Phage display selected magnetite interacting Adhirons for shape controlled nanoparticle synthesis

Adhirons are robust, well expressing, peptide display scaffold proteins, developed as an effective alternative to traditional antibody binding proteins for highly specific molecular recognition applications. This paper reports for the first time the use of these versatile proteins for material binding, and as tools for controlling material synthesis on the nanoscale. A phage library of Adhirons, each displaying two variable binding loops, was screened to identify specific proteins able to interact with [100] faces of cubic magnetite nanoparticles. The selected variable regions display a strong preference for basic residues such as lysine. Molecular dynamics simulations of amino acid adsorption onto a [100] magnetite surface provides a rationale for these interactions, with the lowest adsorption energy observed with lysine. These proteins direct the shape of the forming nanoparticles towards a cubic morphology in room temperature magnetite precipitation reactions, in stark contrast to the high temperature, harsh reaction conditions currently used to produce cubic nanoparticles. These effects demonstrate the utility of the selected Adhirons as novel magnetite mineralization control agents using ambient aqueous conditions. The approach we outline with artificial protein scaffolds has the potential to develop into a toolkit of novel additives for wider nanomaterial fabrication

Analysis of lethal and sublethal impacts of environmental disasters on sperm whales using stochastic modeling

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecotoxicology 26 (2017): 820-830, doi:10.1007/s10646-017-1813-4.Mathematical models are essential for combining data from multiple sources to quantify population endpoints. This is especially true for species, such as marine mammals, for which data on vital rates are difficult to obtain. Since the effects of an environmental disaster are not fixed, we develop time-varying (nonautonomous) matrix population models that account for the eventual recovery of the environment to the pre-disaster state. We use these models to investigate how lethal and sublethal impacts (in the form of reductions in the survival and fecundity, respectively) affect the population’s recovery process. We explore two scenarios of the environmental recovery process and include the effect of demographic stochasticity. Our results provide insights into the relationship between the magnitude of the disaster, the duration of the disaster, and the probability that the population recovers to pre-disaster levels or a biologically relevant threshold level. To illustrate this modeling methodology, we provide an application to a sperm whale population. This application was motivated by the 2010 Deepwater Horizon oil rig explosion in the Gulf of Mexico that has impacted a wide variety of species populations including oysters, fish, corals, and whales.This research is part of the Littoral Acoustic Demonstration Center-Gulf Ecological Monitoring and Modeling (LADC-GEMM) consortium project supported by Gulf of Mexico Research Initiative Year 5–7 Consortia Grants (RFP-IV). Hal Caswell also acknowledges support from ERC Advanced Grant 322989

The sonographic quantitative assessment of the deltoid muscle to detect type 2 diabetes mellitus: a potential noninvasive and sensitive screening method?

BACKGROUND: In our previous published study, we demonstrated that a qualitatively assessed elevation in deltoid muscle echogenicity on ultrasound was both sensitive for and a strong predictor of a type 2 diabetes (T2DM) diagnosis. This study aims to evaluate if a sonographic quantitative assessment of the deltoid muscle can be used to detect T2DM. METHODS: Deltoid muscle ultrasound images from 124 patients were stored: 31 obese T2DM, 31 non-obese T2DM, 31 obese non-T2DM and 31 non-obese non-T2DM. Images were independently reviewed by 3 musculoskeletal radiologists, blinded to the patient\u27s category. Each measured the grayscale pixel intensity of the deltoid muscle and humeral cortex to calculate a muscle/bone ratio for each patient. Following a 3-week delay, the 3 radiologists independently repeated measurements on a randomly selected 40 subjects. Ratios, age, gender, race, body mass index, insulin usage and hemoglobin A(1c) were analyzed. The difference among the 4 groups was compared using analysis of variance or chi-square tests. Both univariate and multivariate linear mixed models were performed. Multivariate mixed-effects regression models were used, adjusting for demographic and clinical variables. Post hoc comparisons were done with Bonferroni adjustments to identify any differences between groups. The sample size achieved 90% power. Sensitivity and specificity were calculated based on set threshold ratios. Both intra- and inter-radiologist variability or agreement were assessed. RESULTS: A statistically significant difference in muscle/bone ratios between the groups was identified with the average ratios as follows: obese T2DM, 0.54 (P \u3c 0.001); non-obese T2DM, 0.48 (P \u3c 0.001); obese non-T2DM, 0.42 (P = 0.03); and non-obese non-T2DM, 0.35. There was excellent inter-observer agreement (intraclass correlation coefficient 0.87) and excellent intra-observer agreements (intraclass correlation coefficient 0.92, 0.95 and 0.94). Using threshold ratios, the sensitivity for detecting T2DM was 80% (95% CI 67% to 88%) with a specificity of 63% (95% CI 50% to 75%). CONCLUSIONS: The sonographic quantitative assessment of the deltoid muscle by ultrasound is sensitive and accurate for the detection of T2DM. Following further studies, this process could translate into a dedicated, simple and noninvasive screening method to detect T2DM with the prospects of identifying even a fraction of the undiagnosed persons worldwide. This could prove especially beneficial in screening of underserved and underrepresented communities

Comprehensive Peroxidase-Based Hematologic Profiling for The Prediction of 1-Year Myocardial Infarction and Death

Background— Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone. Methods and Results— Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in ≥10% of subjects with events) and 24 low-risk (observed in ≥10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% (P\u3c0.001) of patients to different risk categories for death/MI when added to traditional risk factors. Conclusion— Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI

Comprehensive Peroxidase-Based Hematologic Profiling for The Prediction of 1-Year Myocardial Infarction and Death

Background— Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone. Methods and Results— Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in ≥10% of subjects with events) and 24 low-risk (observed in ≥10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% (P\u3c0.001) of patients to different risk categories for death/MI when added to traditional risk factors. Conclusion— Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI

RACE-IT - Rapid Acute Coronary Syndrome Exclusion using the Beckman Coulter Access high-sensitivity cardiac troponin I: A stepped-wedge cluster randomized trial

Background: Protocols utilizing high-sensitivity cardiac troponin (hs-cTn) assays for the evaluation of suspected acute coronary syndrome (ACS) in the emergency department (ED) have been gaining popularity across the US and the world. These protocols more rapidly rule-out ACS and more accurately identify the presence of acute myocardial injury. At this time, few randomized trials have evaluated the safety and operational impact of these assays, resulting in limited evidence to guide the use and implementation of hs-cTn in the ED. Objective: The main study objective is to test the effectiveness of a rapid ACS rule-out pathway using hs-cTnI in safely discharging patients from the ED for whom clinical suspicion for ACS exists. Design: This prospective, implementation trial (n = 11,070) will utilize a stepped wedge cluster randomized trial design. The design will allow for all participating sites to capture benefit from the implementation of the hs-cTnI pathway while providing data evaluating the effectiveness in providing safe and rapid evaluation of patients with clinical suspicion for ACS. Summary: Demonstrating that clinical pathways using hs-cTnI can be effectively implemented to rapidly rule-out ACS while conserving costly hospital resources has significant implications for the care of patients with possible acute cardiac conditions in EDs across the US. Clinicaltrialsgov identifier: NCT04488913

Interaction of Brn3a and HIPK2 mediates transcriptional repression of sensory neuron survival

The Pit1-Oct1-Unc86 domain (POU domain) transcription factor Brn3a controls sensory neuron survival by regulating the expression of Trk receptors and members of the Bcl-2 family. Loss of Brn3a leads to a dramatic increase in apoptosis and severe loss of neurons in sensory ganglia. Although recent evidence suggests that Brn3a-mediated transcription can be modified by additional cofactors, the exact mechanisms are not known. Here, we report that homeodomain interacting protein kinase 2 (HIPK2) is a pro-apoptotic transcriptional cofactor that suppresses Brn3a-mediated gene expression. HIPK2 interacts with Brn3a, promotes Brn3a binding to DNA, but suppresses Brn3a-dependent transcription of brn3a, trkA, and bcl-xL. Overexpression of HIPK2 induces apoptosis in cultured sensory neurons. Conversely, targeted deletion of HIPK2 leads to increased expression of Brn3a, TrkA, and Bcl-xL, reduced apoptosis and increases in neuron numbers in the trigeminal ganglion. Together, these data indicate that HIPK2, through regulation of Brn3a-dependent gene expression, is a critical component in the transcriptional machinery that controls sensory neuron survival

Constitutive interferon signaling maintains critical threshold of MLKL expression to license necroptosis

Interferons (IFNs) are critical determinants in immune-competence and autoimmunity, and are endogenously regulated by a low-level constitutive feedback loop. However, little is known about the functions and origins of constitutive IFN. Recently, lipopolysaccharide (LPS)-induced IFN was implicated as a driver of necroptosis, a necrotic form of cell death downstream of receptor-interacting protein (RIP) kinase activation and executed by mixed lineage kinase like-domain (MLKL) protein. We found that the pre-established IFN status of the cell, instead of LPS-induced IFN, is critical for the early initiation of necroptosis in macrophages. This pre-established IFN signature stems from cytosolic DNA sensing via cGAS/STING, and maintains the expression of MLKL and one or more unknown effectors above a critical threshold to allow for MLKL oligomerization and cell death. Finally, we found that elevated IFN-signaling in systemic lupus erythematosus (SLE) augments necroptosis, providing a link between pathological IFN and tissue damage during autoimmunity