Nonhematopoietic Peroxisome Proliferator-Activated Receptor-α Protects Against Cardiac Injury and Enhances Survival in Experimental Polymicrobial Sepsis.

OBJECTIVES: Peroxisome proliferator-activated receptor-α is significantly down-regulated in circulating leukocytes from children with sepsis. Peroxisome proliferator-activated receptor-α null (Ppara) mice have greater mortality than wild-type mice when subjected to sepsis by cecal ligation and puncture. We sought to characterize the role of peroxisome proliferator-activated receptor-α in sepsis and to identify the mechanism whereby peroxisome proliferator-activated receptor-α confers a survival advantage. DESIGN: Prospective randomized preclinical study. SETTING: Laboratory investigation. SUBJECTS: Male C57Bl/6J and Ppara mice (B6.129S4-Ppara/J), aged 12-16 weeks. INTERVENTIONS: Bone marrow chimeric mice were generated and subjected to cecal ligation and puncture. Survival was measured for 7 days. Separate groups of nontransplanted mice underwent cecal ligation and puncture and were euthanized 24 hours later for plasma and tissue analyses. MEASUREMENTS AND MAIN RESULTS: Ppara mice had dramatically reduced survival compared with wild-type mice irrespective of the peroxisome proliferator-activated receptor-α status of the bone marrow they received (3% vs 63%; p < 0.0001). No difference in survival was observed between Ppara mice that received wild-type versus Ppara marrow or in wild-type mice receiving wild-type versus Ppara marrow. In septic, nontransplanted mice at 24 hours, Ppara mice had elevated cardiac troponin levels compared with wild-type mice. Cardiac histologic injury scores were greater in Ppara versus wild-type mice. Expression of transcription factors and enzymes related to fatty acid oxidation in the heart were profoundly down-regulated in both wild-type and Ppara mice, but more so in the Ppara mice. CONCLUSIONS: Peroxisome proliferator-activated receptor-α expression in nonhematopoietic tissues plays a critical role in determining clinical outcome in experimental polymicrobial sepsis and is more important to survival in sepsis than hematopoietic peroxisome proliferator-activated receptor-α expression. Cardiac injury due to inadequate energy production from fatty acid substrate is a probable mechanism of decreased survival in Ppara mice. These results suggest that altered peroxisome proliferator-activated receptor-α-mediated cellular metabolism may play an important role in sepsis-related end-organ injury and dysfunction, especially in the heart.

Novel HALO® image analysis to determine cell phenotype in porous precision-templated scaffolds.

Image analysis platforms have gained increasing popularity in the last decade for the ability to automate and conduct high-throughput, multiplex, and quantitative analyses of a broad range of pathological tissues. However, imaging tissues with unique morphology or tissues containing implanted biomaterial scaffolds remain a challenge. Using HALO®, an image analysis platform specialized in quantitative tissue analysis, we have developed a novel method to determine multiple cell phenotypes in porous precision-templated scaffolds (PTS). PTS with uniform spherical pores between 30 and 40 µm in diameter have previously exhibited a specific immunomodulation of macrophages toward a pro-healing phenotype and an overall diminished foreign body response (FBR) compared to PTS with larger or smaller pore sizes. However, signaling pathways orchestrating this pro-healing in 40 µm PTS remain unclear. Here, we use HALO® to phenotype PTS resident cells and found a decrease in pro-inflammatory CD86 and an increase in pro-healing CD206 expression in 40 µm PTS compared to 100 µm PTS. To understand the mechanisms that drive these outcomes, we investigated the role of myeloid-differentiation-primary-response gene 88 (MyD88) in regulating the pro-healing phenomenon observed only in 40 µm PTS. When subcutaneously implanted in MyD88KO mice, 40 µm PTS reduced the expression of CD206, and the scaffold resident cells displayed an average larger nuclear size compared to 40 µm PTS implanted in mice expressing MyD88. Overall, this study demonstrates a novel image analysis method for phenotyping cells within PTS and identifies MyD88 as a critical mediator in the pore-size-dependent regenerative healing and host immune response to PTS.

Challenges in Predicting Recurrence After Resection of Node-Negative Non-Small Cell Lung Cancer.

BACKGROUND: One in 5 patients with completely resected early-stage non-small cell lung cancer will recur within 2 years. Risk stratification may facilitate a personalized approach to the use of adjuvant therapy and surveillance imaging. We developed a prediction model for recurrence based on five clinical variables (tumor size and grade, visceral pleural and lymphovascular invasion, and sublobar resection), and tested the hypothesis that the addition of several new molecular markers of poor long-term outcome (vascular endothelial growth factor C; microRNA precursors 486 and 30d) would enhance prediction. METHODS: We performed a retrospective cohort study of patients with completely resected, node-negative non-small cell lung cancer from 2011 to 2014 (follow-up through 2016) using the Lung Cancer Biospecimen Resource Network. Cox regression was used to estimate the 2-year risk of recurrence. Our primary measure of model performance was the optimism-corrected C statistic. RESULTS: Among 173 patients (mean tumor size, 3.6 cm; 12% sublobar resection, 32% poorly differentiated, 16% lymphovascular invasion, 26% visceral pleural invasion), the 2-year recurrence rate was 23% (95% confidence interval, 17% to 31%). A prediction model using five known risk factors for recurrence performed only slightly better than chance in predicting recurrence (optimism-corrected C statistic, 0.54; 95% confidence interval, 0.51 to 0.68). The addition of biomarkers did not improve the model's ability to predict recurrence (corrected C statistic, 0.55; 95% confidence interval, 0.52 to 0.71). CONCLUSIONS: We were unable to predict lung cancer recurrence using a risk-prediction model based on five well-known clinical risk factors and several biomarkers. Further research should consider novel predictors of recurrence to stratify patients with completely resected early-stage non-small cell lung cancer according to their risk of recurrence.