Improving Earthquake Disaster Models with Post-Event Data: Insights from the 2015 Gorkha, Nepal Earthquake

Immense amounts of data are collected following earthquake disasters. Yet, it remains unclear how researchers’ might take full advantage of diverse post-disaster datasets. Using data from the 2015 Gorkha Nepal earthquake, this dissertation explores three ways in which post- disaster survey and assessment datasets can be used to inform models of seismic risk, vulnerability, and recovery processes. The first article presents an empirical analysis of scale issues in disaster vulnerability indices using a novel dataset of 750,000 households. This study finds that using aggregated household data to create social vulnerability indices can produce results that are meaningfully different from equivalent indices produced directly with household-level data. These results inform future development of vulnerability indices. The second article develops a Bayesian item-response theory modeling framework for estimating household-level reconstruction behavior from reconstruction progress surveys. This study provides a new way to quantitatively assess earthquake recovery, with results showing large differences in reconstruction probabilities among different levels of aid receipt, household willingness to commit additional resources, and geographic location. The final article uses engineering damage assessment data to develop a model for spatially interpolating geolocated clusters of rapid damage assessments onto a high-resolution grid. Incorporating ground truthed data significantly improves existing rapid estimates for completely damaged buildings and is feasible with the current scope of rapid damage assessment collection. Together, these contributions cast a vision for an improved disaster modeling ecosystem that more effectively integrates novel post-disaster data streams

Crowdsourced assessment of surgical skill proficiency in cataract surgery

OBJECTIVE: To test whether crowdsourced lay raters can accurately assess cataract surgical skills. DESIGN: Two-armed study: independent cross-sectional and longitudinal cohorts. SETTING: Washington University Department of Ophthalmology. PARTICIPANTS AND METHODS: Sixteen cataract surgeons with varying experience levels submitted cataract surgery videos to be graded by 5 experts and 300+ crowdworkers masked to surgeon experience. Cross-sectional study: 50 videos from surgeons ranging from first-year resident to attending physician, pooled by years of training. Longitudinal study: 28 videos obtained at regular intervals as residents progressed through 180 cases. Surgical skill was graded using the modified Objective Structured Assessment of Technical Skill (mOSATS). Main outcome measures were overall technical performance, reliability indices, and correlation between expert and crowd mean scores. RESULTS: Experts demonstrated high interrater reliability and accurately predicted training level, establishing construct validity for the modified OSATS. Crowd scores were correlated with (r = 0.865, p \u3c 0.0001) but consistently higher than expert scores for first, second, and third-year residents (p \u3c 0.0001, paired t-test). Longer surgery duration negatively correlated with training level (r = -0.855, p \u3c 0.0001) and expert score (r = -0.927, p \u3c 0.0001). The longitudinal dataset reproduced cross-sectional study findings for crowd and expert comparisons. A regression equation transforming crowd score plus video length into expert score was derived from the cross-sectional dataset (r CONCLUSIONS: Crowdsourced rankings correlated with expert scores, but were not equivalent; crowd scores overestimated technical competency, especially for novice surgeons. A novel approach of adjusting crowd scores with surgery duration generated a more accurate predictive model for surgical skill. More studies are needed before crowdsourcing can be reliably used for assessing surgical proficiency

Correction to: Emergence of knock-down resistance in the Anopheles gambiae complex in the Upper River Region, The Gambia, and its relationship with malaria infection in children.

Unfortunately, the original article [1] contained an error mistakenly carried forward by the Production department handling this article whereby some figures and their captions were interchanged. The correct figures (Figs. 1, 2, 3, 4, 5) and captions are presented in this erratum. The original article has also been updated to reflect this correction

The clonal evolution of metastatic colorectal cancer

Tumor heterogeneity and evolution drive treatment resistance in metastatic colorectal cancer (mCRC). Patient-derived xenografts (PDXs) can model mCRC biology; however, their ability to accurately mimic human tumor heterogeneity is unclear. Current genomic studies in mCRC have limited scope and lack matched PDXs. Therefore, the landscape of tumor heterogeneity and its impact on the evolution of metastasis and PDXs remain undefined. We performed whole-genome, deep exome, and targeted validation sequencing of multiple primary regions, matched distant metastases, and PDXs from 11 patients with mCRC. We observed intricate clonal heterogeneity and evolution affecting metastasis dissemination and PDX clonal selection. Metastasis formation followed both monoclonal and polyclonal seeding models. In four cases, metastasis-seeding clones were not identified in any primary region, consistent with a metastasis-seeding-metastasis model. PDXs underrepresented the subclonal heterogeneity of parental tumors. These suggest that single sample tumor sequencing and current PDX models may be insufficient to guide precision medicine

Freshwater Sponges Have Functional, Sealing Epithelia with High Transepithelial Resistance and Negative Transepithelial Potential

Epithelial tissue — the sealed and polarized layer of cells that regulates transport of ions and solutes between the environment and the internal milieu — is a defining characteristic of the Eumetazoa. Sponges, the most ancient metazoan phylum [1], [2], are generally believed to lack true epithelia [3], [4], [5], but their ability to occlude passage of ions has never been tested. Here we show that freshwater sponges (Demospongiae, Haplosclerida) have functional epithelia with high transepithelial electrical resistance (TER), a transepithelial potential (TEP), and low permeability to small-molecule diffusion. Curiously, the Amphimedon queenslandica sponge genome lacks the classical occluding genes [5] considered necessary to regulate sealing and control of ion transport. The fact that freshwater sponge epithelia can seal suggests that either occluding molecules have been lost in some sponge lineages, or demosponges use novel molecular complexes for epithelial occlusion; if the latter, it raises the possibility that mechanisms for occlusion used by sponges may exist in other metazoa. Importantly, our results imply that functional epithelia evolved either several times, or once, in the ancestor of the Metazoa

Expression and Functional Roles of Angiopoietin-2 in Skeletal Muscles

Angiopoietin-1 (ANGPT1) and angiopoietin-2 (ANGPT2) are angiogenesis factors that modulate endothelial cell differentiation, survival and stability. Recent studies have suggested that skeletal muscle precursor cells constitutively express ANGPT1 and adhere to recombinant ANGPT1 and ANGPT2 proteins. It remains unclear whether or not they also express ANGPT2, or if ANGPT2 regulates the myogenesis program of muscle precursors. In this study, ANGPT2 regulatory factors and the effects of ANGPT2 on proliferation, migration, differentiation and survival were identified in cultured primary skeletal myoblasts. The cellular networks involved in the actions of ANGPT2 on skeletal muscle cells were also analyzed.Primary skeletal myoblasts were isolated from human and mouse muscles. Skeletal myoblast survival, proliferation, migration and differentiation were measured in-vitro in response to recombinant ANGPT2 protein and to enhanced ANGPT2 expression delivered with adenoviruses. Real-time PCR and ELISA measurements revealed the presence of constitutive ANGPT2 expression in these cells. This expression increased significantly during myoblast differentiation into myotubes. In human myoblasts, ANGPT2 expression was induced by H(2)O(2), but not by TNFα, IL1β or IL6. ANGPT2 significantly enhanced myoblast differentiation and survival, but had no influence on proliferation or migration. ANGPT2-induced survival was mediated through activation of the ERK1/2 and PI-3 kinase/AKT pathways. Microarray analysis revealed that ANGPT2 upregulates genes involved in the regulation of cell survival, protein synthesis, glucose uptake and free fatty oxidation.Skeletal muscle precursors constitutively express ANGPT2 and this expression is upregulated during differentiation into myotubes. Reactive oxygen species exert a strong stimulatory influence on muscle ANGPT2 expression while pro-inflammatory cytokines do not. ANGPT2 promotes skeletal myoblast survival and differentiation. These results suggest that muscle-derived ANGPT2 production may play a positive role in skeletal muscle fiber repair

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

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

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