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Background: AA amyloidosis develops in patients with chronic inflammatory diseases. The AA amyloid proteins are proteolytic fragments obtained from serum amyloid A (SAA). Previous studies have provided evidence that endosomes or lysosomes might be involved in the processing of SAA, and contribute to the pathology of AA amyloidosis. Objective: To investigate the anatomical distribution of cathepsin (Cath) B and CathL in AA amyloidosis and their ability to process SAA and AA amyloid proteins. Methods and results: CathB and CathL were found immunohistochemically in every patient with AA amyloidosis and displayed a spatial relationship with amyloid in all the cases studied. Both degraded SAA and AA amyloid proteins in vitro. With the help of mass spectrometry 27 fragments were identified after incubation of SAA with CathB, nine of which resembled AA amyloid proteins, and seven fragments after incubation with CathL. CathL did not generate AA amyloid-like peptides. When native human AA amyloid proteins were used as a substrate 26 fragments were identified after incubation with CathB and 18 after incubation with CathL. Conclusion: The two most abundant and ubiquitously expressed lysosomal proteases can cleave SAA and AA amyloid proteins. CathB generates nine AA amyloid-like proteins by its carboxypeptidase activity, whereas CathL may prevent the formation of AA amyloid proteins by endoproteolytic activity within the N-terminal region of SAA. This is particularly interesting, because AA amyloidosis is a systemic disease affecting many organs and tissue types, almost all of which express CathB and CathL. PMID:15897303
The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.
In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.
Now in its fourth year, the AAS Oral History Project has interviewed over 100 space scientists from all over the world. Led by the AAS Historical Astronomy Division (HAD) and partially funded by the American Institute of Physics Niels Bohr Library and ongoing support from the AAS, volunteers have collected oral histories from space scientists at professional meetings starting in 2015, including AAS, DPS, and the IAU general assembly. Each interview lasts one and a half to two hours and focuses on interviewees' personal and professional lives. Questions include those about one's family, childhood, strong influences on one's scientific career, career path, successes and challenges, perspectives on how astronomy is changing as a field, and advice to the next generation. Each interview is audio recorded and transcribed, the content of which is checked with each interviewee. Once complete, interview transcripts are posted online as part of a larger oral history library at -programs/niels-bohr-library/oral-histories. We will present preliminary analysis of those interviewed including characterizing career status, age range, nationality, and primary field. Additionally, we will discuss trends beginning to emerge in analysis of participants' responses about data driven science and advice to the next generation. Future analysis will reveal a rich story of space scientists and will help the community address issues of diversity, controversies, and the changing landscape of science. We are actively recruiting individuals to be interviewed at this meeting from all stages of career from undergraduate students to retired and emeritus astronomers. We are especially interested in interviewing 40+E members of DPS. Contact Sanlyn Buxner to schedule an interview or to find out more information about the project (firstname.lastname@example.org). Contact Jarita Holbrook if you would like to become an interviewer for the project (email@example.com).
Co-Activator Activator (CoAA) has been reported to be a coactivator that regulates steroid receptor-mediated transcription and alternative RNA splicing. Herein we show that CoAA is a dual-function coregulator that inhibits G1/S transition in human kidney cells and suppresses anchorage independent growth and xenograft tumor formation. Suppression occurs in part by downregulating c-myc and its downstream effectors ccnd1 and skp2, and causing accumulation of p27/Kip1 protein. In this cellular setting, CoAA directly represses the proto-oncogene, c-myc by recruiting HDAC3 protein and decreasing both the acetylation of histone H3 and the presence of RNA polymerase II on the c-myc promoter. Interestingly, a splicing isoform of CoAA, Coactivator Modulator (CoAM), antagonizes CoAA-induced G1/S transition and growth inhibition by negatively regulating the mRNA levels of the endogenous CoAA isoform. In addition, we found that expression of CoAA protein is significantly decreased in human renal cell carcinoma as compared to normal kidney. Our study presents evidence that CoAA is a potential tumor suppressor in renal carcinoma and that CoAM is a counterbalancing splice-isoform. This is so far the only example of a nuclear receptor coregulator involved in suppression of kidney cancer, and suggests potentially significant new roles for coregulators in renal cancer biology. PMID:18829545
Half the world's population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment. We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations. We examined associations between residential greenness [measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants' homes] and birth outcomes in a cohort of 64,705 singleton births (from 1999-2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park. An interquartile increase in greenness (0.1 in residential NDVI) was associated with higher term birth weight (20.6 g; 95% CI: 16.5, 24.7) and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30-36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity. Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways (e.g., psychosocial and psychological mechanisms) may underlie associations between residential greenness and birth outcomes. 2b1af7f3a8