1,023 research outputs found

    Cytotoxic edema associated with hemorrhage predicts poor outcome after traumatic brain injury

    Get PDF
    Magnetic resonance imaging (MRI) is rarely used in the acute evaluation of traumatic brain injury (TBI), but may identify findings of clinical importance not detected by computed tomography (CT). We aimed to characterize the association of cytotoxic edema and hemorrhage, including traumatic microbleeds, on MRI obtained within hours of acute head trauma and investigated the relationship to clinical outcomes. Patients prospectively enrolled in the Traumatic Head Injury Neuroimaging Classification study (NCT01132937) with evidence of diffusion-related findings or hemorrhage on neuroimaging were included. Blinded interpretation of MRI for diffusion-weighted imaging and hemorrhage was conducted, with subsequent quantification of apparent diffusion coefficient (ADC) values. Of 161 who met criteria, 82 patients had conspicuous hyperintense lesions on diffusion-weighted imaging (DWI) with corresponding regions of hypointense ADC in proximity to hemorrhage. Median time from injury to MRI was 21 (10-30) hours. Median ADC values per patient grouped by time from injury to MRI were lowest within 24 hours after injury. ADC values associated with hemorrhagic lesions are lowest early after injury, with an increase in diffusion during the subacute period, suggesting transformation from cytotoxic to vasogenic edema during the subacute post-injury period. Of 118 patients with outcome data, 60 had Glasgow Outcome Scale Extended <6 at 30/90 days post-injury. Cytotoxic edema on MRI (OR 2.91 [1.32-6.37], P=0.008) and TBI severity (OR 2.51 [1.32-4.74], P=0.005) were independent predictors of outcome. These findings suggest that in TBI patients with findings of hemorrhage on CT, patients with DWI/ADC lesions on MRI are more likely to do worse

    Changes in Plasma von Willebrand Factor and Cellular Fibronectin in MRI-Defined Traumatic Microvascular Injury

    Get PDF
    The neuropathology of traumatic brain injury (TB) is diverse, including primary injury to neurons, axons, glial cells, vascular structures, and secondary processes, such as edema and inflammation that vary between individual patients. Traumatic microvascular injury is an important endophenotype of TBI-related injury. We studied patients who sustained a TBI requiring ER evaluation and had an MRI performed within 48 h of injury. We classified patients into 3 groups based on their MRI findings: (1) those that had evidence of traumatic microvascular injury on susceptibility or diffusion weighted MRI sequences without frank hemorrhage [Traumatic Vascular Injury (TVI) group; 20 subjects]. (2) those who had evidence of intraparenchymal, subdural, epidural, or subarachnoid hemorrhage [Traumatic Hemorrhage (TH) group; 26 subjects], and (3) those who had no traumatic injuries detected by MRI [MRI-negative group; 30 subjects]. We then measured plasma protein biomarkers of vascular injury [von Willebrand Factor (vWF) or cellular fibronectin (cFn)] and axonal injury (phosphorylated neurofilament heavy chain; pNF-H). We found that the TVI group was characterized by decreased expression of plasma vWF (p &lt; 0.05 compared to MRI-negative group; p &lt; 0.00001 compared to TH group) ≤48 h after injury. cFN was no different between groups ≤48 h after injury, but was increased in the TVI group compared to the MRI-negative (p &lt; 0.00001) and TH (p &lt; 0.00001) groups when measured &gt;48 h from injury. pNF-H was increased in both the TH and TVI groups compared to the MRI-negative group ≤48 h from injury. When we used the MRI grouping and molecular biomarkers in a model to predict Glasgow Outcome Scale-Extended (GOS-E) score at 30–90 days, we found that inclusion of the imaging data and biomarkers substantially improved the ability to predict a good outcome over clinical information alone. These data indicate that there is a distinct, vascular-predominant endophenotype in a subset of patients who sustain a TBI and that these injuries are characterized by a specific biomarker profile. Further work to will be needed to determine whether these biomarkers can be useful as predictive and pharmacodynamic biomarkers for vascular-directed therapies after TBI

    “Excellence R Us”: university research and the fetishisation of excellence

    Get PDF
    The rhetoric of “excellence” is pervasive across the academy. It is used to refer to research outputs as well as researchers, theory and education, individuals and organisations, from art history to zoology. But does “excellence” actually mean anything? Does this pervasive narrative of “excellence” do any good? Drawing on a range of sources we interrogate “excellence” as a concept and find that it has no intrinsic meaning in academia. Rather it functions as a linguistic interchange mechanism. To investigate whether this linguistic function is useful we examine how the rhetoric of excellence combines with narratives of scarcity and competition to show that the hypercompetition that arises from the performance of “excellence” is completely at odds with the qualities of good research. We trace the roots of issues in reproducibility, fraud, and homophily to this rhetoric. But we also show that this rhetoric is an internal, and not primarily an external, imposition. We conclude by proposing an alternative rhetoric based on soundness and capacity-building. In the final analysis, it turns out that that “excellence” is not excellent. Used in its current unqualified form it is a pernicious and dangerous rhetoric that undermines the very foundations of good research and scholarship

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

    Get PDF
    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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

    Get PDF
    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

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

    Get PDF
    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 Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

    Get PDF
    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

    Get PDF
    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

    Crafting organization

    Full text link
    The recent shift in attention away from organization studies as science has allowed for consideration of new ways of thinking about both organization and organizing and has led to several recent attempts to \u27bring down\u27 organizational theorizing. In this paper, we extend calls for organization to be represented as a creative process by considering organization as craft. Organizational craft, we argue, is attractive, accessible, malleable, reproducible, and marketable. It is also a tangible way of considering organization studies with irreverence. We draw on the hierarchy of distinctions among fine art, decorative art, and craft to suggest that understanding the organization of craft assists in complicating our understanding of marginality. We illustrate our argument by drawing on the case of a contemporary Australian craftworks and marketplace known initially as the Meat Market Craft Centre (\u27MMCC\u27) and then, until its recent closure, as Metro! &Dagger; Stella Minahan was a board member and then the Chief Executive Officer of the Metro! Craft Centre.<br /
    corecore