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A recommended “minimum data set” framework for SD-OCT retinal image acquisition and analysis from the Atlas of Retinal Imaging in Alzheimer’s Study (ARIAS)

Introduction: We propose a minimum data set framework for the acquisition and analysis of retinal images for the development of retinal Alzheimer\u27s disease (AD) biomarkers. Our goal is to describe methodology that will increase concordance across laboratories, so that the broader research community is able to cross‐validate findings in parallel, accumulate large databases with normative data across the cognitive aging spectrum, and progress the application of this technology from the discovery stage to the validation stage in the search for sensitive and specific retinal biomarkers in AD. Methods: The proposed minimum data set framework is based on the Atlas of Retinal Imaging Study (ARIAS), an ongoing, longitudinal, multi‐site observational cohort study. However, the ARIAS protocol has been edited and refined with the expertise of all co‐authors, representing 16 institutions, and research groups from three countries, as a first step to address a pressing need identified by experts in neuroscience, neurology, optometry, and ophthalmology at the Retinal Imaging in Alzheimer\u27s Disease (RIAD) conference, convened by the Alzheimer\u27s Association and held in Washington, DC, in May 2019. Results: Our framework delineates specific imaging protocols and methods of analysis for imaging structural changes in retinal neuronal layers, with optional add‐on procedures of fundus autofluorescence to examine beta‐amyloid accumulation and optical coherence tomography angiography to examine AD‐related changes in the retinal vasculature. Discussion: This minimum data set represents a first step toward the standardization of retinal imaging data acquisition and analysis in cognitive aging and AD. A standardized approach is essential to move from discovery to validation, and to examine which retinal AD biomarkers may be more sensitive and specific for the different stages of the disease severity spectrum. This approach has worked for other biomarkers in the AD field, such as magnetic resonance imaging; amyloid positron emission tomography; and, more recently, blood proteomics. Potential context of use for retinal AD biomarkers is discussed

Systemic Delivery of Oncolytic Adenoviruses Targeting Transforming Growth Factor-β Inhibits Established Bone Metastasis in a Prostate Cancer Mouse Model

Abstract We have examined whether Ad.sT?RFc and TAd.sT?RFc, two oncolytic viruses expressing soluble transforming growth factor-? receptor II fused with human Fc (sTGF?RIIFc), can be developed to treat bone metastasis of prostate cancer. Incubation of PC-3 and DU-145 prostate tumor cells with Ad.sT?RFc and TAd.sT?RFc produced sTGF?RIIFc and viral replication; sTGF?RIIFc caused inhibition of TGF-?-mediated SMAD2 and SMAD3 phosphorylation. Ad(E1-).sT?RFc, an E1? adenovirus, produced sTGF?RIIFc but failed to replicate in tumor cells. To examine the antitumor response of adenoviral vectors, PC-3-luc cells were injected into the left heart ventricle of nude mice. On day 9, mice were subjected to whole-body bioluminescence imaging (BLI). Mice bearing hind-limb tumors were administered viral vectors via the tail vein on days 10, 13, and 17 (2.5?1010 viral particles per injection per mouse, each injection in a 0.1-ml volume), and subjected to BLI and X-ray radiography weekly until day 53. Ad.sT?RFc, TAd.sT?RFc, and Ad(E1-).sT?RFc caused significant inhibition of tumor growth; however, Ad.sT?RFc was the most effective among all the vectors. Only Ad.sT?RFc and TAd.sT?RFc inhibited tumor-induced hypercalcemia. Histomorphometric and synchrotron micro-computed tomographic analysis of isolated bones indicated that Ad.sT?RFc induced significant reduction in tumor burden, osteoclast number, and trabecular and cortical bone destruction. These studies suggest that Ad.sT?RFc and TAd.sT?RFc can be developed as potential new therapies for prostate cancer bone metastasis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98454/1/hum%2E2012%2E040.pd

Reclaiming heritage: colourization, culture wars and the politics of nostalgia

This article considers the discursive continuities between a specifically liberal defence of cultural patrimony, evident in the debate over film colourization, and the culture war critique associated with neo-conservatism. It examines how a rhetoric of nostalgia, linked to particular ideas of authenticity,canonicity and tradition,has been mobilized by the right and the left in attempts to stabilize the confguration and perceived transmission of American cultural identity. While different in scale, colourization and multiculturalism were seen to create respective (postmodern) barbarisms against which defenders of culture, heritage and good taste could unite. I argue that in its defence of the ‘classic’ work of art, together with principles of aesthetic distinction and the value of cultural inheritance,the anti-colourization lobby helped enrich and legitimize a discourse of tradition that, at the end of the 1980s, was beginning to reverberate powerfully in the conservative challenge to a ‘crisis’ within higher education and the humanities. This article attempts to complicate the contemporary politics of nostalgia, showing how a defence of cultural patrimony has distinguished major and minor culture wars, engaging left and right quite differently but with similar presuppositions

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment