A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density

Breast Cancer Now. Grant Number: 2015MayPR515National Institute for Health Research. Grant Numbers: IS‐BRC‐1215‐20007, NF‐SI‐0513‐10076Prevent Breast Cancer. Grant Numbers: GA09‐002, GA11‐002Cancer Research UK. Grant Numbers: C1287/A10118, C1287/A16563, C569/A16891National Institutes of Health. Grant Numbers: X01HG007492, U19 CA148065Canadian Institutes of Health Research. Grant Number: GPH‐129344Horizon 2020 Research and Innovation Programme. Grant Numbers: 634935, 633784European Union. Grant Number: HEALTH‐F2‐2009‐22317

Prediction of reader estimates of mammographic density using convolutional neural networks.

Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.Mammographic density is an important risk factor for breast cancer. In recent research, percentage density assessed visually using visual analogue scales (VAS) showed stronger risk prediction than existing automated density measures, suggesting readers may recognize relevant image features not yet captured by hand-crafted algorithms. With deep learning, it may be possible to encapsulate this knowledge in an automatic method. We have built convolutional neural networks (CNN) to predict density VAS scores from full-field digital mammograms. The CNNs are trained using whole-image mammograms, each labeled with the average VAS score of two independent readers. Each CNN learns a mapping between mammographic appearance and VAS score so that at test time, they can predict VAS score for an unseen image. Networks were trained using 67,520 mammographic images from 16,968 women and for model selection we used a dataset of 73,128 images. Two case-control sets of contralateral mammograms of screen detected cancers and prior images of women with cancers detected subsequently, matched to controls on age, menopausal status, parity, HRT and BMI, were used for evaluating performance on breast cancer prediction. In the case-control sets, odd ratios of cancer in the highest versus lowest quintile of percentage density were 2.49 (95% CI: 1.59 to 3.96) for screen-detected cancers and 4.16 (2.53 to 6.82) for priors, with matched concordance indices of 0.587 (0.542 to 0.627) and 0.616 (0.578 to 0.655), respectively. There was no significant difference between reader VAS and predicted VAS for the prior test set (likelihood ratio chi square, p = 0.134 ). Our fully automated method shows promising results for cancer risk prediction and is comparable with human performance.This paper presents independent research funded by NIHR under its Programme Grants for Applied Research programme (reference number RP-PG-0707-10031: “Improvement in risk prediction, early detection and prevention of breast cancer”) with additional funding from the Prevent Breast Cancer Appeal and supported by the NIHR Manchester Biomedical Research Centre Award No. IS-BRC-1215-20007

Identifying cellular signalling molecules in developmental disorders of the brain: Evidence from focal cortical dysplasia and tuberous sclerosis

AIMS: We understand little of the pathogenesis of developmental cortical lesions, because we understand little of the diversity of the cell types that contribute to the diseases or how those cells interact. We tested the hypothesis that cellular diversity and cell–cell interactions play an important role in these disorders by investigating the signalling molecules in the commonest cortical malformations that lead to childhood epilepsy, focal cortical dysplasia (FCD) and tuberous sclerosis (TS). METHODS: Transcriptional profiling clustered cases into molecularly distinct groups. Using gene expression data, we identified the secretory signalling molecules in FCD/TS and characterised the cell types expressing these molecules. We developed a functional model using organotypic cultures. RESULTS: We identified 113 up-regulated secretory molecules in FCDIIB/TS. The top 12 differentially expressed genes (DEGs) were validated by immunohistochemistry. This highlighted two molecules, Chitinase 3-like protein 1 (CHI3L1) and C-C motif chemokine ligand 2 (CCL2) (MCP1) that were expressed in a unique population of small cells in close proximity to balloon cells (BC). We then characterised these cells and developed a functional model in organotypic slice cultures. We found that the number of CHI3L1 and CCL2 expressing cells decreased following inhibition of mTOR, the main aberrant signalling pathway in TS and FCD. CONCLUSIONS: Our findings highlight previously uncharacterised small cell populations in FCD and TS which express specific signalling molecules. These findings indicate a new level of diversity and cellular interactions in cortical malformations and provide a generalisable approach to understanding cell–cell interactions and cellular heterogeneity in developmental neuropathology

A short educational intervention diminishes causal illusions and specific paranormal beliefs in undergraduates

Cognitive biases such as causal illusions have been related to paranormal and pseudoscientific beliefs and, thus, pose a real threat to the development of adequate critical thinking abilities. We aimed to reduce causal illusions in undergraduates by means of an educational intervention combining training-in-bias and training-in-rules techniques. First, participants directly experienced situations that tend to induce the Barnum effect and the confirmation bias. Thereafter, these effects were explained and examples of their influence over everyday life were provided. Compared to a control group, participants who received the intervention showed diminished causal illusions in a contingency learning task and a decrease in the precognition dimension of a paranormal belief scale. Overall, results suggest that evidence-based educational interventions like the one presented here could be used to significantly improve critical thinking skills in our students

BSE and BCOS Guideline for Transthoracic Echocardiographic Assessment of Adult Cancer Patients Receiving Anthracyclines and/or Trastuzumab

The subspecialty of cardio-oncology aims to reduce cardiovascular morbidity and mortality in patients with cancer or following cancer treatment. Cancer therapy can lead to a variety of cardiovascular complications, including left ventricular systolic dysfunction, pericardial disease, and valvular heart disease. Echocardiography is a key diagnostic imaging tool in the diagnosis and surveillance for many of these complications. The baseline assessment and subsequent surveillance of patients undergoing treatment with anthracyclines and/or human epidermal growth factor receptor (HER) 2-positive targeted treatment (e.g., trastuzumab and pertuzumab) form a significant proportion of cardio-oncology patients undergoing echocardiography. This guideline from the British Society of Echocardiography and British Cardio-Oncology Society outlines a protocol for baseline and surveillance echocardiography of patients undergoing treatment with anthracyclines and/or trastuzumab. The methodology for acquisition of images and the advantages and disadvantages of techniques are discussed. Echocardiographic definitions for considering cancer therapeutics-related cardiac dysfunction are also presented

Fluid Intelligence and Psychosocial Outcome: From Logical Problem Solving to Social Adaptation

While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized.Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher.Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts

Chronic Obstructive Pulmonary Disease and Lung Cancer: Underlying Pathophysiology and New Therapeutic Modalities

Chronic obstructive pulmonary disease (COPD) and lung cancer are major lung diseases affecting millions worldwide. Both diseases have links to cigarette smoking and exert a considerable societal burden. People suffering from COPD are at higher risk of developing lung cancer than those without, and are more susceptible to poor outcomes after diagnosis and treatment. Lung cancer and COPD are closely associated, possibly sharing common traits such as an underlying genetic predisposition, epithelial and endothelial cell plasticity, dysfunctional inflammatory mechanisms including the deposition of excessive extracellular matrix, angiogenesis, susceptibility to DNA damage and cellular mutagenesis. In fact, COPD could be the driving factor for lung cancer, providing a conducive environment that propagates its evolution. In the early stages of smoking, body defences provide a combative immune/oxidative response and DNA repair mechanisms are likely to subdue these changes to a certain extent; however, in patients with COPD with lung cancer the consequences could be devastating, potentially contributing to slower postoperative recovery after lung resection and increased resistance to radiotherapy and chemotherapy. Vital to the development of new-targeted therapies is an in-depth understanding of various molecular mechanisms that are associated with both pathologies. In this comprehensive review, we provide a detailed overview of possible underlying factors that link COPD and lung cancer, and current therapeutic advances from both human and preclinical animal models that can effectively mitigate this unholy relationship

Feasibility of comparing medical management and surgery (with neurosurgery or stereotactic radiosurgery) with medical management alone in people with symptomatic brain cavernoma - protocol for the Cavernomas: A Randomised Effectiveness (CARE) pilot trial.

INTRODUCTION: The top research priority for cavernoma, identified by a James Lind Alliance Priority setting partnership was 'Does treatment (with neurosurgery or stereotactic radiosurgery) or no treatment improve outcome for people diagnosed with a cavernoma?' This pilot randomised controlled trial (RCT) aims to determine the feasibility of answering this question in a main phase RCT. METHODS AND ANALYSIS: We will perform a pilot phase, parallel group, pragmatic RCT involving approximately 60 children or adults with mental capacity, resident in the UK or Ireland, with an unresected symptomatic brain cavernoma. Participants will be randomised by web-based randomisation 1:1 to treatment with medical management and with surgery (neurosurgery or stereotactic radiosurgery) versus medical management alone, stratified by prerandomisation preference for type of surgery. In addition to 13 feasibility outcomes, the primary clinical outcome is symptomatic intracranial haemorrhage or new persistent/progressive focal neurological deficit measured at 6 monthly intervals. An integrated QuinteT Recruitment Intervention (QRI) evaluates screening logs, audio recordings of recruitment discussions, and interviews with recruiters and patients/parents/carers to identify and address barriers to participation. A Patient Advisory Group has codesigned the study and will oversee its progress. ETHICS AND DISSEMINATION: This study was approved by the Yorkshire and The Humber-Leeds East Research Ethics Committee (21/YH/0046). We will submit manuscripts to peer-reviewed journals, describing the findings of the QRI and the Cavernomas: A Randomised Evaluation (CARE) pilot trial. We will present at national specialty meetings. We will disseminate a plain English summary of the findings of the CARE pilot trial to participants and public audiences with input from, and acknowledgement of, the Patient Advisory Group. TRIAL REGISTRATION NUMBER: ISRCTN41647111