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.

ObjectiveTo describe the prevalence and dynamic pain characteristics of dysmenorrhea among female medical students through a menstrual diary-based observational study. MethodsFrom April to June 2021, female students were recruited from a medical college in Shanghai to complete menstrual diaries and record dysmenorrhea-related characteristics for two menstrual cycles. Dysmenorrhea severity was assessed using the visual analogue scale (VAS) (no pain: 0; mild: 1‒3; moderate: 4‒6; severe: 7‒10). A total of 323 diaries were collected, of which 303 were 93.81% valid (valid response rate: 93.81%), covering 596 complete menstrual cycles. Among them, 293 participants completed diaries for two cycles and were included in the analysis of persistent dysmenorrhea. Period, point, and persistent prevalence of dysmenorrhea were calculated using the number of participants as the denominator. Paired comparisons were performed using Cochran’s Q test and Bonferroni-adjusted McNemar tests. Using menstrual cycles with dysmenorrhea as the unit of analysis, the distributions of pain onset, peak timing, and pain duration across different severities were compared using the χ² tests or Fisher’s precision probability tests. ResultsAmong 303 female college students, 269 experienced dysmenorrhea during the first recorded cycle, and 288 had dysmenorrhea in any cycle. Among 596 complete menstrual cycles recorded, 527 were associated with dysmenorrhea (88.42%), and among 293 students who completed 2 complete recorded cycles, 239 had persistent dysmenorrhea. The period, point, and persistent prevalence of dysmenorrhea among female college students were 95.05% (288/303), 88.78% (269/303), and 81.57% (239/293), respectively (Q=61.61, P<0.001). The prevalence of persistently severe dysmenorrhea was 5.12% (15/293). Among the 527 dysmenorrheic cycles, there were statistically significant differences in the distribution of pain onset time (P=0.003) and pain duration (P<0.001) among different degrees of dysmenorrhea; mild dysmenorrhea mostly started on the first day of menstruation (52.83%), and moderate dysmenorrhea mostly started before menstruation (50.19%). Pain duration increased with severity; the proportions of cycles with pain lasting ≥4 days were 13.20%, 43.03%, and 51.56% for mild, moderate, and severe dysmenorrhea cycles, respectively. For all severity groups, mean pain scores peaked on the first day of menstruation and then decreased day by day to a stable level. ConclusionDysmenorrhea is highly prevalent among female medical students, and differences exist across pain severity levels in onset time, duration, and dynamic changes in pain. Identification and health guidance for those with persistently moderate-to-severe dysmenorrhea should be strengthened, and medical evaluation should be conducted when necessary.

ObjectiveTo review the application of the International Classification of Functioning, Disability and Health (ICF) in the field of visual impairment (VI) rehabilitation. MethodsLiterature related to ICF and VI rehabilitation was retrieved from PubMed, Web of Science, CNKI, Wanfang Data, and VIP from inception to May, 2026. Standards and policy documents related to VI published before May, 2026 were retrieved from the National Standards Full-text Disclosure System of the Standardization Administration of China, the China Disabled Persons' Federation and the Chinese Government Portal. Following PRISMA-ScR, based on the three-dimensional ICF framework, an integrated analysis was conducted from the dimensions of theory, practice and policy. ResultsA total of 17 articles involving 2 648 participants, and four domestic VI assessment standards and one guideline were included. At the theoretical level, domestic VI standards showed the highest alignment with the ICF dimension of body functions, while the coverage of the activities and participation dimension was uneven, and the coverage of the environmental factors dimension was the weakest. At the practical level, the ICF was primarily used for developing assessment tools, conducting clinical evaluations, implementing interventions and exploring service models. At the policy level, the overall orientation of domestic special education and medical insurance payment aligned with the ICF concept of whole person rehabilitation, yet specific implementation rules remained to be formulated. ConclusionICF provides a comprehensive and systematic approach for integrating the VI rehabilitation system in China, demonstrating significant application value in standard construction, clinical practice optimization and policy refinement.

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 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.

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 explore the mechanism of Pingchuanning Formula(PCN)for inhibiting airway inflammation in rats with asthmatic cold syndrome.Methods A total of 105 SD rats were randomized equally into 7 groups,including a control group,an asthmatic cold syndrome model group,3 PCN treatment groups at high,medium and low doses,a Guilong Kechuanning(GLCKN)treatment group,and a dexamethasone(DEX)treatment group.In all but the control rats,asthma cold syndrome models were established and daily gavage of saline,PCN,GLCKN or DEX was administered 29 days after the start of modeling.The changes in general condition,lung function and lung histopathology of the rats were observed,and inflammatory factors in the alveolar lavage fluid(BALF),oxidative stress,lung tissue ultrastructure,cytokine levels,and expressions of the genes related to the HMGB1/Beclin-1 axis and autophagy were analyzed.Results The rat models had obvious manifestations of asthmatic cold syndrome with significantly decreased body mass,food intake,and water intake,reduced FEV0.3,FVC,and FEV0.3/FVC,obvious inflammatory cell infiltration in the lung tissue,and increased alveolar inflammation score and counts of neutrophils,eosinophils,lymphocytes,macrophages,and leukocytes in the BALF.The rat models also had significantly increased MDA level and decreased SOD level and exhibited obvious ultrastructural changes in the lung tissues,where the expressions of HMGB1,Beclin-1,ATG5,TNF-α,IL-6,IL-1β,and IL-13 and the LC3II/I ratio were increased,while the levels of Bcl-2 and IFN-γ were decreased.PCN treatment significantly improved these pathological changes in the rat models,and its therapeutic effect was better than that of GLKCN and similar to that of DEX.Conclusion PCN can effectively alleviate airway inflammation in rat models of asthmatic cold syndrome possibly by modulating the HMGB1/Beclin-1 signaling axis to suppress cell autophagy,thereby attenuating airway inflammatory damages.