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.

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

PURPOSE: Deep vein thrombosis (DVT) of the left and right lower extremities was treated in the same way, but the left and right extremities received different levels of attention. This study aimed to investigate the differences between the right and left lower extremity deep vein thrombosis (LEDVT). METHODS: Clinical characteristics of LEDVT patients from July 2020 to June 2022 were retrospectively analyzed to compare the incidence of LEDVT on different limbs, demographics, predisposing factors, and anatomical characteristics. The exclusion criteria were bilateral LEDVT and recurrent thrombosis. Measured data was analyzed using independent samples t-test or Mann-Whitney test. Count data were analyzed by Chi-square test. A p < 0.05 was considered a statistically significant difference. RESULTS: There were 478 patients included in this study and the ratio of left to right LEDVT on the left and right limbs was 3.16:1 (363:115). Left LEDVT predominantly affected female, with the major aged > 50 years (50 - 60 years: 16.80%; > 60 years: 57.30%). The primary predisposing factor was iliac vein compression syndrome, with iliofemoral thrombosis being the main type. Male patients with LEDVT on the right limb were predominant and the age of onset was usually ≤ 60 years (52.17%). The main predisposing factor was recent surgery or trauma (< 30 days) and femoropopliteal thrombosis was the main type. In more detail, the left iliac vein was compressed mainly in the proximal segment, and the right iliac vein was compressed mainly in the intermediate and distal segments. Recent surgery or trauma to the locomotor system and genitourinary system often induced LEDVT. CONCLUSION The incidence of LEDVT on the left is significantly higher than that on the right. LEDVT on different sides has different characteristics, which is crucial for prevention and diagnosis in the relevant population so there are also differences in treatment of the affected limbs.
Humans ; Venous Thrombosis/etiology* ; Male ; Female ; Middle Aged ; Lower Extremity/blood supply* ; Retrospective Studies ; Adult ; Aged ; Age Factors ; Sex Factors ; Risk Factors ; Acute Disease ; Incidence ; Aged, 80 and over ; Young Adult ; Adolescent

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

Objective To explore the relationship between the polymorphism of excision repair cross-complementation group 1 (ERCC1) C8092A locus and the efficacy and prognosis of platinum-based chemotherapy for lung cancer (LC), and to provide a theoretical basis for precision treatment of LC. Methods From January 2014 to October 2017, 120 patients from two tertiary hospitals in Haikou City, and with pathologically confirmed lung cancer treated with platinum-based chemotherapy were selected as the research objects. After informed consent was obtained, peripheral blood samples were collected for DNA extraction, and the genotype of ERCC1 C8092A locus was detected by mass spectrometry. WHO's Response Evaluation Criteria in Solid Tumours (RECIST) was used to judge patients' chemotherapy efficacy and patients' survival status was obtained by telephone follow-up and other means. Results Among the 120 LC patients, the genotype frequencies of ERCC1 C8092A locus were 67 cases of CC wildtype (55.8%), 45 cases of CA heterozygous type (37.5%), and 8 cases of AA rare mutation type (6.7%), which conformed to Hardy-Weinberg equilibrium (χ2=0.140, P>0.05). The total effective rate of chemotherapy was 32.5%, with the highest effective rate in patients with the CA genotype (42.2%) at the ERCC1 C8092A locus and the lowest in patients with the CC genotype (25.4%). The overall one-year survival rate was 68.3% and the three-year survival rate was 35.8%. The patients with ERCC1 C8092A AA genotype had the lowest survival rate, with a one-year survival rate of 50.0% and three-year survival rate of only 25.0%. However, there were no statistical differences in the overall survival rate among the three genotypes of carriers of ERCC1 C8092A (χ2=0.328, P=0.849). Conclusions The polymorphism of ERCC1 C8092A locus is associated with the efficacy of platinum-based chemotherapy for LC, and patients with CA genotype have the highest efficacy. The one-year and three-year survival rates of patients with CC genotype are significantly higher than those of CA and AA genotypes.

Objective To investigate the infection status and changing trend of hepatitis C virus(HCV)infection in hospitalized patients in medical institutions,and provide reference for formulating HCV infection prevention and control strategies.Methods HCV infection surveillance results from cross-sectional survey data reported to China Healthcare-associated Infection(HAI)Surveillance System in 2020 were summarized and analyzed,HCV positive was serum anti-HCV positive or HCV RNA positive,survey result was compared with the survey results from 2003.Results In 2020,1 071 368 inpatients in 1 573 hospitals were surveyed,738 535 of whom underwent HCV test,4 014 patients were infected with HCV,with a detection rate of 68.93％and a HCV positive rate of 0.54％.The positive rate of HCV in male and female patients were 0.60％and 0.48％,respectively,with a statistically sig-nificant difference(x2=47.18,P＜0.001).The HCV positive rate in the 50-＜60 age group was the highest(0.76％),followed by the 40-＜50 age group(0.71％).Difference among all age groups was statistically signifi-cant(x2=696.74,P＜0.001).In 2003,91 113 inpatients were surveyed.35 145 of whom underwent HCV test,resulting in a detection rate of 38.57％;775 patients were infected with HCV,with a positive rate of 2.21％.In 2020,HCV positive rates in hospitals of different scales were 0.46％-0.63％,with the highest in hospital with bed numbers ranging 600-899.Patients'HCV positive rates in hospitals of different scales was statistically signifi-cant(X2=35.34,P＜0.001).In 2020,12 provinces/municipalities had over 10 000 patients underwent HCV-rela-ted test,and HCV positive rates ranged 0.19％-0.81％,with the highest rate from Hainan Province.HCV posi-tive rates in different departments were 0.06％-0.82％,with the lowest positive rate in the department of pedia-trics and the highest in the department of internal medicine.In 2003 and 2020,HCV positive rates in the depart-ment of infectious diseases were the highest,being 7.95％and 3.48％,respectively.Followed by departments of orthopedics(7.72％),gastroenterology(3.77％),nephrology(3.57％)and general intensive care unit(ICU,3.10％)in 2003,as well as departments of gastroenterology(1.35％),nephrology(1.18％),endocrinology(0.91％),and general intensive care unit(ICU,0.79％)in 2020.Conclusion Compared with 2003,HCV positive rate decreased significantly in 2020.HCV infected patients were mainly from the department of infectious diseases,followed by departments of gastroenterology,nephrology and general ICU.HCV infection positive rate varies with gender,age,and region.

Malignant tumor is a serious threat to human survival and development, and the delay of medical treatment for cancer patients has an effect on the survival rate of patients. This paper summarizes the definition of delayed medical treatment and the current situation, influencing factors and prevention and control countermeasures of delayed medical treatment in cancer patients, so as to provide references for medical personnel to formulate relevant measures of delayed medical treatment.

OBJECTIVE: To explore the potential mechanism of resistance to axitinib in clear cell renal cell carcinoma (ccRCC), with a view to expanding the understanding of axitinib resistance, facilitating the design of more specific treatment options, and improving the treatment effectiveness and survival prognosis of patients. METHODS: By exploring the half maximum inhibitory concentration (IC₅₀) of axitinib on ccRCC cell lines 786-O and Caki-1, cell lines resistant to axitinib were constructed by repeatedly stimulated with axitinib at this concentration for 30 cycles in vitro. Cell lines that were not treated by axitinib were sensitive cell lines. The phenotypic differences of cell proliferation and apoptosis levels between drug resistant and sensitive lines were tested. Genes that might be involved in the drug resistance process were screened from the differentially expressed genes that were co-upregulated in the two drug resistant lines by transcriptome sequencing. The expression level of the target gene in the drug resistant lines was verified by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB). The expression differences of the target gene in ccRCC tumor tissues and adjacent tissues were analyzed in the Gene Expression Profiling Interactive Analysis (GEPIA) public database, and the impact of the target gene on the prognosis of ccRCC patients was analyzed in the Kaplan-Meier Plotter (K-M Plotter) database. After knocking down the target gene in the drug resistant lines using RNA interference by lentivirus vector, the phenotypic differences of the cell lines were tested again. WB was used to detect the levels of apoptosis-related proteins in the different treated cell lines to find molecular pathways that might lead to drug resistance. RESULTS: Cell lines 786-O-R and Caki-1-R resistant to axitinib were successfully constructed in vitro, and their IC₅₀ were significantly higher than those of the sensitive cell lines (10.99 μmol/L, P < 0.01; 11.96 μmol/L, P < 0.01, respectively). Cell counting kit-8 (CCK-8) assay, colony formation, and 5-ethynyl-2 '-deoxyuridine (EdU) assay showed that compared with the sensitive lines, the proliferative ability of the resistant lines decreased, but apoptosis staining showed a significant decrease in the level of cell apoptosis of the resistant lines (P < 0.01). Although resistant to axitinib, the resistant lines had no obvious new replicated cells in the environment of 20 μmol/L axitinib. Nuclear protein 1 (NUPR1) gene was screened by transcriptome sequencing, and its RNA (P < 0.0001) and protein expression levels significantly increased in the resistant lines. Database analysis showed that NUPR1 was significantly overexpressed in ccRCC tumor tissue (P < 0.05); the ccRCC patients with higher expression ofNUPR1had a worse survival prognosis (P < 0.001). Apoptosis staining results showed that knockdown ofNUPR1inhibited the anti-apoptotic ability of the resistant lines to axitinib (786-O, P < 0.01; Caki-1, P < 0.05). WB results showed that knocking downNUPR1decreased the protein level of B-cell lymphoma-2 (BCL2), increased the protein level of BCL2-associated X protein (BAX), decreased the protein level of pro-caspase3, and increased the level of cleaved-caspase3 in the resistant lines after being treated with axitinib. CONCLUSION ccRCC cell lines reduce apoptosis through theNUPR1 -BAX/ BCL2 -caspase3 pathway, which is involved in the process of resistance to axitinib.
Humans ; Carcinoma, Renal Cell/metabolism* ; Axitinib/pharmacology* ; Kidney Neoplasms/metabolism* ; bcl-2-Associated X Protein ; Nuclear Proteins ; Cell Line, Tumor ; Apoptosis ; Cell Proliferation

OBJECTIVE: To explore the clinical characteristics and prognosis of multiple myeloma(MM) patients with secondary primary malignancies. METHODS: The clinical data of newly diagnosed MM patients admitted to the First Affiliated Hospital of Zhengzhou University from January 2011 to December 2019 were retrospectively analyzed. The patients with secondary primary malignancies were retrieved, and their clinical features and prognosis were evaluated. RESULTS: A total of 1 935 patients with newly diagnosed MM were admitted in this period, with a median age of 62 (18-94) years old, of which 1 049 cases were hospitalized twice or more. There were eleven cases with secondary primary malignancies (the incidence rate was 1.05%), including three cases of hematological malignancies (2 cases of acute myelomonocytic leukemia and 1 case of acute promyelocytic leukemia) and eight cases of solid tumors (2 cases of lung adenocarcinoma, and 1 case each of endometrial cancer, esophageal squamous cell carcinoma, primary liver cancer, bladder cancer, cervical squamous cell carcinoma, and meningioma). The median age of onset was 57 years old. The median time between diagnosis of secondary primary malignancies and diagnosis of MM was 39.4 months. There were seven cases with primary or secondary plasma cell leukemia, the incidence rate was 0.67%, and the median age of onset was 52 years old. Compared with the randomized control group, the β2-microglobulin level in the secondary primary malignancies group was lower (P=0.028), and more patients were in stage I/II of ISS (P=0.029). Among the 11 patients with secondary primary malignancies, one survived, ten died, and the median survival time was 40 months. The median survival time of MM patients after the secondary primary malignancies was only seven months. All seven patients with primary or secondary plasma cell leukemia died, with a median survival time of 14 months. The median overall survival time of MM patients with secondary primary malignancies was longer than that of the patients with plasma cell leukemia (P=0.027). CONCLUSION The incidence rate of MM with secondary primary malignancies is 1.05%. MM patients with secondary primary malignancies have poor prognosis and short median survival time, but the median survival time is longer than that of patients with plasma cell leukemia.
Humans ; Middle Aged ; Aged ; Aged, 80 and over ; Multiple Myeloma/complications* ; Leukemia, Plasma Cell ; Retrospective Studies ; Esophageal Neoplasms/complications* ; Esophageal Squamous Cell Carcinoma/complications* ; Prognosis ; Neoplasms, Second Primary

Oxidative Phosphorylation ; Acetylglucosamine ; Uridine Diphosphate N-Acetylglucosamine/metabolism*