Application Of Atmospheric Correction To Hyperspectral Data: Comparisons Of Different Techniques On Hymap Data

(c) 2004 Ian C Lauhttp://trove.nla.gov.au/work/765806

Testing Protein Leverage in Lean Humans: A Randomised Controlled Experimental Study

A significant contributor to the rising rates of human obesity is an increase in energy intake. The ‘protein leverage hypothesis’ proposes that a dominant appetite for protein in conjunction with a decline in the ratio of protein to fat and carbohydrate in the diet drives excess energy intake and could therefore promote the development of obesity. Our aim was to test the ‘protein leverage hypothesis’ in lean humans by disguising the macronutrient composition of foods offered to subjects under ad libitum feeding conditions. Energy intakes and hunger ratings were measured for 22 lean subjects studied over three 4-day periods of in-house dietary manipulation. Subjects were restricted to fixed menus in random order comprising 28 foods designed to be similar in palatability, availability, variety and sensory quality and providing 10%, 15% or 25% energy as protein. Nutrient and energy intake was calculated as the product of the amount of each food eaten and its composition. Lowering the percent protein of the diet from 15% to 10% resulted in higher (+12±4.5%, p = 0.02) total energy intake, predominantly from savoury-flavoured foods available between meals. This increased energy intake was not sufficient to maintain protein intake constant, indicating that protein leverage is incomplete. Urinary urea on the 10% and 15% protein diets did not differ statistically, nor did they differ from habitual values prior to the study. In contrast, increasing protein from 15% to 25% did not alter energy intake. On the fourth day of the trial, however, there was a greater increase in the hunger score between 1–2 h after the 10% protein breakfast versus the 25% protein breakfast (1.6±0.4 vs 25%: 0.5±0.3, p = 0.005). In our study population a change in the nutritional environment that dilutes dietary protein with carbohydrate and fat promotes overconsumption, enhancing the risk for potential weight gain

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

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

Zürich Statement on Future Actions on Per- and Polyfluoroalkyl Substances (PFASs).

Per- and polyfluoroalkyl substances (PFASs) are man-made chemicals that contain at least one perfluoroalkyl moiety, [Formula: see text]. To date, over 4,000 unique PFASs have been used in technical applications and consumer products, and some of them have been detected globally in human and wildlife biomonitoring studies. Because of their extraordinary persistence, human and environmental exposure to PFASs will be a long-term source of concern. Some PFASs such as perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) have been investigated extensively and thus regulated, but for many other PFASs, knowledge about their current uses and hazards is still very limited or missing entirely. To address this problem and prepare an action plan for the assessment and management of PFASs in the coming years, a group of more than 50 international scientists and regulators held a two-day workshop in November, 2017. The group identified both the respective needs of and common goals shared by the scientific and the policy communities, made recommendations for cooperative actions, and outlined how the science-policy interface regarding PFASs can be strengthened using new approaches for assessing and managing highly persistent chemicals such as PFASs. https://doi.org/10.1289/EHP4158