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.

Parkinson’s disease (PD) is a common neurodegenerative disorder with profound impact on patients’ quality of life and long-term health, and early detection and intervention are particularly critical. In recent years, the search for precise and reliable biomarkers has become one of the key strategies to effectively address the clinical challenges of PD. In this paper, we systematically evaluated potential biomarkers, including proteins, metabolites, epigenetic markers, and exosomes, in the peripheral blood of PD patients. Protein markers are one of the main directions of biomarker research in PD. In particular, α‑synuclein and its phosphorylated form play a key role in the pathological process of PD. It has been shown that aggregation of α-synuclein may be associated with pathologic protein deposition in PD and may be a potential marker for early diagnosis of PD. In terms of metabolites, uric acid, as a metabolite, plays an important role in oxidative stress and neuroprotection in PD. It has been found that changes in uric acid levels may be associated with the onset and progression of PD, showing its potential as an early diagnostic marker. Epigenetic markers, such as DNA methylation modifications and miRNAs, have also attracted much attention in Parkinson’s disease research. Changes in these markers may affect the expression of PD-related genes and have an important impact on the onset and progression of the disease, providing new research perspectives for the early diagnosis of PD. In addition, exosomes, as a potential biomarker carrier for PD, are able to carry a variety of biomolecules involved in intercellular communication and pathological regulation. Studies have shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide a new breakthrough for early diagnosis. It has been shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide new breakthroughs in early diagnosis. In summary, through in-depth evaluation of biomarkers in the peripheral blood of PD patients, this paper demonstrates the important potential of these markers in the early diagnosis of PD and in the study of pathological mechanisms. Future studies will continue to explore the clinical application value of these biomarkers to promote the early detection of PD and individualized treatment strategies.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Potassium-calcium activates channel subfamily N member 3(KCNN3/SK3/KCa2.3)is in-volved in regulating cellular calcium signaling,muscle contraction and neurotransmitter release.Dysregu-lation of the KCNN3 channel is associated with the development of various tumors.We use bioinformatics analysis to identify whether KCNN3 regulates the occurrence and development of stomach adenocarcinoma(STAD)as a prognostic target.By analyzing the Human Protein Atlas(HPA)database and The Cancer Genome Atlas(TCGA)database,we found that the protein and mRNA levels of KCNN3 were dramatic-ally reduced in STAD,and TCGA database showed that KCNN3 significantly correlated with the prognosis and clinical features of STAD.In addition,we found that high expression of KCNN3 in STAD reduced the IC50 of several drugs in STAD cells,suggesting that high expression of KCNN3 correlated with the drug sensitivity of STAD.To investigate the underlying biological mechanism,we identified a potential KCNN3 interaction factor,tumor necrosis factor receptor superfamily member 7(CD27/TNFRSF7),which is expressed at low levels in STAD.RT-qPCR and Western blotting confirmed that KCNN3 and CD27 positively correlated with each other at protein and mRNA levels,and co-immunoprecipitation and immunofluorescence experiments confirmed that the two proteins interact and colocalize in the cytoplasm.Moreover,we confirmed the inhibitory effect of KCNN3 on the proliferation,migration and invasion of hu-man STAD cells in vitro and in vivo through subcutaneous tumorigenesis and cellular experiments.Fur-thermore,GO/KEGG enrichment analysis showed that KCNN3 was enriched in signaling pathways regula-ting the immune response and calcium or metal ion transport.Lastly,we verified through cell co-culture,RT-qPCR and CCK8 assays that high expression of KCNN3 can promote the increase of T cell activating factor and the killing effect of T cells on STAD cells.Therefore,our results suggest that KCNN3 is a po-tential inhibitory factor affecting the occurrence and progression of STAD.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

In this study, RAW264.7 cells were employed to investigate the effects of honey-processed Astragalus on their energy metabolism and polarization, and explore the scientific connotation of the enhanced efficacy of honey-processed Astragalus on invigorating spleen-stomach and replenishing Qi. The medicated sera were prepared by intragastric administration of rats with water extracts of crude and honey-processed Astragalus, and the composition changes of medicated sera of crude and honey-processed Astragalus were analyzed by using LC-MS technology. The cell survival rates were detected and the concentrations of medicated sera were screened through CCK-8 assay. The differences of cell phagocytic rates, ATP energy metabolism, and NO secretion between crude and honey-processed Astragalus were evaluated by using neutral red phagocytosis assay, ATP detection kit, and NO detection kit. The effects of crude and honey-processed Astragalus on TNF-α secretion of RAW264.7 cells were detected by employing ELISA kit. The effects of crude and honey-processed Astragalus on polarization of RAW264.7 cells were evaluated by utilizing flow cytometry. The differential metabolites related to glycolysis in cell lysates and culture media were screened by using LC-MS technology. The experiment was approved by the experimental animal ethics committee from Shanxi University of Chinese Medicine (No. AWE202407352). The results showed that the contents of betaine, amino acids, and ononin in the prepared medicated sera of rats treated by intragastric administration with water extracts of honey-processed Astragalus increased compared to those in crude one. The results of CCK-8 experiment showed that there were no cytotoxic effects on RAW264.7 cells in the medicated sera of crude and honey-processd Astragalus at different concentration. The phagocytic index and ATP yield both increased to varying degrees after administration of the medicated sera to cells. The secretion of NO in normal and inflammatory cells increased and decreased respectively, and the effect of honey-processed Astragalus was better than that of crude one. The results of ELISA kit showed that the medicated sera of both crude and honey-processed Astragalus could promote the secretion of TNF-α in a concentration-dependent manner, and the promoting effect of honey-processed Astragalus was stronger than that of crude one. The results of flow cytometry showed that the medicated sera of both crude and honey-processed Astragalus could promote M1-type polarization and inhibit M2-type polarization of RAW264.7 cells, and the effect of honey-processed Astragalus was better than that of crude one. Compared to crude Astragalus, the metabolites related to glycolysis in the cell lysates and culture media of the medicated sera of honey-processed Astragalus were generally on the rise, indicating that the effect on promoting glycolysis of honey-processed Astragalus was better than that of crude one. In summary, honey-processed Astragalus can promote the polarization and energy metabolism of RAW264.7 cells, and participate in positive immune regulation, which is correlated with its enhanced effect of invigorating spleen-stomach and replenishing Qi.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.