Plant-derived exosome-like nanovesicles (PELNs), characterized by a natural lipid bilayer membrane, have rapidly emerged as a prominent research frontier in medicine owing to their unique biological properties and robust therapeutic potential. This review comprehensively examines the biological profiles, mechanistic functions, and recent engineering advancements of PELNs. In terms of composition, PELNs are uniquely enriched in plant-specific glycolipids, phosphatidylserine, secondary metabolites, and highly stable 2'-O-methylated miRNAs. This distinct molecular makeup endows them with exceptional biocompatibility, negligible immunogenicity, and the capacity for cross-species molecular communication. Mechanistically, PELNs demonstrate profound anti-inflammatory efficacy by suppressing the NF-κB and NLRP3 inflammasome pathways. They also serve as potent immune modulators, driving macrophage M1/M2 polarization and regulating T cell activity. Additionally, PELNs exhibit promising antitumor capabilities, targeting malignancies via reactive oxygen species (ROS) induction, TRAIL pathway activation, and tumor microenvironment remodeling. Crucially, the plant miRNAs encapsulated within PELNs remain highly stable in the gastrointestinal tract, allowing them to selectively alter gene expression in specific gut microbiota communities. This interaction deeply influences host immunity and metabolism, highlighting the vital role in cross-species regulation. Advancements in bioengineering have further expanded the clinical utility of PELNs. Targeted delivery efficiency can be significantly amplified via surface functionalization (e.g., folate and RGD sequences) and state-of-the-art drug loading technologies such as sonication and electroporation. Consequently, engineered PELNs surpass traditional synthetic nanocarriers in penetrating natural physiological barriers, particularly for oral and transdermal drug administration. Despite these advantages, clinical translation is currently hindered by the lack of standardized isolation protocols, challenges in scalable manufacturing, and the need for robust quality control frameworks. Looking forward, the integration of multi-omics approaches and AI-driven “molecular fingerprinting”—coupled with the design of synthetic biomimetic vesicles—will be instrumental in overcoming these bottlenecks, ultimately establishing PELNs as a next-generation platform for precision medicine and targeted nanotherapeutic delivery.

Objective: To preliminarily explore the microbiome information of apheresis platelets from healthy blood donors in Nanjing, Jiangsu, and to lay the groundwork for further studies on the microbial community composition and diversity in this region. Methods: Thirteen fresh apheresis platelet samples (5 mL each) were collected from voluntary blood donors at the Nanjing Red Cross Blood Center. After centrifugation and removal of the supernatant, DNA was extracted from the pellet and libraries were constructed. High-throughput sequencing was performed on the Illumina NovaSeq X Plus platform, followed by in-depth bioinformatics analysis. Metagenomic analysis software, including fastp, Bowtie 2, MEGAHIT, Meta-GeneMark, DIAMOND, and Micro_NR, were used to analyze microbial abundance in the apheresis platelet samples. Results: Using Krona for visualization of species annotation and metagenomic sequencing analysis, after removing the human genome background, a total of 71 phyla, 54 classes, 102 orders, 181 families, 421 genera, and 1 340 species of microbes were identified. Starting from relative abundance tables at different taxonomic levels, at the family level, the top 10 most abundant families were: Flavobacteriaceae; Moraxellaceae; Rhizobiaceae; Sphingomonadaceae; Comamonadaceae; Caulobacteraceae; Burkholderiaceae; Acidimicrobiaceae; Streptomycetaceae; Streptosporangiaceae. At the genus level, the top 10 most abundant genera were: Wenyingzhuangia, Acinetobacter, Aquabacterium, Rhizobium, Brevundimonas, Novosphingobium, Astrithrvirus, Unclassified Rhizobiaceae, Acidiferrimicrobium, and Limnobacter. Conclusion: Next-generation sequencing (NGS) was used to comprehensively annotate the metagenome of apheresis platelets from voluntary blood donors in Nanjing, Jiangsu, enabling rapid acquisition of extensive microbial data. Exploratory analysis of the blood microbiome in healthy populations provides valuable guidance for developing context-specific measures to prevent platelet bacterial contamination, thereby enhancing blood safety.

OBJECTIVE To investigate the effects of MIR149 rs2292832 and MIR499 rs3746444 gene polymorphisms on the efficacy of tofacitinib combined with iguratimod in the treatment of moderate‑to‑severe rheumatoid arthritis （RA）， to provide genetic reference for individualized treatment of moderate‑to‑severe RA patients.METHODS This was a prospective cohort study， and patients were grouped according to genotyping results. A total of 320 patients with moderate-to-severe RA diagnosed in the department of immunology of our hospital between January 2023 and January 2024 were enrolled. All patients received standardized treatment with tofacitinib （5 mg twice daily） combined with iguratimod （25 mg twice daily） for 24 weeks treatment course. Clinical efficacy outcomes， including American College of Rheumatology （ACR） 20/50/70 responses， disease activity score‑28 based on C‑reactive protein （DAS28-CRP）， erythrocyte sedimentation rate （ESR） and C-reactive protein （CRP）， were compared among patients with different genotypes. Combined-genotype analysis and multivariate Logistic regression analysis were also performed.RESULTS The MIR149 rs2292832 CC-genotype patients exhibited significantly higher ACR20， ACR50 and ACR70 response rates （88.90%， 67.78%， 45.56%） than those carrying CT- and TT-genotypes （ P ＜0.05）. After 24 weeks treatment， the reductions in DAS28‑CRP， ESR and CRP were significantly greater in CC‑genotype patients than in CT‑ and TT‑genotype patients （ P ＜0.05）， and the 24‑week DAS28‑CRP was significantly lower in the CC‑genotype patients than in CT‑ and TT‑genotype patients （ P ＜0.05）. The MIR499 rs3746444 GG-genotype showed significantly higher ACR20， ACR50 and ACR70 response rates （91.46%， 73.17%， 52.44%） than those carrying AG‑ and AA‑genotypes （ P ＜0.05）. After 24 weeks of treatment， the reductions in DAS28‑CRP， ESR and CRP were significantly greater in GG‑genotype patients than in AG- and AA-genotype patients and the 24‑weeks DAS28‑CRP was significantly lower in the GG‑genotype patients than in AG- and AA-genotype patients （ P ＜0.05）. Among the nine combined‑genotyps， the CC+GG genotype yielded the best treatment response. The MIR149 rs2292832 CC and MIR499 rs3746444 GG genotypes were independent predictors of clinical remission （ P ＜0.01）， whereas baseline DAS28‑CRP ≥ 6.5 served as a negative predictor of clinical remission （ P ＜0.05）.CONCLUSIONS Gene polymorphisms of MIR149 rs2292832 and MIR499 rs3746444 significantly influence the therapeutic effect of tofacitinib combined with iguratimod in patients with moderate-to-severe RA. Patients carrying CC and GG genotypes achieve better treatment responses.

Objective:To summarize the clinical characteristics of elderly patients with stage Ⅰ diffuse large B-cell lymphoma (DLBCL) and analyze the factors associated with prognosis.Methods:A case series study was conducted by retrospectively collecting clinical data from patients aged over 60 years with newly diagnosed stage Ⅰ DLBCL across 20 medical centers in Jiangsu Province, China, between June 2010 and April 2023. The involved site, classification and treatment plan were summarized. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Statistical analyses were performed using the Kaplan-Meier method, and Cox regression model.Results:The study included 255 patients with a median age of 69 years, of whom 130 (51.0%) were male, 66 (25.9%) were aged ≥75 years and 26 (10.1%) had a high Charlson Comorbidity Index (CCI) score of ≥2. Extranodal involvement was observed in 163 (63.9%) patients, with the stomach (37.4%, 61/163), intestine (19.0%, 31/163), testes (11.0%, 18/163), and breast (7.4%, 12/163) being the most frequently affected sites. The non-germinal center B-cell (non-GCB) subtype was prevalent in 63.7% of patients (142/223), with no significant difference between the nodal and extranodal groups ( P=0.681). Furthermore, 73.9% (184/249) and 11.7% (29/249) of patients received the R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and R-miniCHOP regimen, respectively. The overall 3-year PFS rate was 81.5%, and the 3-year OS rate was 85.6%. Patients aged ≥75 years ( HR=2.910, 95% CI 1.565-5.408, P=0.001) and/or with a CCI score ≥2 ( HR=2.324, 95% CI 1.141-4.732, P=0.020) had a significantly poorer PFS. Incorporating age ≥75 years and CCI score ≥2 into the stage-modified international prognostic index (sm-IPI) can better stratify the prognosis of elderly patients with stage Ⅰ DLBCL. The 3-year PFS rate was 48.7% in the high-risk group versus 85.7% in the low-risk group ( P<0.001). Conclusions:Our findings show that the elderly patients with stage Ⅰ DLBCL were predominantly characterized by extranodal involvement (particularly in the stomach and intestinal tract) and non-GCB subtype. Age ≥75 years and CCI ≥2 were identified as independent prognostic factors. The newly established sm-IPI-75-CCI incorporating these factors demonstrated superior prognostic discrimination compared to conventional risk assessment systems.

OBJECTIVE To explore the distribution and drug resistance trends of the main pathogens causing blood-stream infections(BSI)in neonatal intensive care unit(NICU)of Henan Province from 2014 to 2023 so as to pro-vide bases for prevention and control of hospital-associated infections in the neonates and reasonable use of antibi-otics in the whole province.METHODS The data regarding to the pathogens causing BSI in the NICU neonates and drug resistance were retrospectively collected from Jan.2014 to Dec.2023,and the statistical analysis was per-formed by SPSS 26.0 and WHONET 5.6 software.RESULTS Totally 27,984 strains of pathogens were collected from 2014 to 2023,13,547(48.41％)of which were gram-negative bacteria,and 14,437(51.59％)were gram-pos-itive bacteria.Klebsiella pneumoniae(4221 strains,15.08％),Escherichia coli(3735 strains,13.35％),Acine-tobacter baumannii(1288 strains,4.60％),Enterobacter cloacae(847 strains,3.12％)and Pseudomonas aerugi-nosa(655 strain,2.34％)were the major species of gram-negative bacteria;Staphylococcus aureus(4545 strains,16.24％),Staphylococcus epidermidis(3306 strains,11.81％),Staphylococcus haemolyticus(2048 strains,7.32％),Staphylococcus hominis(1085 strains,3.88％)and Enterococcus faecalis(946 strains,3.38％)were the predominant species of gram-positive bacteria.The drug resistant analysis indicated that the drug resistance rate of the K.pneumoniae strains to imipenem showed an upward trend during the past six years,peaking at 44.23％,and it began to decline in 2021;though the drug resistance rate of the E.coli strains to imipenem showed some fluctuations,it gener-ally presented a downward trend,peaking at 7.00％.The drug resistance rates of the K.pneumoniae strains to the third generation of cephalosporins and carbapenems were higher than those of the E.coli,and there was significant differ-ence in the antimicrobial prevalence trend between the two species of Enterobacter during the ten years(P＜0.05).CONCLUSIONS K.pneumoniae and coagulase-negative Staphylococcus are dominant among the pathogens causing BSI in the ICU neonates of the whole province,and the isolation rates of drug-resistant strains are high.It is grossly necessary for the reasonable clinical use of antibiotics to carry out the bacterial drug resistance surveillance.

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.

Objective:To analyze the clinical phenotypes and genetic characteristics of pediatric patients with neurofibromatosis type 1 (NF1).Methods:A cross-sectional study was adopted. Clinical and imaging data of 25 pediatric patients diagnosed as having NF1 in Department of Pediatric Neurology, Linyi People's Hospital Affiliated to Shandong Second Medical University from January 2024 to July 2025 were collected. Whole exome sequencing and Sanger sequencing were used to conduct genetic testing on the pediatric patients and his/her parents. Protein 3D modeling of the domestic and foreign unreported variations was conducted using SWISS-MODEL software.Results:Among the 25 pediatric patients with NF1, 14 were male (56%) and 11 were female (44%), with age ranging from 8 months to 18 years. All pediatric patients exhibited café-au-lait macules, and 7 (28%) presented with plexiform neurofibromas. Genetic test identified 4 types of NF1 variants: nonsense variant ( n=11, 44%), frameshift variant ( n=9, 36%), missense variant ( n=3, 12%), and splice-site variant ( n=2, 8%). Importantly, 5 novel NF1 variants were discovered, including c.3455T>A, c.3709dupG, c.2665_2684del, c.7092_7095delinsTA, and c.3260del. Three pediatric patients inherited NF1 variant from their parents, while the remaining 22 harbored de novo mutation. Conclusion:NF1 exhibits a broad clinical spectrum, primarily affecting the skin and nervous system; this study identifies 5 previously unreported variants, expanding the genetic profile of NF1.

Objective:It aims to systematically evaluate the current status of knowledge,attitude,and practice(KAP)regarding universal commercial medical insurance among residents of the sample province from the demand-side perspective.Methods:Utilizing a quota sampling method,face-to-face surveys were conducted via the Questionnaire Star platform to collect demographic characteristics and KAP data of the participants.Comparisons of differences among different groups were made using t-tests,analysis of variance,and chi-square tests.Furthermore,multiple linear regression and structural equation modeling were utilized to analyze the influencing factors of KAP,as well as the pathways among these three factors.Results:Out of the 415 valid questionnaires collected,there were notable differences in KAP among respondents with diverse demographic backgrounds.Regression analysis revealed that education level,frequency of health check-ups,and engagement in other commercial health insurances significantly influenced knowledge;education level,involvement in other commercial health insurances,and self-assessed health status were pivotal in shaping attitudes;whereas age,education level,frequency of health check-ups,and participation in other commercial health insurances were critical in affecting practice.The path analysis results indicate that knowledge of universal commercial medical insurance has a significant direct association with attitude(β=0.379,P＜0.001)and practice(β=0.323,P＜0.001).It also influences practice through attitude as a mediator(β=0.016,P＜0.001),but the direct effect of attitude on practice is not significant(β=0.04,P=0.403).Conclusion:While residents in the sample province exhibit a positive attitude towards universal commercial medical insurance,there is a need to enhance their level of knowledge and engagement in practice.It is recommended to strengthen targeted educational and promotional measures to promote the healthy and sustainable development of universal insurance.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

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