1.Efficient Loading and Targeted Delivery of Plant Exosomes
Meng XU ; Long-Jiao ZHU ; Jie LI ; Chong-Bin LEI ; Yang-Zi ZHANG ; Hong-Tao TIAN ; Wen-Tao XU
Progress in Biochemistry and Biophysics 2026;53(6):1597-1608
Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.
2.Forensic Research Progress on Bongkrekic Acid Poisoning
Xuan-Long CHEN ; Qiang YUAN ; Yong SUN ; Die ZHANG ; Jian-Bin FU ; Li-Liang LI
Journal of Forensic Medicine 2025;41(2):111-119
Bongkrekic acid(BA)is a toxin with stable properties and no distinctive smell.It exists in common foods such as fermented edible grain products,potato products,spoiled tremella fuciformis and auricularia polytricha,as well as auricularia polytricha that has been soaked too long.It can easily cause food poisoning.At present,there is still a lack of complete method to detect BA,and no spe-cific antidote of BA has been found.Therefore,BA poisoning is easy to be misdiagnosed or missed diagnosed,and its mortality rate remains high.In recent years,studies have revealed the toxic mecha-nism of BA and found that BA can inactivate some enzymes containing thiol groups(-SH)and in-hibit the synthesis and transport of adenosine triphosphate(ATP),causing damage to liver,kidney,brain and other parenchymal organs.This article reviews the autopsy cases and literature of deaths caused by BA poisoning at home and abroad,systematically summarizes the epidemiology,clinical manifestations,pathological changes,toxicological mechanisms,detection methods,forensic diagnostic key points and challenges of BA in forensic medicine,with the aim of providing a reference for foren-sic identification of related cases.
3.Predictive value of bpMRI for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L.
Lai DONG ; Rong-Jie SHI ; Jin-Wei SHANG ; Zhi-Yi SHEN ; Kai-Yu ZHANG ; Cheng-Long ZHANG ; Bin YANG ; Tian-Bao HUANG ; Ya-Min WANG ; Rui-Zhe ZHAO ; Wei XIA ; Shang-Qian WANG ; Gong CHENG ; Li-Xin HUA
National Journal of Andrology 2025;31(5):426-431
Objective: The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods: The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results: Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62-24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16-17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12-3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion: For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans
;
Male
;
Prostatic Neoplasms/diagnostic imaging*
;
Lymphatic Metastasis
;
Retrospective Studies
;
Nomograms
;
Prostate-Specific Antigen/blood*
;
Lymph Nodes/pathology*
;
Pelvis
;
Predictive Value of Tests
;
Prostatectomy
;
Lymph Node Excision
;
Risk Factors
;
Magnetic Resonance Imaging
;
Logistic Models
;
Middle Aged
;
Aged
4.Multiple biomarkers risk score for accurately predicting the long-term prognosis of patients with acute coronary syndrome.
Zhi-Yong ZHANG ; Xin-Yu WANG ; Cong-Cong HOU ; Hong-Bin LIU ; Lyu LYU ; Mu-Lei CHEN ; Xiao-Rong XU ; Feng JIANG ; Long LI ; Wei-Ming LI ; Kui-Bao LI ; Juan WANG
Journal of Geriatric Cardiology 2025;22(7):656-667
BACKGROUND:
Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients.
METHODS:
We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables.
RESULTS:
During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively).
CONCLUSIONS
CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.
5.Ablation of macrophage transcriptional factor FoxO1 protects against ischemia-reperfusion injury-induced acute kidney injury.
Yao HE ; Xue YANG ; Chenyu ZHANG ; Min DENG ; Bin TU ; Qian LIU ; Jiaying CAI ; Ying ZHANG ; Li SU ; Zhiwen YANG ; Hongfeng XU ; Zhongyuan ZHENG ; Qun MA ; Xi WANG ; Xuejun LI ; Linlin LI ; Long ZHANG ; Yongzhuo HUANG ; Lu TIE
Acta Pharmaceutica Sinica B 2025;15(6):3107-3124
Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.
6.Associations between Pesticide Metabolites and Decreased Estimated Glomerular Filtration Rate Among Solar Greenhouse Workers: A Specialized Farmer Group.
Teng Long YAN ; Xin SONG ; Xiao Dong LIU ; Wu LIU ; Yong Lan CHEN ; Xiao Mei ZHANG ; Xiang Juan MENG ; Bin Shuo HU ; Zhen Xia KOU ; Tian CHEN ; Xiao Jun ZHU
Biomedical and Environmental Sciences 2025;38(2):265-269
7.Cucurbitacin B alleviates skin lesions and inflammation in a psoriasis mouse model by inhibiting the cGAS-STING signaling pathway.
Yijian ZHANG ; Xueting WANG ; Yang YANG ; Long ZHAO ; Huiyang TU ; Yiyu ZHANG ; Guoliang HU ; Chong TIAN ; Beibei ZHANG ; Zhaofang BAI ; Bin ZHANG
Chinese Journal of Cellular and Molecular Immunology 2025;41(5):428-436
Objective To investigate the effects of cucurbitacin B (CucB) on alleviating skin lesions and inflammation in psoriasis mice via the cGAS-STING signaling pathway. Methods The expression of genes associated with the cGAS-STING signaling pathway in psoriatic lesions and non-lesional skin was analyzed, and hallmark gene set enrichment analysis was performed. The cytotoxicity of CucB on BMDMs was evaluated using the CCK-8 assay. The expression levels of genes and proteins related to the cGAS-STING signaling pathway, along with the secretion of inflammatory cytokines, were measured at different concentrations of CucB using quantitative PCR, Western blotting, and ELISA. Imiquimod-induced psoriasis BALB/c mice were divided into four groups: normal group, model group, low-dose CucB group [0.1 mg/ (kg.d)], and high-dose CucB group [0.4 mg/ (kg.d)], with five mice per group. PASI scoring was performed to assess the severity of psoriasis after 6 days of treatment, and HE staining was conducted to observe pathological damage. Meanwhile, the mRNA levels of inflammatory cytokines and their secretion were detected by qPCR and ELISA. Results Most cGAS-STING signaling-related genes were upregulated in lesional skin of psoriasis patients, and the hallmark gene set enrichment analysis revealed that the most significantly upregulated genes were primarily associated with immune response signaling pathways. CucB inhibited dsDNA-induced phosphorylation of interferon regulatory factor 3 (IRF3) and STING proteins in both bone-marrow derived macrophages(BMDMs) and THP-1 cells. CucB also suppressed dsDNA-induced mRNA expression of IFNB1, TNF, IFIT1, CXCL10, ISG15, and reduced the secretion of cytokines such as IFN-β, IL-1β, and TNF-α in THP-1 cells. In the imiquimod-induced psoriasis mouse model, CucB treatment reduced psoriatic symptoms, alleviated skin lesions, and attenuated inflammation. ELISA and qPCR results showed that CucB significantly reduced serum secretion levels of IL-6, TNF-α, and IL-1β, as well as the mRNA levels of IL23A, IL1B, IL6, TNF, and IFNB1. Conclusion CucB inhibits cytoplasmic DNA-induced activationc of the GAS-STING pathway. CucB significantly attenuates skin lesions and inflammation in IMQ-induced psoriatic mice, and the potential molecular mechanism may be related to the down-regulation of the cGAS-STING pathway.
Animals
;
Psoriasis/pathology*
;
Signal Transduction/drug effects*
;
Membrane Proteins/genetics*
;
Mice
;
Nucleotidyltransferases/genetics*
;
Disease Models, Animal
;
Mice, Inbred BALB C
;
Skin/metabolism*
;
Triterpenes/therapeutic use*
;
Humans
;
Cytokines/metabolism*
;
Inflammation/drug therapy*
;
Male
8.Liraglutide may alleviate acetaminophen-induced liver injury by enhancing autophagy
Guo-jing XING ; Wen-bin LI ; Long-long LUO ; Li-fei WANG ; Yuan DENG ; Zhen WANG ; Zhao-jie ZHANG ; Xiao-hui YU ; Jiu-cong ZHANG
Chinese Pharmacological Bulletin 2025;41(10):1867-1875
Aim To investigate the protective effect of liraglutide(LIRA)on acetaminophen(APAP)-in-duced hepatotoxicity at the in vivo level and to reveal the underlying mechanism.Methods Forty SPF grade male C57BL/6J mice were randomly divided into the Control,LIRA(200 μg·kg-1),APAP(500 mg·kg-1),LIRA+APAP,LIRA+APAP+3-methylade-nine(3-MA,30 mg·kg-1)groups,with eight mice in each group.The mice were administered for three con-secutive days,and the materials were taken after 24 h.The general condition and body weight of mice in each group were recorded,and liver morphology was ob-served.Serum ALT and AST levels,as well as SOD ac-tivity,MDA,and GSH content in liver homogenates,were measured using biochemical assay kits.The levels of inflammatory cytokines IL-6,TNF-α,and IL-1β in serum were detected by ELISA.Liver pathological changes were assessed by HE staining,while mitochon-drial and autophagosome structures in liver tissues were observed using transmission electron microscopy.The number of PCNA-positive cells in liver tissues was e-valuated using immunohistochemical staining.The pro-tein expression levels of LC3Ⅱ,p62,Bax,Bcl-2,PC-NA,and CyclinD1 in liver tissues were determined by Western blot.Results LIRA pretreatment can im-prove the general condition of mice with acetamino-phen-induced liver injury(AILI),reduce serum ALT and AST levels,and effectively ameliorate the appear-ance and morphology of the liver as well as the patho-logical damage to liver tissue.Simultaneously,the lev-els of inflammatory cytokines IL-6,TNF-α,and IL-1βare significantly decreased;SOD activity and GSH con-tent are significantly increased,while MDA content is significantly reduced.Transmission electron microsco-py observations reveal the presence of numerous auto-phagosomes in the cytoplasm of liver tissue.Immuno-histochemical staining results indicate a significant in-crease in the number of PCNA-positive cells.Further-more,the expression of LC3Ⅱ,Bcl-2,PCNA,and Cy-clinD1 proteins in liver tissue is significantly upregulat-ed,while the expression of p62 and Bax proteins is significantly downregulated.However,after interven-tion with the autophagy inhibitor 3-MA,the aforemen-tioned protective effects of LIRA are significantly.Conclusions LIRA pretreatment can significantly im-prove liver injury in AILI mice.Its protective mecha-nism may be related to enhancing autophagy in hepato-cytes,thereby reducing oxidative stress,inflammatory response and apoptosis in liver of AILI mice.
9.Clinical application of an artificial intelligence system in predicting benign or malignant pulmonary nodules and pathological subtypes
Zhuowen YANG ; Zhizhong ZHENG ; Bin LI ; Yiming HUI ; Mingzhi LIN ; Jiying DANG ; Suiyang LI ; Chunjiao ZHANG ; Long YANG ; Liang SI ; Tieniu SONG ; Yuqi MENG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(08):1086-1095
Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.
10.Guidelines for the Digital Ancient Books of TCM Indexing
Weina ZHANG ; Bing LI ; Bin LI ; Jing XIE ; Yan DONG ; Wei LONG ; Chuchu ZHANG ; Tong WEI ; Sihong LIU ; Yang WU ; Hongtao LI ; Lin TONG ; Guangkun CHEN ; Fei DONG ; Rui WANG ; He LU ; Meng LI ; Jingpeng DENG ; Tengfei WANG ; Xiaoying LI ; Di ZHANG
Chinese Journal of Information on Traditional Chinese Medicine 2025;32(3):1-11
Guidelines for Digital Ancient Books of TCM Indexing(T/CIATCM 119-2024)is based on the theoretical knowledge,disciplinary methods,and practical applications of TCM classical cataloging.Taking digital ancient books of TCM as the object,it systematically reveals the content of TCM knowledge,which is an essential indexing processing standard for building an intelligent retrieval system for TCM ancient books,and can provide support for the deep development and innovative utilization of TCM knowledge.It can not only promote the co-construction and sharing of ancient book resources in the TCM industry,but also promote the standardization construction and application of TCM information.This standard specifies the principles,methods,and examples of free indexing of digital ancient books of TCM based on their original content.It is applicable to the indexing and processing of digital ancient books of TCM for TCM professional libraries and related institutions,and to the data processing and construction of various types of TCM ancient book databases.

Result Analysis
Print
Save
E-mail