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.

The ventral anterior (VA) nucleus of the thalamus is a major target of the basal ganglia and is closely associated with the pathogenesis of Parkinson's disease (PD). Notably, the VA receives direct innervation from the hypothalamic histaminergic system. However, its role in PD remains unknown. Here, we assessed the contribution of histamine to VA neuronal activity and PD motor deficits. Functional magnetic resonance imaging showed reduced VA activity in PD patients. Optogenetic activation of VA neurons or histaminergic afferents significantly alleviated motor deficits in 6-OHDA-induced PD rats. Furthermore, histamine excited VA neurons via H1 and H2 receptors and their coupled hyperpolarization-activated cyclic nucleotide-gated channels, inward-rectifier K⁺ channels, or Ca²⁺-activated K⁺ channels. These results demonstrate that histaminergic afferents actively compensate for Parkinsonian motor deficits by biasing VA activity. These findings suggest that targeting VA histamine receptors and downstream ion channels may be a potential therapeutic strategy for PD motor dysfunction.
Animals ; Histamine/metabolism* ; Male ; Oxidopamine/toxicity* ; Rats ; Ventral Thalamic Nuclei/physiopathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Parkinson Disease/metabolism* ; Neurons/physiology* ; Humans ; Optogenetics

Human naïve pluripotent stem cells (PSCs) hold great promise for embryonic development studies. Existing induction and culture strategies for these cells, heavily dependent on MEK inhibitors, lead to widespread DNA hypomethylation, aberrant imprinting loss, and genomic instability during extended culture. Here, employing high-content analysis alongside a bifluorescence reporter system indicative of human naïve pluripotency, we screened over 1,600 chemicals and identified seven promising candidates. From these, we developed four optimized media-LAY, LADY, LUDY, and LKPY-that effectively induce and sustain PSCs in the naïve state. Notably, cells reset or cultured in these media, especially in the LAY system, demonstrate improved genome-wide DNA methylation status closely resembling that of pre-implantation counterparts, with partially restored imprinting and significantly enhanced genomic stability. Overall, our study contributes advancements to naïve pluripotency induction and long-term maintenance, providing insights for further applications of naïve PSCs.
Humans ; DNA Methylation/drug effects* ; Genomic Instability ; Pluripotent Stem Cells/metabolism* ; Cell Culture Techniques/methods* ; Cells, Cultured

Traditional Chinese medicine (TCM) is an ancient medical system distinctive and effective in treating cancer, depression, coronavirus disease 2019 (COVID-19), and other diseases. However, the relatively abstract diagnostic methods of TCM lack objective measurement, and the complex mechanisms of action are difficult to comprehend, which hinders the application and internationalization of TCM. Recently, while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for TCM research, the rise of machine learning (ML) has significantly enhanced their integration with TCM. This article introduces representative methodological cases in quality control, mechanism research, diagnosis, and treatment processes of TCM, revealing the potential applications of ML technology in TCM. Furthermore, the challenges faced by ML in TCM applications are summarized, and future directions are discussed.

OBJECTIVE: To investigate the effects of thymoquinone on the proliferation of acute myeloid leukemia (AML) cells and its molecular mechanism, so as to provide theoretical basis for the basic research on the anti-leukemia of traditional Chinese medicine. METHODS: The HL-60 and THP-1 cells were treated with thymoquinone at different concentration gradients, cell proliferation was detected by CCK-8 method, morphological changes were detected by Wright-Giemsa method, apoptosis was detected by Annexin V/PI double staining flow cytometry, and apoptosis and signal pathway protein expression were detected by Western blot. Real-time quantitative fluorescence PCR and Western blot were used to detect the expression changes of high mobility family members of SRY-related proteins (SOX). RESULTS: Thymoquinone inhibited the malignant proliferation of HL-60 and THP-1 cells, up-regulated the expression of pro-apoptotic protein Bax, down-regulated the expression of anti-apoptotic protein Bcl-2 and Survivin, and hydrolyzed Caspase-3 to induce the apoptosis of HL-60 and THP-1 cells. Thymoquinone could also significantly down-regulate the phosphorylation of PI3K, Akt and mTOR, and inhibit the malignant biological characteristics of HL-60 and THP-1 cells by inhibiting the activation of PI3K/Akt/mTOR pathway. After thymoquinone intervention in HL-60 and THP-1 cells, the expression of SOX2 and SOX4 could be down-regulated significantly. At low concentration ( < 10 μmol/L), the expression of SOX12 was weakly affected by thymoquinone. With increasing concentration, the expression of SOX12 could be down-regulated, however, thymoquinone had no effect on SOX11 expression. CONCLUSION Thymoquinone can inhibit the proliferation of AML cells, and its mechanism may be related to inhibiting the activation of PI3K/Akt/mTOR signaling pathway, regulating the expression of apoptotic proteins and core members of SOX family.
Humans ; Benzoquinones/pharmacology* ; Cell Proliferation/drug effects* ; Leukemia, Myeloid, Acute/metabolism* ; Apoptosis/drug effects* ; HL-60 Cells ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; bcl-2-Associated X Protein/metabolism* ; Cell Line, Tumor ; Phosphatidylinositol 3-Kinases/metabolism* ; THP-1 Cells

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To investigate the recovery of plasma metabolism in asymptomatic and mild patients of coronavirus disease 2019(COVID-19)one year after recovery.Methods A total of 174 participants were recruited from the communities in Wuhan,including 80 healthy volunteers and the COVID-19 patients who had recovered for one year.According to the disease severity,the recovered COVID-19 patients were grouped as asymptomatic patients(n=80)and mild patients(n=14).The liquid chromatography mass spectrometry platform was employed to study the metabolomic characteristics of the plasma from all the participants.Results The plasma metabolites in asymptomatic patients and mild patients remained abnormal compared with those in healthy volunteers.Among the differential metabolites in asymptomatic patients and mild patients,some metabolites showed a downward trend only in mild patients,such as phosphatidylethanolamine[20∶3(5Z,8Z,11Z)/P-18∶0],sphingomyelin(d18∶1/24∶0),and cholesteryl(15∶0).The metabolic pathway involving the differential metabolites in mild patients was mainly glycerophospholipid metabolism.Conclusions Even one year after recovery,the mild COVID-19 patients still exhibit metabolic abnormalities.Hence,these patients may experience an extended period of time for recovery.
Humans ; COVID-19/metabolism* ; Metabolomics ; SARS-CoV-2 ; Metabolome ; Female ; Male ; Adult ; Middle Aged

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.