Alternative Approaches Can Reduce the Use of Test Animals under REACH.

Abstract not availableJRC.I-Institute for Health and Consumer Protection (Ispra

The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes

Traditionally, building‐level disaster risk reduction (DRR) measures are aimed at a single natural hazard. However, in many countries the society faces the threat of multiple hazards. Building‐level DRR measures that aim to decrease earthquake vulnerability can have opposing or conflicting effects on flood vulnerability, and vice versa. In a case study of Afghanistan, we calculate the risk of floods and earthquakes, in terms of average annual losses (AAL), in the current situation. Next, we develop two DRR scenarios, where building‐level measures to reduce flood and earthquake risk are implemented. We use this to identify districts for which DRR measures of one hazard increase the risk of another hazard. We then also calculate the optimal situation between the two scenarios by, for each district, selecting the DRR scenario for which the AAL as a ratio of the total exposure is lowest. Finally, we assess the sensitivity of the total risk to each scenario. The optimal measure differs spatially throughout Afghanistan, but in most districts it is more beneficial to take flood DRR measures. However, in the districts where it is more beneficial to take earthquake measures, the reduction in risk is considerable (up to 40%, while flood DRR measures lead to a reduction in risk by 16% in individual districts). The introduction of asynergies between DRR measures in risk analyses allows policy‐makers to spatially differentiate building codes and other building‐level DRR measures to address the most prevalent risk while not compromising the risk resulting from other hazards

A randomized trial provided new evidence on the accuracy and efficiency of traditional vs. electronically annotated abstraction approaches in systematic reviews

Abstract Objectives Data Abstraction Assistant (DAA) is a software for linking items abstracted into a data collection form for a systematic review to their locations in a study report. We conducted a randomized cross-over trial that compared DAA-facilitated single-data abstraction plus verification ("DAA verification"), single data abstraction plus verification ("regular verification"), and independent dual data abstraction plus adjudication ("independent abstraction"). Study Design and Setting This study is an online randomized cross-over trial with 26 pairs of data abstractors. Each pair abstracted data from six articles, two per approach. Outcomes were the proportion of errors and time taken. Results Overall proportion of errors was 17% for DAA verification, 16% for regular verification, and 15% for independent abstraction. DAA verification was associated with higher odds of errors when compared with regular verification (adjusted odds ratio [OR] = 1.08; 95% confidence interval [CI]: 0.99–1.17) or independent abstraction (adjusted OR = 1.12; 95% CI: 1.03–1.22). For each article, DAA verification took 20 minutes (95% CI: 1–40) longer than regular verification, but 46 minutes (95% CI: 26 to 66) shorter than independent abstraction. Conclusion Independent abstraction may only be necessary for complex data items. DAA provides an audit trail that is crucial for reproducible research

Exploiting Nucleotide Composition to Engineer Promoters

The choice of promoter is a critical step in optimizing the efficiency and stability of recombinant protein production in mammalian cell lines. Artificial promoters that provide stable expression across cell lines and can be designed to the desired strength constitute an alternative to the use of viral promoters. Here, we show how the nucleotide characteristics of highly active human promoters can be modelled via the genome-wide frequency distribution of short motifs: by overlapping motifs that occur infrequently in the genome, we constructed contiguous sequence that is rich in GC and CpGs, both features of known promoters, but lacking homology to real promoters. We show that snippets from this sequence, at 100 base pairs or longer, drive gene expression in vitro in a number of mammalian cells, and are thus candidates for use in protein production. We further show that expression is driven by the general transcription factors TFIIB and TFIID, both being ubiquitously present across cell types, which results in less tissue- and species-specific regulation compared to the viral promoter SV40. We lastly found that the strength of a promoter can be tuned up and down by modulating the counts of GC and CpGs in localized regions. These results constitute a “proof-of-concept” for custom-designing promoters that are suitable for biotechnological and medical applications

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

Costs of shoulder pain and resource use in primary health care: a cost-of-illness study in Sweden

<p>Abstract</p> <p>Background</p> <p>Painful shoulders pose a substantial socioeconomic burden. A prospective cost-of-illness study was performed to assess the costs associated with healthcare use and loss of productivity in patients with shoulder pain in primary health care in Sweden.</p> <p>Methods</p> <p>The study was performed in western Sweden, in a region with 24 000 inhabitants. Data were collected during six months from electronic patient records at three primary healthcare centres in two municipalities. All patients between 20 and 64 years of age who presented with shoulder pain to a general practitioner or a physiotherapist were included. Diagnostic codes were used for selection, and the cases were manually controlled. The cost for sick leave was calculated according to the human capital approach. Sensitivity analysis was used to explore uncertainty in various factors used in the model.</p> <p>Results</p> <p>204 (103 women) patients, mean age 48 (SD 11) years, were registered. Half of the cases were closed within six weeks, whereas 32 patients (16%) remained in the system for more than six months. A fifth of the patients were responsible for 91% of the total costs, and for 44% of the healthcare costs. The mean healthcare cost per patient was €326 (SD 389) during six months. Physiotherapy treatments accounted for 60%. The costs for sick leave contributed to 84% of the total costs. The mean annual total cost was €4139 per patient. Estimated costs for secondary care increased the total costs by one third.</p> <p>Conclusions</p> <p>The model applied in this study provides valuable information that can be used in cost evaluations. Costs for secondary care and particularly for sick leave have a major influence on total costs and interventions that can reduce long periods of sick leave are warranted.</p