503 research outputs found

    A paediatric bone index derived by automated radiogrammetry

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    Hand radiographs are obtained routinely to determine bone age of children. This paper presents a method that determines a Paediatric Bone Index automatically from such radiographs. The Paediatric Bone Index is designed to have minimal relative standard deviation (7.5%), and the precision is determined to be 1.42%. Introduction We present a computerised method to determine bone mass of children based on hand radiographs, including a reference database for normal Caucasian children. Methods Normal Danish subjects (1,867), of ages 7-17, and 531 normal Dutch subjects of ages 5-19 were included. Historically, three different indices of bone mass have been used in radiogrammetry all based on A = pi TW(1 - T/W), where T is the cortical thickness and W the bone width. The indices are the metacarpal index A/W-2, DXR-BMD=A/W, and Exton-Smith's index A/(WL), where L is the length of the bone. These indices are compared with new indices of the form A/((WLb)-L-a), and it is argued that the preferred index has minimal SD relative to the mean value at each bone age and sex. Finally, longitudinal series of X-rays of 20 Japanese children are used to derive the precision of the measurements. Results The preferred index is A/((WL0.33)-L-1.33), which is named the Paediatric Bone Index, PBI. It has mean relative SD 7.5% and precision 1.42%. Conclusions As part of the BoneXpert method for automated bone age determination, our method facilitates retrospective research studies involving validation of the proposed index against fracture incidence and adult bone mineral densit

    An analysis of simple computational strategies to facilitate the design of functional molecular information processors

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    BACKGROUND: Biological macromolecules (DNA, RNA and proteins) are capable of processing physical or chemical inputs to generate outputs that parallel conventional Boolean logical operators. However, the design of functional modules that will enable these macromolecules to operate as synthetic molecular computing devices is challenging. RESULTS: Using three simple heuristics, we designed RNA sensors that can mimic the function of a seven-segment display (SSD). Ten independent and orthogonal sensors representing the numerals 0 to 9 are designed and constructed. Each sensor has its own unique oligonucleotide binding site region that is activated uniquely by a specific input. Each operator was subjected to a stringent in silico filtering. Random sensors were selected and functionally validated via ribozyme self cleavage assays that were visualized via electrophoresis. CONCLUSIONS: By utilising simple permutation and randomisation in the sequence design phase, we have developed functional RNA sensors thus demonstrating that even the simplest of computational methods can greatly aid the design phase for constructing functional molecular devices. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1297-x) contains supplementary material, which is available to authorized users

    Use of the gamma method for self-contained gene-set analysis of SNP data

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    Gene-set analysis (GSA) evaluates the overall evidence of association between a phenotype and all genotyped single nucleotide polymorphisms (SNPs) in a set of genes, as opposed to testing for association between a phenotype and each SNP individually. We propose using the Gamma Method (GM) to combine gene-level P-values for assessing the significance of GS association. We performed simulations to compare the GM with several other self-contained GSA strategies, including both one-step and two-step GSA approaches, in a variety of scenarios. We denote a ‘one-step' GSA approach to be one in which all SNPs in a GS are used to derive a test of GS association without consideration of gene-level effects, and a ‘two-step' approach to be one in which all genotyped SNPs in a gene are first used to evaluate association of the phenotype with all measured variation in the gene and then the gene-level tests of association are aggregated to assess the GS association with the phenotype. The simulations suggest that, overall, two-step methods provide higher power than one-step approaches and that combining gene-level P-values using the GM with a soft truncation threshold between 0.05 and 0.20 is a powerful approach for conducting GSA, relative to the competing approaches assessed. We also applied all of the considered GSA methods to data from a pharmacogenomic study of cisplatin, and obtained evidence suggesting that the glutathione metabolism GS is associated with cisplatin drug response

    Edge localized mode control with an edge resonant magnetic perturbation

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    A low amplitude (δbr∕BT=1 part in 5000) edge resonantmagnetic field perturbation with toroidalmode number n=3 and poloidal mode numbers between 8 and 15 has been used to suppress most large type I edge localized modes(ELMs) without degrading core plasma confinement. ELMs have been suppressed for periods of up to 8.6 energy confinement times when the edge safety factor q95 is between 3.5 and 4. The large ELMs are replaced by packets of events (possibly type II ELMs) with small amplitude, narrow radial extent, and a higher level of magnetic field and density fluctuations, creating a duty cycle with long “active” intervals of high transport and short “quiet” intervals of low transport. The increased transport associated with these events is less impulsive and slows the recovery of the pedestal profiles to the values reached just before the large ELMs without the n=3 perturbation. Changing the toroidal phase of the perturbation by 60° with respect to the best ELM suppression case reduces the ELM amplitude and frequency by factors of 2–3 in the divertor, produces a more stochastic response in the H-mode pedestal profiles, and displays similar increases in small scale events, although significant numbers of large ELMs survive. In contrast to the best ELM suppression case where the type I ELMs are also suppressed on the outboard midplane, the midplane recycling increases until individual ELMs are no longer discernable. The ELM response depends on the toroidal phase of the applied perturbation because intrinsic error fields make the target plasma nonaxisymmetric, and suggests that at least some of the variation in ELM behavior in a single device or among different devices is due to differences in the intrinsic error fields in these devices. These results indicate that ELMs can be suppressed by small edge resonantmagnetic field perturbations. Extrapolation to next-step burning plasma devices will require extending the regime of operation to lower collisionality and understanding the physical mechanism responsible for the ELM suppression.This work was funded by the U.S. Department of Energy under Grant Nos. DE-FC02-04ER54698, DE-FG02- 04ER54758, DE-FG03-01ER54615, W-7405-ENG-48, DEFG03-96ER54373, DE-FG02-89ER53297, DE-AC05- 00OR22725, and DE-AC04-94AL85000

    Children in reviews: Methodological issues in child-relevant evidence syntheses

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    BACKGROUND: The delivery of optimal medical care to children is dependent on the availability of child relevant research. Our objectives were to: i) systematically review and describe how children are handled in reviews of drug interventions published in the Cochrane Database of Systematic Reviews (CDSR); and ii) determine when effect sizes for the same drug interventions differ between children and adults. METHODS: We systematically identified all of the reviews relevant to child health in the CDSR 2002, Issue 4. Reviews were included if they investigated the efficacy or effectiveness of a drug intervention for a condition that occurs in both children and adults. Information was extracted on review characteristics including study methods, results, and conclusions. RESULTS: From 1496 systematic reviews, 408 (27%) were identified as relevant to both adult and child health; 52% (213) of these included data from children. No significant differences were found in effect sizes between adults and children for any of the drug interventions or conditions investigated. However, all of the comparisons lacked the power to detect a clinically significant difference and wide confidence intervals suggest important differences cannot be excluded. A large amount of data was unavailable due to inadequate reporting at the trial and systematic review level. CONCLUSION: Overall, the findings of this study indicate there is a paucity of child-relevant and specific evidence generated from evidence syntheses of drug interventions. The results indicate a need for a higher standard of reporting for participant populations in studies of drug interventions

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

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    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

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    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

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    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
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