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.

Diabetic nephropathy （DKD）， as a common microvascular complication of diabetes mellitus （DM）， is a major cause of end-stage renal disease （ESRD）. Its clinical manifestations include increased urinary protein excretion， thickening of the glomerular basement membrane， and renal tubulointerstitial fibrosis. The pathogenesis of DKD is complex and involves multiple factors， including disordered glucose metabolism， hemodynamic alterations， and oxidative stress. Although modern medical approaches can alleviate certain symptoms， they still have limitations such as insufficient therapeutic targeting and prominent adverse effects. The transforming growth factor-β/Smad （TGF-β/Smad） signaling pathway is not only a tissue fibrosis pathway that has attracted considerable attention in recent years， but also regulates multiple protein molecules， including the glomerular podocyte slit diaphragm protein Podocin， interleukin-1β （IL-1β）， and superoxide dismutase （SOD）， thereby participating in various pathological processes and ultimately mediating renal injury. Flavonoid compounds， owing to their sustained pharmacological effects， broad spectrum of action， and high safety profile， have become ideal candidates for targeted therapy research in DKD. Existing studies have shown that these compounds can exert inhibitory effects on renal fibrosis， alleviate inflammatory responses， protect podocytes， and reduce oxidative stress by regulating the interactions between the TGF-β/Smad signaling pathway and the aforementioned protein molecules， thereby maintaining renal structure and function， reducing proteinuria， and significantly improving DKD lesions. This review briefly outlines the composition and functions of the TGF-β/Smad signaling pathway， elucidates the mechanisms by which this pathway regulates DKD， and focuses on summarizing major studies from the past decade on flavonoid-based interventions in DKD through targeted inhibition of the TGF-β/Smad signaling pathway. Furthermore， it discusses the considerable therapeutic potential of flavonoids in the treatment of this disease， aiming to provide a scientific basis for future clinical prevention and treatment of DKD and to promote the development of targeted drugs.

ObjectiveTo explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P0.05）， and compared with the model group， both were significantly increased in the Sini San group （P0.05， P0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P0.05， P0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.

ObjectiveTo explore the efficacy and mechanisms of Sini San in the treatment of depression and liver injury based on gut microbiota. MethodsThirty-two male Sprague-Dawley （SD） rats were randomly divided into a normal group， model group （M）， Sini San group （MS， 2.5 g·kg^-1）， and fluoxetine group （MF， 2 mg·kg^-1）. Except for the normal group， rats in the other three groups were subjected to chronic unpredictable mild stress （CUMS）. After 8 weeks， the open-field test and sucrose preference test were conducted. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum corticosterone （CORT）， adrenocorticotropic hormone （ACTH）， corticotropin-releasing factor （CRF）， lipopolysaccharide （LPS）， Zonulin， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， γ-aminobutyric acid （GABA） levels in the hippocampus and prefrontal cortex， and brain-derived neurotrophic factor （BDNF） levels in the hippocampus. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect hippocampal BDNF mRNA expression. Serum alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using the ultraviolet lactate dehydrogenase method. The ultrastructure of the intestinal epithelium was observed by electron microscopy， and gut microbiota in rat feces were analyzed using 16S rDNA high-throughput sequencing. ResultsCompared with the normal group， the sucrose preference of rats in the model group was significantly reduced （P<0.01）， whereas it was significantly increased in the Sini San group compared with the model group （P<0.05）. Compared with the normal group， hippocampal GABA protein levels and BDNF mRNA expression in the model group were significantly decreased （P<0.05）， and compared with the model group， both were significantly increased in the Sini San group （P<0.05， P<0.01）. Compared with the normal group， serum LPS and Zonulin levels in the model group were significantly increased （P<0.05， P<0.01）， and compared with the model group， Zonulin levels in the Sini San group were significantly decreased （P<0.05）. No obvious changes were observed in the ultrastructure of the jejunal mucosa among groups. Compared with the normal group， widened and blurred tight junctions， sparse and shortened microvilli， and mitochondrial swelling with cristae disruption in epithelial cells were observed in the ileal and colonic mucosa of the model group， which were markedly improved in the Sini San and fluoxetine groups. The results of 16S rDNA high-throughput sequencing showed that Sini San improved CUMS-induced dysbiosis of Bacteroidetes and Proteobacteria. Correlation analysis indicated that Bacteroidetes and Proteobacteria were significantly correlated with depression-related indicators， liver function， and intestinal mucosal permeability. ConclusionSini San exerts antidepressant and hepatoprotective effects by improving Bacteroidetes and Proteobacteria and inhibiting the increase in intestinal mucosal permeability in CUMS rats.

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.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To study the inhibitory effect of secondary metabolites of Pseudomonas aeruginosa(PA)on Candida albicans(CA)and to explore some of the mechanisms.Methods PA and CA strains were i-solated from clinical specimens from the hospital.Then,PA strains with inhibitory effects on CA were screened through cross-line test and co-incubation test,and crude extracts of PA secondary metabolites were prepared,and were tested together with pyocyanin,phenazine-1-carboxylic acid,1-hydroxyphenazine,and 3-ox-ododecyl-l-homoserine lactone(3-oxo-HSL).The inhibitory effects of various PA secondary metabolites on CA were determined through minimum inhibitory concentration test,minimum bactericidal concentration test,time-sterilization curve measurement,and XTT method activity measurement test,and some mechanisms by which PA secondary metabolites inhibited CA were explored.Results The strongest inhibitory effect on CA was 1-hydroxyphenazine,and at a concentration of 6.250 μg/mL,the relative activity of CA decreased to 0.00%.Next were pyocyanin and PA crude extract,and the relative fungal activity of CA decreased to 0.00%at concentrations of 200 and 100 μg/mL.1-hydroxyphenazine,pyocyanin,3-oxo-HSL and PA crude extract all had inhibitory effects on the formation of CA hyphae.Reactive oxygen species(ROS)were generated in CA cells treated with 1-hydroxyphenazine,phenazine 1-carboxylic acid,pyocyanin,and PA crude extract,and the highest levels of ROS were induced by pyocyanin and 1-hydroxyphenazine.Conclusion Phenazine secondary metabolites 1-hydroxyphenazine and pyocyanin have significant inhibitory effects on the growth and activity of CA,and both induce the highest amount of ROS.The quorum-sensing signal molecule 3-oxo-HSL have no in-hibitory effect on CA growth,but have a significant inhibitory effect on the formation of fungal hyphae.

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

Poly(ADP-ribosyl)ation (PARylation) is a specific form of post-translational modification (PTM) predominantly triggered by the activation of poly-ADP-ribose polymerase 1 (PARP1). However, the role and mechanism of PARylation in the advancement of acute kidney injury (AKI) remain undetermined. Here, we demonstrated the significant upregulation of PARP1 and its associated PARylation in murine models of AKI, consistent with renal biopsy findings in patients with AKI. This elevation in PARP1 expression might be attributed to trimethylation of histone H3 lysine 4 (H3K4me3). Furthermore, a reduction in PARylation levels mitigated renal dysfunction in the AKI mouse models. Mechanistically, liquid chromatography-mass spectrometry indicated that PARylation mainly occurred in receptor for activated C kinase 1 (RACK1), thereby facilitating its subsequent phosphorylation. Moreover, the phosphorylation of RACK1 enhanced its dimerization and accelerated the ubiquitination-mediated hypoxia inducible factor-1α (HIF-1α) degradation, thereby exacerbating kidney injury. Additionally, we identified a PARP1 proteolysis-targeting chimera (PROTAC), A19, as a PARP1 degrader that demonstrated superior protective effects against renal injury compared with PJ34, a previously identified PARP1 inhibitor. Collectively, both genetic and drug-based inhibition of PARylation mitigated kidney injury, indicating that the PARylated RACK1/HIF-1α axis could be a promising therapeutic target for AKI treatment.

OBJECTIVES: To investigate the effect of high glucose on macrophage polarization and the role of immune-responsive gene 1 (IRG1) in mediating its effect. METHODS: RAW264.7 cells were transfected with IRG1-overexpressing plasmid or IRG1 siRNA via electroporation and cultured in either normal or high glucose for 72 h to observe the changes in cell viability and morphology using CCK-8 assay and phase contrast microscopy. The protein levels of IRG1, iNOS, Arg-1, IL-1β and IL-10 in the treated cells were detected with Western blotting, and the fluorescence intensities of iNOS and Arg-1 were detected using immunofluorescence assay. The protein levels of IL-1β and IL-10 in the culture medium were determined with ELISA. RESULTS: High glucose exposure significantly reduced IRG1 and Arg-1 expressions, increased iNOS and IL-1β expressions and IL-1β secretion, and decreased IL-10 level in RAW264.7 cells. Transfection with the IRG1-overexpressing plasmid provided the cells with obvious resistance to high glucose-induced changes in iNOS, Arg-1, IL-1β and IL-10, whereas IRG1 knockdown further enhanced the effects of high glucose exposure on Arg-1 expression and the expression and secretion of IL-10. CONCLUSIONS High glucose promotes M1 polarization of the macrophages possibly through a mechanism to inhibit the expression of IRG1 protein, thus leading to chronic inflammatory response.
Animals ; Mice ; Macrophages/drug effects* ; Glucose/pharmacology* ; Interleukin-10/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; RAW 264.7 Cells ; Interleukin-1beta/metabolism* ; Arginase/metabolism* ; RNA, Small Interfering/genetics* ; Transfection ; Inflammation