Genome wide DNA methylation profiling of osteoarthritic articular cartilage

Optimising joint reconstruction management in arthritis and bone tumour patient

Computational modeling of beam-customization devices for heavy-charged-particle radiotherapy

A model for beam customization with collimators and a range-compensating filter based on the phase-space theory for beam transport is presented for dose distribution calculation in treatment planning of radiotherapy with protons and heavier ions. Independent handling of pencil beams in conventional pencil-beam algorithms causes unphysical collimator-height dependence in the middle of large fields, which is resolved by the framework comprised of generation, transport, collimation, regeneration, range-compensation, and edge-sharpening processes with a matrix of pencil beams. The model was verified to be consistent with measurement and analytic estimation at a submillimeter level in penumbra of individual collimators with a combinational-collimated carbon-ion beam. The model computation is fast, accurate, and readily applicable to pencil-beam algorithms in treatment planning with capability of combinational collimation to make best use of the beam-customization devices.Comment: 16 pages, 5 figure

Sentiment analysis of multiple implicit features per sentence in consumer review data

With the rise of e-commerce, online consumer reviews have become crucial for consumers' purchasing decisions. Most of the existing research focuses on the detection of explicit features and sentiments in such reviews, thereby ignoring all that is reviewed implicitly. This study builds, in extension of an existing implicit feature algorithm that can only assign one implicit feature to each sentence, a classifier that predicts the presence of multiple implicit features in sentences. The classifier makes its prediction based on a custom score function and a trained threshold. Only if this score exceeds the threshold, we allow for the detection of multiple implicit feature. In this way, we increase the recall while limiting the decrease in precision. In the more realistic scenario, the classifier-based approach improves the F1-score from 62.9% to 64.5% on a restaurant review data set. The precision of the computed sentiment associated with the detected features is 63.9%

Identification of Risk Factors for Dupilumab-associated OculaSurface Disease in Patients with Atopic Dermatitis

This study identified risk factors for the development of dupilumab-associated ocular surface disease in patients with moderate-to-severe atopic dermatitis in a large prospective daily practice cohort. Data from the Dutch BioDay Registry were used to assess the risk of developing dupilumab-associated ocular surface di-sease, by performing univariate and multivariate logistic regression analyses. A total of 469 patients were included, of which 152/469 (32.4%) developed dupi-lumab-associated ocular surface disease. Multivariate analysis showed a statistically significant association of the development of dupilumab-associated ocular surface disease with a history of any eye disease (his-tory of self-reported episodic acute allergic conjunctivitis excluded) combined with the use of ophthalmic medication at the start of dupilumab (odds ratio 5.16, 95% confidence interval 2.30–11.56, p < 0.001). In conclusion, a history of any eye disease (history of self-reported episodic acute allergic conjunctivitis ex-cluded) combined with the use of ophthalmic medication at baseline was associated with the development of dupilumab-associated ocular surface disease in patients with atopic dermatitis

Aggressive behavior, emotional, and attention problems across childhood and academic attainment at the end of primary school

Purpose: To assess whether aggressive behavior and emotional problems from early childhood onwards are related to academic attainment at the end of primary education, and whether these associations are independent of attention problems. Methods: Data on 2546 children participating in a longitudinal birth cohort in Rotterdam were analyzed. Aggressive behavior, attention and emotional problems at ages 1½, 3, 5 and 10 years were assessed with the Child Behavior Checklist. Academic attainment at the end of primary school (12 years of age) was measured with the CITO test, a national Dutch academic test score. Results: Aggressive behavior from age 1½ to 10 years was negatively associated with academic attainment, but these associations attenuated to non-significance when accounting for comorbid attention problems. For emotional problems, first, only problems at 10 years were associated with poorer academic attainment. Yet, when accounting for attention problems, the association reversed: more emotional problems from 1½ to 10 years were associated with a better academic attainment. Attention problems at ages 1½ to 10 years were negatively associated with academic attainment, independent of comorbid emotional problems or aggressive behavior. Conclusions: Attention problems across childhood are related to a poorer academic attainment, while emotional problems predicted better academic attainment. Moreover, the relationship between aggressive behavior and academic attainment was explained by comorbid attention problems. Future research should determine the mechanisms through which attention problems and emotional problems affect academic attainment, to inform strategies for the promotion of better educational attainment

Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation

This is the final version of the article. Available from Springer Nature via the DOI in this record.Raw data were submitted to the European Genome-phenome Archive (EGA) under accession EGAS00001001077.X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males. However, ~10% of genes show variable degrees of escape from XCI between females, although little is known about the causes of variable XCI. Using a discovery data-set of 1867 females and 1398 males and a replication sample of 3351 females, we show that genetic variation at three autosomal loci is associated with female-specific changes in X-chromosome methylation. Through cis-eQTL expression analysis, we map these loci to the genes SMCHD1/METTL4, TRIM6/HBG2, and ZSCAN9. Low-expression alleles of the loci are predominantly associated with mild hypomethylation of CpG islands near genes known to variably escape XCI, implicating the autosomal genes in variable XCI. Together, these results suggest a genetic basis for variable escape from XCI and highlight the potential of a population genomics approach to identify genes involved in XCI.This research was financially supported by several institutions: BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO, numbers 184.021.007 and 184.033.111); the UK Medical Research Council; Wellcome (www.wellcome.ac.uk; [grant number 102215/2/13/2 to ALSPAC]); the University of Bristol to ALSPAC; the UK Economic and Social Research Council (www.esrc.ac.uk; [ES/N000498/1] to CR); the UK Medical Research Council (www.mrc.ac.uk; grant numbers [MC_UU_12013/1, MC_UU_12013/2 to JLM, CR]); the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria; the Munich Center of Health Sciences (MC-Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ; the Wellcome Trust, Medical Research Council, European Union (EU), and the National Institute for Health Research (NIHR)- funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking

A joint physics and radiobiology DREAM team vision - towards better response prediction models to advance radiotherapy

Radiotherapy developed empirically through experience balancing tumour control and normal tissue toxicities. Early simple mathematical models formalized this practical knowledge and enabled effective cancer treatment to date. Remarkable advances in technology, computing, and experimental biology now create opportunities to incorporate this knowledge into enhanced computational models. The ESTRO DREAM (Dose Response, Experiment, Analysis, Modelling) workshop brought together experts across disciplines to pursue the vision of personalized radiotherapy for optimal outcomes through advanced modelling. The ultimate vision is leveraging quantitative models dynamically during therapy to ultimately achieve truly adaptive and biologically guided radiotherapy at the population as well as individual patient-based levels. This requires the generation of models that inform response-based adaptations, individually optimized delivery and enable biological monitoring to provide decision support to clinicians. The goal is expanding to models that can drive the realization of personalized therapy for optimal outcomes. This position paper provides their propositions that describe how innovations in biology, physics, mathematics, and data science including AI could inform models and improve predictions. It consolidates the DREAM team's consensus on scientific priorities and organizational requirements. Scientifically, it stresses the need for rigorous, multifaceted model development, comprehensive validation and clinical applicability and significance. Organizationally, it reinforces the prerequisites of interdisciplinary research and collaboration between physicians, medical physicists, radiobiologists, and computational scientists throughout model development. Solely by a shared understanding of clinical needs, biological mechanisms, and computational methods, more informed models can be created. Future research environment and support must facilitate this integrative method of operation across multiple disciplines. [Abstract copyright: Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Researchers’ attitudes to the 3Rs - An upturned hierarchy?

Animal use in biomedical research is generally justified by its potential benefits to the health of humans, or other animals, or the environment. However, ethical acceptability also requires scientists to limit harm to animals in their research. Training in laboratory animal science (LAS) helps scientists to do this by promoting best practice and the 3Rs. This study evaluated scientists’ awareness and application of the 3Rs, and their approach to other ethical issues in animal research. It was based on an online survey of participants in LAS courses held in eight venues in four European countries: Portugal (Porto, Braga), Germany (Munich, Heidelberg), Switzerland (Basel, Lausanne, Zurich), and Denmark (Copenhagen). The survey questions were designed to assess general attitudes to animal use in biomedical research, Replacement alternatives, Reduction and Refinement conflicts, and harm-benefit analysis. The survey was conducted twice: immediately before the course (‘BC’, N = 310) and as a follow-up six months after the course (‘AC’, N = 127). While courses do appear to raise awareness of the 3Rs, they had no measurable effect on the existing low level of belief that animal experimentation can be fully replaced by non-animal methods. Most researchers acknowledged ethical issues with their work and reported that they discussed these with their peers. The level of an animal’s welfare, and especially the prevention of pain, was regarded as the most pressing ethical issue, and as more important than the number of animals used or the use of animals as such. Refinement was considered more feasible than Replacement, as well as more urgent, and was also favoured over Reduction. Respondents in the survey reversed the ‘hierarchy’ of the 3Rs proposed by their architects, Russell and Burch, prioritizing Refinement over Reduction, and Reduction over Replacement. This ordering may conflict with the expectations of the public and regulators.</div