Immune Response Signaling Research Articles

Activation of the cGAS-sting Pathway Mediated by Nanocomplexes for Tumor Therapy.

cGAS (cyclic GMP-AMP synthase)-STING (stimulator of interferon genes) pathway is an natural immune response signaling pathway in the human body that is essential for sensing abnormal DNA aggregation in the cell. When the cGAS protein senses abnormal or damaged DNA, it forms a second messenger called cyclic dinucleotide (cGAMP). The cycled dinucleotide will activate the downstream STING protein, thereby inducing the expression of inflammatory cytokines such as type I interferon, which binds to receptors on its own cell membrane and ultimately initiates multiple immune response pathways. This signaling pathway plays an important immune role in antimicrobial and antitumor functions, etc. so the development of drugs targeting this signaling pathway has important clinical application value. In recent years nanocomplexes based cGAS-STING signaling pathway activation and inhibition treatments have been gradually developed. In this review, on the basis of elaborating the main activation mechanism of the cGAS-STING pathway, we further introduced the nanocomplexes that effectively activate the cGAS-STING pathway, focusing on the composition, types and applications of the nanocomplexes. In addition, we discussed the key challenges and future research directions of the way that stimulating the cGAS-STING signaling pathway in the form of nanocomplexes to activate immuno-tumor therapy. Our work aims to provide a better understanding of the progress of nanotherapeutics in the cGAS-STING pathway, providing a promising anti-tumor therapeutic strategy.

Methylsulfonylmethane (MSM) Supplementation in Adult Horses Supports Improved Skeletal Muscle Inflammatory Gene Expression Following Exercise.

Methylsulfonylmethane (MSM) is a sulfur-containing molecule with reported anti-inflammatory and antioxidant activities. Exercise causes the formation of free radicals and stimulates inflammatory gene expression in leukocytes and skeletal muscle. The hypothesis that dietary supplementation with MSM alters the exercise-mediated inflammatory and oxidant response was assessed in unfit adult thoroughbred geldings. Ten geldings (6.7 ± 1.6 yr) were assigned to a diet supplemented without (CON, n = 5) or with 21 g of MSM (n = 5) for 30 days. Following the supplementation period, horses performed a standardized exercise test (SET) with blood collections before (t = 0), 10 min, 1 h, 4 h, and 24 h post-SET. Skeletal muscle biopsies were retrieved from the middle gluteus before and 1 h post-SET for total RNA isolation. All horses were rested for 120 days before the experiment was repeated in a cross-over design. Plasma total antioxidant capacity was unaffected (p > 0.05) by either exercise or MSM. Plasma glutathione peroxidase activity was less (p < 0.05) in MSM horses than in the CON. Plasma IL6, IL8, IL10, and TNFα were unaffected (p > 0.05) by either exercise or diet. Transcriptomic analysis of skeletal muscle revealed 35 genes were differentially expressed (DEG; p < 0.05) by 2-fold or more in response to exercise; no MSM DEGs were noted. A comparison of the exercise by diet contrasts revealed that horses supplemented with MSM contained a greater number of exercise-responsive genes (630; logFC > 0.2; q < 0.05) by comparison to the CON (237), with many of these mapping to the immune response (71) and cytokine signal transduction (60) pathways. These results suggest supplementation of MSM as a dietary aid for improved anti-inflammatory responses in skeletal muscle following exercise.

Combining machine learning and single-cell sequencing to identify key immune genes in sepsis

This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from peripheral blood samples obtained from sepsis patients (n = 23) and healthy controls (n = 10). 5148 differentially expressed genes were identified using the DESeq2 technique and 5636 differentially expressed genes were identified by the limma method(|Log2 Fold Change|≥2, FDR < 0.05). A total of 1793 immune-related genes were identified from the ImmPort database, with 358 genes identified in both groups. Next, a Biological association network was constructed, and five key hub genes (CD4, HLA-DOB, HLA-DRB1, HLA-DRA, AHNAK) were identified using a combination of three topological analysis algorithms (MCC, Closeness, and MNC) and four machine learning algorithms (Random Forest, LASSO regression, SVM, and XGBoost). immune cell distribution showed that the key genes correlated with multiple immune cell infiltrations. Gene Set Enrichment Analysis (GSEA) revealed that the key genes involved multiple immune response and inflammation-related signaling pathways. Subsequently, diagnostic models were constructed using four machine learning algorithms (Logistic regression, AdaBoost, KNN, and XGBoost) based on the identified key genes. Models with the highest performance were then selected. Ultimately, single-cell sequencing data revealed that the identified key genes were expressed in various immune cells, while Quantitative PCR (qPCR) tests confirmed their reduced expression in the sepsis group.

Circadian Regulation of the Rice Immune Response during Rice Blast Infection via Metabolic and Calcium Signaling.

The circadian clock is crucial in plant immunity and metabolism, yet the coordinating mechanisms remain elusive. In the present study, transcriptome analysis of M. oryzae-infected rice leaves and rhythmic analysis showed reduced amplitudes of circadian and phytochrome genes, impacting immune response, metabolic pathways, and calcium signaling. The amplitudes of pattern-triggered immunity (PTI)-related genes declined, while the rhythmicity of effector-triggered immunity (ETI)-related genes disappeared. Moreover, alterations in the phases of metabolic pathways were observed, potentially involved in immune response regulation like phytohormone biosynthesis. Calcium signaling exhibited a circadian pattern similar to that of the whole-transcriptome analysis. The administration of CaCl2 alleviated, whereas the calcium ion chelator EGTA aggravated, the phenotypes of rice blasts, suggesting their role in regulating the circadian clock-mediated immune response in rice. Our study highlighted the significance of circadian regulation in rice blast-induced immune modulation, which may contribute to developing immunomodulators and the formulation of chronobiology-based precise therapeutic regimens.

Urinary proteomics identifies distinct immunological profiles of sepsis associated AKI sub-phenotypes

BackgroundPatients with sepsis-induced AKI can be classified into two distinct sub-phenotypes (AKI-SP1, AKI-SP2) that differ in clinical outcomes and response to treatment. The biologic mechanisms underlying these sub-phenotypes remains unknown. Our objective was to understand the underlying biology that differentiates AKI sub-phenotypes and associations with kidney outcomes.MethodsWe prospectively enrolled 173 ICU patients with sepsis from a suspected respiratory infection (87 without AKI and 86 with AKI on enrollment). Among the AKI patients, 66 were classified as AKI-SP1 and 20 as AKI-SP2 using a three-plasma biomarker classifier. Aptamer-based proteomics assessed 5,212 proteins in urine collected on ICU admission. We compared urinary protein abundances between AKI sub-phenotypes, conducted pathway analyses, tested associations with risk of RRT and blood bacteremia, and predicted AKI-SP2 class membership using LASSO.Measurement and main resultsIn total, 117 urine proteins were higher in AKI-SP2, 195 were higher in AKI-SP1 (FDR < 0.05). Urinary proteins involved in inflammation and chemoattractant of neutrophils and monocytes (CXCL1 and REG3A) and oxidative stress (SOD2) were abundant in AKI-SP2, while proteins involved in collagen deposition (GP6), podocyte derived (SPOCK2), proliferation of mesenchymal cells (IL11RA), anti-inflammatory (IL10RB and TREM2) were abundant in AKI-SP1. Pathways related to immune response, complement activation and chemokine signaling were upregulated in AKI-SP2 and pathways of cell adhesion were upregulated in AKI-SP1. Overlap was present between urinary proteins that differentiated AKI sub-phenotypes and proteins that differentiated risk of RRT during hospitalization. Variable correlation was found between top aptamers and ELISA based protein assays. A LASSO derived urinary proteomic model to classify AKI-SP2 had a mean AUC of 0.86 (95% CI: 0.69–0.99).ConclusionOur findings suggest AKI-SP1 is characterized by a reparative, regenerative phenotype and AKI-SP2 is characterized as an immune and inflammatory phenotype associated with blood bacteremia. We identified shared biology between AKI sub-phenotypes and eventual risk of RRT highlighting potential therapeutic targets. Urine proteomics may be used to non-invasively classify SP2 participants.

Positive Selection of TLR2 and MyD88 Genes Provides Insights Into the Molecular Basis of Immunological Adaptation in Amphibians.

The transition from water to land of amphibians is evolutionarily significant in the history of vertebrates, and immunological adaptation is an important challenge for amphibians to respond to the dramatic changes of the environmental pathogens during their origin and diversification. Toll-like receptors (TLRs) are important pattern recognition receptors for the innate immune response and TLRs signaling pathway play essential roles in the immune responses to pathogens and inflammatory reaction. However, the evolutionary patterns and molecular mechanisms underlying their adaptation in amphibians are poorly documented to date. Here, we determined the coding regions, expression patterns of TLR2 and Myeloid differentiation factor 88 (MyD88) in the large treefrog (Zhangixalus dennysi), and explored the evolutionary patterns of these two genes in amphibians. Quantitative Real-time PCR analyses showed that the TLR2 and MyD88 mRNA were expressed in all the organs/tissues examined, both with the highest levels in the heart and the lowest levels in the body fat for TLR2 and lung for MyD88. The highly conservation and functional significance of these two genes in amphibians were supported based on the sequence characteristics and evolutionary analyses. Significantly positive selection was found to be acting on TLR2 and MyD88 in amphibians based on different site models. Strong signal of positive selection among different amphibian lineages for these two genes was also detected and a series of positively selected sites were identified based on the branch-site analysis. Our results suggest that amphibians have adapted to different pathogenic microorganisms during their transition from the aquatic to terrestrial environment and diversification into various habitats. The present study will provide new insights into the evolutionary process and molecular basis underlying the immunological adaptation in vertebrates.

Toxicogenomic Assessment of In Vitro Macrophages Exposed to Profibrotic Challenge Reveals a Sustained Transcriptomic Immune Signature.

Immune signalling is a crucial component in the progression of fibrosis. However, approaches for the safety assessment of potentially profibrotic substances, that provide information on mechanistic immune responses, are underdeveloped. This study aimed to develop a novel framework for assessing the immunotoxicity of fibrotic compounds. We exposed macrophages in vitro to multiple sublethal concentrations of the profibrotic agent bleomycin, over multiple timepoints, and generated RNA sequencing data. Using a toxicogenomic approach, we performed dose-dependent analysis to discover genes dysregulated by bleomycin exposure in a dose-responsive manner. A subset of immune genes displayed a sustained dose-dependent and differential expression response to profibrotic challenge. An immunoassay revealed cytokines and proteinases responding to bleomycin exposure that closely correlated to transcriptomic alterations, underscoring the integration between transcriptional immune response and external immune signalling activity. This study not only increases our understanding of the immunological mechanisms of fibrosis, but also offers an innovative framework for the toxicological evaluation of substances with potential fibrogenic effects on macrophage signalling. Our work brings a new immunotoxicogenomic direction for hazard assessment of fibrotic compounds, through the implementation of a time and resource efficient in vitro methodology.

Advanced whole transcriptome sequencing and artificial intelligence/machine learning (AI/ML) in imiquimod-induced psoriasis-like inflammation of human keratinocytes.

Although the HaCaT keratinocyte model has been used in previous research to study the effects of antipsoriatic agents, there is still a lack of comprehensive understanding of the mechanism of imiquimod (IMQ)-induced proliferation and signal transduction in psoriasis-like keratinocytes. This study aimed to investigate the molecular mechanisms and pathways associated with psoriasis-like inflammation caused by IMQ in human keratinocytes. HaCaT cells were exposed to different concentrations of IMQ to induce inflammation similar to that observed in psoriasis. Cell viability was evaluated using the MTT assay and cell morphology was examined using phase-contrast microscopy. Gene expression profiles were analyzed through whole transcriptome sequencing, followed by bio-informatics network analysis using IPA software. The GSEA was conducted with the aim of identifying enriched pathways. The expression of key cytokines IL-6 and TNF-α was confirmed by QPCR. Artificial intelligence/machine learning (AI/ML) algorithms were used to predict potential diseases and phenotypes associated with the observed gene profiles. IMQ treatment demonstrated a substantial positive impact on cell survival without any detectable alterations in the morphology of HaCaT cells. A comprehensive analysis of the entire set of transcribed genes identified 513 genes that exhibited differential expression. Bioinformatics analysis revealed key pathways associated with immune response, cellular proliferation, and cytokine signaling. GSEA identified significant enrichment in the IFN-γ response and JAK-STAT signaling pathways. QPCR analysis confirmed the increased mRNA expression levels of IL-6 and TNF-α in cells treated with IMQ. AI/ML algorithms have identified potential correlations with diseases, such as multiple sclerosis, lympho-proliferative malignancy, and autoimmune disorders. Our results highlight the importance of specific genes and pathways, particularly those associated with IFN-γ pathway and IL-6/JAK-STAT signaling. AI/ML predictions indicate potential associations with various diseases and provide valuable insights for the development of novel therapeutic approaches for psoriasis and related disorders.

Unveiling the dual anti-viral and anti-bacterial potential of Tridax procumbens: integrating system biology and molecular modeling for therapeutic insights

This study evaluates the dual anti-viral and anti-bacterial activity of Tridax procumbens using system biology and molecular docking targeting the tumor necrosis factor (TNF) signaling pathway. The bioactive potential of Tridax procumbens was studied using phytochemical databases, and the essential biomolecules were selected for the study. The principle of geneVenn diagrams and protein target prediction was used to identify overlapping molecular targets with viral and bacterial diseases, which was later validated using various database mining tools like GeneCards and OMIM. Cytoscape software was applied to construct protein-protein interaction networks, which showed that TNF, AKT1, EGFR, SRC, and ESR1 are the hub genes of the networks. The gene ontology (GO) enrichment analysis also recapitulated the modulated biological processes, cellular components, and molecular functions of Tridax procumbens compounds, including their action on the TNF signaling in inflammation and immune responses. Molecular docking studies showed strong binding affinities of compounds such as cynaroside and 5,7,2,3,4-Pentahydroxy-3,6-dimethoxyflavone 7-glucoside to TNF, and molecular dynamics simulations confirmed these interactions’ stability. The findings suggest that Tridax procumbens exerts its therapeutic effects by modulating the TNF signaling pathway, offering significant anti-viral and anti-bacterial properties. This integrative approach provides insights into the Tridax procumbens’s mechanisms of action, supporting its potential as a source of novel therapeutic agents against infectious and bacterial diseases. There is still a need for further experimental research to define the full spectrum of Tridax procumbens’ therapeutic application.

Functional Analysis of Macrophages and Mirnas in the Metastasis Suppression By iPS Cell-Derived Extracellular Vesicles

Extracellular vesicles (EVs) carry cell-derived information and play an important role in intercellular communication. In general, cancer cell-derived EVs have the ability to transmit cancer cell-inducing information to tissue cells to which the cancer cells metastasize, thereby promoting metastasis. However, it has been found that cancer cell-derived EVs may also have an inhibitory effect on metastasis. We also found such an effect in mouse melanoma. EVs derived from metastatic B16F10 cells (F10 cells) showed a metastasis-promoting effect, but contrarily, EVs derived from Nanog⁺F10 cells, a higher metastatic cell line than F10, showed a metastasis inhibition effect in a similar manner as anti-metastasis vaccines. Therefore, we hypothesized that EVs derived from poorly differentiated cells have metastasis- inhibition properties, and focused on iPS-EVs, which are even less differentiated than Nanog⁺F10 cells, and examined their ability to suppress melanoma metastasis. The results showed that iPS-EVs had greater inhibitory effect on melanoma metastasis. This result suggests the involvement of immune cells. Therefore, we analyzed the metastasis inhibitory effect of iPS-EVs in vitro using J774.1 macrophage cultured cells. Fluorescently labeled EVs were added to macrophages, and macrophages incorporating EVs were separated by a cell sorter. Isolated macrophages were co-cultured with Nanog⁺F10 on the top of Transwell inserts; after 22 hours, the number of invasive Nanog⁺F10 cells was counted. The results showed that when cultured with macrophages incorporating iPS-EVs, the number of invasive cells decreased compared to controls, indicating that iPS-EVs induced macrophage activation. In this study, miRNAs in EVs were analyzed to elucidate the molecular mechanisms by which iPS-EVs affected immune cells. Differential analysis revealed that 37 miRNAs were up-regulated and 43 miRNAs were down-regulated, respectively significantly in iPS-EVs compared to Nanog⁺F10-EVs. Target genes were determined using TargetScanMouse_8.0 for each of the four miRNAs with most enhanced expression and the four miRNAs with most suppressed expression. Functional association analysis of these genes and immune function-specific keyword analysis were performed to predict the hub genes that should be important for the metastasis suppression mechanism. The top 30 genes with highest relevance scores were selected using Cytoscape software. Of the 30 genes, 5 genes with high relevance scores and 2 miRNAs targeting those genes were predicted. In the immune function-specific keyword analysis, 17 keywords related to suppression of metastasis were pre-defined for each of the three categories of immune response, immune cells, and inflammatory signals. Sixty one genes were found to contain one or more keywords among the functional information of 669 target genes. The five genes involved in the "hub gene" were selected as candidate hub genes, and the miRNAs targeting them were narrowed down to two. As a result, we predicted nine candidate hub genes and two miRNAs (miR-466f-3p and miR-342-5p) that might markedly regulate the expression of these genes. EVs were isolated from each cell line of iPS, F10, and Nanog⁺F10. RNA was extracted from EVs by ultracentrifugation using CD81 as a marker, and miR-466f-3p was quantified. The results confirmed that miR-466f-3p was internalized more in iPS-EVs than in F10-EVs or Nanog⁺F10-EVs.

Dichotomous outcomes of TNFR1 and TNFR2 signaling in NK cell-mediated immune responses during inflammation

Natural killer (NK) cell function is regulated by a balance of activating and inhibitory signals. Tumor necrosis factor (TNF) is an inflammatory cytokine ubiquitous across homeostasis and disease, yet its role in regulation of NK cells remains unclear. Here, we find upregulation of the immune checkpoint protein, T cell immunoglobulin and mucin domain 3 (Tim3), is a biomarker of TNF signaling in NK cells during Salmonella Typhimurium infection. In mice with conditional deficiency of either TNF receptor 1 (TNFR1) or TNF receptor 2 (TNFR2) in NK cells, we find TNFR1 limits bacterial clearance whereas TNFR2 promotes it. Mechanistically, via single cell RNA sequencing we find that both TNFR1 and TNFR2 induce the upregulation of Tim3, while TNFR1 accelerates NK cell death but TNFR2 promotes NK cell accumulation and effector function. Our study thus highlights the complex interplay of TNF-based regulation of NK cells by the two TNF receptors during inflammation.

Identification and functional network analysis of inflammatory and apoptosis-related genes associated with infectious chronic rhinosinusitis: Thermal modeling of medical biological systems

The aim of this study was to identify inflammatory and apoptotic genes associated with infectious chronic sinusitis and to analyze their functional networks in medical biological systems by thermal modeling. Bioinformatics analysis was used to identify genes involved in apoptosis and inflammation and construct their functional networks. Finally, thermal modeling techniques were used to explore the dynamic changes of these genes in the pathogenesis of chronic sinusitis. In a comparative analysis, thermal modeling analysis revealed that these genes play important roles in apoptosis, immune response, and inflammatory signaling pathways. In addition, the heat model also revealed the interaction network between different genes, providing a new perspective for understanding the coordination mechanism of inflammation and apoptosis. Through the identification of genes associated with infectious chronic sinusitis and thermal modeling analysis of their functional networks, this study revealed the complex interaction between apoptosis and inflammation in the disease process.

Identification of Plasma Protein Biomarkers for Predicting Lung Cancer.

Lung cancer remains a leading cause of cancer-related mortality worldwide, necessitating the development of effective early diagnostic strategies. Despite advancements in imaging and screening technologies, late-stage diagnoses remain common, limiting treatment options and reducing survival rates. Thus, there is a critical need for reliable, minimally invasive biomarkers to improve early detection and patient outcomes. Plasma protein biomarkers offer promising potential for early lung cancer detection and continuous disease monitoring. This study explored the potential of specific plasma protein markers as early indicators of lung cancer. Plasma samples were collected from normal healthy individuals and lung cancer patients, and protein purification and analysis were conducted using LC-MS/MS. A mixed-effect model was applied to select lung cancer-related protein markers based on label-free relative quantification values. We identified 29 proteins with potential for early lung cancer diagnosis, including complement proteins (CFB, C3, C8G, C1QA, C1R, C6), orosomucoid proteins (ORM1, ORM2), ceruloplasmin (CP), alpha-1-B glycoprotein (A1BG), and others. These proteins play diverse roles in immune response, inflammation, and cell signaling, suggesting their relevance in lung cancer pathophysiology. Our findings suggest the potential of plasma proteins as early diagnostic biomarkers for lung cancer. Further validation in larger cohorts is needed to confirm their clinical utility. Integrating these biomarkers into existing diagnostic modalities could enhance early detection accuracy, leading to improved patient outcomes.

Prognostic value of myocardial redox signalling: a machine learning multi-omics approach

Abstract Background Oxidative stress has been proposed to be implicated in cardiovascular pathology. Studies have linked myocardial oxidative stress with the development of atrial fibrillation, but its role in the prediction of long-term outcomes and mortality is yet to be elucidated. Purpose To apply discovery network transcriptomics and genomics to atrial tissue (AT) obtained from patients undergoing cardiac surgery, to phenotype myocardial redox-state and identify potential therapeutic targets. Methods We included 1,032 patients undergoing cardiac surgery. Arm 1 included 258 patients in whom atrial tissue (right atrial appendage) was used for ex-vivo quantification of NOX-derived superoxide by lucigenin-enhanced chemiluminescence. Arm 2 included 414 patients in whom exploratory, unsupervised gene network analysis in human atrial tissue RNA sequencing data was performed to identify atrial tissue redox-sensitive signatures (blue signature). Arm 3 included 881 patients genotyped with the genome-wide SNP array UK Biobank Axiom Array and used for machine learning construction of GenRedOx, a SNP model built to predict the blue transcriptomic signature. Associations with future incidence of major adverse myocardial events (MAME: cardiovascular death and/or heart failure) was assessed across all arms using cox regression models (adjusted for age, sex, hypertension, dyslipidaemia, diabetes mellitus, body mass index, and plasma TNFa). Results Over a median follow-up of 5.27 years [IQR: 4.29-6.83] high atrial tissue (AT) NOX-derived superoxide was independently associated with MAME risk (Adj. HR[95%CI]: 11.7 [2.18 , 62.82], p=0.004, a). Unsupervised transcriptomic analysis in Arm 2 revealed 15 coexpressed gene ‘modules’ or 'signatures' (b). The blue signature was significantly associated with AT superoxide production with "immune response-regulating and activating signalling" being amongst the top enriched pathways. Patients with high eigengene values for the blue signature showed a 5.5-fold higher adjusted risk of MAME (c). In Arm 3, extreme gradient boosting of SNP data, trained using the blue transcriptomic signature as ground truth, revealed GenRedOx (d), a genomic artificial intelligence score, which was found to be prognostic of MAME in the validation stage (e). Homozygosity for the minor allele of SNP rs723897 in the Chemokine-Like Factor Super Family 7 (CMTM7) gene had the highest gain in the model. Conclusion We present for the first time two novel human myocardial transcriptomic and genomic signatures that reflect changes in redox state and identify long-term cardiovascular risk. Targeting pathways in the myocardium related with immune response signalling may lead to the development of novel therapeutics in cardiovascular disease.

An immune signature of postoperative cognitive decline: a prospective cohort study.

Postoperative cognitive decline (POCD) is the predominant complication affecting patients over 60 years old following major surgery, yet its prediction and prevention remain challenging. Understanding the biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This study aimed to provide a comprehensive analysis of immune cell trajectories differentiating patients with and without POCD and to derive a predictive score enabling the identification of high-risk patients during the preoperative period. Twenty-six patients aged 60 years old and older undergoing elective major orthopedic surgery were enrolled in a prospective longitudinal study, and the occurrence of POCD was assessed 7 days after surgery. Serial samples collected before surgery, and 1, 7, and 90 days after surgery were analyzed using a combined single-cell mass cytometry and plasma proteomic approach. Unsupervised clustering of the high-dimensional mass cytometry data was employed to characterize time-dependent trajectories of all major innate and adaptive immune cell frequencies and signaling responses. Sparse machine learning coupled with data-driven feature selection was applied to the presurgery immunological dataset to classify patients at risk for POCD. The analysis identified cell-type and signaling-specific immune trajectories differentiating patients with and without POCD. The most prominent trajectory features revealed early exacerbation of JAK/STAT and dampening of inhibitory κB and nuclear factor-κB immune signaling responses in patients with POCD. Further analyses integrating immunological and clinical data collected before surgery identified a preoperative predictive model comprising one plasma protein and 10 immune cell features that classified patients at risk for POCD with excellent accuracy (AUC=0.80, P =2.21e-02 U -test). Immune system-wide monitoring of patients over 60 years old undergoing surgery unveiled a peripheral immune signature of POCD. A predictive model built on immunological data collected before surgery demonstrated greater accuracy in predicting POCD compared to known clinical preoperative risk factors, offering a concise list of biomarker candidates to personalize perioperative management.

TNFα has differential effects on the transcriptome profile of selected populations in murine cartilage

ObjectiveTo further our understanding of the role of tumor necrosis factor (TNF)α on the inflammatory response in chondrocytes. DesignWe explored the effects of TNFα on the transcriptome of epiphyseal chondrocytes from newborn C57BL/6 mice at the total and single cell (sc) resolution. ResultsGene set enrichment analysis of total RNA-Seq from TNFα-treated chondrocytes revealed enhanced response to biotic stimulus, defense and immune response and cytokine signaling and suppressed cartilage and skeletal morphogenesis and development. scRNA-Seq analyzed 14,239 ​cells and 24,320 genes and distinguished 16 ​cell clusters. The more prevalent ones were constituted by limb bud and chondrogenic cells and fibroblasts comprising ∼73 ​% of the cell population. Genes expressed by joint fibroblasts were detected in 5 clusters comprising ∼45 ​% of the cells isolated. Pseudotime trajectory finding revealed an association between fibroblast and chondrogenic clusters which was not modified by TNFα. TNFα decreased the total cells recovered by 18.5 ​% and the chondrogenic, limb bud and mesenchymal clusters by 32 ​%, 27 ​% and 7 ​%, respectively. TNFα had profound effects on the insulin-like growth factor (IGF) axis decreasing Igf1, Igf2 and Igfbp4 and inducing Igfbp3 and Igfbp5, explaining an inhibition of collagen biosynthesis, cartilage and skeletal morphogenesis. Ingenuity Pathway Analysis of scRNA-Seq data revealed that TNFα enhanced the osteoarthritis, rheumatoid arthritis, pathogen induced cytokine storm and interleukin 6 signaling pathways and suppressed fibroblast growth factor signaling. ConclusionsEpiphyseal chondrocytes are constituted by diverse cell populations distinctly regulated by TNFα to promote inflammation and suppression of matrix biosynthesis and growth.

Amlexanox reduces new-onset atrial fibrillation risk in sepsis by downregulating S100A12: a Mendelian randomization study.

Sepsis is characterized by high morbidity and mortality rates, alongside limited therapeutic efficacy. Atrial fibrillation (AF), the most common arrhythmia, has been closely linked to sepsis in prior research. However, the specific mechanisms through which sepsis leads to new-onset AF remain poorly understood. This study focuses on identifying critical genes that are dysregulated in the development of new-onset AF within the context of sepsis, with the goal of uncovering new potential targets for its diagnosis and prevention. Our study began by applying Mendelian Randomization (MR) to assess the causal link between sepsis and AF. We then sourced sepsis and AF datasets from the Gene expression Omnibus (GEO) database. Using Weighted Gene Co-expression Network Analysis (WGCNA), we pinpointed key modules and genes associated with both sepsis and AF conditions. Protein-protein interaction (PPI) network was constructed. The Transcriptional Regulatory Relationships Unravelled by Sentence-based Text-mining (TRRUST) database helped build the transcription factor (TF) interaction network. Key genes were scrutinized through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to delve into their roles in new-onset AF's pathophysiology during sepsis. We employed the CIBERSORT algorithm to evaluate immune infiltration and the association between key genes and immune cells. The Connectivity Map (CMap) database facilitated the prediction of potential small molecule compounds targeting key genes. To culminate, an acute sepsis mouse model was developed to validate the implicated mechanisms of key genes involved in new-onset AF during sepsis, and to assess the prophylactic effectiveness of identified drug candidates. MR revealed potential independent risk factors for new-onset AF in sepsis. S100A12 was identified as a core interaction gene with elevated levels in sepsis and AF, underscoring its diagnostic and predictive significance. S100A12, along with associated genes, was mainly linked to immune and inflammatory response signaling pathways, correlating with immune cell levels. Targeting S100A12 identifies five potential small molecule therapeutics: amlexanox, balsalazide, methandriol, olopatadine, and tiboloe. In animal studies, acute sepsis increased S100A12 expression in serum and atrial tissues, correlating positively with inflammatory markers (IL-1β, IL-6, TNF-α) and negatively with heart rate, indicating a predisposition to AF. Early amlexanox administration can reduced S100A12 expression, dampened inflammation, and lessened new-onset AF risk in sepsis. This study demonstrates that sepsis may independently increase the risk of new-onset AF. We identified S100A12 as a key gene influencing the new-onset AF in sepsis through immune regulation, presenting considerable diagnostic and predictive value. Notably, amlexanox, by targeting S100A12 emerges as the most clinical relevant intervention for managing new-onset AF in sepsis patients.

Key role for inflammation-related signaling in the pathogenesis of myopia based on evidence from proteomics analysis

The mechanisms underlying myopia pathogenesis are not well understood. Using publicly-available human and animal datasets, we expound on the roles of known, implicated proteins, and new myopia-related signaling pathways were hypothesized. Proteins identified from human serum or ocular fluids, and from ocular tissues in myopic animal models, were uploaded and analyzed with the QIAGEN Ingenuity Pathway Analysis (IPA) software (March 2023). With each IPA database update, more potentially-relevant proteins and signaling pathways previously unavailable during data acquisition are added, allowing extraction of novel conclusions from existing data. Canonical pathway analysis was used to analyze these data and calculate an IPA activation z-score—which indicates not only whether an association is significant, but also whether the pathway is likely activated or inhibited. Cellular immune response and cytokine signaling were frequently found to be affected in both human and animal myopia studies. Analysis of two publicly-available proteomic datasets highlighted a potential role of the innate immune system and inflammation in myopia development, detailing specific signaling pathways involved such as Granzyme A (GzmA) and S100 family signaling in the retina, and activation of myofibroblast trans-differentiation in the sclera. This perspective in myopia research may facilitate development of more effective and targeted therapeutic agents.

Transcriptomic and Proteomic Insights into Host Immune Responses in Pediatric Severe Malarial Anemia: Dysregulation in HSP60-70-TLR2/4 Signaling and Altered Glutamine Metabolism.

Severe malarial anemia (SMA, Hb < 6.0 g/dL) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission zones. This study explored the entire expressed human transcriptome in whole blood from 66 Kenyan children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25), focusing on host immune response networks. RNA-seq analysis revealed 6862 differentially expressed genes, with equally distributed up-and down-regulated genes, indicating a complex host immune response. Deconvolution analyses uncovered leukocytic immune profiles indicative of a diminished antigenic response, reduced immune priming, and polarization toward cellular repair in SMA. Weighted gene co-expression network analysis revealed that immune-regulated processes are central molecular distinctions between non-SMA and SMA. A top dysregulated immune response signaling network in SMA was the HSP60-HSP70-TLR2/4 signaling pathway, indicating altered pathogen recognition, innate immune activation, stress responses, and antigen recognition. Validation with high-throughput gene expression from a separate cohort of Kenyan children (n = 50) with varying severities of malarial anemia (n = 38 non-SMA and n = 12 SMA) confirmed the RNA-seq findings. Proteomic analyses in 35 children with matched transcript and protein abundance (n = 19 non-SMA and n = 16 SMA) confirmed dysregulation in the HSP60-HSP70-TLR2/4 signaling pathway. Additionally, glutamine transporter and glutamine synthetase genes were differentially expressed, indicating altered glutamine metabolism in SMA. This comprehensive analysis underscores complex immune dysregulation and novel pathogenic features in SMA.

416 (PB404): G protein nucleolar 3 promotes cell-cycle progression and suppresses immune response signaling in castrate-resistant prostate cancer by collaborating with the androgen-receptor

416 (PB404): G protein nucleolar 3 promotes cell-cycle progression and suppresses immune response signaling in castrate-resistant prostate cancer by collaborating with the androgen-receptor