Angoff anchor statements: setting a flawed gold standard?

http://www.mededpublish.org/manuscripts/120

Identification of Variegated Coloring in Skin Tumors: Neural Network vs. Rule-Based Induction Methods

The use of neural networks for automatic identification of variegated coloring, which is believed to be one of the most predictive features for malignant melanoma, is described. The Nestor development system (NDS) was chosen for neural network implementation. At the heart of NDS is a three-layer neural network called a restricted Coulomb energy (RCE) network. The learning scheme and the database for detection of variegated coloring are discussed. Results are reporte

Mutations in CHMP2B in lower motor neuron predominant amyotrophic lateral sclerosis (ALS)

Background: Amyotrophic lateral sclerosis (ALS), a common late-onset neurodegenerative disease, is associated with fronto-temporal dementia (FTD) in 3-10% of patients. A mutation in CHMP2B was recently identified in a Danish pedigree with autosomal dominant FTD. Subsequently, two unrelated patients with familial ALS, one of whom also showed features of FTD, were shown to carry missense mutations in CHMP2B. The initial aim of this study was to determine whether mutations in CHMP2B contribute more broadly to ALS pathogenesis. Methodology/Principal Findings: Sequencing of CHMP2B in 433 ALS cases from the North of England identified 4 cases carrying 3 missense mutations, including one novel mutation, p. Thr104Asn, none of which were present in 500 neurologically normal controls. Analysis of clinical and neuropathological data of these 4 cases showed a phenotype consistent with the lower motor neuron predominant (progressive muscular atrophy (PMA)) variant of ALS. Only one had a recognised family history of ALS and none had clinically apparent dementia. Microarray analysis of motor neurons from CHMP2B cases, compared to controls, showed a distinct gene expression signature with significant differential expression predicting disassembly of cell structure; increased calcium concentration in the ER lumen; decrease in the availability of ATP; down-regulation of the classical and p38 MAPK signalling pathways, reduction in autophagy initiation and a global repression of translation. Transfection of mutant CHMP2B into HEK-293 and COS-7 cells resulted in the formation of large cytoplasmic vacuoles, aberrant lysosomal localisation demonstrated by CD63 staining and impairment of autophagy indicated by increased levels of LC3-II protein. These changes were absent in control cells transfected with wild-type CHMP2B. Conclusions/Significance: We conclude that in a population drawn from North of England pathogenic CHMP2B mutations are found in approximately 1% of cases of ALS and 10% of those with lower motor neuron predominant ALS. We provide a body of evidence indicating the likely pathogenicity of the reported gene alterations. However, absolute confirmation of pathogenicity requires further evidence, including documentation of familial transmission in ALS pedigrees which might be most fruitfully explored in cases with a LMN predominant phenotype

Exploring what lies behind public preferences for avoiding health losses caused by lapses in healthcare safety and patient lifestyle choices

© 2013 Singh et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.Background: Although many studies have identified public preferences for prioritising health care interventions based on characteristics of recipient or care, very few of them have examined the reasons for the stated preferences. We conducted an on-line person trade-off (PTO) study (N=1030) to investigate whether the public attach a premium to the avoidance of ill health associated with alternative types of responsibilities: lapses in healthcare safety, those caused by individual action or lifestyle choice; or genetic conditions. We found that the public gave higher priority to prevention of harm in a hospital setting such as preventing hospital associated infections than genetic disorder but drug administration errors were valued similar to genetic disorders. Prevention of staff injuries, lifestyle diseases and sports injuries, were given lower priority. In this paper we aim to understand the reasoning behind the responses by analysing comments provided by respondents to the PTO questions. Method: A majority of the respondents who participated in the survey provided brief comments explaining preferences in free text responses following PTO questions. This qualitative data was transformed into explicit codes conveying similar meanings. An overall coding framework was developed and a reliability test was carried out. Recurrent patterns were identified in each preference group. Comments which challenged the assumptions of hypothetical scenarios were also investigated. Results: NHS causation of illness and a duty of care were the most cited reasons to prioritise lapses in healthcare safety. Personal responsibility dominated responses for lifestyle related contexts, and many respondents mentioned that health loss was the result of the individual’s choice to engage in risky behaviour. A small proportion of responses questioned the assumptions underlying the PTO questions. However excluding these from the main analysis did not affect the conclusions. Conclusion: Although some responses indicated misunderstanding or rejection of assumptions we put forward, the results were still robust. The reasons put forward for responses differed between comparisons but responsibility was the most frequently cited. Most preference elicitation studies only focus on eliciting numerical valuations but allowing for qualitative data can augment understanding of preferences as well as verifying results.EPSRC through the MATCH programme(EP/F063822/1 and EP/G012393/1) and HERG within Brunel University

Homochiral self-sorted and emissive IrIII metallo-cryptophanes

We thank the EPSRC (DTG award 1238852, EP/K039202/1, EP/M02105X/1, EP/J001325/1), Leverhulme Trust (RPG-2014-148), University of St Andrews, and the MEXT/JSPS Grants in Aid for Scientific Research (JP25102005 and JP25102001) for funding; Simon Barrett for assistance with NMR; Martin Huscroft for assistance with HPLC, and Stephen Boyer for elemental analysis measurements.The racemic ligands (±)-tris(isonicotinoyl)-cyclotriguaiacylene (L1), or (±)-tris(4-pyridyl-methyl)-cyclotriguaiacylene (L2) assemblewith racemic (Λ, Δ)- [Ir(ppy)2(MeCN)2]+, in which ppy = 2-phenylpyridinato to form [{Ir(ppy)2}3(L)2]3+ metallo-cryptophane cages. The crystal structure of [{Ir(ppy)2}3(L1)2]∙3BF4 has MM-ΛΛΛ nd PP-ΔΔΔ isomers, and homochiral self-sorting occurs in solution, a processaccelerated by a chiral guest. Self-recognition between L1 and L2 within cagesdoes not occur, and cages show very slow ligand-exchange. Both cages are phosphorescent,with [{Ir(ppy)2}3(L2)2]3+ havingenhanced and blue-shifted emission when compared with [{Ir(ppy)2}3(L1)2]3+ .PostprintPeer reviewe

Balancing equity and efficiency in the Dutch basic benefits package using the principle of proportional shortfall

Economic evaluations are increasingly used to inform decisions regarding the allocation of scarce health care resources. To systematically incorporate societal preferences into these evaluations, quality-adjusted life year gains could be weighted according to some equity principle, the most suitable of which is a matter of frequent debate. While many countries still struggle with equity concerns for priority setting in health care, the Netherlands has reached a broad consensus to use the concept of proportional shortfall. Our study evaluates the concept and its support in the Dutch health care context. We discuss arguments in the Netherlands for using proportional shortfall and difficulties in transitioning from principle to practice. In doing so, we address universal issues leading to a systematic consideration of equity concerns for priority setting in health care. The article thus has relevance to all countries struggling with the formalization of equity concerns for priority setting

MesoGraph: automatic profiling of mesothelioma subtypes from histological images

Mesothelioma is classified into three histological subtypes, epithelioid, sarcomatoid, and biphasic, according to the relative proportions of epithelioid and sarcomatoid tumor cells present. Current guidelines recommend that the sarcomatoid component of each mesothelioma is quantified, as a higher percentage of sarcomatoid pattern in biphasic mesothelioma shows poorer prognosis. In this work, we develop a dual-task graph neural network (GNN) architecture with ranking loss to learn a model capable of scoring regions of tissue down to cellular resolution. This allows quantitative profiling of a tumor sample according to the aggregate sarcomatoid association score. Tissue is represented by a cell graph with both cell-level morphological and regional features. We use an external multicentric test set from Mesobank, on which we demonstrate the predictive performance of our model. We additionally validate our model predictions through an analysis of the typical morphological features of cells according to their predicted score

Malignant Mesothelioma subtyping via sampling driven multiple instance prediction on tissue image and cell morphology data

Malignant Mesothelioma is a difficult to diagnose and highly lethal cancer usually associated with asbestos exposure. It can be broadly classified into three subtypes: Epithelioid, Sarcomatoid, and a hybrid Biphasic subtype in which significant components of both of the previous subtypes are present. Early diagnosis and identification of the subtype informs treatment and can help improve patient outcome. However, the subtyping of malignant mesothelioma, and specifically the recognition of transitional features from routine histology slides has a high level of inter-observer variability. In this work, we propose an end-to-end multiple instance learning (MIL) approach for malignant mesothelioma subtyping. This uses an adaptive instance-based sampling scheme for training deep convolutional neural networks on bags of image patches that allows learning on a wider range of relevant instances compared to max or top-N based MIL approaches. We also investigate augmenting the instance representation to include aggregate cellular morphology features from cell segmentation. The proposed MIL approach enables identification of malignant mesothelial subtypes of specific tissue regions. From this a continuous characterisation of a sample according to predominance of sarcomatoid vs epithelioid regions is possible, thus avoiding the arbitrary and highly subjective categorisation by currently used subtypes. Instance scoring also enables studying tumor heterogeneity and identifying patterns associated with different subtypes. We have evaluated the proposed method on a dataset of 234 tissue micro-array cores with an AUROC of 0.89±0.05 for this task. The dataset and developed methodology is available for the community at: https://github.com/measty/PINS