Development of a biomarker mortality risk model in acute respiratory distress syndrome

Background: There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome. Methods: This is a secondary analysis using a cohort of 252 mechanically ventilated subjects with the diagnosis of acute respiratory distress syndrome. Survival to day 7 with both day 0 (first day of presentation) and day 7 sample availability was required. Blood was collected for biomarker measurements at first presentation to the intensive care unit and on the seventh day. Biomarkers included cytokine-chemokines, dual-functioning cytozymes, and vascular injury markers. Logistic regression, latent class analysis, and classification and regression tree analysis were used to identify the plasma biomarkers most predictive of 28-day ARDS mortality. Results: From eight biologically relevant biomarker candidates, six demonstrated an enhanced capacity to predict mortality at day 0. Latent-class analysis identified two biomarker-based phenotypes. Phenotype A exhibited significantly higher plasma levels of angiopoietin-2, macrophage migration inhibitory factor, interleukin-8, interleukin-1 receptor antagonist, interleukin-6, and extracellular nicotinamide phosphoribosyltransferase (eNAMPT) compared to phenotype B. Mortality at 28 days was significantly higher for phenotype A compared to phenotype B (32% vs 19%, p = 0.04). Conclusions: An adult biomarker-based risk model reliably identifies ARDS subjects at risk of death within 28 days of hospitalization.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Are mice good models for human neuromuscular disease? Comparing muscle excursions in walking between mice and humans

The mouse is one of the most widely used animal models to study neuromuscular diseases and test new therapeutic strategies. However, findings from successful pre-clinical studies using mouse models frequently fail to translate to humans due to various factors. Differences in muscle function between the two species could be crucial but often have been overlooked. The purpose of this study was to evaluate and compare muscle excursions in walking between mice and humans

A Negative Feedback Loop That Limits the Ectopic Activation of a Cell Type–Specific Sporulation Sigma Factor of Bacillus subtilis

Two highly similar RNA polymerase sigma subunits, σF and σG, govern the early and late phases of forespore-specific gene expression during spore differentiation in Bacillus subtilis. σF drives synthesis of σG but the latter only becomes active once engulfment of the forespore by the mother cell is completed, its levels rising quickly due to a positive feedback loop. The mechanisms that prevent premature or ectopic activation of σG while discriminating between σF and σG in the forespore are not fully comprehended. Here, we report that the substitution of an asparagine by a glutamic acid at position 45 of σG (N45E) strongly reduced binding by a previously characterized anti-sigma factor, CsfB (also known as Gin), in vitro, and increased the activity of σG in vivo. The N45E mutation caused the appearance of a sub-population of pre-divisional cells with strong activity of σG. CsfB is normally produced in the forespore, under σF control, but sigGN45E mutant cells also expressed csfB and did so in a σG-dependent manner, autonomously from σF. Thus, a negative feedback loop involving CsfB counteracts the positive feedback loop resulting from ectopic σG activity. N45 is invariant in the homologous position of σG orthologues, whereas its functional equivalent in σF proteins, E39, is highly conserved. While CsfB does not bind to wild-type σF, a E39N substitution in σF resulted in efficient binding of CsfB to σF. Moreover, under certain conditions, the E39N alteration strongly restrains the activity of σF in vivo, in a csfB-dependent manner, and the efficiency of sporulation. Therefore, a single amino residue, N45/E39, is sufficient for the ability of CsfB to discriminate between the two forespore-specific sigma factors in B. subtilis

The Case for Probe-class NASA Astrophysics Missions

Astrophysics spans an enormous range of questions on scales from individual planets to the entire cosmos. To address the richness of 21st century astrophysics requires a corresponding richness of telescopes spanning all bands and all messengers. Much scientific benefit comes from having the multi-wavelength capability available at the same time. Most of these bands,or measurement sensitivities, require space-based missions. Historically, NASA has addressed this need for breadth with a small number of flagship-class missions and a larger number of Explorer missions. While the Explorer program continues to flourish, there is a large gap between Explorers and strategic missions. A fortunate combination of new astrophysics technologies with new, high capacity, low dollar-per-kg to orbit launchers, and new satellite buses allow for cheaper missions with capabilities approaching strategic mission levels. NASA has recognized these developments by calling for Probe-class mission ideas for mission studies, spanning most of the electromagnetic spectrum from GeV gamma-rays to the far infrared, and the new messengers of neutrinos and ultra-high energy cosmic rays. The key insight from the Probes exercise is that order-of-magnitude advances in science performance metrics are possible across the board for initial total cost estimates in the range 500M-1B dollars

Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer

"Background Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival. Methods Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression. Results Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes. Conclusion Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.