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 pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Objective: To construct an index system of public health risk assessment for air pollution emergency, so as to provide a tool of evaluating the public health risks of air pollution emergency. Methods: Index system of public health risk assessment for air pollution emergency was established through literature review and group discussions. The index system was determined through two rounds of Delphi expert consultations involving specialists in environmental health, toxicology, epidemiology, health emergency response, and atmospheric monitoring. The effectiveness of the consultation was evaluated by positive coefficient, authority coefficient and coordination coefficient. The weights of index were determined using a combination weighting method of the expert scoring method and the entropy weight method. Results: Fifteen experts participated in the consultation, including 11 males and 4 females. There were 8 experts with a doctor degree, 6 experts with a master degree, 1 experts with a bachelor degree. A total of 11 experts with senior professional titles, and 4 experts with associate senior professional titles. The average work experience was (23.73±10.48) years. The expert positive coefficients for the two rounds of consultations were 83.33% and 100%, respectively. The expert authority coefficients were 0.794 and 0.811, respectively. The coefficients of variation for the importance, feasibility, and sensitivity scores of each index in the two rounds of comsultations were 0.097 to 0.352, 0.078 to 0.478, 0.115 to 0.388, and 0.049 to 0.133, 0.052 to 0.153, 0.049 to 0.178, respectively. The Kendall's coefficients of concordance were 0.237 and 0.440 (both with P<0.05) for the two rounds of consultations. The constructed assessment index system included "likelihood" "hazard" "vulnerability" "controllability" with comprehensive weights of 0.206 7, 0.059 6, 0.378 1, and 0.355 5, respectively. Among the 13 second indicators, "monitoring capability" had the highest comprehensive weight of 0.192 6. Among the 40 tertiary indicators, "real-time monitoring of atmospheric pollutants" "retrospective evaluation of early forecasting results" "types, quantities, and combined effects of atmospheric pollutants" "exposure modes of the population to atmospheric pollutants" had relatively high comprehensive weights of 0.089 5, 0.043 1, 0.041 1 and 0.040 3, respectively. Conclusion The constructed index system of public health risk assessment for air pollution emergency can be applied to the public health risk assessment for air pollution emergencies.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective: To investigate the effects of different doses of X ⁃rays irradiation combined with allogeneic lymphocyte infusion on the establishment of aplastic anemia in mice. Methods: Forty BALB/c mice were randomly divided into four groups : the 3 Gy group (n = 9) , the 4 Gy group (n = 9) , the 5 Gy group (n = 10) , and the con⁃trol group (n = 12) . In the 3 Gy , 4 Gy , and 5 Gy groups , the experimental mice were exposed to corresponding do⁃ses of X ⁃ray and then intravenously infused with 0. 2 mL mixed suspension of the thymus and spleen cells from DBA/2 mice , at a concentration of 1 × 107 cells/mL , within 4 hours after irradiation. The control group did not un⁃dergo X ⁃ray irradiation and infused with an equivalent volume of physiological saline instead. Blood samples were collected from the orbital venous plexus of BALB/c mice and analyzed using an animal automated hematology analy⁃zer to measure peripheral blood parameters , including red blood cells ( RBC) , white blood cells ( WBC) , and platelets (PLT) . The general condition of mice was monitored daily , and survival rates were recorded for each group. At the experimental endpoint , the tibias were harvested for hematoxylin and eosin (HE) staining , while the femurs were used to prepare bone marrow smears for morphological examination. For the 5 Gy group , T ⁃cell subsets(ELISA) at the endpoint. Results : In the 3 Gy group , pancytopenia was observed , but platelet recovery occured rapidly , returning to normal levels by day 17 post⁃modeling. No deaths occurred during the observation period. At myeloid⁃to⁃erythroid (M/E) ratio , and no significant morphological abnormalities were noted in cells at any devel⁃with hematopoietic cells. In the 4 Gy group , pancytopenia persisted throughout the observation period. The survival rate was 90% . Endpoint analysis showed hypocellular marrow by morphological examination. HE staining indicated minimal fatty infiltration in the bone marrow tissue. In the 5 Gy group , pancytopenia was observed , though erythro⁃cyte counts returned to normal levels by day 24. The survival rate during the observation period was 50% . Endoint analysis revealed vacuolization of marrow particles and reduced hematopoietic cells with predominantly non⁃hematopoietic cells in bone marrow morphology. HE staining demonstrated severe fatty infiltration in the bone mar⁃row tissue , with scarcity of immature cells and hematopoietic precursor cells. Flow cytometry analysis showed a de⁃creased proportion of CD4 + T cells (% ) and an increased proportion of CD8 + T cells (% ) . ELISA confirmed elevated secretion of negative hematopoietic regulators : interferon⁃gamma ( IFN⁃γ) and tumor necrosis factor⁃alpha (TNF⁃α ) . Conclusion Combined administration of varying radiation doses with allogeneic lymphocyte infusion consistently induced peripheral blood cytopenia in mice , characterized by reductions in RBC , WBC , and PLT counts. Integrated analysis of bone marrow morphology , histopathological assessment via HE staining , and immuno logical parameters confirmed that a mouse model of aplastic anemia can be successfully established using 5 Gy X ⁃ ray irradiation coupled with infusion of 2 × 106 allogeneic lymphocytes.

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 inte-gration 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.

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 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