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:Hippocampal injury caused by aortic coarctation has been poorly studied,and combined detection of tumor necrosis factor α,nuclear factor κB and ionized calcium binding adaptor molecule-1 expression in aortic dissection has not been reported.OBJECTIVE:To observe histomorphologic changes in the hippocampus of a mouse model of aortic dissection and investigate the expression and significance of tumor necrosis factor alpha,nuclear factor kappaB and ionized calcium binding adaptor molecule-1 in the hippocampus of aortic dissection mice.METHODS:Sixteen healthy 3-week-old male C57BL/6 mice were randomly divided into two groups:control group and aortic dissection group,with eight mice in each group.In the aortic dissection group,mice were given β-aminopropionitrile monofumarate as drinking water for 4 weeks,and the angiotensin Ⅱ microinfiltration pump was then implanted to establish an animal model of aortic dissection.Mice in the control group were given normal diet and water.After the model was established,the maximum diameter of the ascending aorta was measured,hematoxylin-eosin staining and EVG staining were performed to evaluate the model formation rate,and the levels of inflammatory factors tumor necrosis factor α and interleukin 6 in serum were detected by enzyme-linked immunosorbent assay.The hippocampus was dissected and stained with hematoxylin-eosin to observe the pathological changes of the hippocampus in brain sections.The protein expression of tumor necrosis factor α,nuclear factor κB and ionized calcium binding adaptor molecule-1 was detected by western blot analysis.RESULTS AND CONCLUSION:(1)Compared with the control group,the maximum diameter of the ascending aorta in the aortic dissection group was significantly enlarged.(2)Hematoxylin-eosin staining of the aorta showed obvious thickening of the middle aorta and destruction and disorder of the aortic wall structure in mice.Neurons in the CA1 and CA3 regions of mice were sparsely arranged,reduced in size,and showed pyknosis with deeply stained nuclei.(3)Serum levels of inflammatory factors tumor necrosis factor α and interleukin 6 were increased in the aortic dissection group compared with the control group(P＜0.01).(4)The expression levels of tumor necrosis factor α,nuclear factor κB,phosphorylated nuclear factor κB,and ionized calcium binding adaptor molecule-1 in the hippocampus were increased in the aortic dissection group compared with the control group(P＜0.05).To conclude,microglial activation and increased expression of tumor necrosis factor α and nuclear factor κB may be involved in hippocampal neuron injury in aortic dissection mice.

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:Hippocampal injury caused by aortic coarctation has been poorly studied,and combined detection of tumor necrosis factor α,nuclear factor κB and ionized calcium binding adaptor molecule-1 expression in aortic dissection has not been reported.OBJECTIVE:To observe histomorphologic changes in the hippocampus of a mouse model of aortic dissection and investigate the expression and significance of tumor necrosis factor alpha,nuclear factor kappaB and ionized calcium binding adaptor molecule-1 in the hippocampus of aortic dissection mice.METHODS:Sixteen healthy 3-week-old male C57BL/6 mice were randomly divided into two groups:control group and aortic dissection group,with eight mice in each group.In the aortic dissection group,mice were given β-aminopropionitrile monofumarate as drinking water for 4 weeks,and the angiotensin Ⅱ microinfiltration pump was then implanted to establish an animal model of aortic dissection.Mice in the control group were given normal diet and water.After the model was established,the maximum diameter of the ascending aorta was measured,hematoxylin-eosin staining and EVG staining were performed to evaluate the model formation rate,and the levels of inflammatory factors tumor necrosis factor α and interleukin 6 in serum were detected by enzyme-linked immunosorbent assay.The hippocampus was dissected and stained with hematoxylin-eosin to observe the pathological changes of the hippocampus in brain sections.The protein expression of tumor necrosis factor α,nuclear factor κB and ionized calcium binding adaptor molecule-1 was detected by western blot analysis.RESULTS AND CONCLUSION:(1)Compared with the control group,the maximum diameter of the ascending aorta in the aortic dissection group was significantly enlarged.(2)Hematoxylin-eosin staining of the aorta showed obvious thickening of the middle aorta and destruction and disorder of the aortic wall structure in mice.Neurons in the CA1 and CA3 regions of mice were sparsely arranged,reduced in size,and showed pyknosis with deeply stained nuclei.(3)Serum levels of inflammatory factors tumor necrosis factor α and interleukin 6 were increased in the aortic dissection group compared with the control group(P＜0.01).(4)The expression levels of tumor necrosis factor α,nuclear factor κB,phosphorylated nuclear factor κB,and ionized calcium binding adaptor molecule-1 in the hippocampus were increased in the aortic dissection group compared with the control group(P＜0.05).To conclude,microglial activation and increased expression of tumor necrosis factor α and nuclear factor κB may be involved in hippocampal neuron injury in aortic dissection mice.

Objective To study the photodynamic performance and the killing effect of photodynamic therapy on lung cancer of novel chlorin compounds 2-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） acetic acid（D1）and 4-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） butanoic acid （D2）. Methods The ultraviolet visible absorption spectrum and fluorescence spectrum of D1 and D2 were determined. The singlet oxygen generation capacity of D1 and D2 was measured by using DPBF as singlet oxygen capture agent. Fluorescence assay was used to detect the cellular phagocytosis rate of the compounds in A549 cells, and MTT assay was used to detect their dark toxicity and phototoxicity. A nude mouse model of lung cancer was established to investigate the antitumor activity of the compounds mediated photodynamic action in vivo, and the blood concentration of D2 in nude mice, its distribution in tumor tissue and skin tissue were further detected. Results D1 and D2 had strong absorption at 652 nm with the best excitation wavelength at 429 nm and 427 nm, and the optimal emission wavelength was at about 659 nm. They also had a higher singlet oxygen generation rate than the control drug m-THPC. D1 and D2 had no dark toxicity at concentrations below 10 μmol/L, and could be ingested by A549 cells, basically reaching saturation in 18~24 hours. After laser irradiation at 650 nm wavelength, D1 and D2 showed significant antitumor activity in vivo and in vitro （P<0.01）. However, D2 could selectively accumulate in tumor tissues after administration, and the optimal treatment time was less than 30 min after administration. Conclusion D2 had excellent photodynamic antitumor activity and could selectively aggregate in tumor tissues, which had the potential to be a candidate drug for photosensitizer and treatment of lung cancer with independent intellectual property rights, and was worth further research.

Antimicrobial resistance (AMR) poses a critical global health threat. This review systematically examines AMR surveillance technology advances, from conventional culture methods to modern molecular diagnostics (e.g., whole-genome sequencing) and artificial intelligence-assisted approaches. It focuses on the current application of mass spectrometry, machine learning predictive models, and real-time surveillance networks. To address challenges including inadequate technical standardization, clinical translation barriers, and data-sharing limitations, we propose integrated ^"genotype-phenotype^" strategies and global standardization framework, while exploring future applications of CRISPR-based portable detection, single-cell sequencing, and blockchain technologies.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

AIM:To investigate the prevalence of visual impairment and its correction status among junior high school students in Xi'an, so as to provide evidence for the development of targeted myopia prevention and control strategies.METHODS: A stratified cluster sampling design was adopted. From March to May 2025, students in grades 7-9 were recruited from three schools in Xi'an, Shaanxi Province, China: Dongfang Middle School, the Middle School Attached to Xi'an University of Technology, and the Xingqing Campus of the High School Affiliated to Xi'an Jiaotong University. In total, 3 974 students were invited, including 1 726 in grade 7, 1 206 in grade 8, and 1 042 in grade 9. The visual acuity was measured monocularly using a 5 m standard logarithmic visual acuity chart, with the fellow eye occluded; the line corresponding to the smallest optotype that could be correctly identified was recorded as the visual acuity value. Non-cycloplegic autorefraction was performed with a desktop autorefractor to obtain spherical equivalent(SE)values for refractive error screening.RESULTS: This study initially included 3 974 students, of whom 32 did not participate in the vision test, resulting in 3 942 students being included in the final analysis. Among them, 3 067(77.80%)were identified with poor vision. The prevalence of myopia was 81.47%(1 746)in males and 87.55%(1 575)in females(P<0.01). A stratified analysis by grade showed myopia rates of 81.72%(1 386)in junior grade one, 84.47%(1 017)in junior grade two, and 88.10%(918)in junior grade three, demonstrating a significant upward trend with increasing grade level(χ2=19.8484, P<0.01). Among the 3 321 myopic students, 2 287 adopted corrective measures. The rates of full correction, under-correction, and non-correction among all myopic students were 48.15%(1 599), 20.71%(688), and 31.14%(1 034), respectively. The rate of non-correction was significantly higher in male students than in females(32.70% vs 29.40%, χ2=4.2222, P<0.05).CONCLUSION: The findings indicate a high prevalence of visual impairment among junior high school students in Xi'an, coupled with suboptimal spectacle-wearing and full-correction rates. There is an urgent need for collaborative efforts across society, schools, and families to implement effective interventions to slow the onset and progression of myopia in this population.

Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.