Tussilagone protects acute lung injury from PM2.5 via alleviating Hif-1α/NF-κB-mediated inflammatory response

Complement system is activated in acute inflammatory response to environmental particulates in the lungs

Short-term exposure (typically ranging from a few hours to 7 days) to particulate matter (PM) elicits acute inflammatory responses with significant activation of complement component C5. However, the relationship between PM-induced complement system activation, acute inflammation, and the contributing factors remains unclear. In this study, we aimed to investigate the intensity of acute inflammatory responses, as well as the activation levels of complement C5 and its related products, C5aR1 and C5b-9, following exposure to different types of PM. Acute inflammatory responses and complement activation were assessed in mice intratracheally administered four types of PM: titanium dioxide (TiO₂), diesel exhaust particles (DEP), Asian sand dust (ASD), and ambient PM with an aerodynamic diameter ≤ 2.5 μm (PM2.5). Complement system and inflammatory markers were evaluated by analyzing increased C5 protein levels, C5b-9 deposition, and C5aR1 expression. Additionally, dark-field microscopy and Raman microscopy were used to detect PM components adjacent to infiltrating neutrophils, and elemental composition was quantified using ICP-MS and EDXRF. ASD, DEP, and PM2.5 exposure significantly increased C5b-9 deposition in lung tissues. All PM-exposed groups exhibited substantial upregulation of C5aR1 expression, primarily in neutrophils. Raman spectroscopic analysis revealed Si, K, Mg, Al, and Fe adjacent to infiltrating neutrophils in ASD-exposed lungs. Furthermore, elemental analysis identified Si, Mg, Al, and K as the most potent contributors to complement activation and inflammatory responses. Of the four types of PM, ASD induced the most severe acute inflammatory response and complement system activation. Therefore, ASD-induced complement system activation, driven at least partly by its mineral components, may play a critical role in neutrophil activation and acute pulmonary inflammation. These findings highlight the differential impact of PM types on complement system activation and underscore the importance of PM composition in the evaluation of air pollution-related health risks, particularly acute pulmonary inflammation.

Identification and Assessment of lncRNAs and mRNAs in PM2.5-Induced Hepatic Steatosis

Research indicates that fine particulate matter (PM2.5) exposure is associated with the onset of non-alcoholic fatty liver disease (NAFLD), the most prevalent chronic liver disorder. However, the underlying pathogenesis mechanisms remain to be fully understood. Our study investigated the hub long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) associated with hepatic steatosis caused by PM2.5 exposure and their pathological mechanisms. The analysis of gene profiles in the GSE186900 dataset from the Gene Expression Omnibus (GEO) enabled the identification of 38 differentially expressed lncRNAs and 1945 mRNAs. To explore further, a co-expression network was established utilizing weighted gene co-expression network analysis (WGCNA). Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized for functional enrichment analysis. Our analysis identified specific modules, particularly the blue and turquoise modules, which showed a strong correlation with NAFLD. Through functional enrichment analysis, we identified several lncRNAs (including Gm15446, Tmem181b-ps, Adh6-ps1, Gm5848, Zfp141, Rmrp, and Rb1) which may be involved in modulating NAFLD, multiple metabolic pathways, inflammation, cell senescence, apoptosis, oxidative stress, and various signaling pathways. The hub lncRNAs identified in our study provide novel biomarkers and potential targets for the diagnosis and treatment of NAFLD.

Protective Effects of Nerolidol on Thrombotic Events, Systemic Inflammation, Oxidative Stress, and DNA Damage Following Pulmonary Exposure to Diesel Exhaust Particles

Background/Objectives: Inhalation of environmental particulate air pollution has been reported to cause pulmonary and systemic events including coagulation disturbances, systemic inflammation, and oxidative stress. Nerolidol, a naturally occurring sesquiterpene alcohol, has effective antioxidant and anti-inflammatory effects. Hence, the aim in the present investigation was to evaluate the potential ameliorative effects of nerolidol on the coagulation and systemic actions induced by pulmonary exposure to diesel exhaust particles (DEPs). Methods: Nerolidol (100 mg/kg) was given to mice by oral gavage one hour before the intratracheal instillation of DEPs (0.5 mg/kg), and 24 h later various markers of coagulation and systemic toxicity were evaluated. Results: Nerolidol treatment significantly abrogated DEP-induced platelet aggregation in vivo and in vitro. Nerolidol has also prevented the shortening of the prothrombin time and activated plasma thromboplastin time triggered by DEP exposure. Likewise, while the concentrations of fibrinogen and plasminogen activator inhibitor-1 were increased by DEP administration, that of tissue plasminogen activator was significantly decreased. These effects were abolished in the group of mice concomitantly treated with nerolidol and DEP. Moreover, plasma markers of inflammation, oxidative stress, and endothelial dysfunction which were significantly increased in the DEP-treated group, returned to control levels in the nerolidol + DEP group. Nerolidol treatment significantly ameliorated the increase in the concentrations of hypoxia-inducible factor 1α, galectin-3, and neutrophil gelatinase-associated lipocalin induced by pulmonary exposure to DEP. The co-administration of nerolidol + DEPs significantly mitigated the increase in markers of oxidative DNA damage, 8-hydroxy-2-deoxyguanosine, and apoptosis, cleaved-caspase-3, induced by DEP. Conclusions: Collectively, our data demonstrate that nerolidol exert significant ameliorative actions against DEP-induced thrombotic events, endothelial dysfunction, systemic inflammation, oxidative stress, DNA damage, and apoptosis. Pending further pharmacological and toxicological studies, nerolidol could be a promising agent to alleviate the toxicity of inhaled DEPs and other pollutant particles.

Identification and Evaluation of Hub Long Non-Coding RNAs and mRNAs in PM2.5-Induced Lung Cell Injury

Exposure to air pollution, especially fine particulate matter (PM2.5), is closely linked to various adverse health effects, particularly in the respiratory system. The present study was designed to investigate the lncRNA-mRNA interactions in PM2.5-induced lung cell injury using weighted gene co-expression network analysis (WGCNA). We downloaded the gene expression data of GSE138870 from the Gene Expression Omnibus (GEO) database and screened for differentially expressed lncRNAs and mRNAs. We constructed co-expression modules with WGCNA. Furthermore, functional enrichment analysis was also performed. We also constructed lncRNA-mRNA co-expression networks and lncRNA-mRNA-pathway networks to identify key regulatory relationships. The results revealed several modules significantly correlated with PM2.5-induced lung injury, such as the turquoise and blue modules. Genes within these modules were enriched in pathways related to signal transduction, metabolism, and cancer. Hub lncRNAs in the turquoise module, including LOC100129034 and CROCCP2, were found to be co-expressed with mRNAs involved in apoptosis and proliferation regulation. In the blue module, lnc-CLVS2-2 and GARS1-DT were connected to genes related to cell migration, invasion, and lung injury. These findings contribute novel perspectives to the molecular mechanisms involved in PM2.5-induced lung injury and suggest that WGCNA could be a valuable tool for predicting and understanding this disease process.

Subacute PM2.5 Exposure Induces Hepatic Insulin Resistance Through Inflammation and Oxidative Stress

Epidemiological studies prove that type II diabetes, characterized by insulin resistance (IR), may be caused by fine particulate matter 2.5 (PM2.5). However, underlying mechanisms whereby PM2.5, particularly during short-term exposure, induces liver dysfunction leading to IR remains poorly understood. In the present study, HepG2 cells and the BALB/c mouse model were used to explore how PM2.5 affects insulin sensitivity. The effects of subacute PM2.5 exposure on glucose metabolism were examined using commercial kits. Oxidative stress and inflammation were detected by fluorescent staining and RT-qPCR. The phosphorylation of PI3K/AKT was examined by Western blot. Subacute PM2.5 exposure induced IR, as reflected by increased glucose levels in cell supernatants, elevated insulin levels, and the impaired intraperitoneal glucose tolerance test in mice. PM2.5 induced oxidative stress, as evidenced by increased reactive oxygen species, cytochrome P450 2E1, and malondialdehyde, along with reduced superoxide dismutase 1/2 and silent information regulator 1. IL-6 and TNF-α were found to be upregulated using RT-qPCR. Western blot showed that PM2.5 inhibited the PI3K-AKT signaling pathway, indicated by the decreased phosphorylation of PI3K/AKT in HepG2 cells. Additionally, H&E staining showed only mild hepatic injury in mice liver. These results firmly suggest that subacute PM2.5 exposure induces insulin resistance through oxidative stress, inflammation, and the inhibition of the PI3K-AKT signaling pathway.

Integrated meta-analyses of genome-wide effects of PM2.5 in human cells identifies widespread dysregulation of genes and pathways associated with cancer progression and patient survival

Epidemiological studies have consistently shown a positive association between exposure to ambient PM2.5, a major component of air pollution, and various types of cancer. Previous biological research has primarily focused on the association between PM2.5 and lung cancer, with limited investigation into other cancer types. In this study, we conducted a meta-analysis on multiple PM2.5-treated normal human cell lines to identify potential molecular targets and pathways of PM2.5. Our analysis revealed 310 common differentially expressed genes (DEGs) that exhibited significant dysregulation upon exposure to PM2.5. These dysregulated genes covered a diverse range of functional categories, including oncogenes, tumor suppressor genes, and immune-related genes, which collectively contribute to PM2.5-induced carcinogenesis. Pathway enrichment analysis revealed the up-regulation of pathways associated with HIF-1, VEGF, and MAPK signalling, all of which have been implicated in various cancers. Induction in the levels of HIF pathway genes (HIF1⍺, HIF2⍺, VEGFA, BNIP3, EPO and PGK1) upon PM2.5 treatment was also confirmed by qRT-PCR. Furthermore, the construction of a protein-protein interaction (PPI) network unveiled hub genes, such as NQO1 and PDGFRB, that are known to be dysregulated and significantly correlated with overall survival in lung and breast cancer patients, suggesting their potential clinical significance. This study provides a deep insight into how PM2.5-mediated dysregulation of oncogenes or tumor suppressor genes across various human tissues may play an important role in PM2.5-induced carcinogenesis. Further exploration of these dysregulated molecular targets may enhance our understanding of the biological effects of PM2.5 and facilitate the development of preventive strategies and targeted therapies for PM2.5-associated cancers.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as "a mixture of solid particles and liquid droplets found in the air". These particles vary widely in size. Those particles that are less than 2.5 μm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

Characterization of risks and pathogenesis of respiratory diseases caused by rural atmospheric PM2.5

Forty-six percent of the world's population resides in rural areas, the majority of whom belong to vulnerable groups. They mainly use cheap solid fuels for cooking and heating, which release a large amount of PM2.5 and cause adverse effects to human health. PM2.5 exhibits urban-rural differences in its health risk to the respiratory system. However, the majority of research on this issue has focused on respiratory diseases induced by atmospheric PM2.5 in urban areas, while rural areas have been ignored for a long time, especially the pathogenesis of respiratory diseases. This is not helpful for promoting environmental equity to aid vulnerable groups under PM2.5 pollution. Thus, this study focuses on rural atmospheric PM2.5 in terms of its chemical components, toxicological effects, respiratory disease types, and pathogenesis, represented by PM2.5 from rural areas in the Sichuan Basin, China (Rural SC-PM2.5). In this study, organic carbon is the most significant component of Rural SC-PM2.5. Rural SC-PM2.5 significantly induces cytotoxicity, oxidative stress, and inflammatory response. Based on multiomics, bioinformatics, and molecular biology, Rural SC-PM2.5 inhibits ribonucleotide reductase regulatory subunit M2 (RRM2) to disrupt the cell cycle, impede DNA replication, and ultimately inhibit lung cell proliferation. Furthermore, this study supplements and supports the epidemic investigation. Through an analysis of the transcriptome and human disease database, it is found that Rural SC-PM2.5 may mainly involve pulmonary hypertension, sarcoidosis, and interstitial lung diseases; in particular, congenital diseases may be ignored by epidemiological surveys in rural areas, including tracheoesophageal fistula, submucous cleft of the hard palate, and congenital hypoplasia of the lung. This study contributes to a greater scientific understanding of the health risks posed by rural PM2.5, elucidates the pathogenesis of respiratory diseases, clarifies the types of respiratory diseases, and promotes environmental equity.

Exploring the Microbial Community Structure in the Chicken House Environment by Metagenomic Analysis

The environmental conditions of chicken houses play an important role in the growth and development of these animals. The chicken house is an essential place for the formation of microbial aerosols. Microbial aerosol pollution and transmission can affect human and animal health. In this work, we continuously monitored fine particulate matter (PM2.5) in the chicken house environment for four weeks and studied the microbial community structure in the aerosols of the chicken house environment through metagenomic sequencing. Our results found that bacteria, fungi, viruses, and archaea were the main components of PM2.5 in the chicken house environment, accounting for 89.80%, 1.08%, 2.06%, and 0.49%, respectively. Conditional pathogens are a type of bacteria that poses significant harm to animals themselves and to farm workers. We screened ten common conditional pathogens and found that Staphylococcus had the highest relative abundance, while Clostridium contained the most microbial species, up to 456. Basidiomycetes and Ascomycota in fungi showed dramatic changes in relative abundance, and other indexes showed no significant difference. Virulence factors (VF) are also a class of molecules produced by pathogenic microbes that can cause host diseases. The top five virulence factors were found in four groups: FbpABC, HitABC, colibactin, acinetobactin, and capsule, many of which are used for the iron uptake system. In the PM2.5 samples, eight avian viruses were the most significant discoveries, namely Fowl aviadovirus E, Fowl aviadovirus D, Avian leukosis virus, Avian endogenous retrovirus EAV-HP, Avian dependent parvovirus 1, Fowl adenovus, Fowl aviadovirus B, and Avian sarcoma virus. The above results significantly improve our understanding of the microbial composition of PM2.5 in chicken houses, filling a gap on virus composition; they also indicate a potential threat to poultry and to human health. This work provides an important theoretical basis for animal house environmental monitoring and protection.

Exosomes derived miR-362 exacerbates pneumonia by increasing Interleukin-6 via targeting VENTX

Pneumonia is a condition characterized by lung damage resulting from a robust immune response by the host. While the defense and immunity against bacterial lung infections have been extensively studied, little is known about the specific immune factors involved in the progression of bacterial pneumonia. To address this knowledge gap, our study aimed to compare normal lung tissues with pneumonia tissues using various techniques, including HE staining, RNA sequencing, RT-PCR, and Elisa assay. Our analysis revealed a significant increase in the levels of interleukin-6 (IL-6) in pneumonia tissues compared to normal lung tissues. To further investigate the underlying mechanism, we extracted exosomes from both pneumonia and normal lung tissues using ultracentrifugation. The exosomes were then examined using electron microscopy, diameter analysis, and western blot assay. RNA sequencing of the exosomes revealed an upregulation of several microRNAs (miRNAs), with miR-362 exhibiting the most significant change. This finding was confirmed through RT-PCR analysis conducted on lung tissues and alveolar lavage fluid. To gain insights into the specific target genes of miR-362, we employed bioinformatics analysis, which identified VENTX as a potential target gene. This finding was further validated through RT-PCR, western blot, and luciferase assay. Our experimental evidence demonstrated that miR-362 regulates VENTX expression, as evidenced by the use of miR-362 mimics or inhibitors on lung cells. Furthermore, we discovered that exosomes derived from pneumonia tissues upregulate IL-6 production through the miR-362/VENTX axis. Importantly, the blocking of IL-6 generation, which is facilitated by miR-362 inhibitor and VENTX overexpression lentivirus, can be achieved by treating exosomes. Moreover, we conducted in vivo experiments using pneumonia models. Rats were treated with IL-6, miR-362 mimics, or VENTX knock-down lentivirus. The results demonstrated a worse prognosis for rats treated with these factors, indicating their potential as prognostic markers. Taken together, our study suggests that exosomes facilitate IL-6 generation by transferring miR-362, thereby suppressing VENTX transcription. Consequently, the IL-6/miR-362/VENTX axis emerges as a promising therapeutic target for pneumonia.

Tussilagone attenuates atherosclerosis through inhibiting MAPKs-mediated inflammation in macrophages

Atherosclerosis is a common chronic inflammatory disease. Recent studies have highlighted the key role of macrophages and inflammation in process of atherosclerotic lesion formation. A natural product, tussilagone (TUS), has previously exhibited anti-inflammatory activities in other diseases. In this study, we explored the potential effects and mechanisms of TUS on the inflammatory atherosclerosis. Atherosclerosis was induced in ApoE^-/- mice by feeding them with a high-fat diet (HFD) for 8 weeks, followed by administration of TUS (10, 20 mg ·kg^-1·d^-1, i.g.) for 8 weeks. We demonstrated that TUS alleviated inflammatory response and reduced atherosclerotic plaque areas in HFD-fed ApoE^-/- mice. Pro-inflammatory factor and adhesion factors were inhibited by TUS treatment. In vitro, TUS suppressed foam cell formation and oxLDL-induced inflammatory response in MPMs. RNA-sequencing analysis indicated that MAPK pathway was related to the anti-inflammation and anti-atherosclerosis effects of TUS. We further confirmed that TUS inhibited MAPKs phosphorylation in plaque lesion of aortas and cultured macrophages. MAPK inhibition blocked oxLDL-induced inflammatory response and prevented the innately pharmacological effects of TUS. Our findings present a mechanistic explanation for the pharmacological effect of TUS against atherosclerosis and indicate TUS as a potentially therapeutic candidate for atherosclerosis.

hUC-MSCs exosomal miR-451 alleviated acute lung injury by modulating macrophage M2 polarization via regulating MIF-PI3K-AKT signaling pathway

In the previous study, we have proved that exosomal miR-451 from human umbilical cord mesenchymal stem cells (hUC-MSCs) attenuated burn-induced acute lung injury (ALI). However, the mechanism of exosomal miR-451 in ALI remains unclear. Therefore, this study aimed to study the molecular mechanism of hUC-MSCs-derived exosomal miR-451 on ALI by regulating macrophage polarization. Exosomes were isolated and identified by transmission electron microscope (TEM) and nanoparticle tracking analysis (NTA). The expression of miR-451, macrophage migration inhibitory factor (MIF) and PI3K/AKT signaling pathway proteins were detected by qRT-PCR and western blot. Flow cytometry was used to detect the CD80 and CD206 positive cells. Severe burn rat model was established and HE was used to detect the inflammatory cell infiltration and inflammatory injury. Dual luciferase reporter system was used to detect the regulation of miR-451 to MIF. The contents of cytokines were detected by ELISA. The results showed that hUC-MSCs exosomes promoted macrophage M1 to M2 polarization. Furthermore, hUC-MSCs-derived exosomal miR-451 alleviated ALI development and promoted macrophage M1 to M2 polarization. Moreover, MIF was a direct target of miR-451. Downregulation of MIF regulated by miR-451 alleviated ALI development promoted macrophage M1 to M2 polarization. In addition, we found that MIF and hUC-MSCs-derived exosomal miR-451 participated in ALI by regulating PI3K/AKT signaling pathway. In conclusion, we indicated that hUC-MSCs-derived exosomal miR-451 alleviated ALI by modulating macrophage M2 polarization via regulating MIF-PI3K-AKT signaling pathway, which provided great scientific significance and clinical application value for the treatment of burn-induced ALI.