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Major depressive disorder is a leading cause of disability worldwide; identifying effective strategies to prevent depression relapse is crucial. This individual participant data meta-analysis addresses whether and for whom psychological interventions can be recommended for relapse prevention of major depressive disorder. One- and two-stage individual patient data meta-analyses were conducted on 14 randomized controlled trials (N = 1,720). The relapse risk over 12 months was substantially lower for those who received a psychological intervention versus treatment as usual, antidepressant medication, or evaluation-only control (hazard ratio, 0.60; 95% confidence interval, 0.48–0.74). The number of previous depression episodes moderated the treatment effect, with psychological interventions demonstrating greater efficacy for patients with three or more previous episodes. Our results suggest that adding psychological interventions to current treatment to prevent depression relapse is recommended. For patients at lower risk of relapse, less-intensive approaches may be indicated., This project was funded in part by internal funds fromthe Alliance for Public Health at the Amsterdam University MedicalCentre—Mental Health Stream.

Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects—from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.

Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects—from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats.

Contains fulltext : 293885.pdf (Publisher’s version ) (Open Access), BACKGROUND: Many patients with Inflammatory Bowel Diseases (IBD) suffer from psychological distress, fatigue and sleep disturbances, which are associated with reduced quality of life (QoL) and increased societal costs. Only limited psychosocial treatment options are available. As Mindfulness-Based Cognitive Therapy (MBCT) has demonstrated to improve psychological distress, QoL and sleep in other populations, MBCT might also be effective in patients with IBD. METHODS: The MindIBD study is a prospective, multicentre, randomised controlled trial comparing MBCT plus Treatment As Usual (TAU) versus TAU alone in a targeted number of 136 IBD patients in remission, aged 16 years and older with at least mild psychological distress (Hospital Anxiety and Depression Scale (HADS) total score ≥ 11). Primary outcome is reduction of psychological distress post-intervention, measured by the HADS. In addition, the effect of MBCT on sleep quality (including actigraphy and electroencephalography recordings), fatigue, disease activity, perceived disease control, QoL and positive mental health will be examined. Assessments will be conducted at baseline and at 3, 6, 9 and 12 months follow-up. Cost-effectiveness will be determined and a process evaluation will be conducted. DISCUSSION: This study will provide valuable insight into the clinical effect of MBCT on psychological distress, sleep quality, fatigue and QoL in IBD patients and into the cost-effectiveness. If effective, MBCT can be a valuable addition to the available psychosocial interventions for patients with IBD. Moreover, findings from this study may also be applicable in patients with other chronic conditions. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04646785, registered on 30/11/2020.

Contains fulltext : 296229.pdf (Publisher’s version ) (Open Access), Discontinuing antidepressant medication (ADM) can be challenging for patients and clinicians. In the current study we investigated if Mindfulness-Based Cognitive Therapy (MBCT) added to supported protocolized discontinuation (SPD) is more effective than SPD alone to help patients discontinue ADM. This study describes a prospective, cluster-randomized controlled trial (completed). From 151 invited primary care practices in the Netherlands, 36 (24%) were willing to participate and randomly allocated to SPD+MBCT (k = 20) or SPD (k = 16). Adults using ADM > 9 months were invited by GPs to discuss tapering, followed by either MBCT+SPD, or SPD alone. Exclusion criteria included current psychiatric treatment; substance use disorder; non-psychiatric indication for ADM; attended MBCT within past 5 years; cognitive barriers. From the approximately 3000 invited patients, 276 responded, 119 participated in the interventions and 92 completed all assessments. All patients were offered a decision aid and a personalized tapering schedule (with GP). MBCT consisted of eight group sessions of 2.5 hours and one full day of practice. SPD was optional and consisted of consultations with a mental health assistant. Patients were assessed at baseline and 6, 9 and 12 months follow-up, non-blinded. In line with our protocol, primary outcome was full discontinuation of ADM within 6 months. Secondary outcomes were depression, anxiety, withdrawal symptoms, rumination, well-being, mindfulness skills, and self-compassion. Patients allocated to SPD + MBCT (n = 73) were not significantly more successful in discontinuing (44%) than those allocated to SPD (n = 46; 33%), OR 1.60, 95% CI 0.73 to 3.49, p = .24, number needed to treat = 9. Only 20/73 allocated to MBCT (27%) completed MBCT. No serious adverse events were reported. In conclusion, we were unable to demonstrate a significant benefit of adding MBCT to SPD to support discontinuation in general practice. Actual participation in patient-tailored

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A subset of autoimmune diseases is characterized by predominant pathogenic IgG4 autoantibodies (IgG4-AID). Why IgG4 predominates in these disorders is unknown. We hypothesized that dysregulated B cell maturation or aberrant class switching causes overrepresentation of IgG4+ B cells and plasma cells. Therefore, we compared the B cell compartment of patients from four different IgG4-AID with two IgG1-3-AID and healthy donors, using flow cytometry. Relative subset abundance at all maturation stages was normal, except for a, possibly treatment-related, reduction in immature and naïve CD5+ cells. IgG4+ B cell and plasma cell numbers were normal in IgG4-AID patients, however they had a (sub)class-independent 8-fold increase in circulating CD20-CD138+ cells. No autoreactivity was found in this subset. These results argue against aberrant B cell development and rather suggest the autoantibody subclass predominance to be antigen-driven. The similarities between IgG4-AID suggest that, despite displaying variable clinical phenotypes, they share a similar underlying immune profile.

Beleid, kennis - Het veranderende klimaat en de maatregelen die we nemen om de opwarming van de aarde tegen te gaan, beïnvloeden het welzijn van dieren in de veehouderij. In de zienswijze ‘Laat dierenwelzijn niet ondersneeuwen’ signaleert en agendeert de RDA knelpunten voor productiedieren die worden veroorzaakt door de klimaatproblematiek. Dit document is een bijlage bij: Verzamelbrief dierenwelzijn gezelschapsdieren.

Introduction: Lifestyle factors are expected to contribute to the persistence and burden of low-back pain (LBP). However, there are no systematic reviews on the (cost-)effectiveness of combined lifestyle interventions for overweight or obese people with LBP. Aim: To assess whether combined lifestyle interventions are (cost-)effective for people with persistent LBP who are overweight or obese, based on a systematic review. Design: Systematic review Method: PubMed, Cochrane, Embase, CINAHL, PsycINFO and the Wiley/Cochrane Library were searched from database inception till January 6th 2023. Two independent reviewers performed study selection, data-extraction and risk of bias scoring using the Cochrane RoB tool 2 and/or the Consensus Health Economic Criteria list. GRADE was used to assess the level of certainty of the evidence. Results: In total 2510 records were screened, and 4 studies on 3 original RCTs with 216 participants were included. Low certainty evidence (1 study) showed that combined lifestyle interventions were not superior to usual care for physical functioning, pain and lifestyle outcomes. Compared to usual care, moderate certainty evidence showed that healthcare (-$292, 95%CI: 872; −33), medication (-$30, 95% CI -65; −4) and absenteeism costs (-$1000, 95%CI: 3573; −210) were lower for the combined lifestyle interventions. Conclusion: There is low certainty evidence from 3 studies with predominantly small sample sizes, short follow-up and low intervention adherence that combined lifestyle interventions are not superior to physical functioning, pain and lifestyle outcomes compared to usual care, but are likely to be cost-effective.

DNA damage threatens genomic integrity and instigates stem cell failure. To bypass genotoxic lesions during replication, cells employ DNA damage tolerance (DDT), which is regulated via PCNA ubiquitination and REV1. DDT is conserved in all domains of life, yet its relevance in mammals remains unclear. Here, we show that inactivation of both PCNA-ubiquitination and REV1 results in embryonic and adult lethality, and the accumulation of DNA damage in hematopoietic stem and progenitor cells (HSPCs) that ultimately resulted in their depletion. Our results reveal the crucial relevance of DDT in the maintenance of stem cell compartments and mammalian life in unperturbed conditions.

Purpose: Ongoing angiogenesis renders the tumor endothelium unresponsive to inflammatory cytokines and interferes with adhesion of leukocytes, resulting in escape from immunity. This process is referred to as tumor endothelial cell anergy. We aimed to investigate whether anti-angiogenic agents can overcome endothelial cell anergy and provide pro-inflammatory conditions. Experimental design: Tissues of renal cell carcinoma (RCC) patients treated with VEGF pathway-targeted drugs and control tissues were subject to RNAseq and immunohistochemical profiling of the leukocyte infiltrate. Analysis of adhesion molecule regulation in cultured endothelial cells, in a preclinical model and in human tissues was performed and correlated to leukocyte infiltration. Results: It is shown that treatment of RCC patients with the drugs sunitinib or bevacizumab overcomes tumor endothelial cell anergy. This treatment resulted in an augmented inflammatory state of the tumor, characterized by enhanced infiltration of all major leukocyte subsets, including T cells, regulatory T cells, macrophages of both M1- and M2-like phenotypes and activated dendritic cells. In vitro, exposure of angiogenic endothelial cells to anti-angiogenic drugs normalized ICAM-1 expression. In addition, a panel of tyrosine kinase inhibitors was shown to increase transendothelial migration of both non-adherent and monocytic leukocytes. In primary tumors of RCC patients, ICAM-1 expression was found to be significantly increased in both the sunitinib and bevacizumab-treated groups. Genomic analysis confirmed the correlation between increased immune cell infiltration and ICAM-1 expression upon VEGF-targeted treatment. Conclusion: The results support the emerging concept that anti-angiogenic therapy can boost immunity and show how immunotherapy approaches can benefit from combination with anti-angiogenic compounds.

A subset of autoimmune diseases is characterized by predominant pathogenic IgG4 autoantibodies (IgG4-AID). Why IgG4 predominates in these disorders is unknown. We hypothesized that dysregulated B cell maturation or aberrant class switching causes overrepresentation of IgG4+ B cells and plasma cells. Therefore, we compared the B cell compartment of patients from four different IgG4-AID with two IgG1-3-AID and healthy donors, using flow cytometry. Relative subset abundance at all maturation stages was normal, except for a, possibly treatment-related, reduction in immature and naïve CD5+ cells. IgG4+ B cell and plasma cell numbers were normal in IgG4-AID patients, however they had a (sub)class-independent 8-fold increase in circulating CD20-CD138+ cells. No autoreactivity was found in this subset. These results argue against aberrant B cell development and rather suggest the autoantibody subclass predominance to be antigen-driven. The similarities between IgG4-AID suggest that, despite displaying variable clinical phenotypes, they share a similar underlying immune profile.

Item does not contain fulltext, Background: Mindfulness-based cognitive therapy (MBCT) is effective for relapse prevention in major depressive disorder (MDD). It reduces cognitive reactivity (CR) and rumination, and enhances self-compassion and mindfulness. Although rumination and mindfulness after MBCT are associated with relapse, the association of CR, rumination, self-compassion, and mindfulness with relapse before initiation of MBCT has never been investigated. Methods: Data were drawn from two randomized controlled trials, including a total of 282 remitted MDD participants (>= 3 depressive episodes) who had been using maintenance antidepressant medication (mADM) for at least 6 months before baseline. All participants were offered MBCT while either their mADM was maintained or discontinued after MBCT. CR, rumination, self-compassion, and mindfulness were assessed at baseline by self-rated questionnaires and were used in Cox proportional hazards regression models to investigate their association with relapse. Results: CR and mindfulness were associated with relapse, independent of residual symptoms, previous depressive episodes, and mADM-use. Higher CR and lower mindfulness increased the risk of relapse. Self-compassion was not associated with relapse. For rumination, a significant interaction with mADM-use was found. Rumination was associated with relapse in patients who discontinued their mADM, while this effect was absent if patients continued mADM. Conclusions: These results show that CR, rumination, and mindfulness are associated with relapse in remitted MDD-patients before initiation of MBCT, independent of residual symptoms and previous depressive episodes. This information could improve decisions in treatment planning in remitted individuals with a history of depression.

Radboud University, 08 juli 2022, Promotores : Speckens, A.E.M., Hulscher, M.E.J.L. Co-promotores : Huijbers, M.J., Regeer, E.J., Contains fulltext : 250457.pdf (Publisher’s version ) (Closed access)

Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging-based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network-based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.

Galectin-1 (Gal1) is a glycan-binding protein that promotes tumor progression by several distinct mechanisms. Through direct binding to vascular endothelial growth factor (VEGF)-receptor 2, Gal1 is able to induce VEGF-like signaling, which contributes to tumor angiogenesis. Furthermore, several studies have demonstrated an immunosuppressive function of Gal1 through effects on both effector and regulatory T cells. Elevated Gal1 expression and secretion have been shown in many tumor types, and high Gal1 serum levels have been connected to poor prognosis in cancer patients. These findings suggest that therapeutic strategies directed against Gal1 would enable simultaneous targeting of angiogenesis, immune evasion and metastasis. In the current study, we have analyzed the potential of Gal1 as a cancer vaccine target. We show that it is possible to generate high anti-Gal1 antibody levels in mice immunized with a recombinant vaccine protein consisting of bacterial sequences fused to Gal1. Growth of Gal1 expressing melanomas was significantly impaired in the immunized mice compared to the control group. This was associated with improved perfusion of the tumor vasculature, as well as increased infiltration of macrophages and cytotoxic T cells (CTLs). The level of granzyme B, mainly originating from CTLs in our model, was significantly elevated in Gal1 vaccinated mice and correlated with a decrease in tumor burden. We conclude that vaccination against Gal1 is a promising pro-immunogenic approach for cancer therapy that could potentially enhance the effect of other immunotherapeutic strategies due to its ability to promote CTL influx in tumors., Authors in thesis list of papers: Julia Femel, Luuk Van Hooren, Falk Saupe, Elisabeth JM Huijbers, Danielle RJ Verboogen, Matthias Reichel, Jessica Cedervall, Victor L Thijssen, Lars Hellman, Arjan W Griffioen, Anna Dimberg, Anna-Karin Olsson

Contains fulltext : 252777.pdf (Publisher’s version ) (Open Access), Negative self-referential processing has fruitfully been studied in unipolar depressed patients, but remarkably less in patients with bipolar disorder (BD). This exploratory study examines the relation between task-based self-referential processing and depressive symptoms in BD and their possible importance to the working mechanism of mindfulness-based cognitive therapy (MBCT) for BD. The study population consisted of a subsample of patients with BD (n = 49) participating in an RCT of MBCT for BD, who were assigned to MBCT + TAU (n = 23) or treatment as usual (TAU) (n = 26). Patients performed the self-referential encoding task (SRET), which measures (1) positive and (2) negative attributions to oneself as well as (3) negative self-referential memory bias, before and after MBCT + TAU or TAU. At baseline, all three SRET measures were significantly related to depressive symptoms in patients with BD. Moreover, repeated measures analyses of variance revealed that negative self-referential memory bias diminished over time in the MBCT + TAU group, compared with the TAU group. Given the preliminary nature of our findings, future research should explore the possibly mediating role of reducing negative self-referential memory bias in preventing and treating depressive symptoms in BD through MBCT.

Contains fulltext : 242463.pdf (Publisher’s version ) (Open Access), Background: Preliminary evidence suggests that Mindfulness-Based Cognitive Therapy (MBCT) is a promising treatment for bipolar disorder (BD). A proposed working mechanism of MBCT in attenuating depressive symptoms is reducing depressive rumination. The primary aim of this study was to investigate the effect of MBCT on self-reported trait depressive rumination and an experimental state measure of negative intrusive thoughts in BD patients. Exploratively, we investigated the effect of MBCT on positive rumination and positive intrusive thoughts. Methods: The study population consisted of a subsample of bipolar type I or II patients participating in a multicenter randomized controlled trial comparing MBCT + treatment as usual (TAU) (N = 25) to TAU alone (N = 24). Trait depressive rumination (RRS brooding subscale) and intrusive thoughts (breathing focus task (BFT)) were assessed at baseline (full subsample) and post-treatment (MBCT + TAU; n = 15, TAU; n = 15). During the BFT, participants were asked to report negative, positive and neutral intrusive thoughts while focusing on their breathing. Results: Compared to TAU alone, MBCT + TAU resulted in a significant pre- to post-treatment reduction of trait depressive rumination (R2 = .16, F(1, 27) = 5.15, p = 0.031; medium effect size (f2 = 0.19)) and negative intrusive thoughts on the BFT (R2 = .15, F(1, 28) = 4.88, p = 0.036; medium effect size (f2 = 0.17)). MBCT did not significantly change positive rumination or positive intrusive thoughts. Conclusions: MBCT might be a helpful additional intervention to reduce depressive rumination in BD which might reduce risk of depressive relapse or recurrence. Considering the preliminary nature of our findings, future research should replicate our findings and explore whether this reduction in rumination following MBCT indeed mediates a reduction in depressive symptoms and relapse or recurrence in BD.

Muscle-specific kinase (MuSK) myasthenia gravis (MG) is a neuromuscular autoimmune disease belonging to a growing group of IgG4 autoimmune diseases (IgG4-AIDs), in which the majority of pathogenic autoantibodies are of the IgG4 subclass. The more prevalent form of MG with acetylcholine receptor (AChR) antibodies is caused by IgG1-3 autoantibodies. A dominant role for IgG4 in autoimmune disease is intriguing due to its antiinflammatory characteristics. It is unclear why MuSK autoantibodies are predominantly IgG4. We hypothesized that MuSK MG patients have a general predisposition to generate IgG4 responses, therefore resulting in high levels of circulating IgG4. To investigate this, we quantified serum Ig isotypes and IgG subclasses using nephelometric and turbidimetric assays in MuSK MG and AChR MG patients not under influence of immunosuppressive treatment. Absolute serum IgG1 was increased in both MuSK and AChR MG patients compared to healthy donors. In addition, only MuSK MG patients on average had significantly increased and enriched serum IgG4. Although more MuSK MG patients had elevated serum IgG4, for most the IgG4 serum levels fell within the normal range. Correlation analyses suggest MuSK-specific antibodies do not solely explain the variation in IgG4 levels. In conclusion, although serum IgG4 levels are slightly increased, the levels do not support ubiquitous IgG4 responses in MuSK MG patients as the underlying cause of dominant IgG4 MuSK antibodies.

BACKGROUND: Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and improve learning curves. The study objective was to provide a comprehensive overview of current literature on the accuracy of anatomy recognition algorithms in intrathoracic and -abdominal surgery.METHODS: This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Pubmed, Embase, and IEEE Xplore were searched for original studies up until January 2022 on computer-aided anatomy recognition, without requiring intraoperative imaging or calibration equipment. Extracted features included surgical procedure, study population and design, algorithm type, pre-training methods, pre- and post-processing methods, data augmentation, anatomy annotation, training data, testing data, model validation strategy, goal of the algorithm, target anatomical structure, accuracy, and inference time.RESULTS: After full-text screening, 23 out of 7124 articles were included. Included studies showed a wide diversity, with six possible recognition tasks in 15 different surgical procedures, and 14 different accuracy measures used. Risk of bias in the included studies was high, especially regarding patient selection and annotation of the reference standard. Dice and intersection over union (IoU) scores of the algorithms ranged from 0.50 to 0.98 and from 74 to 98%, respectively, for various anatomy recognition tasks. High-accuracy algorithms were typically trained using larger datasets annotated by expert surgeons and focused on less-complex anatomy. Some of the high-accuracy algorithms were developed using pre-training and data augmentation.CONCLUSIONS: The accuracy of included anatomy recognition algorithms varied substantially, ranging from moderate

The presence of autoreactive antibodies is a hallmark of many autoimmune diseases. The effector functions of (auto)antibodies are determined by their constant domain, which defines the antibody isotype and subclass. The most prevalent isotype in serum is IgG, which is often the only isotype used in diagnostic testing. Nevertheless, autoantibody responses can have their own unique isotype/subclass profile. Because comparing autoantibody isotype profiles may yield new insights into disease pathophysiology, here we summarize the isotype/subclass profiles of the most prominent autoantibodies. Despite substantial variation between (and within) autoantibody responses, this unprecedented comparison shows that autoantibodies share distinctive isotype patterns across different diseases. Although most autoantibody responses are dominated by IgG (and mainly IgG1), several specific diseases are characterized by a predominance of IgG4. In other diseases, IgE plays a key role. Importantly, shared features of autoantibody isotype/subclass profiles are seen in clinically unrelated diseases, suggesting potentially common trajectories in response evolution, disease pathogenesis, and treatment response. Isotypes beyond IgG are scarcely investigated in many autoantibody responses, leaving substantial gaps in our understanding of the pathophysiology of autoimmune diseases. Future research should address isotype/subclass profiling in more detail and incorporate autoantibody measurements beyond total IgG in disease models and clinical studies.

Myasthenia gravis (MG) is an acquired autoimmune disorder caused by autoantibodies binding acetylcholine receptors (AChR), muscle-specific kinase (MuSK), agrin or low-density lipoprotein receptor-related protein 4 (Lrp4). These autoantibodies inhibit neuromuscular transmission by blocking the function of these proteins and thereby cause fluctuating skeletal muscle weakness. Several reports suggest that these autoantibodies might also affect the central nervous system (CNS) in MG patients. A comprehensive overview of the timing and localization of the expression of MG-related antigens in other organs is currently lacking. To investigate the spatio-temporal expression of MG-related genes outside skeletal muscle, we used in silico tools to assess public expression databases. Acetylcholine esterase, nicotinic AChR α1 subunit, agrin, collagen Q, downstream of kinase-7, Lrp4, MuSK and rapsyn were included as MG-related genes because of their well-known involvement in either congenital or autoimmune MG. We investigated expression of MG-related genes in (1) all human tissues using GTEx data, (2) specific brain regions, (3) neurodevelopmental stages, and (4) cell types using datasets from the Allen Institute for Brain Sciences. MG-related genes show heterogenous spatio-temporal expression patterns in the human body as well as in the CNS. For each of these genes, several (new) tissues, brain areas and cortical cell types with (relatively) high expression were identified suggesting a potential role for these genes outside skeletal muscle. The possible presence of MG-related antigens outside skeletal muscle suggests that autoimmune MG, congenital MG or treatments targeting the same proteins may affect MG-related protein function in other organs., Pattern Recognition and Bioinformatics

Contains fulltext : 244198.pdf (Publisher’s version ) (Open Access), BACKGROUND: Mindfulness-Based Interventions (MBIs) are widely used in clinical and non-clinical populations, but little attention has been given to potential adverse effects (AEs). AIMS: This study aimed to gain insight in the prevalence and course of AEs during Mindfulness-Based Cognitive Therapy (MBCT) for patients with bipolar disorder (BD). METHOD: The current mixed-methods study was conducted as part of a RCT on (cost-) effectiveness of MBCT in 144 patients with BD (Trial registered on 25th of April 2018, ClinicalTrials.gov, NCT03507647). During MBCT, occurrence of AEs was monitored prospectively, systematically, and actively (n = 72). Patients who reported AEs were invited for semi-structured interviews after completing MBCT (n = 29). Interviews were analysed with directed content analysis, using an existing framework by Lindahl et al. RESULTS: AEs were reported by 29 patients, in seven of whom the experiences could not be attributed to MBCT during the interview. AEs were reported most frequently up to week 3 and declined afterwards. Baseline anxiety appeared to be a risk factor for developing AEs. Seven existing domains of AEs were observed: cognitive, perceptual, affective, somatic, conative, sense of self, and social. Influencing factors were subdivided into predisposing, precipitating, perpetuating, and mitigating factors. With hindsight, more than half of patients considered the reported AEs as therapeutic rather than harmful. CONCLUSIONS: Although the occurrence of AEs in MBCT for patients with BD is not rare, even in this population with severe mental illness they were not serious or had lasting bad effects. In fact, most of them were seen by the patients as being part of a therapeutic process, although some patients only experienced AEs as negative.

30 december 2021, Contains fulltext : 242463.pdf (Publisher’s version ) (Open Access), Background: Preliminary evidence suggests that Mindfulness-Based Cognitive Therapy (MBCT) is a promising treatment for bipolar disorder (BD). One of the proposed working mechanisms of MBCT in attenuating depressive symptoms is through the reduction of depressive rumination. In BD the effect of MBCT on rumination is less well studied. The primary aim of this study was to investigate the effect of MBCT on self-reported trait depressive rumination and an experimental state measure of negative intrusive thoughts. On an exploratory note, we investigated the effect of MBCT on positive rumination and positive intrusive thoughts.Methods: The study population consisted of a subsample of bipolar type I or II patients participating in a multicenter randomized controlled trial comparing MBCT + treatment as usual (TAU) (N = 25) to TAU alone (N = 24). Trait depressive rumination (RRS brooding subscale) and negative intrusive thoughts (breathing focus task (BFT)) were assessed at baseline and post-treatment. During the BFT, participants were asked to report negative, positive and neutral intrusive thoughts while focusing on their breathing. Results: Compared to TAU alone, MBCT + TAU resulted in a significant pre- to post-treatment reduction of trait depressive rumination (R2 = 0.16, F(1, 28) = 5.30, p = .029; medium effect size (f2 = 0.19)) and negative intrusive thoughts on the BFT (R2 = .15, F(1, 28) = 4.88, p = .036; medium effect size (f2 = 0.17)). MBCT did not significantly change positive rumination or positive intrusive thoughts on the BFT. Conclusions: MBCT might be a helpful additional intervention to reduce depressive rumination in BD which might reduce risk of depressive relapse or recurrence. Future research is required to replicate our findings and to explore whether this reduction in rumination following MBCT indeed mediates a reduction in depressive symptoms and leads to relapse prevention in BD.

Available online 8 June 2021., A variety of strategies are used to combine multi-echo functional magnetic resonance imaging (fMRI) data, yet recent literature lacks a systematic comparison of the available options. Here we compare six different approaches derived from multi-echo data and evaluate their influences on BOLD sensitivity for offline and in particular real- time use cases: a single-echo time series (based on Echo 2), the real-time T 2 ∗ -mapped time series ( T 2 ∗ FIT ) and four combined time series ( T 2 ∗ -weighted, tSNR-weighted, TE-weighted, and a new combination scheme termed T 2 ∗ FIT -weighted). We compare the influences of these six multi-echo derived time series on BOLD sensitivity using a healthy participant dataset ( N = 28) with four task-based fMRI runs and two resting state runs. We show that the T 2 ∗ FIT -weighted combination yields the largest increase in temporal signal-to-noise ratio across task and resting state runs. We demonstrate additionally for all tasks that the T 2 ∗ FIT time series consistently yields the largest offline effect size measures and real-time region-of-interest based functional contrasts and temporal contrast-to- noise ratios. These improvements show the promising utility of multi-echo fMRI for studies employing real-time paradigms, while further work is advised to mitigate the decreased tSNR of the T 2 ∗ FIT time series. We recommend the use and continued exploration of T 2 ∗ FIT for offline task-based and real-time region-based fMRI analysis. Supporting information includes: a data repository ( https://dataverse.nl/dataverse/rt-me-fmri ), an interactive web-based application to explore the data ( https://rt-me-fmri.herokuapp.com/ ), and further materials and code for reproducibility ( https://github.com/jsheunis/rt- me- fMRI ).

Radboud University, 27 januari 2021, Promotores : Speckens, A.E.M., Kuyken, W. Co-promotores : Huijbers, M.J., Ravesteijn, H.J. van, Contains fulltext : 228870.pdf (publisher's version ) (Open Access)

Radboud University, 21 september 2021, Promotores : Speckens, A.E.M., Spinhoven, P., Greven, C.U. Co-promotor : Huijbers, M.J., Contains fulltext : 236408.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 232402.pdf (Publisher’s version ) (Open Access)

Item does not contain fulltext, Steeds meer mensen gebruiken langdurig antidepressiva en niet alleen patiënten aarzelen om te stoppen. Meestal heeft de patiënt noch de huisarts duidelijk voor ogen wat er precies aan de orde moet komen in een gesprek over stoppen. Wij hebben bij zowel patiënten als zorgprofessionals geïnventariseerd wat voor hen de belangrijkste onderwerpen zijn, en een keuzehulp ontwikkeld voor gezamenlijke besluitvorming.

Digital technology is having a major impact on many areas of society, and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists, and representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency, and reproducibility in science. The perspective also includes a call to build an international community working in this important area.

In 2019, 34.000 divorces occurred in the Netherlands, after which 40% of the minor children involved, grew up with a stepparent. Adolescents who grow up in divorced families and stepfamilies appear to experience a lower sense of family belonging compared to those with intact families. The aim of this study is to examine whether living with a stepparent predicted adolescents’ perceptions of family belonging and the role of the quality of the parent-child relationship in this association. For this study, cross-sectional data were used from the first wave of the ongoing longitudinal study “Where Do I Belong?”. The sample consists of 188 adolescents from divorced families, aged 11 to 19. A stepwise multiple regression analysis was used to first examine if a live-in stepparent is a predictor for adolescents’ sense of family belonging. Next, if the quality of the parent-child relationship is a predictor. And finally, if there is an interaction effect. Analyses showed that for both parents' families, a live-in stepparent was a significant predictor, yet that the quality of the parent-child relationship seemed to be a more important predictor. The interaction effect was significant within the mother's family only. This research contributes to the knowledge of problems of divorced- and stepfamilies, which is required to improve expertise for better information and support for those families and to improve the overall well-being and development of children after parental divorce.

Latest published: 04 Feb 2021, A multi-echo fMRI dataset (N=28 healthy participants) with four task-based and two resting state runs was collected, curated and made available to the community. Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control, and adaptive paradigms, although the variety of experimental task paradigms supports a multitude of use cases. Tasks include finger tapping, emotional face and shape matching, imagined finger tapping and imagined emotion processing. This work provides a detailed description of the full dataset; methods to collect, prepare, standardize and preprocess it; quality control measures; and data validation measures. A web-based application is provided as a supplementary tool with which to interactively explore, visualize and understand the data and its derivative measures: https://rt-me-fmri.herokuapp.com/. The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri. Supporting information and code for reproducibility can be accessed at https://github.com/jsheunis/rt-me-fMRI

We introduce a new and time-efficient memory-encoding paradigm for functional magnetic resonance imaging (fMRI). This paradigm is optimized for mapping multiple contrasts using a mixed design, using auditory (environmental/vocal) and visual (scene/face) stimuli. We demonstrate that the paradigm evokes robust neuronal activity in typical sensory and memory networks. We were able to detect auditory and visual sensory-specific encoding activities in auditory and visual cortices. Also, we detected stimulus-selective activation in environmental-, voice-, scene-, and face-selective brain regions (parahippocampal place and fusiform face area). A subsequent recognition task allowed the detection of sensory-specific encoding success activity (ESA) in both auditory and visual cortices, as well as sensory-unspecific positive ESA in the hippocampus. Further, sensory-unspecific negative ESA was observed in the precuneus. Among others, the parallel mixed design enabled sustained and transient activity comparison in contrast to rest blocks. Sustained and transient activations showed great overlap in most sensory brain regions, whereas several regions, typically associated with the default-mode network, showed transient rather than sustained deactivation. We also show that the use of a parallel mixed model had relatively little influence on positive or negative ESA. Together, these results demonstrate a feasible, versatile, and brief memory-encoding task, which includes multiple sensory stimuli to guarantee a comprehensive measurement. This task is especially suitable for large-scale clinical or population studies, which aim to test task-evoked sensory-specific and sensory-unspecific memory-encoding performance as well as broad sensory activity across the life span within a very limited time frame.

Contains fulltext : 238430.pdf (Publisher’s version ) (Open Access)

A variety of strategies are used to combine multi-echo functional magnetic resonance imaging (fMRI) data, yet recent literature lacks a systematic comparison of the available options. Here we compare six different approaches derived from multi-echo data and evaluate their influences on BOLD sensitivity for offline and in particular real-time use cases: a single-echo time series (based on Echo 2), the real-time T2*-mapped time series (T2*FIT) and four combined time series (T2*-weighted, tSNR-weighted, TE-weighted, and a new combination scheme termed T2*FIT-weighted). We compare the influences of these six multi-echo derived time series on BOLD sensitivity using a healthy participant dataset (N = 28) with four task-based fMRI runs and two resting state runs. We show that the T2*FIT-weighted combination yields the largest increase in temporal signal-to-noise ratio across task and resting state runs. We demonstrate additionally for all tasks that the T2*FIT time series consistently yields the largest offline effect size measures and real-time region-of-interest based functional contrasts and temporal contrast-to-noise ratios. These improvements show the promising utility of multi-echo fMRI for studies employing real-time paradigms, while further work is advised to mitigate the decreased tSNR of the T2*FIT time series. We recommend the use and continued exploration of T2*FIT for offline task-based and real-time region-based fMRI analysis. Supporting information includes: a data repository (https://dataverse.nl/dataverse/rt-me-fmri), an interactive web-based application to explore the data (https://rt-me-fmri.herokuapp.com/), and further materials and code for reproducibility (https://github.com/jsheunis/rt-me-fMRI).

Digital technology is having a major impact on many areas of society, and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists, and representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency, and reproducibility in science. The perspective also includes a call to build an international community working in this important area.

Digital technology is having a major impact on many areas of society and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists and the representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency and reproducibility in science. The retrospective also includes a call to build an international community working on this important area.

Digital technology is having a major impact on many areas of society and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists and the representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency and reproducibility in science. The retrospective also includes a call to build an international community working on this important area.

Contains fulltext : 225979.pdf (Publisher’s version ) (Open Access)

30 april 2020, Contains fulltext : 220957.pdf (Publisher’s version ) (Open Access)