T cells and their immunometabolism: A novel way to understanding sepsis immunopathogenesis and future therapeutics

Physiologic disruption and metabolic reprogramming in infection and sepsis

Effective responses against severe systemic infection require coordination between two complementary defense strategies that minimize the negative impact of infection on the host: resistance, aimed at pathogen elimination, and disease tolerance, which limits tissue damage and preserves organ function. Resistance and disease tolerance mostly rely on divergent metabolic programs that may not operate simultaneously in time and space. Due to evolutionary reasons, the host initially prioritizes the elimination of the pathogen, leading to dominant resistance mechanisms at the potential expense of disease tolerance, which can contribute to organ failure. Here, we summarize our current understanding of the role of physiological perturbations resulting from infection in immune response dynamics and the metabolic program requirements associated with resistance and disease tolerance mechanisms. We then discuss how insight into the interplay of these mechanisms could inform future research aimed at improving sepsis outcomes and the potential for therapeutic interventions.

Decoding the potential role of regulatory T cells in sepsis-induced immunosuppression

Sepsis, a multiorgan dysfunction with high incidence and mortality, is caused by an imbalanced host-to-infection immune response. Organ-support therapy improves the early survival rate of sepsis patients. In the long term, those who survive the "cytokine storm" and its secondary damage usually show higher susceptibility to secondary infections and sepsis-induced immunosuppression, in which regulatory T cells (Tregs) are evidenced to play an essential role. However, the potential role and mechanism of Tregs in sepsis-induced immunosuppression remains elusive. In this review, we elucidate the role of different functional subpopulations of Tregs during sepsis and then review the mechanism of sepsis-induced immunosuppression from the aspects of regulatory characteristics, epigenetic modification, and immunometabolism of Tregs. Thoroughly understanding how Tregs impact the immune system during sepsis may shed light on preclinical research and help improve the translational value of sepsis immunotherapy.

Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation

Introduction

Burns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient's prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models.

Methods

We analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR.

Results

In both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury.

Conclusion

This study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated.

The clinical trajectory of peripheral blood immune cell subsets, T-cell activation, and cytokines in septic patients

OBJECTIVE AND DESIGN

Changes in the immune status of patients with sepsis may have a major impact on their prognosis. Our research focused on changes in various immune cell subsets and T-cell activation during the progression of sepsis.

METHODS AND SUBJECTS

We collected data from 188 sepsis patients at the First Affiliated Hospital of Zhejiang University School of Medicine. The main focus was on the patient's immunocyte subset typing, T-cell activation/Treg cell analysis, and cytokine assay, which can indicate the immune status of the patient.

RESULTS

The study found that the number of CD4+ T cells, CD8+ T cells, NK cells, and B cells decreased early in the disease, and the decrease in CD4+ and CD8+ T cells was more pronounced in the death group. T lymphocyte activation was inhibited, and the number of Treg cells increased as the disease progressed. T lymphocyte inhibition was more significant in the death group, and the increase in IL-10 was more significant in the death group. Finally, we used patients' baseline conditions and immunological detection indicators for modeling and found that IL-10, CD4+ Treg cells, CD3+HLA-DR+ T cells, and CD3+CD69+ T cells could predict patients' prognosis well.

CONCLUSION

Our study found that immunosuppression occurs in patients early in sepsis. Early monitoring of the patient's immune status may provide a timely warning of the disease.

A comprehensive analysis of immune features and construction of an immune gene diagnostic model for sepsis

Sepsis is a life-threatening syndrome resulting from immune system dysfunction that is caused by infection. It is of great importance to analyze the immune characteristics of sepsis, identify the key immune system related genes, and construct diagnostic models for sepsis. In this study, the sepsis transcriptome and expression profiling data were merged into an integrated dataset containing 277 sepsis samples and 117 non-sepsis control samples. Single-sample gene set enrichment analysis (ssGSEA) was used to assess the immune cell infiltration. Two sepsis immune subtypes were identified based on the 22 differential immune cells between the sepsis and the healthy control groups. Weighted gene co-expression network analysis (WCGNA) was used to identify the key module genes. Then, 36 differentially expressed immune-related genes were identified, based on which a robust diagnostic model was constructed with 11 diagnostic genes. The expression of 11 diagnostic genes was finally assessed in the training and validation datasets respectively. In this study, we provide comprehensive insight into the immune features of sepsis and establish a robust diagnostic model for sepsis. These findings may provide new strategies for the early diagnosis of sepsis in the future.

The pathogenesis and potential therapeutic targets in sepsis

Sepsis is defined as "a life-threatening organ dysfunction caused by dysregulated host systemic inflammatory and immune response to infection." At present, sepsis continues to pose a grave healthcare concern worldwide. Despite the use of supportive measures in treating traditional sepsis, such as intravenous fluids, vasoactive substances, and oxygen plus antibiotics to eradicate harmful pathogens, there is an ongoing increase in both the morbidity and mortality associated with sepsis during clinical interventions. Therefore, it is urgent to design specific pharmacologic agents for the treatment of sepsis and convert them into a novel targeted treatment strategy. Herein, we provide an overview of the molecular mechanisms that may be involved in sepsis, such as the inflammatory response, immune dysfunction, complement deactivation, mitochondrial damage, and endoplasmic reticulum stress. Additionally, we highlight important targets involved in sepsis-related regulatory mechanisms, including GSDMD, HMGB1, STING, and SQSTM1, among others. We summarize the latest advancements in potential therapeutic drugs that specifically target these signaling pathways and paramount targets, covering both preclinical studies and clinical trials. In addition, this review provides a detailed description of the crosstalk and function between signaling pathways and vital targets, which provides more opportunities for the clinical development of new treatments for sepsis.

Caveolin-1: A Review of Intracellular Functions, Tissue-Specific Roles, and Epithelial Tight Junction Regulation

Caveolin-1 (Cav1) is a vital protein for many cellular processes and is involved in both the positive and negative regulation of these processes. Cav1 exists in multiple cellular compartments depending on its role. Of particular interest is its contribution to the formation of plasma membrane invaginations called caveolae and its involvement in cytoskeletal interactions, endocytosis, and cholesterol trafficking. Cav1 participates in stem cell differentiation as well as proliferation and cell death pathways, which is implicated in tumor growth and metastasis. Additionally, Cav1 has tissue-specific functions that are adapted to the requirements of the cells within those tissues. Its role has been described in adipose, lung, pancreatic, and vascular tissue and in epithelial barrier maintenance. In both the intestinal and the blood brain barriers, Cav1 has significant interactions with junctional complexes that manage barrier integrity. Tight junctions have a close relationship with Cav1 and this relationship affects both their level of expression and their location within the cell. The ubiquitous nature of Cav1 both within the cell and within specific tissues is what makes the protein important for ongoing research as it can assist in further understanding pathophysiologic processes and can potentially be a target for therapies.

Machine learning-based identification of CYBB and FCAR as potential neutrophil extracellular trap-related treatment targets in sepsis

Objective

Sepsis related injury has gradually become the main cause of death in non-cardiac patients in intensive care units, but the underlying pathological and physiological mechanisms remain unclear. The Third International Consensus Definitions for Sepsis and Septic Shock (SEPSIS-3) definition emphasized organ dysfunction caused by infection. Neutrophil extracellular traps (NETs) can cause inflammation and have key roles in sepsis organ failure; however, the role of NETs-related genes in sepsis is unknown. Here, we sought to identify key NETs-related genes associate with sepsis.

Methods

Datasets GSE65682 and GSE145227, including data from 770 patients with sepsis and 54 healthy controls, were downloaded from the GEO database and split into training and validation sets. Differentially expressed genes (DEGs) were identified and weighted gene co-expression network analysis (WGCNA) performed. A machine learning approach was applied to identify key genes, which were used to construct functional networks. Key genes associated with diagnosis and survival of sepsis were screened out. Finally, mouse and human blood samples were collected for RT-qPCR verification and flow cytometry analysis. Multiple organs injury, apoptosis and NETs expression were measured to evaluated effects of sulforaphane (SFN).

Results

Analysis of the obtained DEGs and WGCNA screened a total of 3396 genes in 3 modules, and intersection of the results of both analyses with 69 NETs-related genes, screened out seven genes (S100A12, SLC22A4, FCAR, CYBB, PADI4, DNASE1, MMP9) using machine learning algorithms. Of these, CYBB and FCAR were independent predictors of poor survival in patients with sepsis. Administration of SFN significantly alleviated murine lung NETs expression and injury, accompanied by whole blood CYBB mRNA level.

Conclusion

CYBB and FCAR may be reliable biomarkers of survival in patients with sepsis, as well as potential targets for sepsis treatment. SFN significantly alleviated NETs-related organs injury, suggesting the therapeutic potential by targeting CYBB in the future.

Protective role of the novel cytokine Metrnl/ interleukin-41 in host immunity defense during sepsis by promoting macrophage recruitment and modulating Treg/Th17 immune cell balance

BACKGROUND

Metrnl play an immunocytokine-like role in several diseases, which is also known as meteorin-like because it is homologous to the neurotrophic factor meteorin (Metrn). Although the expression and function of Metrnl, including neurotrophic, immunomodulatory, and insulin resistance functions in different tissues have been extensively studied, its role in sepsis has remained largely limited.

METHODS

The present work analyzed the levels of Metrnl and cytokines in the circulation, such as tumor necrosis factor (TNF-α), interleukin (IL-1)β, IL-6, IL-8, together with IL-10 among septic adult patients. Clinical information was obtained from such patients, including sofa score, procalcitonin(PCT)count, and C-reactive count (CRP) within 24 h when entering the intensive care unit (ICU). We constructed a sepsis model in Metrnl-deficient or normal wild-type mice using cecal ligation and perforation to study its functions in bacterial burden, survival, cytokine/chemokine generation, peritoneal lavage fluid neutrophils, macrophage and lymphocyte recruitment, and Treg/Th17 immune cell balance after CLP-induced sepsis.

RESULTS

The expression of Metrnl was remarkably elevated in the early phase of sepsis clinically. Its serum content in patients dying of sepsis slightly decreased relative to that in survivors. Furthermore, the concentration of Metrnl in septic cases when entering the ICU independently predicted the 28-day mortality. For septic patients who had low serum Metrnl content (≤ 274.40 pg/mL), the death risk increased by 2.3 folds relative to those who had a high serum content. It is reported that Metrnl is probably insufficient among patients dying of sepsis. Additionally, the content of Metrnl in the serum of septic patients when entering the ICU is markedly and negatively related to the levels of TNF-α, IL-1β, IL-6, IL-8, IL-17, PCT, and Sofa score. Collectively, Metrnl could be a potential therapeutic target for sepsis. A low-lethality non-severe sepsis (NSS) model was constructed, which suggested that Metrnl insufficiency elevated the death rate and reduced bacterial clearance during sepsis. For Metrnl-deficient mice, impaired sepsis immunity defense might be related to decreased macrophage recruitment and Treg/Th17 lymphocyte imbalance. Recombinant Metrnl administered to Metrnl-deficient mice abolished the immunity defense impairment following NSS while protecting the high-lethality severe sepsis (SS) model in wild-type (WT) mice. In addition, Metrnl-induced sepsis prevention was intricately associated with the increased recruitment of peritoneal macrophages and modulation of the Treg/TH17 immune cell balance. Furthermore, CCL3 exposure in Metrnl-deficient mice reduced peritoneal bacterial loads while improving survival during sepsis partially by promoting the recruitment of peritoneal macrophages. Furthermore, Metrnl regulated the polarization of M1 macrophages through the ROS signaling pathway and promoted macrophage phagocytosis, thereby killing Escherichia coli.

CONCLUSIONS

The present proof-of-concept work suggests that Metrnl-mediated recruitment of macrophages significantly affects sepsis defense in the host and modulates the Treg/Th17 immune cell balance. Findings in this work shed more light on the development of host-directed treatments that can be used to manipulate host immunity to treat sepsis.

Immunometabolic reprogramming, another cancer hallmark

Molecular carcinogenesis is a multistep process that involves acquired abnormalities in key biological processes. The complexity of cancer pathogenesis is best illustrated in the six hallmarks of the cancer: (1) the development of self-sufficient growth signals, (2) the emergence of clones that are resistant to apoptosis, (3) resistance to the antigrowth signals, (4) neo-angiogenesis, (5) the invasion of normal tissue or spread to the distant organs, and (6) limitless replicative potential. It also appears that non-resolving inflammation leads to the dysregulation of immune cell metabolism and subsequent cancer progression. The present article delineates immunometabolic reprogramming as a critical hallmark of cancer by linking chronic inflammation and immunosuppression to cancer growth and metastasis. We propose that targeting tumor immunometabolic reprogramming will lead to the design of novel immunotherapeutic approaches to cancer.

Screening of potential immune-related genes expressed during sepsis using gene sequencing technology

To screen potential pivotal targets in sepsis through peripheral blood. Septic patients (n = 23) and healthy volunteers (n = 10) were enrolled according to SEPSIS 3.0. Peripheral blood was collected within 24 h of enrollment, RNA-seq was performed on the peripheral blood. The sequencing data was screened for DEGs (p < 0.01; logFC ≥ 2). PPI, WGCNA and survival curve analysis were used to identify potential targets. Then, 5 PBMC samples were conducted by single-cell sequencing for cell lineage location. Finally, mouse sepsis model and clinic samples were performed to verify the targets gene using RNA-seq and RT-PCR, respectively. Compared to the control group, 1007 DEGs were found in septic group. BCL9L, BCL11B, CD247, CD96, MAFG and SAMD3 were in the core of network. These six genes correlated to the survival rate of septic patients and they were mainly expressed in T cells, except that MAFG was located in monocyte cell. The expression levels of six key genes were confirmed by animal and clinical samples. BCL9L, BCL11B, CD247, CD96 and SAMD3 were decreased in sepsis and mainly expressed in the T cell; while MAFG increased in sepsis and localizes to monocytes. These genes may be therapeutic targets for sepsis.

Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis

BACKGROUND

Neonatal sepsis (NS), a life-threatening condition, is characterized by organ dysfunction and is the most common cause of neonatal death. However, the pathogenesis of NS is unclear and the clinical inflammatory markers currently used are not ideal for diagnosis of NS. Thus, exploring the link between immune responses in NS pathogenesis, elucidating the molecular mechanisms involved, and identifying potential therapeutic targets is of great significance in clinical practice. Herein, our study aimed to explore immune-related genes in NS and identify potential diagnostic biomarkers. Datasets for patients with NS and healthy controls were downloaded from the GEO database; GSE69686 and GSE25504 were used as the analysis and validation datasets, respectively. Differentially expressed genes (DEGs) were identified and Gene Set Enrichment Analysis (GSEA) was performed to determine their biological functions. Composition of immune cells was determined and immune-related genes (IRGs) between the two clusters were identified and their metabolic pathways were determined. Key genes with correlation coefficient > 0.5 and p < 0.05 were selected as screening biomarkers. Logistic regression models were constructed based on the selected biomarkers, and the diagnostic models were validated.

RESULTS

Fifty-two DEGs were identified, and GSEA indicated involvement in acute inflammatory response, bacterial detection, and regulation of macrophage activation. Most infiltrating immune cells, including activated CD8 + T cells, were significantly different in patients with NS compared to the healthy controls. Fifty-four IRGs were identified, and GSEA indicated involvement in immune response and macrophage activation and regulation of T cell activation. Diagnostic models of DEGs containing five genes (PROS1, TDRD9, RETN, LOC728401, and METTL7B) and IRG with one gene (NSUN7) constructed using LASSO algorithm were validated using the GPL6947 and GPL13667 subset datasets, respectively. The IRG model outperformed the DEG model. Additionally, statistical analysis suggested that risk scores may be related to gestational age and birth weight, regardless of sex.

CONCLUSIONS

We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS. Our findings provide a new perspective for future research on NS pathogenesis.

Remifentanil attenuates endoplasmic reticulum stress and inflammatory injury in LPS-induced damage in HK-2 cells

Renal injury is a fatal complication in critically ill patients with sepsis. As an ultrashort-acting synthetic opioid derivative, remifentanil has been reported to mitigate renal injury and sepsis. Nevertheless, whether remifentanil also suppresses sepsis-triggered renal injury is uncertain. The aim of this study was to investigate the effect of remifentanil on endoplasmic reticulum stress (ERS) and inflammatory response in an in vitro lipopolysaccharide (LPS)-stimulated renal tubular epithelial cell (HK-2) model and its mechanism. The viability of HK-2 cells with the absence or presence of LPS treatment was surveyed by cell counting kit-8 assay. Under the condition of LPS treatment, apoptosis was appraised by TUNEL assay and western blot. Levels of inflammatory factors were estimated though corresponding kits. Western blot tested the expression of toll-like receptor 4 (TLR4)/nuclear factor-kappaB (NF-κB) signaling-associated proteins. Also, the expression of ERS-related proteins was detected by western blot. Further, ERS inducer tunicamycin (TM) was added and the aforementioned experiments were conducted again. The results underlined the protective effects of remifentanil on LPS-evoked viability injury, inflammation, activation of TLR4/NF-κB signaling and ERS in HK-2 cells. Moreover, the impacts of remifentanil on the biological events of LPS-insulted HK-2 cells were all reversed by TM administration. To conclude, remifentanil might have a remarkable ameliorative effect on sepsis-induced renal injury, which implied the potential of remifentanil-based drug therapy in sepsis-induced renal injury.

The Impact of Curcumin on Immune Response: An Immunomodulatory Strategy to Treat Sepsis

Primary and secondary immunodeficiencies cause an alteration in the immune response which can increase the rate of infectious diseases and worsened prognoses. They can also alter the immune response, thus, making the infection even worse. Curcumin is the most biologically active component of the turmeric root and appears to be an antimicrobial agent. Curcumin cooperates with various cells such as macrophages, dendritic cells, B, T, and natural killer cells to modify the body's defence capacity. Curcumin also inhibits inflammatory responses by suppressing different metabolic pathways, reduces the production of inflammatory cytokines, and increases the expression of anti-inflammatory cytokines. Curcumin may also affect oxidative stress and the non-coding genetic material. This review analyses the relationships between immunodeficiency and the onset of infectious diseases and discusses the effects of curcumin and its derivatives on the immune response. In addition, we analyse some of the preclinical and clinical studies that support its possible use in prophylaxis or in the treatment of infectious diseases. Lastly, we examine how nanotechnologies can enhance the clinical use of curcumin.

Inflammatory pathophysiological mechanisms implicated in postpartum depression

Postpartum Depression (PPD) is a serious psychiatric disorder of women within the first year after delivery. It grievously damages women's physical and mental health. Inflammatory reaction theory is well-established in depression, and also has been reported associated with PPD. This review summarized the inflammatory pathophysiological mechanisms implicated in PPD, including decreased T cell activation, increased proinflammatory cytokines secretion, active kynurenine pathway, and initiated NLRP3 inflammasome. Clinical and preclinical research are both gathered. Potential therapeutical alternatives targeting the inflammatory mechanisms of PPD were introduced. In addition, this review briefly discussed the differences of inflammatory mechanisms between PPD and depression. The research of inflammation in PPD is limited and seems just embarking, which indicates the direction we can further study. As a variety of risky factors contribute to PPD collectively, therapy for women with PPD should be comprehensive, and clinical heterogeneity should be taken into consideration. As PPD has a predictability, early clinical screening and interventions are also needed. This review aims to help readers better understand the inflammatory pathological mechanisms in PPD, so as to identify biomarkers and potential therapeutic targets in the future.

Construction of Autophagy-Related Gene Classifier for Early Diagnosis, Prognosis and Predicting Immune Microenvironment Features in Sepsis by Machine Learning Algorithms

Background

The immune system plays a fundamental role in the pathophysiology of sepsis, and autophagy and autophagy-related molecules are crucial in innate and adaptive immune responses; however, the potential roles of autophagy-related genes (ARGs) in sepsis are not comprehensively understood.

Methods

A systematic search was conducted in ArrayExpress and Gene Expression Omnibus (GEO) cohorts from July 2005 to May 2022. Machine learning approaches, including modified Lasso penalized regression, support vector machine, and artificial neural network, were applied to identify hub ARGs, thereby developing a prediction model termed ARG classifier. Diagnostic and prognostic performance of the model was comprehensively analyzed using multi-transcriptome data. Subsequently, we systematically correlated the ARG classifier/hub ARGs with immunological characteristics of multiple aspects, including immune cell infiltration, immune and molecular pathways, cytokine levels, and immune-related genes. Further, we collected clinical specimens to preliminarily investigate ARG expression levels and to assess the diagnostic performance of ARG classifier.

Results

A total of ten GEO and three ArrayExpress datasets were included in this study. Based on machine learning algorithms, eight key ARGs (ATG4C, BAX, BIRC5, ERBB2, FKBP1B, HIF1A, NCKAP1, and NFKB1) were integrated to establish ARG classifier. The model exhibited excellent diagnostic values (AUC > 0.85) in multiple datasets and multiple points in time and superiorly distinguished sepsis from other critical illnesses. ARG classifier showed significant correlations with clinical characteristics or endotypes and performed better in predicting mortality (AUC = 0.70) than other clinical characteristics. Additionally, the identified hub ARGs were significantly associated with immune cell infiltration (B, T, NK, dendritic, T regulatory, and myeloid-derived suppressor cells), immune and molecular pathways (inflammation-promoting pathways, HLA, cytolytic activity, apoptosis, type-II IFN response, complement and coagulation cascades), levels of several cytokines (PDGFRB, IL-10, IFNG, and TNF), which indicated that ARG classifier/hub ARGs adequately reflected the immune microenvironment during sepsis. Finally, using clinical specimens, the expression levels of key ARGs in patients with sepsis were found to differ significantly from those of control patients, and ARG classifier exhibited superior diagnostic performance, compared to procalcitonin and C-reactive protein.

Conclusion

Collectively, a diagnostic and prognostic model (ARG classifier) based on eight ARGs was developed which may assist clinicians in diagnosis of sepsis and recognizing patient at high risk to guide personalized treatment. Additionally, the ARG classifier effectively reflected the immune microenvironment diversity of sepsis and may facilitate personalized counseling for specific therapy.

Micro/Nanostructured Topography on Titanium Orchestrates Dendritic Cell Adhesion and Activation via β2 Integrin-FAK Signals

Background and Purpose

In clinical application of dental implants, the functional state of dendritic cells (DCs) has been suggested to have a close relationship with the implant survival rate or speed of osseointegration. Although microscale surfaces have a stable osteogenesis property, they also incline to trigger unfavorable DCs activation and threaten the osseointegration process. Nanoscale structures have an advantage in regulating cell immune response through orchestrating cell adhesion, indicating the potential of hierarchical micro/nanostructured surface in regulation of DCs’ activation without sacrificing the advantage of microscale topography.

Materials and Methods

Two micro/nanostructures were fabricated based on microscale rough surfaces through anodization or alkali treatment, the sand-blasted and acid-etched (SA) surface served as control. The surface characteristics, in vitro and in vivo DC immune reactions and β2 integrin-FAK signal expression were systematically investigated. The DC responses to different surface topographies after FAK inhibition were also tested.

Results

Both micro/nano-modified surfaces exhibited unique composite structures, with higher hydrophilicity and lower roughness compared to the SA surface. The DCs showed relatively immature functional states with round morphologies and significantly downregulated β2 integrin-FAK levels on micro/nanostructures. Implant surfaces with micro/nano-topographies also triggered lower levels of DC inflammatory responses than SA surfaces in vivo. The inhibited FAK activation effectively reduced the differences in topography-caused DC activation and narrowed the differences in DC activation among the three groups.

Conclusion

Compared to the SA surface with solely micro-scale topography, titanium surfaces with hybrid micro/nano-topographies reduced DC inflammatory response by influencing their adhesion states. This regulatory effect was accompanied by the modulation of β2 integrin-FAK signal expression. The β2 integrin-FAK-mediated adhesion plays a critical role in topography-induced DC activation, which represents a potential target for material–cell interaction regulation.

The effect of age on the clinical characteristics and innate immune cell function in the patients with abdominal sepsis

Sepsis is a life-threatening dysregulated host response to infection that compromises organ health, and abdominal sepsis is a commonly presenting critical illness in intensive care units (ICU). In this study, we investigate the effect of age on clinical sepsis characteristics and innate immune cells (neutrophils and monocytes) functionality in abdominal sepsis patients. We recruited 32 patients with abdominal sepsis from the Beijing Ditan Hospital’s ICU from February 2021 to September 2021, and selected 18 healthy volunteers that were age- and sex-matched as controls for a prospective cohort study. Elderly abdominal sepsis patients (age >65 years) had the following altered characteristics compared to nonelderly patient controls: lower mean arterial pressure, monocytes percentage, and red blood cell volume distribution width (p < 0.05); higher neutrophils percentage and neutrophils-to-lymphocytes ratio (p < 0.05); significantly increased monocyte-produced reactive oxygen (p < 0.05); increases neutrophilic secretion of TNF-α, as well as lower monocytic secretion of TNF-α (p < 0.05); higher neutrophil percentage (which was significantly higher in peripheral blood than monocyte percentage). Elderly patients also had significantly increased phagocytic activity in their neutrophils and monocytes (p < 0.05), significantly reduced neutrophils-produced reactive oxygen (p < 0.001), and significantly increased TNF-α secretion by monocytes and neutrophils (p < 0.05). We found that elderly patients have decreased immune cell function and increased release of cytokines compared to younger patients, suggesting individualized treatment plans targeting the elderly septic microenvironment could help prevent organ failure in elderly septic patients and improves patient survival.

Assessment of serum interleukin-28 as a biomarker to predict mortality in traumatic patients with sepsis

BACKGROUND

Serious trauma due to various factors is a major global public issue, and sepsis is a major cause of trauma-associated mortality. Timely diagnosis and suitable treatment of post-traumatic sepsis are crucial to improve the hospital outcome of traumatic patients. IL-28 is a newly discovered member of IFN-λ family with multiple functions in inflammatory response. To date, its role in the pathogenic mechanisms of post-traumatic sepsis still remains unknown.

METHODS

In total, 20 healthy controls, 55 traumatic patients without sepsis and 54 traumatic patients with sepsis were enrolled in this study. Serum IL-28A/B levels were investigated by ELISA.

RESULTS

IL-28A/B levels were significantly increased in traumatic patients compared to healthy volunteers. Moreover, septic trauma patients displayed a significant increase in IL-28A/B levels compared with non-septic patients. In septic patients, IL-28A/B were negatively correlated with IFN-γ, IL-5, IL-13 and IL-17, and positively associated with IL-10. Moreover, IL-28A (AUC: 0.821, 95 %CI: 0.693-0.949) and IL-28B (AUC: 0.811, 95 %CI: 0.691-0.931) were both beneficial to predict increased mortality risk in septic trauma patients, though there was no statistical difference in the predictive value between them.

CONCLUSIONS

Early serum levels of IL-28A/B were associated with the development of post-trauma sepsis and could be applied to assess the outcome of traumatic patients with sepsis. Thus, IL-28 may be a potential indicator for post-traumatic sepsis.

Inhibition of endoplasmic reticulum stress and the downstream pathways protects CD4+ T cells against apoptosis and immune dysregulation in sepsis

BACKGROUND

Immunosuppression mediated by CD4⁺ T cell apoptosis and dysfunction is a key factor in promoting the progression of sepsis. Endoplasmic reticulum (ER) stress participates in the apoptosis and dysfunction of immune cells.

AIM

We aimed to investigate the role of ER stress inhibition in CD4⁺ T cells in both in vitro and in vivo models of sepsis.

METHODS

In vitro model of sepsis was established with lipopolysaccharide (LPS) and the rat model of sepsis was established using cecal ligation and puncture (CLP). After the LPS treatment or CLP, ER stress inhibitors including 4-PBA, SNJ-1945, and SP600125 were used to treat cells or rats, and the CD4⁺ T cells were obtained by magnetic bead sorting. The effects of ER stress inhibitors on apoptosis and the function of CD4⁺ T cells were evaluated.

RESULTS

After the LPS stimulation or CLP, the levels of ER stress and downstream markers (PERK, eIF2α, IRE-1α, ATF6, ATF4, XBP-1s, GRP78, CHOP, and p-JNK) were increased in CD4⁺ T cells at the beginning of sepsis. Meanwhile, the number of apoptotic CD4⁺ T cells markedly increased. In addition, sepsis impaired the function of CD4⁺ T cells, manifested by the increased population of Th1, Th2, Th17, and Treg, as well as the production of TNF-α, interleukin (IL)-6, IL-4, and IL-10. However, inhibitors of ER stress, JNK, and calpain all decreased the induction of Th1 and Th17, enhanced the increase of Th2 and Treg, decreased the production of TNF-α and IL-6, and enhanced the production of IL-4 and IL-10.

CONCLUSION

Our findings indicate that ER stress inhibitors may play a protective role by reducing CD4⁺ T cell apoptosis and maintaining CD4⁺ T cell function, which may be useful for enhancing the immune function and poor prognosis of patients with sepsis.

Macrophage Polarization and Reprogramming in Acute Inflammation: A Redox Perspective

Macrophage polarization refers to the process by which macrophages can produce two distinct functional phenotypes: M1 or M2. The balance between both strongly affects the progression of inflammatory disorders. Here, we review how redox signals regulate macrophage polarization and reprogramming during acute inflammation. In M1, macrophages augment NADPH oxidase isoform 2 (NOX2), inducible nitric oxide synthase (iNOS), synaptotagmin-binding cytoplasmic RNA interacting protein (SYNCRIP), and tumor necrosis factor receptor-associated factor 6 increase oxygen and nitrogen reactive species, which triggers inflammatory response, phagocytosis, and cytotoxicity. In M2, macrophages down-regulate NOX2, iNOS, SYNCRIP, and/or up-regulate arginase and superoxide dismutase type 1, counteract oxidative and nitrosative stress, and favor anti-inflammatory and tissue repair responses. M1 and M2 macrophages exhibit different metabolic profiles, which are tightly regulated by redox mechanisms. Oxidative and nitrosative stress sustain the M1 phenotype by activating glycolysis and lipid biosynthesis, but by inhibiting tricarboxylic acid cycle and oxidative phosphorylation. This metabolic profile is reversed in M2 macrophages because of changes in the redox state. Therefore, new therapies based on redox mechanisms have emerged to treat acute inflammation with positive results, which highlights the relevance of redox signaling as a master regulator of macrophage reprogramming.

Role of Caveolin-1 in Sepsis – A Mini-Review

Sepsis is a generalized disease characterized by an extreme response to a severe infection. Moreover, challenges remain in the diagnosis, treatment and management of septic patients. In this mini-review we demonstrate developments on cellular pathogenesis and the role of Caveolin-1 (Cav-1) in sepsis. Studies have shown that Cav-1 has a significant role in sepsis through the regulation of membrane traffic and intracellular signaling pathways. In addition, activation of apoptosis/autophagy is considered relevant for the progression and development of sepsis. However, how Cav-1 is involved in sepsis remains unclear, and the precise mechanisms need to be further investigated. Finally, the role of Cav-1 in altering cell permeability during inflammation, in sepsis caused by microorganisms, apoptosis/autophagy activation and new therapies under study are discussed in this mini-review.

Th17/Regulatory T-Cell Imbalance and Acute Kidney Injury in Patients with Sepsis

To analyze the predictive value of the Th17/Treg ratio for renal injury in sepsis patients, a prospective observational study was conducted. Adult patients with sepsis were enrolled and divided into a sepsis-induced acute kidney injury (SAKI) group and a sepsis-without-AKI group. Logistic regression was used to analyze the independent predictors of SAKI, and the ROC curve was plotted to evaluate the predictive value of the Th17/Treg ratio for renal injury in patients with sepsis. A total of 124 patients were enrolled in this study, including 60 cases (48.39%) of SAKI. Patients who developed sepsis-induced acute kidney injury had a higher Th17/Treg ratio level compared to patients without it (0.11 [0.07, 0.28] versus 0.06 [0.05, 0.16], p < 0.05, respectively. The area under the receiver operating characteristic curve of the Th17/Treg ratio to predict sepsis-induced acute kidney injury was 0.669 (95% CI 0.574−0.763, p < 0.05). The Th17/Treg ratio was associated with SAKI (OR 1.15, 95%CI [1.06−1.24], p < 0.05, non-adjusted and R 1.12, 95%CI [1.00−1.25], p < 0.05, adjusted). The use of the Th17/Treg ratio improved the prediction performance of the prediction model of NAGL. The median Th17/Treg ratio significantly increased with the stratified KDIGO stage (p < 0.05). Th17/Treg imbalance was associated with occurrence of acute kidney injury and AKI severity in patients with sepsis. The Th17/Treg ratio could be a potential predictive marker of sepsis-induced acute kidney injury.

Dichloroacetate improves systemic energy balance and feeding behavior during sepsis

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to an infection. The metabolic aberrations associated with sepsis underly an acute and organism-wide hyperinflammatory response and multiple organ dysfunction; however, crosstalk between systemic metabolomic alterations and metabolic reprogramming at organ levels remains unknown. We analyzed substrate utilization by the respiratory exchange ratio, energy expenditure, metabolomic screening, and transcriptional profiling in a cecal ligation and puncture model to show that sepsis increases circulating free fatty acids and acylcarnitines but decreases levels of amino acids and carbohydrates, leading to a drastic shift in systemic fuel preference. Comparative analysis of previously published metabolomics from septic liver indicated a positive correlation with hepatic and plasma metabolites during sepsis. In particular, glycine deficiency was a common abnormality of the plasma and liver during sepsis. Interrogation of the hepatic transcriptome in septic mice suggested that the septic liver may contribute to systemic glycine deficiency by downregulating genes involved in glycine synthesis. Interestingly, intraperitoneal injection of the pyruvate dehydrogenase kinase (PDK) inhibitor dichloroacetate reversed sepsis-induced anorexia, energy imbalance, inflammation, dyslipidemia, hypoglycemia, and glycine deficiency. Collectively, our data indicated that PDK inhibition rescued systemic energy imbalance and metabolic dysfunction in sepsis partly through restoration of hepatic fuel metabolism.

LNCRNA XIST Inhibits miR-377-3p to Hinder Th17 Cell Differentiation through Upregulating ETS1

Background

Th17 cell differentiation is involved in the development and progression of many diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Present study mainly focused on the role of LINC-XIST in Th17 cell differentiation.

Methods

The naïve CD4+ T cells were isolated from human whole blood. Cells were cultured under Th17 cell-polarizing condition for 6 days. The expression of LINC-XIST and miR-153-3p was measured by qPCR. The relationship between LINC-XIST, miR-153-3p, and ETS1 was predicted by TargetScan website and authenticated by luciferase reporter assay. ELISA assays were conducted to evaluate the IL-17 concentration. Western blot was utilized to measure the protein expression of ETS1. Th17 cell frequency was examined by flow cytometry.

Results

The expression of XIST markedly decreased and miR-153-3p expression markedly increased with Th17 cell differentiation. The mRNA expression of IL-17, IL-17 concentration, and Th17 cell frequency were observably decreased in overexpressed LINC-XIST group. Luciferase reporter assay authenticated that miR-153-5p was directly regulated by LINC-XIST. miR-153-3p inhibitor observably decreased IL-17 concentration, mRNA expression of IL-17, and Th17 cell frequency while si-XIST reversed this impact. ETS1 was confirmed to be regulated by miR-153-5p via luciferase reporter assay. In addition, ETS1 markedly decreased IL-17 mRNA expression, IL-17 concentration, and Th17 cell frequency while miR-153-5p mimic reversed this impact.

Conclusion

LNCRNA XIST inhibited miR-377-3p to hinder Th17 cell differentiation through upregulating ETS1.

Construction of an HLA Classifier for Early Diagnosis, Prognosis, and Recognition of Immunosuppression in Sepsis by Multiple Transcriptome Datasets

Background: Sepsis is a clinical syndrome, due to a dysregulated inflammatory response to infection. Accumulating evidence shows that human leukocyte antigen (HLA) genes play a key role in the immune responses to sepsis. Nevertheless, the effects of HLA genes in sepsis have still not been comprehensively understood.

Methods: A systematical search was performed in the Gene Expression Omnibus (GEO) and ArrayExpress databases from inception to 10 September 2021. Random forest (RF) and modified Lasso penalized regression were conducted to identify hub genes in multi-transcriptome data, thus we constructed a prediction model, namely the HLA classifier. ArrayExpress databases, as external validation, were utilized to evaluate its diagnostic, prognostic, and predictive performance. Immune cell infiltration score was calculated via CIBERSORTx tools and single-sample gene set enrichment analysis (ssGSEA). Gene set variation analysis (GSVA) and ssGSEA were conducted to determine the pathways that are significantly enriched in different subgroups. Next, we systematically correlated the HLA classifier with immunological characteristics from multiple perspectives, such as immune-related cell infiltration, pivotal molecular pathways, and cytokine expression. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression level of HLA genes in clinical samples.

Results: A total of nine datasets comprising 1,251 patients were included. Based on RF and modified Lasso penalized regression in multi-transcriptome datasets, five HLA genes (B2M, HLA-DQA1, HLA-DPA1, TAP1, and TAP2) were identified as hub genes, which were used to construct an HLA classifier. In the discovery cohort, the HLA classifier exhibited superior diagnostic value (AUC = 0.997) and performed better in predicting mortality (AUC = 0.716) than clinical characteristics or endotypes. Encouragingly, similar results were observed in the ArrayExpress databases. In the E-MTAB-7581 dataset, the use of hydrocortisone in the HLA high-risk subgroup (OR: 2.84, 95% CI 1.07–7.57, p = 0.037) was associated with increased risk of mortality, but not in the HLA low-risk subgroup. Additionally, immune infiltration analysis by CIBERSORTx and ssGSEA revealed that B cells, activated dendritic cells, NK cells, T helper cells, and infiltrating lymphocytes (ILs) were significantly richer in HLA low-risk phenotypes, while Tregs and myeloid-derived suppressor cells (MDSCs) were more abundant in HLA high-risk phenotypes. The HLA classifier was significantly negatively correlated with B cells, activated dendritic cells, NK cells, T helper cells, and ILs, yet was significantly positively correlated with Tregs and MDSCs. Subsequently, molecular pathways analysis uncovered that cytokine-cytokine receptor (CCR) interaction, human leukocyte antigen (HLA), and antigen-presenting cell (APC) co-stimulation were significantly enriched in HLA low-risk endotypes, which was significantly negatively correlated with the HLA classifier in multi-transcriptome data. Finally, the expression levels of several cytokines (IL-10, IFNG, TNF) were significantly different between the HLA subgroups, and the ratio of IL-10/TNF was significantly positively correlated with HLA score in multi-transcriptome data. Results of qRT-PCR validated the higher expression level of B2M as well as lower expression level of HLA-DQA1, HLA-DPA1, TAP1, and TAP2 in sepsis samples compared to control sample.

Conclusion: Based on five HLA genes, a diagnostic and prognostic model, namely the HLA classifier, was established, which is closely correlated with responses to hydrocortisone and immunosuppression status and might facilitate personalized counseling for specific therapy.

Coronavirus disease 2019 (COVID-19) update: From metabolic reprogramming to immunometabolism

The field of immunometabolism investigates and describes the effects of metabolic rewiring in immune cells throughout activation and the fates of these cells. Recently, it has been appreciated that immunometabolism plays an essential role in the progression of viral infections, cancer, and autoimmune diseases. Regarding COVID‐19, the aberrant immune response underlying the progression of diseases establishes two major respiratory pathologies, including acute respiratory distress syndrome (ARDS) or pneumonia‐induced acute lung injury (ALI). Both innate and adaptive immunity (T cell‐based) were impaired in the course of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. Current findings have deciphered that macrophages (innate immune cells) are involved in the inflammatory response seen in COVID‐19. It has been demonstrated that immune system cells can change metabolic reprogramming in some conditions, including autoimmune diseases, cancer, and infectious disease, including COVID‐19. The growing findings on metabolic reprogramming in COVID‐19 allow an exploration of metabolites with immunomodulatory properties as future therapies to combat this hyperinflammatory response. The elucidation of the exact role and mechanism underlying this metabolic reprograming in immune cells could help apply more precise approaches to initial diagnosis, prognosis, and in‐hospital therapy. This report discusses the latest findings from COVID‐19 on host metabolic reprogramming and immunometabolic responses.

Identification of Immune-Related Genes Concurrently Involved in Critical Illnesses Across Different Etiologies: A Data-Driven Analysis

Severe trauma and sepsis can lead to multiple organ dysfunction syndrome, which is a leading cause of death in intensive care units with mortality rates in excess of 50%. In addition to infection, the degree of immuno-inflammatory response also influences the outcome. The genomic changes observed after a variety of pathophysiological insults, such as trauma, sepsis, burns are similar, and consist of innate immune activation and adaptive immunity suppression. However, the characteristics of the shared mechanisms of aforementioned critical illnesses and the clinical relevance remain less explored. In the present study, we performed a data analysis to identify functional genes concurrently involved in critical illnesses across differing etiologies (trauma and sepsis derived from community-acquired pneumonia/abdominal source) and explored the shared signaling pathways these common genes involved in to gain insight into the underlying molecular mechanisms. A number of immune-related biological functions were found to be dysregulated in both trauma and sepsis in the present study, so we continued to identify immune-related common genes, profiled the immune cell proportion, and explored the relationships between them. The diagnostic and prognostic value of the immune-related common genes was also evaluated to address their potential clinical utilization as novel biomarkers. Notably, we identified a list of 14 immune-related genes concurrently dysregulated in trauma and sepsis showing favorable diagnostic value, among which S100P can predict prognosis of sepsis patients. Moreover, a spectrum of immune cell subsets including naïve B cells, CD8+ T cells, CD4+ memory resting T cells, activated NK cells, resting dendritic cells, plasma cells, Tregs, macrophages M0 and macrophages M1 was found to be concurrently dysregulated in both trauma and sepsis, and a close relation between above identified immune-related genes and immune cell subsets was observed. Our data-driven findings lay a foundation for future research to elucidate the pathophysiology regarding the aspect of inflammatory and immune response in critical illnesses, and suggest future studies focus on interpreting the function roles of the identified immune-related genes, as well as the reactive immune cell subsets.

Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in Children

Objective

The pathogenesis of sepsis is still unclear due to its complexity, especially in children. This study aimed to analyse the immune microenvironment and regulatory networks related to sepsis in children at the molecular level and to identify key immune-related genes to provide a new basis for the early diagnosis of sepsis.

Methods

The GSE145227 and GSE26440 datasets were downloaded from the Gene Expression Omnibus. The analyses included differentially expressed genes (DEGs), functional enrichment, immune cell infiltration, the competing endogenous RNA (ceRNA) interaction network, weighted gene coexpression network analysis (WGCNA), protein–protein interaction (PPI) network, key gene screening, correlation of sepsis molecular subtypes/immune infiltration with key gene expression, the diagnostic capabilities of key genes, and networks describing the interaction of key genes with transcription factors and small-molecule compounds. Finally, real-time quantitative PCR (RT–qPCR) was performed to verify the expression of key genes.

Results

A total of 236 immune-related DEGs, most of which were enriched in immune-related biological functions, were found. Further analysis of immune cell infiltration showed that M0 macrophages and neutrophils infiltrated more in the sepsis group, while fewer activated memory CD4⁺ T cells, resting memory CD4⁺ T cells, and CD8⁺ T cells did. The interaction network of ceRNA was successfully constructed. Six key genes (FYN, FBL, ATM, WDR75, FOXO1 and ITK) were identified by WGCNA and PPI analysis. We found strong associations between key genes and constructed septic molecular subtypes or immune cell infiltration. Receiver operating characteristic analysis showed that the area under the curve values of the key genes for diagnosis were all greater than 0.84. Subsequently, we successfully constructed an interaction network of key genes and transcription factors/small-molecule compounds. Finally, the key genes in the samples were verified by RT–qPCR.

Conclusion

Our results offer new insights into the pathogenesis of sepsis in children and provide new potential diagnostic biomarkers for the disease.

Characterization of immune-related genes andimmune infiltration features for early diagnosis, prognosis and recognition of immunosuppression in sepsis

Among the body systems, the immune system plays a fundamental role in the pathophysiology of sepsis. The effects of immunogenomic and immune cell infiltration in sepsis were still not been systematically understood. Based on modified Lasso penalized regression and RF, 8 DEIRGs (ADM, CX3CR1, DEFA4, HLA-DPA1, MAPK14, ORM1, RETN, and SLPI) were combined to construct an IRG classifier. In the discovery cohort, IRG classifier exhibited superior diagnostic efficacy and performed better in predicting mortality than clinical characteristics or MARS/SRS endotypes. Encouragingly, similar results were observed in the ArrayExpress databases. The use of hydrocortisone in IRG high-risk subgroup was associated with increased risk of mortality. In IRG low-risk phenotypes, NK cells, T helper cells, and infiltrating lymphocyte (IL) are significantly richer, while T cells regulatory (Tregs) and myeloid-derived suppressor cells (MDSC) are more abundant in IRG high-risk phenotypes. IRG score were significantly negatively correlated with Cytokine cytokine receptor interaction (CCR) and human leukocyte antigen (HLA). Between the IRG subgroups, the expression levels of several cytokines (IL-10, IFNG, TNF) were significantly different, and IRG score was significantly positively correlated with ratio of IL-10/TNF. Results of qRT-PCR validated that higher expression level of ADM, DEFA4, MAPK14, ORM1, RETN, and SLPI as well as lower expression level of CX3CR1 and HLA-DPA1 in sepsis samples compared to control sample. A diagnostic and prognostic model, namely IRG classifier, was established based on 8 IRGs that is closely correlated with responses to hydrocortisone and immunosuppression status and might facilitate personalized counseling for specific therapy.

Immunometabolism at the service of traditional Chinese medicine

To enhance therapeutic efficacy and reduce adverse effects, ancient practitioners of traditional Chinese medicine (TCM) prescribe combinations of plant species/animal species and minerals designated "TCM formulae" developed based on TCM theory and clinical experience. TCM formulae have been shown to exert curative effects on complex diseases via immune regulation but the underlying mechanisms remain unknown at present. Considerable progress in the field of immunometabolism, referring to alterations in the intracellular metabolism of immune cells that regulate their function, has been made over the past decade. The core context of immunometabolism is regulation of the allocation of metabolic resources supporting host defense and survival, which provides a critical additional dimension and emerging insights into how the immune system and metabolism influence each other during disease progression. This review summarizes research findings on the significant association between the immune function and metabolic remodeling in health and disease as well as the therapeutic modulatory effects of TCM formulae on immunometabolism. Progressive elucidation of the immunometabolic mechanisms involved during the course of TCM treatment continues to aid in the identification of novel potential targets against pathogenicity. In this report, we have provided a comprehensive overview of the benefits of TCM based on regulation of immunometabolism that are potentially applicable for the treatment of modern diseases.

Detecting Critical Functional Ingredients Group and Mechanism of Xuebijing Injection in Treating Sepsis

Sepsis is a systemic inflammatory reaction caused by various infectious or noninfectious factors, which can lead to shock, multiple organ dysfunction syndrome, and death. It is one of the common complications and a main cause of death in critically ill patients. At present, the treatments of sepsis are mainly focused on the controlling of inflammatory response and reduction of various organ function damage, including anti-infection, hormones, mechanical ventilation, nutritional support, and traditional Chinese medicine (TCM). Among them, Xuebijing injection (XBJI) is an important derivative of TCM, which is widely used in clinical research. However, the molecular mechanism of XBJI on sepsis is still not clear. The mechanism of treatment of "bacteria, poison and inflammation" and the effects of multi-ingredient, multi-target, and multi-pathway have still not been clarified. For solving this issue, we designed a new systems pharmacology strategy which combines target genes of XBJI and the pathogenetic genes of sepsis to construct functional response space (FRS). The key response proteins in the FRS were determined by using a novel node importance calculation method and were condensed by a dynamic programming strategy to conduct the critical functional ingredients group (CFIG). The results showed that enriched pathways of key response proteins selected from FRS could cover 95.83% of the enriched pathways of reference targets, which were defined as the intersections of ingredient targets and pathogenetic genes. The targets of the optimized CFIG with 60 ingredients could be enriched into 182 pathways which covered 81.58% of 152 pathways of 1,606 pathogenetic genes. The prediction of CFIG targets showed that the CFIG of XBJI could affect sepsis synergistically through genes such as TAK1, TNF-α, IL-1β, and MEK1 in the pathways of MAPK, NF-κB, PI3K-AKT, Toll-like receptor, and tumor necrosis factor signaling. Finally, the effects of apigenin, baicalein, and luteolin were evaluated by in vitro experiments and were proved to be effective in reducing the production of intracellular reactive oxygen species in lipopolysaccharide-stimulated RAW264.7 cells, significantly. These results indicate that the novel integrative model can promote reliability and accuracy on depicting the CFIGs in XBJI and figure out a methodological coordinate for simplicity, mechanism analysis, and secondary development of formulas in TCM.

Antiviral Therapy with Entecavir following Antituberculosis Therapy Alleviates Liver Injury and Restores Innate Immunity in Tuberculosis Patients Coinfected with Hepatitis B Virus

Objective

Coinfection of tuberculosis (TB) and viral hepatitis may increase the risk of antituberculosis treatment-induced hepatotoxicity, which is regarded as a common cause of termination of the first-line antituberculosis drugs. The study aimed at investigating the protective effects of antiviral therapy on the liver and innate immunity in patients with TB-HBV coinfection.

Methods

A total of 100 patients with TB-HBV coinfection were recruited and split into antituberculosis and antiviral groups, 50 per group, according to odd or even date of hospital admission from December 2019 to October 2020. The patients in the anti-TB group received antituberculosis therapy, and those in the antiviral group received antiviral therapy. The clinical effectiveness; HBV-DNA negative conversion rate; liver function assessment involving alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBIL); immune function evaluation including CD4⁺, CD8⁺, CD4⁺/CD8⁺, and CD3⁺ T cells; inflammatory cytokines containing tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interferon-γ (IFN-γ); and intestinal microflora including bifidobacterium, lactobacillus, enterobacterium, enterococcus, and clostridium were main outcome measures after treatment.

Results

It was found that the total response rate in the antiviral group was significantly higher than the anti-TB group after treatment (χ ² = 3.157, P=0.017). There was a significant difference in HBV-DNA negative conversion rates between the antiviral group and anti-TB group (82% vs. 58%, χ ² = 6.384, P=0.001). The ALT, AST, and TBIL in the two groups were all increased after treatment (P < 0.05), but the antiviral group indicated a rise of the above indices compared to the anti-TB group (P < 0.05). The two groups showed a rise on the concentration of CD3⁺, CD4⁺, and CD4⁺/CD8⁺ T cells and a decline on the CD8⁺ T cells after treatment (P < 0.05), but these changes in the antiviral group were more evident to those in the anti-TB group (P < 0.05). There was an increase on the IFN-γ level and decrease on the TNF-α and IL-6 levels in both groups after treatment (P < 0.05), but the antiviral group revealed a higher level of IFN-γ with lower levels of TNF-α and IL-6 compared to the anti-TB group (P < 0.05). After treatment, the number of bifidobacteria and lactobacilli was increased, and the number of enterobacteria, enterococci, and clostridium were decreased in the two groups (P < 0.05), while these changes in the antiviral group were more remarkable compared to the anti-TB group (P < 0.05). There was no significant difference in the incidence of adverse reactions between the two groups (χ2 = 0.267, P=0.731).

Conclusion

Antiviral therapy for tuberculosis-HBV coinfected patients could inhibit HBV replication, providing protection against liver damage, improving innate immunity, and balancing intestinal microflora.

Harnessing Metabolic Reprogramming to Improve Cancer Immunotherapy

Immune escape is one of the hallmarks of cancer. While metabolic reprogramming provides survival advantage to tumor cancer cells, accumulating data also suggest such metabolic rewiring directly affects the activation, differentiation and function of immune cells, particularly in the tumor microenvironment. Understanding how metabolic reprogramming affects both tumor and immune cells, as well as their interplay, is therefore critical to better modulate tumor immune microenvironment in the era of cancer immunotherapy. In this review, we discuss alterations in several essential metabolic pathways in both tumor and key immune cells, provide evidence on their dynamic interaction, and propose innovative strategies to improve cancer immunotherapy via the modulation of metabolic pathways.

Toll-Like Receptors in Adaptive Immunity

The immune (innate and adaptive) system has evolved to protect the host from any danger present in the surrounding outer environment (microbes and associated MAMPs or PAMPs, xenobiotics, and allergens) and dangers originated within the host called danger or damage-associated molecular patterns (DAMPs) and recognizing and clearing the cells dying due to apoptosis. It also helps to lower the tissue damage during trauma and initiates the healing process. The pattern recognition receptors (PRRs) play a crucial role in recognizing different PAMPs or MAMPs and DAMPs to initiate the pro-inflammatory immune response to clear them. Toll-like receptors (TLRs) are first recognized PRRs and their discovery proved milestone in the field of immunology as it filled the gap between the first recognition of the pathogen by the immune system and the initiation of the appropriate immune response required to clear the infection by innate immune cells (macrophages, neutrophils, dendritic cells or DCs, and mast cells). However, in addition to their expression by innate immune cells and controlling their function, TLRs are also expressed by adaptive immune cells. We have identified 10 TLRs (TLR1-TLR10) in humans and 12 TLRs (TLR1-TLR13) in laboratory mice till date as TLR10 in mice is present only as a defective pseudogene. The present chapter starts with the introduction of innate immunity, timing of TLR evolution, and the evolution of adaptive immune system and its receptors (T cell receptors or TCRs and B cell receptors or BCRs). The next section describes the role of TLRs in the innate immune function and signaling involved in the generation of inflammation. The subsequent sections describe the expression and function of different TLRs in murine and human adaptive immune cells (B cells and different types of T cells, including CD4⁺T cells, CD8⁺T cells, CD4⁺CD25⁺T_regs, and CD8⁺CD25⁺T_regs, etc.). The modulation of TLRs expressed on T and B cells has a great potential to develop different vaccine candidates, adjuvants, immunotherapies to target various microbial infections, including current COVID-19 pandemic, cancers, and autoimmune and autoinflammatory diseases.

Proteomics reveals disturbances in the immune response and energy metabolism of monocytes from patients with septic shock

Sepsis results from a dyshomeostatic response to infection, which may lead to hyper or hypoimmune states. Monocytes are central regulators of the inflammatory response, but our understanding of their role in the genesis and resolution of sepsis is still limited. Here, we report a comprehensive exploration of monocyte molecular responses in a cohort of patients with septic shock via proteomic profiling. The acute stage of septic shock was associated with an impaired inflammatory phenotype, indicated by the down-regulation of MHC class II molecules and proinflammatory cytokine pathways. Simultaneously, there was an up-regulation of glycolysis enzymes and a decrease in proteins related to the citric acid cycle and oxidative phosphorylation. On the other hand, the restoration of immunocompetence was the hallmark of recovering patients, in which an upregulation of interferon signaling pathways was a notable feature. Our results provide insights into the immunopathology of sepsis and propose that, pending future studies, immunometabolism pathway components could serve as therapeutic targets in septic patients.

All-trans-retinoic acid restores CD4+ T cell response after sepsis by inhibiting the expansion and activation of myeloid-derived suppressor cells

BACKGROUND

Patients are susceptible to immunosuppression in late-stage of sepsis, in which myeloid-derived suppressor cells (MDSCs) is an important contributor. This study aims to investigate whether all-trans-retinoic acid (ATRA), which has been proved to inhibit MDSCs generation in cancer, will ameliorate sepsis-induced immuno-suppression through modulating MDSCs.

METHODS

A clinically relevant "two-hit'' model of sepsis, the cecal ligation and puncture (CLP) model and secondary pneumonia model, were established in mice. The effects of ATRA on the mortality, the bacterial burden, the expansion and activity of CLP-induced MDSCs, as well as the function of CD4+ T cells were evaluated.

RESULTS

In CLP model, ATRA was found to reduce frequency of MDSCs in spleen of mice and inhibit activity of MDSCs by regulating the generation and activity of arginase-1 and iNOS, and the secretion of immune-supressive cytokines. ATRA administration eventually reduced mortality of secondary infection by Legionella pneumophila in CLP-surviving mice, which might be associated with the restoration of CD4+ T cells proliferating and secreting activity.

CONCLUSION

ATRA can restore CD4+ T cells dysfunction in sepsis by modulating the expansion and function of MDSCs and therefore provides a potential therapy that targets the immunosuppressive state of sepsis.

Innate Lymphoid Cells and Adaptive Immune Cells Cross-Talk: A Secret Talk Revealed in Immune Homeostasis and Different Inflammatory Conditions

The inflammatory immune response has evolved to protect the host from different pathogens, allergens, and endogenous death or damage-associated molecular patterns. Both innate and adaptive immune components are crucial in inducing an inflammatory immune response depending on the stimulus type and its duration of exposure or the activation of the primary innate immune response. As the source of inflammation is removed, the aggravated immune response comes to its homeostatic level. However, the failure of the inflammatory immune response to subside to its normal level generates chronic inflammatory conditions, including autoimmune diseases and cancer. Innate lymphoid cells (ILCs) are newly discovered innate immune cells, which are present in abundance at mucosal surfaces, including lungs, gastrointestinal tract, and reproductive tract. Also, they are present in peripheral blood circulation, skin, and lymph nodes. They play a crucial role in generating the pro-inflammatory immune response during diverse conditions. On the other hand, adaptive immune cells, including different types of T and B cells are major players in the pathogenesis of autoimmune diseases (type 1 diabetes mellitus, rheumatoid arthritis, psoriasis, and systemic lupus erythematosus, etc.) and cancers. Thus the article is designed to discuss the immunological role of different ILCs and their interaction with adaptive immune cells in maintaining the immune homeostasis, and during inflammatory autoimmune diseases along with other inflammatory conditions (excluding pathogen-induced inflammation), including cancer, graft-versus-host diseases, and human pregnancy.

The Trinity of cGAS, TLR9, and ALRs Guardians of the Cellular Galaxy Against Host-Derived Self-DNA

The immune system has evolved to protect the host from the pathogens and allergens surrounding their environment. The immune system develops in such a way to recognize self and non-self and develops self-tolerance against self-proteins, nucleic acids, and other larger molecules. However, the broken immunological self-tolerance leads to the development of autoimmune or autoinflammatory diseases. Pattern-recognition receptors (PRRs) are expressed by immunological cells on their cell membrane and in the cytosol. Different Toll-like receptors (TLRs), Nod-like receptors (NLRs) and absent in melanoma-2 (AIM-2)-like receptors (ALRs) forming inflammasomes in the cytosol, RIG (retinoic acid-inducible gene)-1-like receptors (RLRs), and C-type lectin receptors (CLRs) are some of the PRRs. The DNA-sensing receptor cyclic GMP–AMP synthase (cGAS) is another PRR present in the cytosol and the nucleus. The present review describes the role of ALRs (AIM2), TLR9, and cGAS in recognizing the host cell DNA as a potent damage/danger-associated molecular pattern (DAMP), which moves out to the cytosol from its housing organelles (nucleus and mitochondria). The introduction opens with the concept that the immune system has evolved to recognize pathogens, the idea of horror autotoxicus, and its failure due to the emergence of autoimmune diseases (ADs), and the discovery of PRRs revolutionizing immunology. The second section describes the cGAS-STING signaling pathway mediated cytosolic self-DNA recognition, its evolution, characteristics of self-DNAs activating it, and its role in different inflammatory conditions. The third section describes the role of TLR9 in recognizing self-DNA in the endolysosomes during infections depending on the self-DNA characteristics and various inflammatory diseases. The fourth section discusses about AIM2 (an ALR), which also binds cytosolic self-DNA (with 80–300 base pairs or bp) that inhibits cGAS-STING-dependent type 1 IFN generation but induces inflammation and pyroptosis during different inflammatory conditions. Hence, this trinity of PRRs has evolved to recognize self-DNA as a potential DAMP and comes into action to guard the cellular galaxy. However, their dysregulation proves dangerous to the host and leads to several inflammatory conditions, including sterile-inflammatory conditions autoinflammatory and ADs.

The Regulatory Role of High-Mobility Group Protein 1 in Sepsis-Related Immunity

High-mobility group box 1 (HMGB1), a prototypical damage-associated molecular pattern (DAMP) molecule, participates in multiple processes of various inflammatory diseases through binding to its corresponding receptors. In the early phase, sepsis is mainly characterized as a multi-bacterial-induced complex, excessive inflammatory response accompanied by the release of pro-inflammatory mediators, which subsequently develops into immune paralysis. A growing number of in vivo and in vitro investigations reveal that HMGB1 plays a pivotal role in the processes of inflammatory response and immunosuppression of sepsis. Therefore, HMGB1 exerts an indispensable role in the immune disorder and life-threatening inflammatory syndrome of sepsis. HMGB1 mainly mediate the release of inflammatory factors via acting on immune cells, pyroptosis pathways and phosphorylating nuclear factor-κB. Moreover HMGB1 is also associated with the process of sepsis-related immunosuppression. Neutrophil dysfunction mediated by HMGB1 is also an aspect of the immunosuppressive mechanism of sepsis. Myeloid-derived suppressor cells (MDSCs), which are also one of the important cells that play an immunosuppressive effect in sepsis, may connect with HMGB1. Thence, further understanding of HMGB1-associated pathogenesis of sepsis may assist in development of promising treatment strategies. This review mainly discusses current perspectives on the roles of HMGB1 in sepsis-related inflammation and immunosuppressive process and its related internal regulatory mechanisms.

How could we forget immunometabolism in SARS-CoV2 infection or COVID-19?

SARS-CoV2 infection or COVID-19 has created panic around the world since its first origin in December 2019 in Wuhan city, China. The COVID-19 pandemic has infected more than 46.4 million people, with 1,199,727 deaths. The immune system plays a crucial role in the severity of COVID-19 and the development of pneumonia-induced acute lung injury (ALI) or acute respiratory distress syndrome (ARDS). Along with providing protection, both innate and T cell-based adaptive immune response dysregulate during severe SARS-CoV2 infection. This dysregulation is more pronounced in older population and patients with comorbidities (Diabetes, hypertension, obesity, other pulmonary and autoimmune diseases). However, COVID-19 patients develop protective antibodies (Abs) against SARS-CoV2, but they do not long for last. The induction of the immune response against the pathogen also requires metabolic energy that generates through the process of immunometabolism. The change in the metabolic stage of immune cells from homeostasis to an inflammatory or infectious environment is called immunometabolic reprogramming. The article describes the cellular immunology (macrophages, T cells, B cells, dendritic cells, NK cells and pulmonary epithelial cells (PEC) and vascular endothelial cells) and the associated immune response during COVID-19. Immunometabolism may serve as a cell-specific therapeutic approach to target COVID-19.

Colorectal cancer stem cell vaccine with high expression of MUC1 serves as a novel prophylactic vaccine for colorectal cancer

Targeted clearance of colorectal cancer stem cells (CCSCs) has become a novel strategy for tumor immunotherapy. Molecule mucin1 (MUC1) is one of targetable cell surface antigens in CCSCs. However, the critical role of MUC1 in anti-tumor effects of CCSC vaccine remains unclear. In the present study, we showed that MUC1 may be required for CCSC vaccine to exert tumor immunity. CD133⁺CCSCs were isolated from CT26 cell line using a magnetic-activated cell sorting system, and MUC1 shRNA or recombinant plasmid was further used to decrease or increase the expression of MUC1 in CD133⁺CCSCs. Mice were subcutaneously immunized with the CCSC lysates, MUC1 knockin CCSCs, and MUC1 knockdown CCSCs respectively, followed by a challenge with CT26 cells. We found that CCSC vaccine significantly reduced the tumor growth via a target killing of CCSCs as evidenced by a decrease of CD133⁺ cells and ALDH⁺ cells in tumors. Moreover, CCSC vaccine markedly increased the cytotoxicity of NK cells and the splenocytes, and promoted the release of IFN-γ, Perforin, and Granzyme B, and also reduced the TGF-β1 expression. Additionally, CCSC vaccination enhanced the antibody production and decreased the myeloid derived suppressor cells and Treg subsets. More importantly, MUC1 knockdown partly impaired the anti-tumor efficacy of CCSC vaccine, whereas MUC1 overexpression dramatically enhanced the CCSC vaccine immunity. Overall, these results reveal a novel role and molecular mechanisms of MUC1 in CCSC vaccine against colorectal cancer.

Increased Th17 and Th22 Cell Percentages Predict Acute Lung Injury in Patients with Sepsis

PURPOSE

This study was conducted to investigate the percentages of Th22 and Th17 cells in the peripheral blood of septic patients with and without acute lung injury (ALI) and their clinical significance.

METHODS

A total of 479 patients were divided into non-ALI and ALI groups. The percentages of Th22 and Th17 cells and the levels of interleukin 22 (IL-22), 6 (IL-6), and 17 (IL-17) were determined. Receiver operating characteristic curve analysis was performed to assess the diagnostic value of Th22 and Th17 cells to predict sepsis-induced ALI.

RESULTS

The lung injury prediction score (LIPS), IL-6, IL-17, and IL-22 levels and the percentages of Th17 and Th22 cells were significantly higher in the ALI group (P < 0.05). They were significant factors affecting sepsis-induced ALI (P < 0.05). Multivariate logistic regression analysis showed that the LIPS (OR = 1.130), IL-17 (OR = 1.982), IL-22 (OR = 2.612) and the percentages of Th17 (OR = 2.211) and Th22 (OR = 3.230) cells were independent risk factors for ALI. The area under the curve of Th22 cells was 0.844 to predict ALI with a cutoff value of 6.81%. The sensitivity and specificity for early diagnosis of sepsis-induced ALI by the Th22 cell percentage were 78.72% and 89.13%, respectively.

CONCLUSIONS

Th22 and Th17 cells in peripheral blood are significantly increased in septic patients with ALI and they may be used as biomarkers for early diagnosis of sepsis-induced ALI.

CD4 T Cell Responses and the Sepsis-Induced Immunoparalysis State

Sepsis remains a major cause of death in the United States and worldwide, and costs associated with treating septic patients place a large burden on the healthcare industry. Patients who survive the acute phase of sepsis display long-term impairments in immune function due to reductions in numbers and function of many immune cell populations. This state of chronic immunoparalysis renders sepsis survivors increasingly susceptible to infection with newly or previously encountered infections. CD4 T cells play important roles in the development of cellular and humoral immune responses following infection. Understanding how sepsis impacts the CD4 T cell compartment is critical for informing efforts to develop treatments intended to restore immune system homeostasis following sepsis. This review will focus on the current understanding of how sepsis impacts the CD4 T cell responses, including numerical representation, repertoire diversity, phenotype and effector functionality, subset representation (e.g., Th1 and Treg frequency), and therapeutic efforts to restore CD4 T cell numbers and function following sepsis. Additionally, we will discuss recent efforts to model the acute sepsis phase and resulting immune dysfunction using mice that have previously encountered infection, which more accurately reflects the immune system of humans with a history of repeated infection throughout life. A thorough understanding of how sepsis impacts CD4 T cells based on previous studies and new models that accurately reflect the human immune system may improve translational value of research aimed at restoring CD4 T cell-mediated immunity, and overall immune fitness following sepsis.

Early Activation of Myeloid-Derived Suppressor Cells Participate in Sepsis-Induced Immune Suppression via PD-L1/PD-1 Axis

Background: Myeloid derived suppressor cells (MDSCs) have been reported to keep elevating during sepsis. The current study was performed to investigate the immunosuppressive effect of MDSCs and their subsets with the underlying mechanisms. Methods: The immunosuppressive status was manifested by the apoptosis of splenocytes, quantity of T cells and PD-1 expression. The dynamics of quantity and PD-L1 level of MDSCs and the subsets were determined over time. The subset of MDSCs with high PD-L1 level was co-cultured with T cells to observe the suppressive effect. Results: Abdominal abscess was observed after 7 days post-sepsis. Five biomarkers related to organ functions were all significantly higher in the CLP group. The survival rate was consistent with the middle grade severity of sepsis model. Apoptosis of splenocytes increased over time during sepsis; CD4 + T cell decreased from day 1 post-sepsis; CD8+ T cells significantly reduced at day 7. The PD-1 expression in spleen was upregulated from an early stage of sepsis, and negatively related with the quantity of T cells. MDSCs were low at day 1 post-sepsis, but increased to a high level later; the dynamics of PMN-MDSC was similar to MDSCs. PD-L1 on MDSCs was highest at day 1 post-sepsis; PMN-MDSC was the main subset expressing PD-L1. The PMN-MDSC with high PD-L1 expression level extracted on day 1 after surgery from CLP mice significantly inhibited the proliferation of T cells. Conclusions: Sepsis-induced immunosuppression is initiated from a very early stage, a high expression level of PD-L1 on MDSCs and the main subset, PMN-MDSC might play a critical role suppressive role on T cells through PD-L1/PD-1 axis.

Baicalin suppresses Th1 and Th17 responses and promotes Treg response to ameliorate sepsis-associated pancreatic injury via the RhoA-ROCK pathway

Recent studies have reported that the imbalance of T helper 1 cell (Th1), Th17 and regulatory T cell (Treg) have been confirmed to play a vital role in the development of sepsis and other inflammatory diseases. Baicalin (BA) has anti-inflammatory properties and improves survival in sepsis. We investigated whether baicalin could regulate Th1, Th17 and Treg responses to ameliorate sepsis-associated pancreatic injury through the ras homolog family member A (RhoA)-Rho kinase (ROCK) pathway. The sepsis model was established by using the cecal ligation and puncture (CLP) method. Fifty mice were randomly divided into five groups (n = 10): sham group, model group, low-dose group (BA-L, 100 mg/kg of baicalin), medium-dose group (BA-M, 200 mg/kg of baicalin) and highdose group (BA-H, 300 mg/kg of baicalin). The effects of baicalin on the pancreatic injury, on changes of Th1, Th17 and Treg cells in vivo and in vitro, on RhoA, ROCK1 and signal transducer and activator of transcription (STAT) signaling pathways, and on levels of interferon-γ (IFN-γ), interleukin-17 (IL-17) and IL-10 were examined. Treatment of the CLP mice with baicalin significantly reduced the extent, scope and severity of the pathological changes of sepsis-associated pancreatic injury. Baicalin evidently reduced Th1 and Th17 cells and increased Treg cells in peripheral blood, spleen, pancreatic tissue and significantly inhibited T-box protein expressed in T cells (T-bet), retinoic acid receptor-related orphan receptor γt (RORγt) and increased forkhead/winged helix transcription factor (Foxp3) expressions in the pancreatic tissue. Baicalin reduced the expressions of RhoA, ROCK1, phosphorylated STAT4 (p-STAT4), p-STAT3 and increased the expression of p-STAT5 in peripheral blood, spleen and pancreatic tissue. Baicalin reduced the expressions of IFN-γ and IL-17 and increased the IL-10 in serum and pancreatic tissue. Baicalin is capable of ameliorating sepsis-associated pancreatic injury and regulating Th1, Th17 and Treg responses in sepsis. The present study provided a potential adjunctive therapy for treating pancreatic injury in sepsis, and further study is needed to reveal its deeper mechanisms.

Innate lymphoid cell and adaptive immune cell cross-talk: A talk meant not to forget

Innate lymphoid cells (ILCs) are a relatively new class of innate immune cells with phenotypical characters of lymphocytes but genotypically or functionally behave as typical innate immune cells. They have been classically divided into 3 groups (group 1 ILCs or ILC1s, group 2 ILCs or ILC2s, and group 3 ILCs or ILC3s). They serve as the first line of defense against invading pathogens and allergens at mucosal surfaces. The adaptive immune response works effectively in association with innate immunity as innate immune cells serve as APCs to directly stimulate the adaptive immune cells (various sets of T and B cells). Additionally, innate immune cells also secrete various effector molecules, including cytokines or chemokines impacting the function, differentiation, proliferation, and reprogramming among adaptive immune cells to maintain immune homeostasis. Only superantigens do not require their processing by innate immune cells as they are recognized directly by T cells and B cells. Thus, a major emphasis of the current article is to describe the cross-talk between different ILCs and adaptive immune cells during different conditions varying from normal physiological situations to different infectious diseases to allergic asthma.