Level Of Immunity Research Articles

Asthma development is associated with low mucosal IL-10 during viral infections in early life.

Viral infection is a common trigger of severe respiratory illnesses in early life and a risk factor for later asthma development. The mechanism leading to asthma could involve an aberrant airway immune response to viral infections, but this has rarely been studied in a human setting. To investigate insitu virus-specific differences in upper airway immune mediator levels during viral episodes of respiratory illnesses and the association with later asthma. We included 493 episodes of acute respiratory illnesses in 277 children aged 0-3 years from the COPSAC2010 mother-child cohort. Levels of 18 different immune mediators were assessed in nasal epithelial lining fluid using high-sensitivity MesoScale Discovery kits and compared between children with and without viral PCR-identification in nasopharyngeal samples. Finally, we investigated whether the virus-specific immune response was associated with asthma by age 6 years. Viral detection were associated with upregulation of several Type 1 and regulatory immune mediators, including IFN-ɣ, TNF-α, CCL4, CXCL10 and IL-10 and downregulation of Type 2 and Type 17 immune mediators, including CCL13, and CXCL8 (FDR <0.05). Children developing asthma had decreased levels of IL-10 (FDR <0.05) during viral episodes compared to children not developing asthma. We described the airway immune mediator profile during viral respiratory illnesses in early life and showed that children developing asthma by age 6 years have a reduced regulatory (IL-10) immune mediator level. This provides insight into the interplay between early-life viral infections, airway immunity and asthma development.

Immune Markers and Inflammatory Cytokines in Granulomatous Lobular Mastitis: A Case-Control Study.

Granulomatous lobular mastitis (GLM) has seen a rising incidence, though its pathogenesis remains unclear, posing challenges for treatment and contributing to high recurrence rates with conventional therapies. While the role of inflammatory and immune factors in GLM has been recognized, a comprehensive clinical evaluation of these markers is still lacking. This study aims to identify potential diagnostic markers and therapeutic targets by comparing immune markers and cytokine levels in GLM patients and healthy controls. Conducted at Beijing Hospital of Traditional Chinese Medicine, Capital Medical University from July 2023 to May 2024, this study enrolled 30 GLM patients and 15healthy female controls in a 2:1 ratio. Serum levels of immune markers and cytokines were analyzed to explore their potential association with GLM. The study population comprised 30 GLM patients with a mean age of 33.40 ± 4.12 years and 15healthy female controls with a mean age of 32.13 ± 6.19 years. Significantly elevated levels of C-reactive protein (CRP), Immunoglobulin A (IgA), Complement Component 3 (C3), Complement Component 4 (C4), Compliment Component 1q (C1q), Alpha1-antit-rypsin (AAT), α1-acidglycoprotein (AGP), Anti-histone antibodies (Anti-HIS), Anti-Ro52 antibodies (Anti-Ro52), Anti-double stranded DNA antibodies (Anti-dsDNA), Interleukin-6 (IL-6), Interleukin-10 (IL-10), and Tumor Necrosis Factor-α (TNF-α) were observed in GLM patients compared to controls (all P < 0.05). Subgroup analysis revealed higher levels of CRP, C3, C1q, AAT, and AGP in patients with larger mass areas and those with erythema nodosum (all P < 0.05). No significant differences were found in subgroups based on disease duration or recurrence (both P > 0.05). Serum levels of CRP, IgA, AAT, AGP, Anti-HIS, Anti-Ro52, Anti-dsDNA, C3, C4, C1q, IL-6, IL-10, and TNF-α may serve as diagnostic and prognostic indicators for GLM, with CRP, AAT, AGP, and C1q being particularly indicative of disease severity. These markers offer potential therapeutic targets for GLM.

Identification of tumor-antigen signatures and immune subtypes for mRNA vaccine selection in muscle-invasive bladder cancer

BackgroundMuscle-invasive bladder cancer continues to lack reliable diagnostic and prognostic biomarkers. Recently, tumor vaccines targeting specific molecules have emerged as a promising treatment in inhibiting tumor progression, which was rekindled under the background of coronavirus disease-2019 pandemic. However, the application of mRNA vaccine targeting muscle-invasive bladder cancer–specific antigens remains limited, and there has been a lack of comprehensive studies or validations to identify suitable patient subgroups for vaccination. This study aims to explore novel muscle-invasive bladder cancer antigen signatures to identify patients most likely to benefit from vaccination. MethodsGene expression profiles of muscle-invasive bladder cancer samples, along with corresponding clinical data, were retrieved from the Cancer Genome Atlas Program. The least absolute shrinkage and selection operator model was applied to develop signatures for stratifying muscle-invasive bladder cancer patients. Prognostic accuracy of each factor was assessed using receiver operating characteristic analysis. Tumor Immune Estimation Resource was employed to visualize the relationship between the proportion of antigen-presenting cells and the expression of selected genes. The CIBERSORT and WGCNA R packages were used to identify differences in immune infiltration levels across muscle-invasive bladder cancer subgroups. Additionally, the STRING database and Cytoscape were used to construct the protein-protein interaction network. CCK-8 and colony formation assays were employed in invitro experiments. ResultsA total of 49 potential tumor antigens were identified. Using least absolute shrinkage and selection operator Cox regression, 14 tumor antigens were selected to develop a risk evaluation signature. The risk score signature can serve as a valuable tool for predicting the outcomes of muscle-invasive bladder cancer patients. Based on differential clinical, molecular, and immune-related gene profiles, muscle-invasive bladder cancer patients were classified into 2 subtypes: the immune “cold” subtype (immune score 1) and the immune “hot” subtype (immune score 2). The immune score signature, developed using a logistic score model, effectively distinguishes between patients more likely to belong to immune score 1 or 2. Notably, patients with a high risk score exhibited a higher proportion of immune score 2 compared to those with a low risk score. Additionally, the prognostic accuracy was significantly enhanced when the risk score and immune score were combined. Different tumor subtypes displayed distinct immune landscapes and signaling pathways. Moreover, novel tumor antigens associated with oxidative stress were identified. ConclusionThe risk score and immune score signatures based on tumor antigens have identified potential effective neo-antigens for the development of mRNA vaccines targeting muscle-invasive bladder cancer. Patients with low risk score and immune score 1 subtype are more likely to benefit from mRNA vaccination. Additionally, this study highlights the critical role of oxidative stress in modulating the efficacy of the mRNA vaccine.

Role of Cellular Senescence Genes and Immune Infiltration in Sepsis and Sepsis-Induced ARDS Based on Bioinformatics Analysis.

Sepsis is the leading cause of death in critically ill patients; it results in multiorgan dysfunction, including acute respiratory distress syndrome (ARDS). Our study was conducted to determine the role of cellular senescence genes and immune infiltration in sepsis and sepsis-induced ARDS via bioinformatic analyses. Datasets GSE66890 and GSE145227 were obtained from the Gene Expression Omnibus (GEO) database and utilized for bioinformatics analyses. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the differentially expressed genes (DEGs) were performed to identify the key functional modules. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE), were used to screen for characteristic genes in sepsis and sepsis-induced ARDS. ROC curves were generated to evaluate the predictive ability of gene hubs. Differences in immune infiltration levels between the disease and control groups were compared via ssGSEA. The diagnostic value of the hub genes was verified via quantitative PCR (qPCR) in hospitalized patients. Four characteristic genes (ATM, CCNB1, CCNA1, and E2F2) were identified as biomarkers for the progression of sepsis-induced ARDS. E2F2 showed the highest predictive ability for the occurrence of ARDS in patients with sepsis. CD56bright and plasmacytoid dendritic cells exhibited high infiltration in the sepsis-induced ARDS group, whereas eosinophils, MDSCs, macrophages, and neutrophils exhibited low infiltration. In addition, ATM expression was lower in patients with sepsis than in those without sepsis (n = 6). Sepsis-induced ARDS is correlated with circulating immune responses, and the expression of ATM, CCNB1, CCNA1, and E2F2 may serve as potential diagnostic biomarkers and therapeutic targets in sepsis-induced ARDS.

Effects of Nitrite Stress on the Antioxidant, Immunity, Energy Metabolism, and Microbial Community Status in the Intestine of Litopenaeus vannamei.

Nitrite is the main environmental pollutant that endangers shrimp culture. Intestinal health is essential for the disease resistance of shrimp. In this study, Litopenaeus vannamei shrimps were separately exposed to 1 and 5 mg/L of nitrite stress for 48 h, and then the variations in intestinal health were investigated from the aspects of histology, antioxidant, immunity, energy metabolism, and microbial community status. The results showed that nitrite stress damaged intestinal mucosa, and 5 mg/L of nitrite induced more obvious physiological changes than 1 mg/L. Specifically, the relative expression levels of antioxidant (ROMO1, Nrf2, SOD, GPx, and HSP70), ER stress (Bip and XBP1), immunity (proPO, Crus, ALF, and Lys), inflammation (JNK and TNF-α), and apoptosis (Casp-3 and Casp-9) genes were increased. Additionally, intestinal energy metabolism was activated by inducing glucose metabolism (HK, PK, PDH, and LDH), lipid metabolism (AMPK and FAS), tricarboxylic acid cycle (MDH, CS, IDH, SDH, and FH), and electron transfer chain (NDH, CytC, COI, CCO, and AtpH) gene transcription. Further, the homeostasis of intestinal microbiota composition was also disturbed, especially the abundance of some beneficial genera (Clostridium sensu stricto 1, Faecalibacterium, Romboutsia, and Ruminococcaceae UCG-010). These results reveal that nitrite stress could damage the intestinal health of L. vannamei by destroying mucosal integrity, inducing oxidation and ER stress, interfering with physiological homeostasis and energy metabolism, and disrupting the microbial community.

VSIG4 inhibits the anti-inflammatory reaction of immune cells after cardiogenic shock

Abstract Cardiogenic shock (CS) still has a mortality rate of approximately 50%. CS leads to a significant activation of the immune system. The aim of this study was to characterize the immune cell populations and the immune cell-specific changes in CS on admission to the clinic and after revascularization. We developed a web-based platform named 'IRCaS - Immune Cell Regulations in Cardiogenic Shock' to map the temporal course of immune cell-specific processes of CS after acute myocardial infarction (AMI) from admission to 3 days after revascularization. Our tool revealed an endogenous anti-inflammatory response after CS, which is inhibited by the cell-cell receptor VSIG4. The web platform contains newly acquired single-cell sequencing data from patients with CS after AMI on admission and 24, 48, and 72 hours after revascularisation, as well as controls. In total, 171,962 immune cells derived from peripheral blood mononuclear cells (PBMCs) were individually sequenced. Analysis of the immune cell populations revealed, that 24 hours after revascularisation, monocytes increased to 62.4% (vs. 30.4% in controls), while T cells decreased from 46.3% to 25.0%. On the immune cell expression level, we observed an inflammatory response indicated by IL1B which continuously increased from 24 h (1.6+fold), over 48h (3.1+fold) to 72 h (3.5+fold) after revascularization. Interestingly, there was a significant anti-inflammatory response shortly after revascularization, as evidenced by a transient increase in the anti-inflammatory CD16+ monocyte subpopulation from 12.1% to 26.7% at 24 hours and an increase in THBS1 after revascularization, which was only short-lived. We identified a negative feedback in the increasing anti-inflammatory CD16+ cells caused by a subsequent VSIG4 (+5.2-fold) increase. Indeed, overexpression of VSIG4 in monocytes resulted in a significant decrease of anti-inflammatory CD16+ monocytes by 33.9% and a decrease in anti-inflammatory transcripts. Our data show that in addition to the strong inflammatory response in CS, there is also an opposing anti-inflammatory response, which is however only short-lived, as it is attenuated by a negative feedback via an increase in VSIG4. In addition, our webplatform offers time-dynamic gene expression profiles of immune cells, allowing users to select and visualize specific genes during the course of CS after AMI.

Association of dietary insulinemic potential with disease severity and symptoms in patients with COVID-19

AimCOVID-19 has threatened people's lives in world. Studies showed that level of insulin is related to function of immune system and level of inflammation in body. In this study we aimed to evaluate the association between dietary insulinemic potential and level of inflammatory biomarkers, severity and symptoms of COVID-19. MethodsParticipants of this cross-sectional study were 684 people who recovered from COVID-19. Dietary intake of participants was assessed using 168-item food frequency questionnaire during telephone interview, then dietary insulinemic index and load (DII and DIL) calculated for each participants. Data related to study outcomes, include levels of inflammatory biomarkers, disease symptoms, lung infection, saturation of peripheral oxygen, Respiratory Rate, need for respiratory support, duration of disease, hospitalization, recovery from disease and need for respiratory support and score of life satisfaction were collected through an interview with participants and review of their medical records. ResultsAfter controlling for confounders, participants in the highest quartile of DIL had a significantly higher risk of severe COVID-19 (OR: 2.66, 95% CI: 1.01–7.04, Ptrend=0.035), risk of hospitalization (OR: 3.44, 95% CI: 2.27-7.64, Ptrend>0.001), fever (OR: 2.91, 95% CI: 8.08–1.05, Ptrend=0.042), chills (OR: 4.68, 95% CI: 1.77–12.37, Ptrend=0.002) and lower risk of weakness (OR: 0.28, 95% CI: 0.10–0.74, Ptrend=0.012) and myalgia (OR:0.26, CI: 0.10–0.45, Ptrend=0.006) compared to the lowest quartile. In addition our findings showed a significant positive association between DII and risk of fever (OR: 1.71 95% CI: 2.84–1.03, Ptrend=0.049). Our finding failed to find a significand association between DII and risk of sever COVID-19 and hospitalization. Moreover we did not find significant association between DII/DIL and duration of disease, other symptoms and outcomes. ConclusionsOur findings showed that higher DIL was associated with greater risk of sever COVID-19 and hospitalization. More detailed cohort studies are needed to confirm the findings.

The collagenase-induced osteoarthritis (CIOA) model: Where mechanical damage meets inflammation

ObjectiveTo characterize inflammatory and mechanical changes in the collagenase-induced OA (CIOA) model in rats. DesignSkeletally mature, 6-month-old Wistar rats received unilateral intraarticular injections of saline, 500 U or 1000 U of collagenase on days 0 and 2 of the study. Joint tissues were harvested on either day 4 or 70 to evaluate the acute and long-term changes. Blood biomarkers, gait asymmetry and mechanical hyperalgesia were assessed repeatedly up until day 70. ResultsThe intraarticular injection of collagenase triggered an increase in cartilage degeneration and bone resorption over time, particularly for 1000 U. Similarly, mild synovitis was observed on day 70 with an increased number of synovial lining cells, increased fibrosis, and infiltration of peripheral macrophages. Mechanistically, these findings were linked to a dose-related mechanical weakening of the anterior cruciate ligament (ACL), which caused persistent joint destabilization throughout the study. Furthermore, the collagenase injection triggered acute inflammation and swelling of the synovium on day 4 and an acute systemic inflammatory response with increased cytokine and peripheral blood immune cell levels. While mild synovitis persisted until day 70, the systemic inflammatory response returned to control levels after 8 days. Similarly, the observed acute changes in gait and mechanical hyperalgesia also returned to baseline after 21 days. ConclusionBy evaluating inflammatory and mechanical factors at different doses and timepoints, our characterization enables a more targeted study design and increases the clinical relevance of future studies involving the CIOA model.

Pulmonary epithelial wound healing and the immune system. Mathematical modeling and bifurcation analysis of a bistable system

Respiratory diseases such as asthma, acute respiratory distress syndrome (ARDS), influenza or COVID-19 often directly target the epithelium. Elevated immune levels and a ‘cytokine storm’ are directly associated with defective healing dynamics of lung diseases such as COVID-19 or ARDS. The infected cells leave wounded regions in the epithelium which must be healed for the lung to return to a healthy state and carry out its main function of gas-exchange. Due to the complexity of the various interactions between cells of the lung epithelium and surrounding tissue, it is necessary to develop models that can complement experiments to fully understand the healing dynamics. In this mathematical study we model the mechanism of epithelial regeneration. We assume that healing is exclusively driven by progenitor cell proliferation, induced by a chemical activator such as epithelial growth factor (EGF) and cytokines such as interleukin-22 (IL22). Contrary to previous studies of wound healing, we consider the immune system, specifically the T effector cells TH1, TH17, TH22 and Treg to strongly contribute to the healing process, by producing IL22 or regulating the immune response. We therefore obtain a coupled system of two ordinary differential equations for the epithelial and immune cell densities and two functions for the levels of chemicals that either induce epithelial proliferation or recruit immune cells. These functions link the two cell equations. We find that to allow the epithelium to regenerate to a healthy state, the immune system must not exceed a threshold value at the onset of the healing phase. This immune threshold is supported experimentally but was not explicitly built into our equations. Our assumptions are therefore sufficient to reproduce experimental results concerning the ratio TH17/Treg cells as a threshold to predict higher mortality rates in patients. This immune threshold can be controlled by parameters of the model, specifically the base-level growth factor concentration. This conclusion is based on a mathematical bifurcation analysis and linearization of the model equations. Our results suggest treatment of severe cases of lung injury by reducing or suppressing the immune response, in an individual patient, assessed by their disease parameters such as course of lung injury and immune response levels.

Physiological and biochemical assessment of a new three-breed carp cross

The article presents data about the physiological and biochemical assessment of a new three-breed carp cross. The basis for the creation of the cross was the theory of heterosis and the high combinational ability of both parent forms. The effect of heterosis was noted for a number of zootechnical indicators: body weight, head index, number of stamens on the anterior gill arch. The results of a comparative analysis of biochemical parameters such as alanine aminotransferase activity, glucose and total protein content are presented, which allowed us to conclude about the physiological state of the new three-breed cross, about the balance of its carbohydrate metabolism and high rates of protein metabolism, low level of hepatocyte destruction, high immune status and cellular immunity. The new cross is characterized by intensive metabolism of a greater proportion of mature neutrophils and a high level of cellular immunity according to the cytochemical coefficient of lysosomal cationic protein. When obtaining a new three-breed cross, the method of reciprocal hybridization of different carp breeds was used and the choice of an acceptable option with a pronounced effect of heterosis in terms of productivity and vitality was used. The article presents the results of immunological, hematological and biochemical blood tests of the new cross. Also, the article demonstrates the results of studies of the phagocytic activity of neutrophils and determines the content of non-enzymatic cationic protein in them. According to the results of the biochemical assessment, the new three-breed cross showed a high combination of its parent forms with the expected level of the heterosis effect.

Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.

Alzheimer's disease (AD) represents a progressive neurodegenerative disorder characterized by the accumulation of misfolded amyloid beta protein, leading to the formation of amyloid plaques and the aggregation of tau protein into neurofibrillary tangles within the cerebral cortex. The role of carbohydrates, particularly apolipoprotein E (ApoE), is pivotal in AD pathogenesis due to its involvement in lipid and cholesterol metabolism, and its status as a genetic predisposition factor for the disease. Despite its significance, the mechanistic contributions of Lipid Metabolism-related Genes (LMGs) to AD remain inadequately elucidated. This research endeavor seeks to bridge this gap by pinpointing biomarkers indicative of early-stage AD, with an emphasis on those linked to immune cell infiltration. To this end, advanced machine-learning algorithms and data derived from the Gene Expression Omnibus (GEO) database have been employed to facilitate the identification of these biomarkers. Differentially expressed genes (DEGs) were identified by comparing gene expression profiles between healthy individuals and Alzheimer's disease (AD) patients, using data from two Gene Expression Omnibus (GEO) datasets: GSE5281 and GSE138260. Functional enrichment analysis was conducted to elucidate the biological relevance of the DEGs. To ensure the reliability of the results, samples were randomly divided into training and validation sets. The analysis focused on lipid metabolism-related DEGs (LMDEGs) to explore potential biomarkers for AD. Machine learning algorithms, including Support Vector Machine-Recursive Feature Elimination (SVM-RFE) and the Least Absolute Shrinkage and Selection Operator (LASSO) regression model, were applied to identify a key gene biomarker. Additionally, immune cell infiltration and its relationship with the gene biomarker were assessed using the CIBERSORT algorithm. The Integrated Traditional Chinese Medicine (ITCM) database was also referenced to identify Chinese medicines related to lipid metabolism and their possible connection to AD. This comprehensive strategy aims to integrate modern computational methods with traditional medicine to deepen our understanding of AD and its underlying mechanisms. The study identified 137 genes from a pool of 751 lipid metabolism-related genes (LMGs) significantly associated with autophagy and immune response mechanisms. Through the application of LASSO and SVM-RFE machine-learning techniques, four genes-choline acetyl transferase (CHAT), member RAS oncogene family (RAB4A), acyl-CoA binding domain-containing protein 6 (ACBD6), and alpha-galactosidase A (GLA)-emerged as potential biomarkers for Alzheimer's disease (AD). These genes demonstrated strong therapeutic potential due to their involvement in critical biological pathways. Notably, nine Chinese medicine compounds were identified to target these marker genes, offering a novel treatment approach for AD. Further, ceRNA network analysis revealed complex regulatory interactions involving these genes, underscoring their importance in AD pathology. CIBERSORT analysis highlighted a potential link between changes in the immune microenvironment and CHAT expression levels in AD patients, providing new insights into the immunological dimensions of the disease. The discovery of these gene markers offers substantial promise for the diagnosis and understanding of Alzheimer's disease (AD). However, further investigation is necessary to validate their clinical utility. This study illuminates the role of Lipid Metabolism-related Genes (LMGs) in AD pathogenesis, offering potential targets for therapeutic intervention. It enhances our grasp of AD's complex mechanisms and paves the way for future research aimed at refining diagnostic and treatment strategies.

C6 and KLRG2 are pyroptosis subtype-related prognostic biomarkers and correlated with tumor-infiltrating lymphocytes in lung adenocarcinoma

Pyroptosis plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the pyroptosis-related gene (PRG) expression pattern and to identify promising pyroptosis-related biomarkers to improve the prognosis of LUAD. The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the 44 differentially expressed PRGs (DEPRGs). Then, consensus clustering revealed pyroptosis-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic PRGs. After overlapping DEGs and the Lasso regression analysis-based prognostic genes, the predictive risk model was established and validated. Correlation analysis between PRGs and clinicopathological variables was also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels, the risk score, and clinicopathological variables in the predictive risk model. A total of 52 genes from the PubMed were identified as PRGs, and 44 of the 52 genes were pooled as DEPRGs. The most significant GO term was “collagen trimer” (P = 2.46E-13), and KEGG analysis results indicated that 44 DEPRGs were significantly enriched in Salmonella infection (P < 0.001). Then, consensus clustering analysis divided LUAD patients into two clusters, and a total of 79 DEGs were identified according to these cluster subtypes. Subsequently, univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators and we also performed Lasso regression analysis and screened 23 DEGs. After overlapping 23 DEGs and 12 genes, only 4 (KLRG2, MAPK4, C6 and SFRP5) of 12 genes were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model effectively predicted the prognosis (P < 0.001). Combined with the correlation analysis results between the 4 genes and clinicopathological variables, C6 and KLRG2 were screened as prognostic genes. In this study, we constructed a predictive risk model and identified two pyroptosis subtype-related gene expression patterns to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful for accurately characterizing the LUAD and developing personalized treatment.

Metapopulation model of phage therapy of an acute Pseudomonas aeruginosa lung infection.

Phage therapy is increasingly employed as a compassionate treatment for severe infections caused by multidrug-resistant (MDR) bacteria. However, the mixed outcomes observed in larger clinical studies highlight a gap in understanding when phage therapy succeeds or fails. Previous research from our team, using in vivo experiments and single-compartment mathematical models, demonstrated the synergistic clearance of acute P. aeruginosa pneumonia by phage and neutrophils despite the emergence of phage-resistant bacteria. In fact, the lung environment is highly structured, prompting the question of whether immunophage synergy explains the curative treatment of P. aeruginosa when incorporating realistic physical connectivity. To address this, we developed a metapopulation network model mimicking the lung branching structure to assess phage therapy efficacy for MDR P. aeruginosa pneumonia. The model predicts the synergistic elimination of P. aeruginosa by phage and neutrophils but emphasizes potential challenges in spatially structured environments, suggesting that higher innate immune levels may be required for successful bacterial clearance. Model simulations reveal a spatial pattern in pathogen clearance where P. aeruginosa are cleared faster at distal nodes of the bronchial tree than in primary nodes. Interestingly, image analysis of infected mice reveals a concordant and statistically significant pattern: infection intensity clears in the bottom before the top of the lungs. The combined use of modeling and image analysis supports the application of phage therapy for acute P. aeruginosa pneumonia while emphasizing potential challenges to curative success in spatially structured in vivo environments, including impaired innate immune responses and reduced phage efficacy.

Landscape of the immune infiltration and identification of molecular diagnostic markers associated with immune cells in patients with kidney transplantation

Rejection seriously affects the success of kidney transplantations. However, the molecular mechanisms underlying this rejection remain unclear. The GSE21374 and GSE36059 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Next, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to infer the proportions of 22 immune cells. Moreover, infiltrating immune cell-related genes were identified using weighted gene co-expression network analysis (WGCNA), and enrichment analysis was conducted to observe their biological functions. Extreme Gradient Boosting (XGBoost) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithms were used to screen hub genes. Quantitative real-time PCR was conducted to verify the number of immune cells and hub gene expression levels. The rejection and non-rejection groups showed significantly different distributions (P < 0.05) of eight immune cells (B cell memory, Plasma cells, mast cells, follicular helper T cells, T CD8 cells, Macrophages M1, T Cells CD4 memory activated, and gamma delta T cells). Subsequently, CD8A, CRTAM, GBP2, WARS, and VAMP5 were screened as hub genes using the XGBoost and LASSO algorithms and could be used as diagnostic biomarkers. Finally, differential analysis and quantitative real-time PCR suggested that CD8A, CRTAM, GBP2, WARS, and VAMP5 were upregulated in rejection samples compared to non-rejection samples. The present study identified five key infiltrating immune cell-related genes (CD8A, CRTAM, GBP2,WARS, and VAMP5) involved in kidney transplant rejection, which may explain the molecular mechanism of rejection in kidney transplantation development.

The enhancement of teacher immunity in a professional development course: Contributions from supervisory observation and the observer

Classroom observation has been reported to be stressful for language teachers since it can disrupt the equilibrium and push the teachers towards maladaptive language teacher immunity. The present study is an attempt to shed light on the way classroom observation and a professional development (PD) course on classroom observation contribute to language teacher immunity development through self-organization lens. To this end, the researchers in the current study designed an explanatory sequential mixed method study and 13 novice language teachers were invited to fill language teacher immunity scale before and after a professional development course. The qualitative data were collected through narrative frames and semi-structured interviews. The findings revealed that the immunity level of the students differed significantly before and after the intervention. The findings accentuate the importance of in-service programs in reforming the teachers’ narratives of classroom observations and enabling them to transform classroom observations from threats to opportunities.

Correlation between elderly patients with COPD and the impact on immunity in tuberculosis patients: A retrospective study.

The prevalence of chronic obstructive pulmonary disease (COPD) and tuberculosis (TB) is increasing globally, yet their comprehensive impact on the immune system remains underexplored. This study aimed to provide a thorough assessment of the immune status of patients with COPD and tuberculosis (TB-COPD), including their pulmonary conditions, immune cell responses, and changes in lymphocyte subpopulations. A total of 151 patients with TB-COPD patients were included, and clinical data were compared between the TB-COPD group and a group of TB patients without COPD (TB-NCOPD). Lung imaging findings and peripheral blood immune cell levels were compared between the 2 groups. Flow cytometry was used to analyze the absolute counts of lymphocyte subpopulations. The incidence of pulmonary lobe lesions and cavitation in the TB-COPD group aged 70 years or older was significantly higher than that in the control group. At the immune cell level, patients with TB-COPD showed a significant reduction in total lymphocytes, CD4+ T lymphocytes and CD4+/CD8+ ratio. Regardless of COPD status, the CD4+ T cell count in the CMV-infected group was significantly lower than that in the uninfected group (P < .05). Additionally, the CD4+/CD8+ ratio in the COPD + TB CMV + group was significantly lower than that in the uninfected group. Analysis of lymphocyte subpopulations revealed a decrease in the counts of CD4+ T lymphocytes in patients with TB-COPD, potentially associated with the chronic inflammatory state induced by COPD. The one-month treatment outcomes showed that the improvement rate in the control group was 70.58%, which was significantly higher than the 38.92% in the COPD + TB group (P < .001). We observed a significant increase in the number of pulmonary cavity patients in the TB-COPD group, suggesting that COPD may be a potential risk factor for the formation of pulmonary cavities in patients with TB. At the immune cell level, TB-COPD patients showed a notable decrease in lymphocytes and CD4+ T lymphocytes, implying that COPD combined with pulmonary TB may significantly affect the immune system, leading to a reduction in the counts of key immune cells.

Synergizing autophagic cell death and oxaliplatin-induced immunogenic death by a self-delivery micelle for enhanced tumor immunotherapy

Chemotherapy has become an emerging strategy to activate cytotoxic T cell responses by inducing immunogenic cell death (ICD), but the level of antitumor immunity induced by chemotherapeutic agents, such as oxaliplatin (OXA), is limited due to inadequate tumor antigen presentation and T cell activation. Inducing autophagic cell death (ACD) promotes the release of tumor antigen and the recruitment of dendritic cells, therefore strengthening antitumor immune responses. Here we simultaneously activate ICD and ACD with tumor targeting micelle to achieve enhanced antitumor chemo-immunotherapy. A self-delivery micelle is formulated by conjugating OXA prodrug with tocopherol succinate (TOS) as a hydrophobic segment and further encapsulates autophagy activator SMER28 to afford TOPR/SMER28, which specifically targets αvβ3 on tumor cells with c(RGDfK). Upon cellular internalization, OXA is released from the prodrug in response to the high concentration of reduced glutathione (GSH) in tumor cells, triggering ICD and releasing associated molecular patterns (DAMPs) signaling molecules to stimulate immunity. Meanwhile, SMER28 over-activates autophagy to induce autophagic cell death, which further leads to the maturation of dendritic cells and ultimately activates anti-tumor immune response. In the 4T1 tumor-bearing mice, the combination of OXA and SMER28 effectively inhibits tumor growth and activates antitumor immune responses. The tumor targeted micelle releases OXA and SMER28 in an on-demand profile and strengthens tumor chemo-immunotherapy by synergizing ICD and ACD, providing an alternative for antitumor immunotherapy. Statement of significanceChemotherapy induces immunogenic cell death (ICD) to activate anti-tumor immunity. However, the efficacy is limited by low levels of antigen presentation and T cell activation. To strengthen the antitumor immune responses induced by ICD, we first combine autophagic cell death (ACD) with ICD by formulating a glutathione-responsive oxaliplatin prodrug micelle co-encapsulating the autophagy activator SMER28. The activated autophagic level by SMER28 enhances the release of antigen and the recruitment of APCs, and ultimately bolsters T cell-mediated antitumor immune responses. We provide a potential strategy to amplify antitumor immune effects by combining autophagy activation with chemotherapy.

Construction and multiple validations of a robust ferroptosis-related prognostic model in bladder cancer: A comprehensive study.

Ferroptosis is iron-dependent programmed cell death that inhibits tumor growth, particularly in traditional treatment-resistant tumors. Prognostic models constructed from ferroptosis-related genes are lacking; prognostic biomarkers remain insufficient. We acquired gene expression data and corresponding clinical information for bladder cancer (BC) samples from public databases. Ferroptosis-related genes from the ferroptosis database were screened for clinical predictive value. We validated gene expression differences between tumors and normal tissues through polymerase chain reaction and western blotting. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were conducted to explore signaling pathways affecting the overall survival of patients with BC. CIBERSORT was used to quantify the infiltration of 22 immune cell types. We identified 6 genes (EGFR, FADS1, ISCU, PGRMC1, PTPN6, and TRIM26) to construct the prognostic risk model. The high-risk group had a poorer overall survival than the low-risk group. Receiver operating characteristic curves demonstrated excellent predictive accuracy. The validation cohort and 3 independent datasets confirmed the models' general applicability and stability. BC tissues had elevated FADS1, PTPN6, and TRIM26 mRNA and protein levels and decreased ISCU levels. Enrichment analysis indicated that neurosecretory activity might be the main pathway affecting the overall survival. High- and low-risk groups had significantly different immune cell infiltration. Specific ferroptosis-related gene expression was associated with immune cell infiltration levels. The risk score was significantly correlated with patients' clinical characteristics. A novel, widely applicable risk model with independent predictive value for the prognosis of patients with BC was established; candidate molecules for future BC research were identified.

Immunological and Biochemistry Comparative Studies of COVID-19, Vaccinated, and Healthy Individuals

Insufficient information on the immune response to the Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2), an essential component in developing effective vaccines and therapies, is a critical issue. Consequently, establishing clinical methods for evaluating immune responses to the SARS-CoV-2 virus and validating the direct participation of the parameters in the development of adaptive immune responses are necessary. Furthermore, a comprehensive guide to the diseases caused by the novel SARS-CoV-2 coronavirus is critical. Employing universal and non-specific early cytokines, specifically, interferon-gamma (IFN-γ) in immune clinics during immune response assessments, presents potential in several respects. IFN-gamma promotes the production of other antiviral molecules and stimulates immune system responses against the virus. Nonetheless, reports indicated that some individuals with severe COVID-19 exhibited impaired IFN-gamma production, which might contribute to the severity of the illness. Enhancing IFN-gamma synthesis or exogenous IFN-gamma therapy has demonstrated potential as a COVID-19 treatment approach. Significant IL-6 levels are associated with cytokine storm progression, which denotes excessive and uncontrolled immune responses that could lead to tissue damage. Targeting IL-6 with specific inhibitors, such as monoclonal antibodies, could reduce COVID-19 severity in certain patients. The results obtained in this study indicated that blood electrolytes and immune variable levels (interleukin 6 and IFN-gamma) were significantly different among the infected, vaccinated, and control groups.

Characterization of the symmetrical benzimidazole twin drug TL1228: the role as viral entry inhibitor for fighting COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is reliably one of the largest pandemics the world has suffered in recent years. In the search for non-biological antivirals, special emphasis was placed on drug repurposing to accelerate the clinical implementation of effective drugs.The life cycle of the virus has been extensively investigated and many human targets have been identified, such as the molecular chaperone GRP78, representing a host auxiliary factor for SARS-CoV-2 entry. Here we report the inhibitor capacity of TL1228, a small molecule discovered through an in silico screening approach, which could interfere with the interaction of SARS-CoV-2 and its target cells, blocking the recognition of the GRP78 cellular receptor by the viral Spike protein. TL1228 showed in vitro the ability to reduce significantly both pseudoviral and authentic viral activity even through the reduction of GRP78/ACE2 transcript levels. Importantly, TL1228 acts in modulating expression levels of innate immunity and as inflammation markers.