Evolution of oesophageal adenocarcinoma from metaplastic columnar epithelium without goblet cells in Barrett's oesophagus

Supported by the Dutch Cancer Society (KWF) and Cancer Research UK (CR-UK). This work was supported by Cancer Research UK (grant number A14895

Histopathologist Features Predictive of Diagnostic Concordance at Expert Level Amongst a Large International Sample of Pathologists Diagnosing Barrett’s Dysplasia Using Digital Pathology

Objective Guidelines mandate expert pathology review of Barrett’s oesophagus (BO) biopsies that reveal dysplasia, but there are no evidence-based standards to corroborate expert reviewer status. We investigated BO concordance rates and pathologist features predictive of diagnostic discordance. Design Pathologists (n=51) from over 20 countries assessed 55 digitised BO biopsies from across the diagnostic spectrum, before and after viewing matched p53 labelling. Extensive demographic and clinical experience data were obtained via online questionnaire. Reference diagnoses were obtained from a review panel (n=4) of experienced Barrett’s pathologists. Results We recorded over 6000 case diagnoses with matched demographic data. Of 2805H&E diagnoses, we found excellent concordance (>70%) for nondysplastic BO and high-grade dysplasia, and intermediate concordance for low-grade dysplasia (42%) and indefinite for dysplasia (23%). Major diagnostic errors were found in 248 diagnoses (8.8%), which reduced to 232 (8.3%) after viewing p53 labelled slides. Demographic variables correlating with diagnostic proficiency were analysed in multivariate analysis, which revealed that at least 5 years of professional experience was protective against major diagnostic error for H&E slide review (OR 0.48, 95% CI 0.31 to 0.74). Working in a non-teaching hospital was associated with increased odds of major diagnostic error (OR 1.76, 95% CI 1.15 to 2.69); however, this was neutralised when pathologists viewed p53 labelled slides. Notably, neither case volume nor self-identifying as an expert predicted diagnostic proficiency. Extrapolating our data to real-world case prevalence suggests that 92.3% of major diagnostic errors are due to overinterpreting non-dysplastic BO. Conclusion Our data provide evidence-based criteria for diagnostic proficiency in Barrett’s histopathology

How functional programming mattered

In 1989 when functional programming was still considered a niche topic, Hughes wrote a visionary paper arguing convincingly ‘why functional programming matters’. More than two decades have passed. Has functional programming really mattered? Our answer is a resounding ‘Yes!’. Functional programming is now at the forefront of a new generation of programming technologies, and enjoying increasing popularity and influence. In this paper, we review the impact of functional programming, focusing on how it has changed the way we may construct programs, the way we may verify programs, and fundamentally the way we may think about programs

EUROmediCAT signal detection: an evaluation of selected congenital anomaly-medication associations

To evaluate congenital anomaly (CA)-medication exposure associations produced by the new EUROmediCAT signal detection system and determine which require further investigation. Data from 15 EUROCAT registries (1995-2011) with medication exposures at the chemical substance (5th level of Anatomic Therapeutic Chemical classification) and chemical subgroup (4th level) were analysed using a 50% false detection rate. After excluding antiepileptics, antidiabetics, antiasthmatics and SSRIs/psycholeptics already under investigation, 27 associations were evaluated. If evidence for a signal persisted after data validation, a literature review was conducted for prior evidence of human teratogenicity. Thirteen out of 27 CA-medication exposure signals, based on 389 exposed cases, passed data validation. There was some prior evidence in the literature to support six signals (gastroschisis and levonorgestrel/ethinylestradiol (OR 4.10, 95% CI 1.70-8.53; congenital heart disease/pulmonary valve stenosis and nucleoside/tide reverse transcriptase inhibitors (OR 5.01, 95% CI 1.99-14.20/OR 28.20, 95% CI 4.63-122.24); complete absence of a limb and pregnen (4) derivatives (OR 6.60, 95% CI 1.70-22.93); hypospadias and pregnadien derivatives (OR 1.40, 95% CI 1.10-1.76); hypospadias and synthetic ovulation stimulants (OR 1.89, 95% CI 1.28-2.70). Antipropulsives produced a signal for syndactyly while the literature revealed a signal for hypospadias. There was no prior evidence to support the remaining six signals involving the ordinary salt combinations, propulsives, bulk-forming laxatives, hydrazinophthalazine derivatives, gonadotropin releasing hormone analogues and selective serotonin agonists. Signals which strengthened prior evidence should be prioritized for further investigation, and independent evidence sought to confirm the remaining signals. Some chance associations are expected and confounding by indication is possible

Stepwise classification of cancer samples using clinical and molecular data

<p>Abstract</p> <p>Background</p> <p>Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other. Second, the need to measure both data types for all patients may be both unpractical and (cost) inefficient.</p> <p>Results</p> <p>We introduce a novel classification method, a stepwise classifier, which takes advantage of the distinct classification power of clinical data and high-dimensional molecular data. We apply classification algorithms to two data types independently, starting with the traditional clinical risk factors. We only turn to relatively expensive molecular data when the uncertainty of prediction result from clinical data exceeds a predefined limit. Experimental results show that our approach is adaptive: the proportion of samples that needs to be re-classified using molecular data depends on how much we expect the predictive accuracy to increase when re-classifying those samples.</p> <p>Conclusions</p> <p>Our method renders a more cost-efficient classifier that is at least as good, and sometimes better, than one based on clinical or molecular data alone. Hence our approach is not just a classifier that minimizes a particular loss function. Instead, it aims to be cost-efficient by avoiding molecular tests for a potentially large subgroup of individuals; moreover, for these individuals a test result would be quickly available, which may lead to reduced waiting times (for diagnosis) and hence lower the patients distress. Stepwise classification is implemented in R-package <it>stepwiseCM </it>and available at the Bioconductor website.</p

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Spatially organizing future genders: an artistic intervention in the creation of a hir-toilet

Toilets, a neglected facility in the study of human relations at work and beyond, have become increasingly important in discussions about future experiences of gender diversity. To further investigate the spatial production of gender and its potential expressions, we transformed a unisex single-occupancy toilet at Uppsala University into an all-gender or ‘hir-toilet’.1 With the aim to disrupt and expose the dominant spatial organization of the two binary genders, we inaugurated the hir-toilet with the help of a performance artist. We describe and analyse internal and external responses thereto, using Lefebvre’s work on dialectics and space. Focusing on how space is variously lived, conceived and perceived, our analysis questions the very rationale of gender categorizations. The results contribute to a renewed critique of binary thinking in the organization of workplaces by extending our understanding of how space and human relations mutually constitute each other