Genome Wide DNA Copy Number Analysis of Serous Type Ovarian Carcinomas Identifies Genetic Markers Predictive of Clinical Outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Computing linkage disequilibrium aware genome embeddings using autoencoders

Motivation The completion of the genome has paved the way for genome-wide association studies (GWAS), which explained certain proportions of heritability. GWAS are not optimally suited to detect non-linear effects in disease risk, possibly hidden in non-additive interactions (epistasis). Alternative methods for epistasis detection using, e.g. deep neural networks (DNNs) are currently under active development. However, DNNs are constrained by finite computational resources, which can be rapidly depleted due to increasing complexity with the sheer size of the genome. Besides, the curse of dimensionality complicates the task of capturing meaningful genetic patterns for DNNs; therefore necessitates dimensionality reduction. Results We propose a method to compress single nucleotide polymorphism (SNP) data, while leveraging the linkage disequilibrium (LD) structure and preserving potential epistasis. This method involves clustering correlated SNPs into haplotype blocks and training per-block autoencoders to learn a compressed representation of the block’s genetic content. We provide an adjustable autoencoder design to accommodate diverse blocks and bypass extensive hyperparameter tuning. We applied this method to genotyping data from Project MinE, and achieved 99% average test reconstruction accuracy—i.e. minimal information loss—while compressing the input to nearly 10% of the original size. We demonstrate that haplotype-block based autoencoders outperform linear Principal Component Analysis (PCA) by approximately 3% chromosome-wide accuracy of reconstructed variants. To the extent of our knowledge, our approach is the first to simultaneously leverage haplotype structure and DNNs for dimensionality reduction of genetic data

Between the Green Pitch and the Red Tape: The Private Legal Order of FIFA

FIFA, the world governing body of football (or soccer, as it is known in some countries), has long been associated with the World Cup and, lately, corruption scandals. Less known is FIFA’s success in building a private legal order that competes with public orders. This study explains how and why this private legal order has succeeded in governing the behavior of the involved actors and keeping them away from regular courts. We argue that the ability of the order to offer what other governance modes cannot is key: FIFA, as a transnational private authority, offers harmonized institutions that apply across national borders and, in many cases, are better accustomed to the needs of the involved parties. State-made alternatives, on the other hand, are often based on a one-size-fits-all approach and lack certainty of application. In addition, FIFA’s rules increase the gains of clubs and prominent footballers. While the interests of some other involved parties—lesser-known players in particular—might be better served by the application of formal State laws, the established equilibrium discourages deviation. This study contributes to a better understanding of alternative modes of institutional design, particularly by illustrating how private orders function in an environment where reputation plays a limited role

Robust dose-painting-by-numbers vs. nonselective dose escalation for non-small cell lung cancer patients

Purpose: Theoretical studies have shown that dose-painting-by-numbers (DPBN) could lead to large gains in tumor control probability (TCP) compared to conventional dose distributions. However, these gains may vary considerably among patients due to (a) variations in the overall radiosensitivity of the tumor, (b) variations in the 3D distribution of intra-tumor radiosensitivity within the tumor in combination with patient anatomy, (c) uncertainties of the 3D radiosensitivity maps, (d) geometrical uncertainties, and (e) temporal changes in radiosensitivity. The goal of this study was to investigate how much of the theoretical gains of DPBN remain when a

Enabling Patient- and Teleoperator-led Robotic Physiotherapy via Strain Map Segmentation and Shared-authority

In this work, we propose a method for monitoring and managing rotator-cuff (RC) tendon strains in human-robot collaborative physical therapy for shoulder rehabilitation. We integrate a high-resolution biomechanical model with a collaborative industrial robot arm and an impedance controller to provide feedback to a human subject, therapist or both, which prevents the subject from entering unsafe poses during rehabilitation. The biomechanical model estimates RC tendon strain as a function of human shoulder configuration, muscle activation and applied external forces. Subject- and injury-specific data are model estimates of strain that compose strain maps, which capture the relationship between the RC strains and movement of the shoulder degrees of freedom (DoF). High-strain regions of the strain map are identified as unsafe zones by clustering and ellipse fitting to smoothly demarcate these zones. These unsafe areas, which reflect increased risks of (re-)injury, are used to define parameters of an impedance controller and reference pose for real-time biomechanical safety control. Using strain maps we demonstrate both safe patient-led movements and teleoperated movements that prevent the subject from entering unsafe zones. In the teleoperated case, the physical therapist leads the patient remotely using a haptic device. The proposed method has the potential to improve the safety, range of motion, and volume of activity that a patient receives through robot-mediated physical therapy. We validated our approach using three experiments that demonstrate shoulder joint torques of less than 1 Nm during free motion with larger torques occurring only when the subject was asked to actively push into the unsafe boundary or, in the case of teleoperation, to resist the physical therapist.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Human-Robot InteractionBiomechatronics & Human-Machine Contro

The MOMANT study, a caregiver support programme with activities at home for people with dementia: a study protocol of a randomised controlled trial

BACKGROUND: Because of the expected increase in the number of people with dementia, and the associated social and economic costs, there is an urgent need to develop effective and cost-effective care for people with dementia and their caregivers. The intervention proposed here combines two approaches to caregiver support that have shown to be effective in empowering caregivers, i.e., multiple components for caregiver support and actively engaging caregivers to involve the person with dementia in activities at home. The aim is to investigate whether the intervention is effective in improving quality of life in the caregiver and the person with dementia. A further aim will be to investigate whether this intervention can improve caregivers' feeling of competence, experience of caregiving, and mood. METHODS: The study design is a pragmatic, cluster randomised controlled trial with cost-effectiveness analysis. The study participants are informal caregivers and home-living persons with dementia for whom they care, recruited in various regions in the Netherlands. The trial will compare outcomes in two groups of participants: 85 dyads who receive the intervention, and 85 dyads who receive care as usual. The intervention is a caregiver support training that is manual based and consists of 6 group sessions over 2 months. Training takes place in small groups of caregivers led by a health care professional presented at dementia day care centres. Randomisation occurs at the level of the day care centre. Participants are assessed on the outcome measures at baseline, prior to the intervention, and at 3 and 6 months after baseline. DISCUSSION: The study will provide insight into effectiveness and cost-effectiveness of an intervention that has not previously been evaluated or implemented in the Netherlands. The intervention potentially adds to the effective support options for informal caregivers of people with dementia without greatly increasing the workload for health- or social care professionals. TRIAL REGISTRATION: The trial is registered at the Dutch Trial Register at NTR6643 ; August 22 nd, 2017