Early-life antibiotic exposure promotes house dust mite-induced allergic airway inflammation by impacting gut microbiota and lung lipid metabolism.

Asthma is a chronic inflammatory respiratory disease. Early-life antibiotic exposure is a unique risk factor for the incidence and severity of asthma later in life. Perturbations in microbial-metabolite-immune interaction caused by antibiotics are closely associated with the pathogenesis of allergy and asthma. We investigated the effect of early intervention with common oral antibiotics on later asthma exacerbations and found that different antibiotic exposures can amplify different types of immune responses induced by HDM. Cefixime (CFX) promoted a biased type 2 inflammation, azithromycin (AZM) enhanced Th17 immune response, and cefuroxime axetil (CFA) induced eosinophils recruitment. Moreover, early-life antibiotic exposure can have short- and long-term effects on the abundance, composition, and diversity of the gut microbiota. In the model of CFX-promoted type 2 airway inflammation, fecal metabolomics indicated abnormal lipid metabolism and T cell response. Lipidomic also suggested allergic airway inflammation amplified by CFX is closely associated with abnormal lipid metabolism in lung tissues. Moreover, abnormalities in lipid metabolism-related genes (LMRGs) were found to have cellular heterogeneity be associated with asthma severity by bioinformatics analysis.

Identifying oxidative stress-related biomarkers in idiopathic pulmonary fibrosis in the context of predictive, preventive, and personalized medicine using integrative omics approaches and machine-learning strategies.

Background: Idiopathic pulmonary fibrosis (IPF) is a rare interstitial lung disease with a poor prognosis that currently lacks effective treatment methods. Preventing the acute exacerbation of IPF, identifying the molecular subtypes of patients, providing personalized treatment, and developing individualized drugs are guidelines for predictive, preventive, and personalized medicine (PPPM / 3PM) to promote the development of IPF. Oxidative stress (OS) is an important pathological process of IPF. However, the relationship between the expression levels of oxidative stress-related genes (OSRGs) and clinical indices in patients with IPF is unclear; therefore, it is still a challenge to identify potential beneficiaries of antioxidant therapy. Because PPPM aims to recognize and manage diseases by integrating multiple methods, patient stratification and analysis based on OSRGs and identifying biomarkers can help achieve the above goals. Methods: Transcriptome data from 250 IPF patients were divided into training and validation sets. Core OSRGs were identified in the training set and subsequently clustered to identify oxidative stress-related subtypes. The oxidative stress scores, clinical characteristics, and expression levels of senescence-associated secretory phenotypes (SASPs) of different subtypes were compared to identify patients who were sensitive to antioxidant therapy to conduct differential gene functional enrichment analysis and predict potential therapeutic drugs. Diagnostic markers between subtypes were obtained by integrating multiple machine learning methods, their expression levels were tested in rat models with different degrees of pulmonary fibrosis and validation sets, and nomogram models were constructed. CIBERSORT, single-cell RNA sequencing, and immunofluorescence staining were used to explore the effects of OSRGs on the immune microenvironment. Results: Core OSRGs classified IPF into two subtypes. Patients classified into subtypes with low oxidative stress levels had better clinical scores, less severe fibrosis, and lower expression of SASP-related molecules. A reliable nomogram model based on five diagnostic markers was constructed, and these markers' expression stability was verified in animal experiments. The number of neutrophils in the immune microenvironment was significantly different between the two subtypes and was closely related to the degree of fibrosis. Conclusion: Within the framework of PPPM, this work comprehensively explored the role of OSRGs and their mediated cellular senescence and immune processes in the progress of IPF and assessed their capabilities aspredictors of high oxidative stress and disease progression,targets of the vicious loop between regulated pulmonary fibrosis and OS for targeted secondary and tertiary prevention, andreferences for personalized antioxidant and antifibrotic therapies. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00334-4.

Alterations in gut microbiota and urine metabolomics in infants with yin-deficiency constitution aged 0-2 years.

Background: Based on the constitution theroy, infants are classified into balanced constitution (BC) and unbalanced constitution. Yin-deficiency constitution (YINDC) is a common type of unbalanced constitutions in Chinese infants. An infant's gut microbiota directly affects the child's health and has long-term effects on the maturation of the immune and endocrine systems throughout life. However, the gut microbiota of infants with YINDC remains unknown. Herein, we aimed to evaluate the intestinal flora profiles and urinary metabolites in infant with YINDC, find biomarkers to identify YINDC, and promote our understanding of infant constitution classification. Methods: Constitutional Medicine Questionnaires were used to assess the infants' constitution types. 47 infants with 21 cases of YINDC and 26 cases of BC were included, and a cross-sectional sampling of stool and urine was conducted. Fecal microbiota was characterized using 16S rRNA sequencing, and urinary metabolomics was profiled using UPLC-Q-TOF/MS method. YINDC markers with high accuracy were identified using receiver operating characteristic (ROC) analysis. Results: The diversity and composition of intestinal flora and urinary metabolites differed significantly between the YINDC and BC groups. A total of 13 obviously different genera and 55 altered metabolites were identified. Stool microbiome shifts were associated with urine metabolite changes. A combined marker comprising two genera may have a high potential to identify YINDC with an AUC of 0.845. Conclusions: Infants with YINDC had a unique gut microbiota and metabolomic profile resulting in a constitutional microclassification. The altered gut microbiome in YINDC may account for the higher risk of cardiovascular diseases. Metabolomic analysis of urine showed that metabolic pathways, including histidine metabolism, proximal tubule bicarbonate reclamation, arginine biosynthesis, and steroid hormone biosynthesis, were altered in infants with YINDC. Additionally, the combined bacterial biomarker had the ability to identify YINDC. Identifying YINDC in infancy and intervening at an early stage is crucial for preventing cardiovascular diseases.

Damp-heat constitution influences gut microbiota and urine metabolism of Chinese infants.

Background: As an increasingly popular complementary and alternative approach for early detection and treatment of disease, traditional Chinese medicine constitution (TCMC) divides human beings into those with balanced constitution (BC) and unbalanced constitution, where damp-heat constitution (DHC) is one of the most unbalanced constitutions. Many studies have been carried out on the microscopic mechanism of constitution classification; however, most of these studies were conducted in adults and rarely in infants. Many diseases are closely related to intestinal microbiota, and metabolites produced by the interaction between microbiota and the body may impact constitution classification. Herein, we investigated the overall constitution distribution in Chinese infants, and analyzed the profiles of gut microbiota and urine metabolites of DHC to further promote the understanding of infants constitution classification. Methods: General information was collected and TCMC was evaluated by Constitutional Medicine Questionnaires. 1315 questionnaires were received in a cross-sectional study to investigate the constitution composition in Chinese infants. A total of 56 infants, including 30 DHC and 26 BC, were randomly selected to analyze gut microbiota by 16S rRNA sequencing and urine metabolites by UPLC-Q-TOF/MS method. Results: BC was the most common constitution in Chinese infants, DHC was the second common constitution. The gut microbiota and urine metabolites in the DHC group showed different composition compared to the BC group. Four differential genera and twenty differential metabolites were identified. In addition, the combined marker composed of four metabolites may have the high potential to discriminate DHC from BC with an AUC of 0.765. Conclusions: The study revealed the systematic differences in the gut microbiota and urine metabolites between infants with DHC and BC. Moreover, the differential microbiota and metabolites may offer objective evidences for constitution classification.

Identification and immune characteristics of molecular subtypes related to fatty acid metabolism in idiopathic pulmonary fibrosis.

Background: Although fatty acid metabolism has been confirmed to be involved in the pathological process of idiopathic pulmonary fibrosis (IPF), systematic analyses on the immune process mediated by fatty acid metabolism-related genes (FAMRGs) in IPF remain lacking. Methods: The gene expression data of 315 patients with IPF were obtained from Gene Expression Omnibus database and were divided into the training and verification sets. The core FAMRGs of the training set were identified through weighted gene co-expression network analysis. Then, the fatty acid metabolism-related subtypes in IPF were identified on the basis of k-means unsupervised clustering. The scores of fatty acid metabolism and the expression of the fibrosis biomarkers in different subtypes were compared, and functional enrichment analysis was carried out on the differentially expressed genes between subtypes. A random forest model was used to select important FAMRGs as diagnostic markers for distinguishing between subtypes, and a line chart model was constructed and verified by using other datasets and rat models with different degrees of pulmonary fibrosis. The difference in immune cell infiltration among subtypes was evaluated with CIBERSORT, and the correlation between core diagnostic markers and immune cells were analyzed. Results: Twenty-four core FAMRGs were differentially expressed between the training set and normal samples, and IPF was divided into two subtypes. Significant differences were observed between the two subtypes in biological processes, such as linoleic acid metabolism, cilium movement, and natural killer (NK) cell activation. The subtype with high fatty acid metabolism had more severe pulmonary fibrosis than the other subtype. A reliable construction line chart model based on six diagnostic markers was constructed, and ABCA3 and CYP24A1 were identified as core diagnostic markers. Significant differences in immune cell infiltration were found between the two subtypes, and ABCA3 and CYP24A1 were closely related to NK cells. Conclusion: Fatty acid metabolism and the immune process that it mediates play an important role in the occurrence and development of IPF. The analysis of the role of FAMRGs in IPF may provide a new potential therapeutic target for IPF.

Airway immune response in the mouse models of obesity-related asthma.

The prevalence rates of obesity and its complications have increased dramatically worldwide. Obesity can lead to low-grade chronic systemic inflammation, which predisposes individuals to an increased risk of morbidity and mortality. Although obesity has received considerable interest in recent years, the essential role of obesity in asthma development has not been explored. Asthma is a common chronic inflammatory airway disease caused by various environmental allergens. Obesity is a critical risk factor for asthma exacerbation due to systemic inflammation, and obesity-related asthma is listed as an asthma phenotype. A suitable model can contribute to the understanding of the in-depth mechanisms of obese asthma. However, stable models for simulating clinical phenotypes and the impact of modeling on immune response vary across studies. Given that inflammation is one of the central mechanisms in asthma pathogenesis, this review will discuss immune responses in the airways of obese asthmatic mice on the basis of diverse modeling protocols.

Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma.

Background: Although studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking. Methods: Transcriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs. Results: Nineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors. Conclusion: Pyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma.

Autophagy-Related Genes Are Involved in the Progression and Prognosis of Asthma and Regulate the Immune Microenvironment.

Background: Autophagy has been proven to play an important role in the pathogenesis of asthma and the regulation of the airway epithelial immune microenvironment. However, a systematic analysis of the clinical importance of autophagy-related genes (ARGs) regulating the immune microenvironment in patients with asthma remains lacking. Methods: Clustering based on the k-means unsupervised clustering method was performed to identify autophagy-related subtypes in asthma. ARG-related diagnostic markers in low-autophagy subtypes were screened, the infiltration of immune cells in the airway epithelium was evaluated by the CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. On the basis of the expression of ARGs and combined with asthma control, a risk prediction model was established and verified by experiments. Results: A total of 66 differentially expressed ARGs and 2 subtypes were identified between mild to moderate and severe asthma. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes, and the low-autophagy subtype was closely associated with severe asthma, energy metabolism, and hormone metabolism. The autophagy gene SERPINB10 was identified as a diagnostic marker and was related to the infiltration of immune cells, such as activated mast cells and neutrophils. Combined with asthma control, a risk prediction model was constructed, the expression of five risk genes was supported by animal experiments, was established for ARGs related to the prediction model. Conclusion: Autophagy plays a crucial role in the diversity and complexity of the asthma immune microenvironment and has clinical value in treatment response and prognosis.

Astragalus Polysaccharides Enhance the Immune Response to OVA Antigen in BALB/c Mice.

Vaccination has been identified as one of the most effective ways to prevent the transmission of infectious diseases in humans and animals. One of the most critical steps in vaccine development is the selection of a suitable adjuvant. Although various adjuvant candidates have been evaluated in the past few decades, only a limited amount of them are nontoxic and safe for human use. Astragalus polysaccharide (APS), due to its lack of toxicity, has been used as an immunomodulator to enhance immune responses. On the other hand, the immune effects of APS on ovalbumin are yet to be examined. Thus, in this study, we analyzed APS's effects on the immune response to ovalbumin in BALB/c mice. We have also used the classic adjuvant CpG oligodeoxynucleotide as the positive control.

Blank experimental study on the determination of nitrogen and oxygen isotopes by chemical conversion method.

The reduction of nitrate to nitrous oxide by chemical conversion has the characteristics of simple operation and high sensitivity. Therefore, it is widely used in the pretreatment of nitrogen and oxygen isotopes. In this paper, a series of blank experiments were performed to determine various factors influencing the determination process for the chemical conversion method. To determine blank background values for reagents such as deionized water, NaCl and cadmium powder used in the experiment, the optimal experimental conditions of NaN3, NaCl and cadmium powder were determined to maximize the nitrate reduction rate. The results showed that NaCl was burned at 450 °C for 48 hours, and the placement time was not more than one day, which could minimize the pollution introduced by NaCl. When 0.3 g of cadmium powder and 600 nmol of NaN3 were added, the overall reduction efficiency reached 90%. After measuring actual standard samples, the method demonstrated a good accuracy and applicability.