After stroke, peripheral immune cells are activated and these systemic responses may amplify brain damage, but how the injured brain sends out signals to trigger systemic inflammation remains unclear. Here we show that a brain-to-cervical lymph node (CLN) pathway is involved. In rats subjected to focal cerebral ischemia, lymphatic endothelial cells proliferate and macrophages are rapidly activated in CLNs within 24 h, in part via VEGF-C/VEGFR3 signalling. Microarray analyses of isolated lymphatic endothelium from CLNs of ischemic mice confirm the activation of transmembrane tyrosine kinase pathways. Blockade of VEGFR3 reduces lymphatic endothelial activation, decreases pro-inflammatory macrophages, and reduces brain infarction. In vitro, VEGF-C/VEGFR3 signalling in lymphatic endothelial cells enhances inflammatory responses in co-cultured macrophages. Lastly, surgical removal of CLNs in mice significantly reduces infarction after focal cerebral ischemia. These findings suggest that modulating the brain-to-CLN pathway may offer therapeutic opportunities to ameliorate systemic inflammation and brain injury after stroke.

Presepsin is useful for differentiating sepsis from non-infection related systemic inflammatory response syndrome. However, there are no studies investigating the usefulness of presepsin in diagnosing sepsis involving patients with acute kidney injury (AKI). The purpose of this study is to determine levels of blood presepsin in patients with or without sepsis and among non-AKI patients or patients with different degrees of AKI severity. This is a single center retrospective study. 247 patients admitted to the ICU between June 2010 and October 2012 were analyzed for their presepsin levels. We classified the patients into non-AKI and AKI according to the RIFLE (Risk, Injury, Failure, and Loss of kidney function and End-stage kidney disease or simply Loss and ESKD) criteria. We then sub-classified the patients in each group into either non-sepsis or sepsis sub-group and analyzed the accuracy of diagnosing sepsis based on their levels of presepsin. The number of patients for each group was: non-AKI, 112; under AKI: Risk, 50; Injury, 36; Failure, 42; Loss and ESKD, 7. The levels of presepsin in sepsis groups were significantly higher than that in the non-sepsis group among the non-AKI, Risk and Injury patients (p < 0.0001, p < 0.01, p < 0.01, respectively). However, no significant difference in the level of presepsin between non-sepsis and sepsis groups among patients with Failure. In the receiver operating characteristic (ROC) analysis, the area under the curve (AUC) was 0.784 in the non-AKI group and 0.698 in the AKI comprising Risk, Injury and Failure groups. AUC value for non-AKI was not significantly different from that of AKI (p = 0.200). When 670 pg/mL was used as the cutoff value for presepsin, sensitivity and specificity were 70.3% and 81.3%, respectively. When 864 pg/mL was used as the cutoff value for presepsin, sensitivity and specificity were 71.4% and 63.8%, respectively. Presepsin level can be a reliable indicator of sepsis not only among non-AKI patients but also patients with less severe forms of AKI. However, it may not be a reliable indicator of sepsis in patients with a more advanced form of AKI.

Sepsis is one of the most significant causes of mortality in intensive care units. It indicates crosstalk between inflammation and coagulation. In this study, we aimed to identify prognostic markers among sepsis biomarkers and coagulation/fibrinolysis markers. Patients with sepsis according to the Sepsis-3 criteria were enrolled from January 2013 to September 2015. Univariate and multivariate logistic regression analyses were performed to identify an independent predictive marker of 28-day mortality among sepsis biomarkers and coagulation/fibrinolysis markers on ICU admission. Receiver operating characteristic analysis was performed; the optimal cutoff value of 28-day mortality was calculated using the predictive marker. Patients were classified into two groups according to the cutoff level of the predictive marker. Patient characteristics were compared between the groups. A total of 186 patients were enrolled in this study; the 28-day mortality was 19.4% (36/186). PAI-1 was identified as the only independent predictive marker of 28-day mortality by univariate and multivariate logistic regression. The area under the curve was 0.72; the optimal cutoff level was 83 ng/ml (sensitivity, 75%; specificity, 61%). Patients were classified into a higher group (PAI-1 level ≥83 ng/ml; n = 85) and a lower group (PAI-1 level <83 ng/ml; n = 101). All disseminated intravascular coagulation (DIC) scores and Sequential Organ Failure Assessment score were significantly higher in the higher group than in the lower group. PAI-1 can predict prognosis in sepsis patients. PAI-1 reflects DIC with suppressed fibrinolysis and organ failure, with microthrombi leading to microcirculatory dysfunction.

Introduction: Inflammation and coagulation are closely interrelated pathophysiologic processes in the pathogenesis of sepsis. However, the diagnostic criteria of sepsis and disseminated intravascular coagulation (DIC) are different. This study aimed to define a biomarker panel to predict sepsis-induced DIC in emergency department patients. Methods: Eighty-two patients who were admitted to the emergency department of a tertiary university hospital were included in this study. The inclusion criteria were as follows: (1) age >18 years; (2) ≥1 systemic inflammatory response syndrome (SIRS) criteria. Patients were excluded if they lacked biomarker data or apparent clinical manifestations. Eleven biomarkers were assayed from blood drawn on ED admission. Receiver operating curve (ROC) analysis including the area under the ROC and multivariable logistic regression were used to identify an optimal combination of biomarkers to create a diagnostic panel. The derived formula for weighting biomarker values was used to determine the severity of sepsis-induced DIC, which was divided into three categories: mild, moderate, and severe. We also investigated the ability of this classification to predict secondary outcome measures of rates of sepsis and DIC, DIC score, acute physiology and chronic health evaluation (APACHE) II score, sequential organ failure score (SOFA) score, and 28-day all-cause mortality. Results: Among the 11 biomarkers tested, the optimal 2-marker panel comprised presepsin and protein C. The area under the curve for the accuracies of predicting sepsis and DIC from these two biomarkers were 0.913 and 0.880, respectively. When patients were divided according to the severity of sepsis-induced DIC, all secondary outcomes except for mortality were significantly higher depending on the severity (P < .0001). The overall mortality rates of mild, moderate, and severe sepsis-induced DIC were 7.14%, 15.4%, and 28.6%, respectively (P = .0994). Conclusions: A biomarker panel of presepsin and protein C is predictive of the severity of sepsis-induced DIC in suspected ED patients. These criteria for sepsis-induced DIC are very simple, easy to implement, and can be used in intensive care units as a point-of-care test.

Background: Recently, Tie2/TEK receptor tyrosine kinase (Tie2 or syn. angiopoietin‐1 receptor) positive nucleus pulposus progenitor cells were detected in human, cattle, and mouse. These cells show remarkable multilineage differentiation capacity and direct correlation with intervertebral disc (IVD) degeneration and are therefore an interesting target for regenerative strategies. Nevertheless, there remains controversy over the presence and function of these Tie2⁺ nucleus pulposus cells (NPCs), in part due to the difficulty of identification and isolation.Purpose: Here, we present a comprehensive protocol for sorting of Tie2⁺ NPCs from human, canine, bovine, and murine IVD tissue. We describe enhanced conditions for expansion and an optimized fluorescence‐activated cell sorting‐based methodology to sort and analyze Tie2⁺ NPCs.Methods: We present flow cytometry protocols to isolate the Tie2⁺ cell population for the aforementioned species. Moreover, we describe crucial pitfalls to prevent loss of Tie2⁺ NPCs from the IVD cell population during the isolation process. A cross‐species phylogenetic analysis of Tie2 across species is presented.Results: Our protocols are efficient towards labeling and isolation of Tie2⁺ NPCs. The total flow cytometry procedure requires approximately 9 hours, cell isolation 4 to 16 hours, cell expansion can take up to multiple weeks, dependent on the application, age, disease state, and species. Phylogenetic analysis of the TEK gene revealed a strong homology among species.Conclusions: Current identification of Tie2⁺ cells could be confirmed in bovine, canine, mouse, and human specimens. The presented flow cytometry protocol can successfully sort these multipotent cells. The biological function of isolated cells based on Tie2⁺ expression needs to be confirmed by functional assays such as in vitro differentiation. in vitro culture conditions to maintain and their possible proliferation of the Tie2⁺ fraction is the subject of future research.