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.

Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

AIM: To evaluate the application effectiveness of the 3D surgical video system and intraoperative optical coherence tomography(OCT)in idiopathic epiretinal membrane vitrectomy.METHODS: A retrospective analysis was conducted on 61 patients(61 eyes)with idiopathic epiretinal membrane at our hospital from January 2023 to October 2023. The patients were divided into two groups based on the surgical methods: with 31 patients(31 eyes)who underwent surgery using the 3D surgical video system and intraoperative OCT technology in 3D group, and 30 patients(30 eyes)underwent surgery using the Resight non-contact wide-angle lens system in traditional surgery group. Surgical time, membrane peeling time were recorded, followed-up for 6 mo, post-operative best-corrected visual acuity(BCVA), intraocular pressure(IOP), central macular thickness(CMT), and complications were analyzed for the two groups.RESULTS:All patients successfully underwent surgery without experiencing serious intraoperative complications such as major retinal hemorrhage, retinal tears, or retinal detachment. Additionally, no postoperative complications such as endophthalmitis or secondary glaucoma occurred. The surgical duration and membrane peeling time in the 3D group were significantly shorter than those in the traditional surgery group(20.13±1.59 vs 25.97±2.09 min; 3.74±0.89 vs 8.13±1.72 min, respectively; both P<0.001). There were no significant differences in BCVA and CMT between preoperative and 1-month postoperative values for both groups of patients(both P>0.008). However, both BCVA and CMT improved significantly at 3 and 6 mo postoperatively compared to preoperative levels(both P<0.008). At 6 mo postoperatively, the BCVA in the 3D group was significantly better than that in the traditional surgery group(P=0.007). There were no significant differences in CMT or IOP between the two groups at any postoperative time point(all P>0.05).CONCLUSION: Both the 3D surgical video system and the traditional surgical group can treat idiopathic epiretinal membrane, but the 3D surgical video system has advantages in shortening the surgical time, improving surgical efficiency, and enhancing the precision of surgical steps during surgery with the assistance of intraoperative OCT.

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:Rheumatoid arthritis is a chronic autoimmune disease.Early diagnosis is crucial for preventing disease progression and for effective treatment.Therefore,it is of significance to investigate the diagnostic characteristics and immune cell infiltration of rheumatoid arthritis. OBJECTIVE:Based on the Gene Expression Omnibus(GEO)database,to screen potential diagnostic markers of rheumatoid arthritis using machine learning algorithms and to investigate the relationship between the diagnostic characteristics of rheumatoid arthritis and immune cell infiltration in this pathology. METHODS:The gene expression datasets of synovial tissues related to rheumatoid arthritis were obtained from the GEO database.The data sets were merged using a batch effect removal method.Differential expression analysis and functional correlation analysis of genes were performed using R software.Bioinformatics analysis and three machine learning algorithms were used for the extraction of disease signature genes,and key genes related to rheumatoid arthritis were screened.Furthermore,we analyzed immune cell infiltration on all differentially expressed genes to examine the inflammatory state of rheumatoid arthritis and investigate the correlation between their diagnostic characteristics and infiltrating immune cells. RESULTS AND CONCLUSION:In both rheumatoid arthritis and normal synovial tissues,we identified 179 differentially expressed genes,with 124 genes up-regulated and 55 genes down-regulated.Enrichment analysis revealed a significant correlation between rheumatoid arthritis and immune response.Three machine learning algorithms identified LRRC15 and MICB as potential biomarkers of rheumatoid arthritis.LRRC15(area under the curve=0.964,95%confidence interval:0.924-0.992)and MICB(area under the curve=0.961,95%confidence interval:0.923-0.990)demonstrated strong diagnostic performance on the validation dataset.The infiltration of 13 types of immune cells was altered,with macrophages being the most affected.In rheumatoid arthritis,the majority of proinflammatory pathways in immune cell function were activated.Immunocorrelation analysis revealed that LRRC15 and MICB had the strongest correlation with M1 macrophages.To conclude,this study identified LRRC15 and MICB as potential diagnostic markers for rheumatoid arthritis,with strong diagnostic performance and significant correlation with immune cell infiltration.Machine learning and bioinformatics analysis deepened the understanding of immune infiltration in rheumatoid arthritis and provided new ideas for the diagnosis and treatment of rheumatoid arthritis.

Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.

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*

Abstract In recent years, Chinese college students have shown increased awareness of the importance of physical exercise. However, challenges such as insufficient health literacy, declining physical fitness, and low participation rates in physical activity still persist. To address these issues, the study applies behavioral economics theory and incorporates concepts such as anchoring effects, intertemporal decision making, loss aversion, and herd behavior, to examine the irrational factors and decision making preferences underlying college students physical exercise behaviors. By analyzing the cognitive biases in their decision making processes, the research aims to propose targeted and scientifically validated intervention strategies, so as to provide references for improving college students engagement in physical exercise and promoting their overall well being.