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.

Twelve derivatives of asiatic acid were synthesized through acylation, alkylation, oxidative dehydrogenation and other reactions using asiatic acid from usoxane-type pentacyclic triterpenoids as the parent compound. Their structures were confirmed by 1H NMR and 13C NMR, and determined to be novel compounds never reported in literature. Through the MTT method, high-expression human cancer cells (A549 and SGC-7901) were selected for a preliminary in vitro anti-tumor activity study on these compounds. Among them, the IC50 of compound I1 were 11.39 and 9.08 μmol/L respectively, and those of compound I2 were 12.64 and 9.15 μmol/L respectively, which were close to those of sorafenib, a common drug for clinical use. The experimental results show that the synthesized asiatic acid derivatives have certain anti-proliferative effects on the two types of human cancer cells, A549 and SGC-7901, significantly higher than those of asiatic acid. Compounds I1 and I2 show quite strong anti-proliferative effects on human cancer cells A549 and SGC-7901.

Objective To investigate the prevalence and the risk factors of heart disease(HD)in adults aged ≥80 years old in China based on the data from the 8th round of the Chinese Longitudinal Healthy Longevity Survey(CLHLS).Methods A total of 7 675 adults aged ≥80 years old were enrolled from the 8th round of CLHLS dataset.Chi-square tests were employed to examine associations between cardiovascular disease and demographic characteristics,socioeconomic status,social support,lifestyle factors,and health indicators.Logistic regression models were developed to analyze significant predictors of heart disease in the elderly.Results The prevalence of heart disease was 16％(n=1 228)in 7 675 elderly people.Aged 90-99 years old(odds ratio[OR]=0.816),≥100 years old(OR=0.641),female(OR=0.833),and low body mass index(BMI)(＜18.5 kg/m2,OR=0.778)were the protective factors for cardiovascular disease in the elderly;and high BMI(24.0 to 27.9 kg/m2,OR=1.209),rural residence(OR=2.384),health examination(OR=1.164),dysfunction of daily living activities(OR=1.401),hypertension(OR=2.143),diabetes mellitus(OR=1.719),and history of cerebrovascular accident(OR=2.080)were risk factors.Conclusion Male,overweight,rural residence,health examination,dysfunction of daily living activities,hypertension,diabetes mellitus,and a history of cerebrovascular accident are the risk factors for heart disease in the elderly.

Objective:To investigate the effects of Zhibai Dihuang Pills on neurons of cognitive dysfunction in D-galactose (D-gal) model mice.Methods:Totally 60 male mice were divided into four groups using a random number table method: control group, model group, donepezil group, and Zhibai Dihuang Pills group, with 15 mice in each group. Except for the control group, the other groups were subcutaneously injected with D-galactose solution at a dosage of 125 mg/kg once a day for 8 weeks to prepare the aging model. Mice in the donepezil group were intragastrically administered donepezil solution at a dosage of 0.65 mg/kg, and those in the Zhibai Dihuang Pills group were intragastrically administered Zhibai Dihuang Pills solution at a dosage of 1.56 g/kg. The control group was intragastrically administered an equal volume of physiological saline once a day for 8 weeks. The object recognition test and Morris Water Maze were used to assess object recognition memory and spatial learning memory abilities of mice in each group, respectively. Hematoxylin-Eosin (HE) staining and Nissl staining were employed to observe the morphology of neurons in the hippocampal region; Golgi staining was used to observe neuronal dendritic spines; Western Blot was used to detect the protein expression levels of PI3K, p-Akt/Akt, glycogen synthase kinase 3β (GSK3β), postsynaptic density protein-95 (PSD-95), and synaptophysin (SYP) in the hippocampus region; RT-qPCR was performed to detect mRNA expression of PI3K, Akt and GSK3β in the hippocampus region.Results:Compared with the model group, the recognition index in both the donepezil group and the Zhibai Dihuang Pills group increased ( P<0.05), the escape latency was shortened ( P<0.05), the platform crossings times and the target quadrant dwell time increased ( P<0.05), the number of nerve cells in the hippocampal region increased, arranged closely, the number of Nissl bodies increased, the morphology returned to normal, and the density of dendritic spines increased; the protein expressions of PI3K, PSD-95, and SYP in the hippocampal region and the ratio of p-Akt/Akt increased ( P<0.01), the mRNA level of PI3K increased ( P<0.01 or P<0.05), and the protein and mRNA levels of GSK3β decreased ( P<0.01 or P<0.05). Conclusion:Zhibai Dihuang Pills can improve the learning and memory ability and rescue neuronal damage in D-gal model mice, and the mechanism may be related to the activation of PI3K/Akt pathway and the restoration of synaptic connections.

BACKGROUND:Previous studies found that the proliferative scar-specific long non-coding RNA lncRNA HSFAS is a novel biomarker that can be used in the diagnosis of hypertrophic scar,but how it functions in hypertrophic scar is not clear. OBJECTIVE:To investigate the role and mechanism of lncRNA HSFAS in hypertrophic scar.METHODS:Fresh scar tissue and surrounding normal skin tissue samples from three patients with hypertrophic scar were collected,and tissue immunofluorescence was used to detect the expression of lncRNA HSFAS in frozen sections of two skin tissues. Primary fibroblasts were isolated from proliferative scarred skin tissue and normal skin tissue and cultured by enzyme digestion method. Quantitative real-time PCR was used to detect the mRNA expression of lncRNA HSFAS in cells. The proteins bound to lncRNA HSFAS were detected by RNA pull-down combined mass spectrometry. GO and KEGG were used to analyze the main functions and pathways of lncRNA HSFAS involved in hypertrophic scar progression. The targeted binding of lncRNA HSFAS to proteins was determined by catRAPID and RPISeq website analysis. RESULTS AND CONCLUSION:Compared with normal skin tissue and fibroblasts from normal skin tissue,the expression of lncRNA HSFAS in human hypertrophic scar tissue and primary fibroblasts from hypertrophic scar tissue was significantly increased (P<0.05). There were 510 proteins clearly bound to lncRNA HSFAS by RNA pull-down combined mass spectrometry. The results of GO and KEGG analyses showed that these proteins were mainly involved in RNA splicing and processing,chromosome synthesis and separation,and cell cycle. Among them,the proteins involved in RNA splicing and processing included scaffold attachment factor B2 and DICER1,and the binding fraction with lncRNA HSFAS was higher. The results of bioinformatics analysis showed that lncRNA HSFAS was bound to scaffold attachment factor B2 and DICER1 proteins. To conclude,lncRNA HSFAS may affect gene expression by interacting with scaffold attachment factor B2 and DICER1 proteins to regulate RNA splicing and processing modification,thus promoting the occurrence and development of hypertrophic scar.

Objective To explore the diagnostic and prognostic relevance of genes associated with trastuzumab resistance and sensitivity in gastric cancer using machine learning algorithms.Methods The data on resistant and sensitive genes were downloaded from the GEO database and subjected to functional enrichment analysis.Intersection analysis was performed using TCGA and GEO data to identify feature genes related to gastric cancer drug-resistance.LASSO and SVM-RFE methods were used for feature gene selection.The expressions of these feature genes were detected in both test and validation groups,and their diagnostic value was analyzed using receiver operating characteristic curves.The prognostic value of SH3GL2 was assessed using online databases,and its role in patient survival was further explored.CIBERSORT algorithm was used to evaluate the relationship between SH3GL2 and immune cell infiltration in gastric cancer,and analyze its effect on immune microenvironment.Results Fifteen resistance-related genes were identified,and 12 diagnostic biomarkers related to gastric cancer were selected through machine learning,including MMP7,COCH,VCAN,SH3GL2,SYNM,KLK6,STC2,PPP1R1B,CDH3,WNT11,PMEPA1,and BCAT1.SH3GL2 showed low expression in both test and validation groups,and its high expression was associated with poorer prognosis in gastric cancer(P<0.01).SH3GL2 expression level was related to various immune cells(activated CD8+T cells,activated DC cells)and showed positive correlations with immune suppressive factors(such as TGFB1,VTCN1)and negative correlations with immune stimulatory factors(such as CD70,CD80).Conclusion The 12 selected feature genes can serve as potential diagnostic biomarkers for gastric cancer.SH3GL2 has a low expression in gastric cancer,and its high expression might shorten patient survival by inhibiting anti-tumor immunity.

Objective:To construct a volume management program for peritoneal dialysis patients in the peridialysis period.Methods:The intervention map was used as a guiding framework to build a first draft of a volume management program for peritoneal dialysis patients during the peridialysis period based on semi-structured interviews and a literature review in conjunction with a health belief model. Between December 2023 and February 2024, the first draft of the volume management program was revised by two rounds of expert consultation to produce a final program.Results:A total of 15 peritoneal dialysis medical and nursing experts were invited to complete two rounds of Delphi expert consultation. In the two rounds of expert consultation, 15 questionnaires were issued, and 15 valid questionnaires were recovered; the effective recovery rate was 100.00%, and the expert authority coefficient was both 0.903. The final constructed volume management program for peritoneal dialysis patients during the peridialysis period consisted of four first-level items (knowledge training, volume management plan development, behavioral assessment, and belief support), 10 second-level items, and 30 third-level items.Conclusions:The volume management program for peritoneal dialysis patients in the peridialysis period constructed in this study is scientific and can provide a reference for healthcare professionals.

This paper reviews the main contents, characteristics, applications, advantages and limitations of self-management assessment tools for hypertension patients, comparatively analyzes the basic conditions and applications of the existing assessment tools and makes suggestions, with a view to providing references for healthcare professionals in China to select, develop and apply self-management assessment tools for hypertension patients.

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*