaviors and resilience within the ado-lescent demographic.Methods:A total of 7 063 middle school students were selected to assess ASD-like behaviors and resilience in adolescents using the Autism Spectrum Screening Questionnaire(ASSQ)as well as the Resilience Scale for Chinese Adolescent(RSCA).Subgroups bounded by P5 and P95 of the total ASSQ score,a comparative analysis of the resilience scores between these groups was executed.A correlation evaluation and linear regression a-nalysis was carried out between ASSQ and RSCA scores from all participants.Results:The RSCA scores within the high ASSQ scoring group,were inferior to those in the low scoring group.ASSQ scores were negatively correlated with RSCA scores for the full sample(Ps＜0.01);Social interaction scores on the ASSQ were negatively correlated with the five-factor RSCA scores(β=-0.23,-0.27,-0.11,-0.23,-0.37,Ps＜0.05).Conclusion:There was a negative association between autism spectrum disorder-like behaviors and resilience in adolescents,with more severe social interaction symptoms being associated with poorer resilience.

Objective:To discern the association between autism-like behaviors and resilience within the ado-lescent demographic.Methods:A total of 7 063 middle school students were selected to assess ASD-like behaviors and resilience in adolescents using the Autism Spectrum Screening Questionnaire(ASSQ)as well as the Resilience Scale for Chinese Adolescent(RSCA).Subgroups bounded by P5 and P95 of the total ASSQ score,a comparative analysis of the resilience scores between these groups was executed.A correlation evaluation and linear regression a-nalysis was carried out between ASSQ and RSCA scores from all participants.Results:The RSCA scores within the high ASSQ scoring group,were inferior to those in the low scoring group.ASSQ scores were negatively correlated with RSCA scores for the full sample(Ps＜0.01);Social interaction scores on the ASSQ were negatively correlated with the five-factor RSCA scores(β=-0.23,-0.27,-0.11,-0.23,-0.37,Ps＜0.05).Conclusion:There was a negative association between autism spectrum disorder-like behaviors and resilience in adolescents,with more severe social interaction symptoms being associated with poorer resilience.