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.

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: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.

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

This study aims to investigate the pathogenesis of chronic heart failure based on ferroptosis-mediated oxidative stress and predict the targets of Shenfu Injection in treating chronic heart failure. A rat model of chronic heart failure was established by the isoproterenol induction method. According to the random number table method, the modeled rats were assigned into three groups: a model group, a Shenfu Injection group, and a ferrostatin-1(ferroptosis inhibitor) group. In addition, a normal group was designed. After 15 days of intervention, the cardiac mass index and left ventricular mass index were determined. Echocardiography was employed to eva-luate the cardiac function. Hematoxylin-eosin staining and Masson staining were employed to reveal the pathological changes and fibrosis of the heart, and Prussian blue staining to detect the aggregation of iron ions in the myocardial tissue. Transmission electron microscopy was employed to observe the mitochondrion ultrastructure in the myocardial tissue. Colorimetry was adopted to measure the levels of iron metabolism, lipid peroxidation, and antioxidant indicators. Flow cytometry was employed to measure the content of lipid-reactive oxygen species(ROS) and the fluorescence intensity of ROS. Western blot and RT-qPCR were employed to determine the protein and mRNA levels, respectively, of ferroptosis-related factors in the myocardial tissue. The results showed that the rats in the model group had reduced cardiac function, elevated levels of total iron and Fe~(2+), lowered level of glutathione(GSH), increased malondialdehyde(MDA), decreased superoxide dismutase(SOD) and glutathione peroxidase(GSH-Px), and rising levels of ROS and lipid-ROS. In addition, the model group showed fibrous tissue hyperplasia with inflammatory cell infiltration and myocardial fibrosis, iron ion aggregation, and characteristic mitochondrial changes specific for iron death. Moreover, the model group showcased upregulated protein and mRNA levels of p53 and COX2 and downregulated protein and mRNA levels of GPX4, FTH1, SLC7A11, and Nrf2 in the myocardial tissue. The intervention with Shenfu Injection significantly improved the cardiac function, recovered the iron metabolism, lipid peroxidation, and antioxidant indicators, decreased iron deposition, improved mitochondrial structure and function, and alleviated inflammatory cell infiltration and fibrosis. Furthermore, Shenfu Injection downregulated the mRNA and protein levels of p53 and COX2 and upregulated the mRNA and protein levels of GPX4, FTH1, SLC7A11, and Nrf2 in the myocardial tissue. Shenfu Injection can improve the cardiac function by regulating iron metabolism, inhibiting ferroptosis, and reducing oxidative stress injury.
Animals ; Rats ; Antioxidants ; Reactive Oxygen Species ; Cyclooxygenase 2 ; Ferroptosis ; NF-E2-Related Factor 2 ; Tumor Suppressor Protein p53 ; Heart Failure/genetics* ; Oxidative Stress ; Chronic Disease ; Glutathione ; Fibrosis ; Iron ; RNA, Messenger ; Lipids

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.