Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Common causes include gram-negative and gram-positive bacteria as well as fungi. Neutrophils are among the first cells to arrive at an infection site where they function as important effector cells of the innate immune system and as regulators of the host immune response. The regulation of neutrophil migration is therefore important both for the infection-directed host response and for the development of organ dysfunctions in sepsis. Downregulation of CXCR4/CXCL12 stimulates neutrophil migration from the bone marrow. This is followed by transmigration/extravasation across the endothelial cell barrier at the infection site; this process is directed by adhesion molecules and various chemotactic gradients created by chemotactic cytokines, lipid mediators, bacterial peptides, and peptides from damaged cells. These mechanisms of neutrophil migration are modulated by sepsis, leading to reduced neutrophil migration and even reversed migration that contributes to distant organ failure. The sepsis-induced modulation seems to differ between neutrophil subsets. Furthermore, sepsis patients should be regarded as heterogeneous because neutrophil migration will possibly be further modulated by the infecting microorganisms, antimicrobial treatment, patient age/frailty/sex, other diseases (e.g., hematological malignancies and stem cell transplantation), and the metabolic status. The present review describes molecular mechanisms involved in the regulation of neutrophil migration; how these mechanisms are altered during sepsis; and how bacteria/fungi, antimicrobial treatment, and aging/frailty/comorbidity influence the regulation of neutrophil migration.

Monocytes are important in the defense against fungal infections due to their phagocytic and immunoregulatory functions. Platelets also contribute in such immune responses through their release of soluble mediators, including chemokines as well as several other soluble mediators. Both monocytes and platelets express several Toll-like receptors (TLRs) that can recognize fungal molecules and thus initiate intracellular signaling events. TLR ligation on monocytes and platelets may thereby be an early immunological event and function as an initiator of a local proinflammatory crosstalk between platelets and monocytes resulting in (i) monocyte-induced increase of platelet activation and (ii) platelet-associated enhancement of the monocyte activation/function. These effects may have clinical implications both for the efficiency of antifungal treatment and for the predisposition to fungal infections, for example, increased predisposition in patients with thrombocytopenia/monocytopenia due to chemotherapy- or disease-induced bone marrow failure.

Autoimmune polyendocrine syndrome type 1 (APS-1) is caused by mutations in the autoimmune regulator (AIRE) gene. Most patients present with severe chronic mucocutaneous candidiasis and organ-specific autoimmunity from early childhood, but the clinical picture is highly variable. AIRE is crucial for negative selection of T cells, and scrutiny of different patient mutations has previously highlighted many of its molecular mechanisms. In patients with a milder adult-onset phenotype sharing a mutation in the canonical donor splice site of intron 7 (c.879+1G>A), both the predicted altered splicing pattern with loss of exon 7 (Aire^Ex7–/–) and normal full-length AIRE mRNA were found, indicating leaky rather than abolished mRNA splicing. Analysis of a corresponding mouse model demonstrated that the Aire^Ex7–/– mutant had dramatically impaired transcriptional capacity of tissue-specific antigens in medullary thymic epithelial cells but still retained some ability to induce gene expression compared with the complete loss-of-function Aire^C313X–/– mutant. Our data illustrate an association between AIRE activity and the severity of autoimmune disease, with implications for more common autoimmune diseases associated with AIRE variants, such as primary adrenal insufficiency, pernicious anemia, type 1 diabetes, and rheumatoid arthritis.

Sepsis is a dysregulated host response to infection that causes potentially life-threatening organ dysfunction. We investigated the serum metabolomic profile at hospital admission for patients with bacterial sepsis. The study included 60 patients; 35 patients fulfilled the most recent 2016 Sepsis-3 criteria whereas the remaining 25 patients only fulfilled the previous Sepsis-2 criteria and could therefore be classified as having systemic inflammatory response syndrome (SIRS). A total of 1011 identified metabolites were detected in our serum samples. Ninety-seven metabolites differed significantly when comparing Sepsis-3 and Sepsis-2/SIRS patients; 40 of these metabolites constituted a heterogeneous group of amino acid metabolites/peptides. When comparing patients with and without bacteremia, we identified 51 metabolites that differed significantly, including 16 lipid metabolites and 11 amino acid metabolites. Furthermore, 42 metabolites showed a highly significant association with the maximal total Sequential Organ Failure Assessment (SOFA )score during the course of the disease (i.e., Pearson’s correlation test, p-value < 0.005, and correlation factor > 0.6); these top-ranked metabolites included 23 amino acid metabolites and a subset of pregnenolone/progestin metabolites. Unsupervised hierarchical clustering analyses based on all 42 top-ranked SOFA correlated metabolites or the subset of 23 top-ranked amino acid metabolites showed that most Sepsis-3 patients differed from Sepsis-2/SIRS patients in their systemic metabolic profile at the time of hospital admission. However, a minority of Sepsis-3 patients showed similarities with the Sepsis-2/SIRS metabolic profile even though several of them showed a high total SOFA score. To conclude, Sepsis-3 patients are heterogeneous with regard to their metabolic profile at the time of hospitalization.

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. In the present study, we investigated the systemic/serum lipidomic profile at the time of hospital admission for patients with bacterial sepsis. The study included 60 patients; 35 patients fulfilled the most recent 2016 Sepsis-3 criteria (referred to as Sepsis-3) whereas the remaining 25 patients had sepsis only according to the previous Sepsis-2 definition and could be classified as having Systemic Inflammatory Response Syndrome (SIRS). A total of 966 lipid metabolites were identified. Patients fulfilling the Sepsis-3 criteria differed from the Sepsis-2 patients with regard to only 15 lipid metabolites, and especially sphingolipids metabolism differed between these patient subsets. A total of only 43 metabolites differed between patients with and without bacteremia, including 12 lysophosphatidylcholines and 18 triacylglycerols (15 C18/C20 fatty acid metabolites decreased and three C14 myristate acid metabolites that were increased in bacteremia). Unsupervised hierarchical clustering analyses based on the identified sphingolipids, phosphatidylcholine and triacylglycerols showed that (i) the majority of Sepsis-3 patients differed from SIRS patients especially with regard to lysophosphatidylcholine levels; (ii) the minority of Sepsis-3 patients that clustered together with the majority of SIRS patients showed lower Sequential Organ Failure Assessment (SOFA) scores than the other Sepsis-3 patients; and (iii) the variation between the patients in the identified/altered sphingolipid and triacylglycerol metabolites further increased the heterogeneity of Sepsis-3 patients with regard to their systemic lipidomic profile at the time of diagnosis. To conclude, patients fulfilling the Sepsis-3 criteria differ with regard to their metabolic profile, and this variation depends on disease severity.

Background: Severity scores and mortality prediction models (MPMs) are important tools for benchmarking and stratification in the intensive care unit (ICU) and need to be regularly updated using data from a local and contextual cohort. Simplified acute physiology score II (SAPS II) is widely used in European ICUs.Methods: A first‐level customization was performed on the SAPS II model using data from the Norwegian Intensive Care and Pandemic Registry (NIPaR). Two previous SAPS II models (Model A: the original SAPS II model and Model B: a SAPS II model based on NIPaR data from 2008 to 2010) were compared to the new Model C. Model C was based on patients from 2018 to 2020 (corona virus disease 2019 patients omitted; n = 43,891), and its performances (calibration, discrimination, and uniformity of fit) compared to the previous models (Model A and Model B).Results: Model C was better calibrated than Model A with a Brier score 0.132 (95% confidence interval 0.130–0.135) versus 0.143 (95% confidence interval 0.141–0.146). The Brier score for Model B was 0.133 (95% confidence interval 0.130–0.135). In the Cox's calibration regression and for both Model C and Model B but not for Model A. Uniformity of fit was similar for Model B and for Model C, both better than for Model A, across age groups, sex, length of stay, type of admission, hospital category, and days on respirator. The area under the receiver operating characteristic curve was 0.79 (95% confidence interval 0.79–0.80), showing acceptable discrimination.Conclusions: The observed mortality and corresponding SAPS II scores have significantly changed during the last decades and an updated MPM is superior to the original SAPS II. However, proper external validation is required to confirm our findings. Prediction models need to be regularly customized using local datasets in order to optimize their performances.