Peptides identify multiple hotspots within the ligand binding domain of the TNF receptor 2

BACKGROUND: Hotspots are defined as the minimal functional domains involved in protein:protein interactions and sufficient to induce a biological response. RESULTS: Here we describe the use of complex and high diversity phage display libraries to isolate peptides (called Hotspot Ligands or HSPLs) which sub-divide the ligand binding domain of the tumor necrosis factor receptor 2 (TNFR2; p75) into multiple hotspots. We have shown that these libraries could generate HSPLs which not only subdivide hotspots on protein and non-protein targets but act as agonists or antagonists. Using this approach, we generated peptides which were specific for human TNFR2, could be competed by the natural ligands, TNFα and TNFβ and induced an unexpected biological response in a TNFR2-specific manner. CONCLUSIONS: To our knowledge, this is the first report describing the dissection of the TNFR2 into biologically active hotspots with the concomitant identification of a novel and unexpected biological activity

A surrogate-based approach for post-genomic partner identification

BACKGROUND: Modern drug discovery is concerned with identification and validation of novel protein targets from among the 30,000 genes or more postulated to be present in the human genome. While protein-protein interactions may be central to many disease indications, it has been difficult to identify new chemical entities capable of regulating these interactions as either agonists or antagonists. RESULTS: In this paper, we show that peptide complements (or surrogates) derived from highly diverse random phage display libraries can be used for the identification of the expected natural biological partners for protein and non-protein targets. Our examples include surrogates isolated against both an extracellular secreted protein (TNFβ) and intracellular disease related mRNAs. In each case, surrogates binding to these targets were obtained and found to contain partner information embedded in their amino acid sequences. Furthermore, this information was able to identify the correct biological partners from large human genome databases by rapid and integrated computer based searches. CONCLUSIONS: Modified versions of these surrogates should provide agents capable of modifying the activity of these targets and enable one to study their involvement in specific biological processes as a means of target validation for downstream drug discovery

Influence of Dynamic Ozone Dry Deposition on Ozone Pollution

Identifying the contributions of chemistry and transport to observed ozone pollution using regional-to-global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry-climate model - in which the atmosphere and land are coupled through dry deposition-to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process-based representation of snow and deposition to surfaces reduce hemispheric-scale ozone throughout the lower troposphere by 5-12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st-century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by -4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty-first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional-to-global models.Peer reviewe

Clinicopathological evaluation of chronic traumatic encephalopathy in players of American football

IMPORTANCE: Players of American football may be at increased risk of long-term neurological conditions, particularly chronic traumatic encephalopathy (CTE). OBJECTIVE: To determine the neuropathological and clinical features of deceased football players with CTE. DESIGN, SETTING, AND PARTICIPANTS: Case series of 202 football players whose brains were donated for research. Neuropathological evaluations and retrospective telephone clinical assessments (including head trauma history) with informants were performed blinded. Online questionnaires ascertained athletic and military history. EXPOSURES: Participation in American football at any level of play. MAIN OUTCOMES AND MEASURES: Neuropathological diagnoses of neurodegenerative diseases, including CTE, based on defined diagnostic criteria; CTE neuropathological severity (stages I to IV or dichotomized into mild [stages I and II] and severe [stages III and IV]); informant-reported athletic history and, for players who died in 2014 or later, clinical presentation, including behavior, mood, and cognitive symptoms and dementia. RESULTS: Among 202 deceased former football players (median age at death, 66 years [interquartile range, 47-76 years]), CTE was neuropathologically diagnosed in 177 players (87%; median age at death, 67 years [interquartile range, 52-77 years]; mean years of football participation, 15.1 [SD, 5.2]), including 0 of 2 pre–high school, 3 of 14 high school (21%), 48 of 53 college (91%), 9 of 14 semiprofessional (64%), 7 of 8 Canadian Football League (88%), and 110 of 111 National Football League (99%) players. Neuropathological severity of CTE was distributed across the highest level of play, with all 3 former high school players having mild pathology and the majority of former college (27 [56%]), semiprofessional (5 [56%]), and professional (101 [86%]) players having severe pathology. Among 27 participants with mild CTE pathology, 26 (96%) had behavioral or mood symptoms or both, 23 (85%) had cognitive symptoms, and 9 (33%) had signs of dementia. Among 84 participants with severe CTE pathology, 75 (89%) had behavioral or mood symptoms or both, 80 (95%) had cognitive symptoms, and 71 (85%) had signs of dementia. CONCLUSIONS AND RELEVANCE: In a convenience sample of deceased football players who donated their brains for research, a high proportion had neuropathological evidence of CTE, suggesting that CTE may be related to prior participation in football.This study received support from NINDS (grants U01 NS086659, R01 NS078337, R56 NS078337, U01 NS093334, and F32 NS096803), the National Institute on Aging (grants K23 AG046377, P30AG13846 and supplement 0572063345-5, R01 AG1649), the US Department of Defense (grant W81XWH-13-2-0064), the US Department of Veterans Affairs (I01 CX001038), the Veterans Affairs Biorepository (CSP 501), the Veterans Affairs Rehabilitation Research and Development Traumatic Brain Injury Center of Excellence (grant B6796-C), the Department of Defense Peer Reviewed Alzheimer’s Research Program (grant 13267017), the National Operating Committee on Standards for Athletic Equipment, the Alzheimer’s Association (grants NIRG-15-362697 and NIRG-305779), the Concussion Legacy Foundation, the Andlinger Family Foundation, the WWE, and the NFL

A dynamic risk score for early prediction of cardiogenic shock using machine learning

Myocardial infarction and heart failure are major cardiovascular diseases that affect millions of people in the US. The morbidity and mortality are highest among patients who develop cardiogenic shock. Early recognition of cardiogenic shock is critical. Prompt implementation of treatment measures can prevent the deleterious spiral of ischemia, low blood pressure, and reduced cardiac output due to cardiogenic shock. However, early identification of cardiogenic shock has been challenging due to human providers' inability to process the enormous amount of data in the cardiac intensive care unit (ICU) and lack of an effective risk stratification tool. We developed a deep learning-based risk stratification tool, called CShock, for patients admitted into the cardiac ICU with acute decompensated heart failure and/or myocardial infarction to predict onset of cardiogenic shock. To develop and validate CShock, we annotated cardiac ICU datasets with physician adjudicated outcomes. CShock achieved an area under the receiver operator characteristic curve (AUROC) of 0.820, which substantially outperformed CardShock (AUROC 0.519), a well-established risk score for cardiogenic shock prognosis. CShock was externally validated in an independent patient cohort and achieved an AUROC of 0.800, demonstrating its generalizability in other cardiac ICUs

iPSCORE: A Resource of 222 iPSC Lines Enabling Functional Characterization of Genetic Variation across a Variety of Cell Types.

Large-scale collections of induced pluripotent stem cells (iPSCs) could serve as powerful model systems for examining how genetic variation affects biology and disease. Here we describe the iPSCORE resource: a collection of systematically derived and characterized iPSC lines from 222 ethnically diverse individuals that allows for both familial and association-based genetic studies. iPSCORE lines are pluripotent with high genomic integrity (no or low numbers of somatic copy-number variants) as determined using high-throughput RNA-sequencing and genotyping arrays, respectively. Using iPSCs from a family of individuals, we show that iPSC-derived cardiomyocytes demonstrate gene expression patterns that cluster by genetic background, and can be used to examine variants associated with physiological and disease phenotypes. The iPSCORE collection contains representative individuals for risk and non-risk alleles for 95% of SNPs associated with human phenotypes through genome-wide association studies. Our study demonstrates the utility of iPSCORE for examining how genetic variants influence molecular and physiological traits in iPSCs and derived cell lines

Diffusion Tensor Imaging of Frontal Lobe in Autism Spectrum Disorder

To investigate frontal lobe white matter in children with autism spectrum disorder (ASD), we performed diffusion tensor imaging (DTI) in 50 ASD children (mean age: 57.5 ± 29.2 months, 43 males) and 16 typically developing children (mean age: 82.1 ± 41.4 months, 11 males). The apparent diffusion coefficient (ADC) was significantly higher for whole frontal lobe (P = 0.011), long (P < 0.001) and short range (P = 0.0126) association fibers in ASD group. There was a trend toward statistical significance in the fractional anisotropy (FA) of whole frontal lobe fibers (P = 0.11). FA was significantly lower in ASD group for short range fibers (P = 0.0031) but not for long range fibers (P = not significant [NS]). There was no between-group difference in the number of frontal lobe fibers (short and long) (P = NS). The fiber length distribution was significantly more positively skewed in the normal population than in the ASD group (P < 0.001). The long range association fibers of frontal lobe were significantly longer in ASD group (P = 0.026 for both left and right hemispheres). Abnormal frontal FA and ADC may be due to white matter organization abnormalities in ASD. Lack of evidence for excessive short range connectivity in ASD in this study may need to be re-examined with future advances in DTI technology

Communications Biophysics

Contains research objectives, summary of research and reports on three research projects.National Institutes of Health (Grant 5 PO1 GM14940-06)National Institutes of Health (Grant 2 TOl GM01555-06)National Institutes of Health (Grant 1 ROl NS10737-01)National Aeronautics and Space Administration (Grant NGL 22-009-304)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DAAB07-71-C-0300B-D Electrodyne Division, Becton Dickinson and Company (Grant)Boston City Hospital Purchase Order 1176-21-33

Future research directions in pneumonia

Copyright © 2018 by the American Thoracic Society. Pneumonia is a complex pulmonary disease in need of new clinical approaches. Although triggered by a pathogen, pneumonia often results from dysregulations of host defense that likely precede infection. The coordinated activities of immune resistance and tissue resilience then dictate whether and how pneumonia progresses or resolves. Inadequate or inappropriate host responses lead to more severe outcomes such as acute respiratory distress syndrome and to organ dysfunction beyond the lungs and over extended time frames after pathogen clearance, some of which increase the risk for subsequent pneumonia. Improved understanding of such host responses will guide the development of novel approaches for preventing and curing pneumonia and for mitigating the subsequent pulmonary and extrapulmonary complications of pneumonia. The NHLBI assembled a working group of extramural investigators to prioritize avenues of host-directed pneumonia research that should yield novel approaches for interrupting the cycle of unhealthy decline caused by pneumonia. This report summarizes the working group’s specific recommendations in the areas of pneumonia susceptibility, host response, and consequences. Overarching goals include the development of more host-focused clinical approaches for preventing and treating pneumonia, the generation of predictive tools (for pneumonia occurrence, severity, and outcome), and the elucidation of mechanisms mediating immune resistance and tissue resilience in the lung. Specific areas of research are highlighted as especially promising for making advances against pneumonia

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.