ObjectiveThe Plants for Joints (PFJ) intervention significantly improved pain, stiffness, and physical function, and metabolic outcomes, in people with metabolic syndrome-associated osteoarthritis (MSOA). This secondary analysis investigated its effects on body composition.MethodIn the randomized PFJ study, people with MSOA followed a 16-week intervention based on a whole-food plant-based diet, physical activity, and stress management, or usual care. For this secondary analysis, fat mass, muscle mass, and bone mineral density were measured using dual-energy X-ray absorptiometry (DEXA) for all participants. Additionally, in a subgroup (n = 32), hepatocellular lipid (HCL) content and composition of visceral adipose tissue (VAT) were measured using magnetic resonance spectroscopy (MRS). An intention-to-treat analysis with a linear-mixed model adjusted for baseline values was used to analyse between-group differences.ResultsOf 66 people randomized, 64 (97%) completed the study. The PFJ group experienced significant weight loss (−5.2 kg; 95% CI –6.9, −3.6) compared to controls, primarily from fat mass reduction (−3.9 kg; 95% CI –5.3 to −2.5). No significant differences were found in lean mass, muscle strength, or bone mineral density between groups. In the subgroup who underwent MRI scans, the PFJ group had a greater reduction in HCL (−6.5%; 95% CI –9.9, 3.0) compared to controls, with no observed differences in VAT composition.ConclusionThe PFJ multidisciplinary intervention positively impacted clinical and metabolic outcomes, and appears to significantly reduce body fat, including liver fat, while preserving muscle mass and strength.
MULTIFILE
Background: Magnetic resonance imaging (MRI) is being used extensively in the search for pathoanatomical factors contributing to low back pain (LBP) such as Modic changes (MC). However, it remains unclear whether clinical findings can identify patients with MC. The purpose of this explorative study was to assess the predictive value of six clinical tests and three questionnaires commonly used with patients with low-back pain (LBP) on the presence of Modic changes (MC).Methods: A retrospective cohort study was performed using data from Dutch military personnel in the period between April 2013 and July 2016. Questionnaires included the Roland Morris Disability Questionnaire, Numeric Pain Rating Scale, and Pain Self-Efficacy Questionnaire. The clinical examination included (i) range of motion, (ii) presence of pain during flexion and extension, (iii) Prone Instability Test, and (iv) straight leg raise. Backward stepwise regression was used to estimate predictive value for the presence of MC and the type of MC. The exploration of clinical tests was performed by univariable logistic regression models.Results: Two hundred eighty-six patients were allocated for the study, and 112 cases with medical records and MRI scans were available; 60 cases with MC and 52 without MC. Age was significantly higher in the MC group. The univariate regression analysis showed a significantly increased odds ratio for pain during flexion movement (2.57 [95% confidence interval (CI): 1.08-6.08]) in the group with MC. Multivariable logistic regression of all clinical symptoms and signs showed no significant association for any of the variables. The diagnostic value of the clinical tests expressed by sensitivity, specificity, positive predictive, and negative predictive values showed, for all the combinations, a low area under the curve (AUC) score, ranging from 0.41 to 0.53. Single-test sensitivity was the highest for pain in flexion: 60% (95% CI: 48.3-70.4).Conclusion: No model to predict the presence of MC, based on clinical tests, could be demonstrated. It is therefore not likely that LBP patients with MC are very different from other LBP patients and that they form a specific subgroup. However, the study only explored a limited number of clinical findings and it is possible that larger samples allowing for more variables would conclude differently.
INTRODUCTION: After treatment with chemotherapy, many patients with breast cancer experience cognitive problems. While limited interventions are available to improve cognitive functioning, physical exercise showed positive effects in healthy older adults and people with mild cognitive impairment. The Physical Activity and Memory study aims to investigate the effect of physical exercise on cognitive functioning and brain measures in chemotherapy-exposed patients with breast cancer with cognitive problems.METHODS AND ANALYTICS: One hundred and eighty patients with breast cancer with cognitive problems 2-4 years after diagnosis are randomised (1:1) into an exercise intervention or a control group. The 6-month exercise intervention consists of twice a week 1-hour aerobic and strength exercises supervised by a physiotherapist and twice a week 1-hour Nordic or power walking. The control group is asked to maintain their habitual activity pattern during 6 months. The primary outcome (verbal learning) is measured at baseline and 6 months. Further measurements include online neuropsychological tests, self-reported cognitive complaints, a 3-tesla brain MRI, patient-reported outcomes (quality of life, fatigue, depression, anxiety, work performance), blood sampling and physical fitness. The MRI scans and blood sampling will be used to gain insight into underlying mechanisms. At 18 months online neuropsychological tests, self-reported cognitive complaints and patient-reported outcomes will be repeated.ETHICS AND DISSEMINATION: Study results may impact usual care if physical exercise improves cognitive functioning for breast cancer survivors.TRIAL REGISTRATION NUMBER: NTR6104.
Voor de bouw van een woning wordt voor de fundering traditioneel gebruik gemaakt van betonnen fundering systemen. Het doel van dit onderzoek is om tot een eerste concept te komen voor een alternatieve funderingsconstructie, gemaakt van verpakking kunststoffen afkomstig uit huisvuil. Zo wordt de uitstoot van CO2 verminderd en de kunststof op grote schaal voor langere tijd opgeslagen in het bouwelement. Daarbij is afvalkunststof ruim voor handen en biedt het veel perspectief voor grootschalige toepassing in de bouw. Habi-Nex werkt samen met Sip-construct aan het ontwikkelen van nieuwe, lichtgewicht bouwsystemen. Het bouwsysteem bestaat uit lichtgewicht panelen die eenvoudig, met lichte instrumenten te plaatsen zijn. Dit innovatieve bouwsysteem levert nieuwe kansen voor het ontwikkelen van een fundering systeem dat aansluit op de voorsprong van deze bouwtechniek en de potenties die het bouwsysteem kent verder vergroot. Met het lectoraat Circulair Plastics werkt NHLStenden aan onderzoek projecten op het gebied van hergebruik van verpakking kunststoffen. NHLStenden werkt hierbij samen met belangrijke keten partners zoals het Afval fonds, Circular Frysland, Omrin, Lankhorst etc. De grootste vraag vanuit de keten is momenteel waar de kunststoffen kunnen worden gebruik en liefst in grote massa en lange termijn gebruik. Dit is een uitdagend vraagstuk waarin de bouw wordt gezien als potentiele grootafnemer van deze circulaire grondstof.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Dit project richt zich op duurzame extractie en hergebruik van gadolinium (Gd), een zeldzaam aardmetaal dat onder andere wordt gebruikt in computerchips, maar ook in MRI-contrastmiddelen in de medische praktijk. Omdat waterzuiveringsinstallaties deze contrastmiddelen niet kunnen terugwinnen komt Gd via urine in het milieu terecht. De productie van Gd genereert grote hoeveelheden toxisch afval en CO2. Voor de verduurzaming van de chemische sector is het daarom essentieel nieuwe methoden te ontwikkelen om Gd te recyclen en te scheiden. Ons innovatieve proces maakt gebruik van het eiwit Lanmodulin, dat specifiek Gd bindt. Door Lanmodulin op een vaste drager te immobiliseren, kan het herbruikbaar worden ingezet om Gd direct uit urine te filteren. Na binding wordt Gd door een eenvoudige chemische behandeling losgekoppeld van het eiwit en gerecycled. Jaarlijks wordt in Nederland meer dan 500 kg Gd gebruikt in MRI-contrastvloeistoffen. Door Gd uit urine te filteren, kunnen ziekenhuizen hun milieubelasting en afvalproductie verminderen. Het teruggewonnen Gd kan vervolgens hergebruikt worden in verschillende toepassingen buiten het ziekenhuis. Gd extractie bespaart kosten en vermindert de afhankelijkheid van zeldzame aardmetalen van buitenlandse producenten. Het project is geïnspireerd door de Green Deal Duurzame Zorg, die streeft naar halvering van het grondstofverbruik in de zorg in 2030. Het doel van ons onderzoek is om een effectief en duurzaam Gd terugwinning proces te ontwikkelen voor praktijkgebruik. Dit nieuwe, schaalbare proces vormt een milieuvriendelijk systeem dat Gd extraheert voor hergebruik in de chemische industrie. De technologie biedt ook mogelijkheden om andere waardevolle zeldzame aardmetalen uit afvalstromen te winnen, wat bijdraagt aan een circulaire economie. Door recycling van kritieke grondstoffen verlagen we de milieu-impact van de medische sector en dragen we bij aan een duurzamere toekomst.
