Publications by authors named "Peeters L"

In term neonates with hypoxic-ischemic encephalopathy (HIE), cerebellar injury is becoming more and more acknowledged. Animal studies demonstrated that Purkinje cells (PCs) are especially vulnerable for hypoxic-ischemic injury. In neonates, however, the extent and pattern of PC injury has not been investigated.

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Purpose: Knee joint distraction is a surgical procedure with cartilage-regenerating properties. The composition of joint distraction-regenerated cartilage in human patients is poorly documented. In this case-study, provided a unique opportunity to biomolecularly characterize the regenerated tissue from a patient who underwent bilateral distraction and later knee replacements.

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  • MRI is essential for diagnosing and monitoring multiple sclerosis (MS), but standard scans often have limited resolution due to thick slices, which affects automated analysis.
  • This study introduces a single-image super-resolution (SR) reconstruction framework using convolutional neural networks (CNN) to enhance MRI resolution in individuals with MS.
  • The results show that the SR method significantly improves MRI reconstruction accuracy and lesion segmentation, making it a valuable tool for analyzing low-resolution MRI data in clinical settings.
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This paper explores the significant role of real-world data (RWD) in advancing our understanding and management of Multiple Sclerosis (MS). RWD has proven invaluable in MS research and care, offering insights from larger and diverse patient populations. A key focus of the paper is the European Health Data Space (EHDS), a significant development that promises to change how healthcare data is managed across Europe.

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Background: The metabotropic glutamate type 5 (mGlu5) receptor has emerged as a potential target for the treatment of psychosis that is suggested to have greater efficacy than antipsychotic medications that are currently utilized.

Aims: This study sought to elucidate mechanisms of therapeutic action associated with the modulation of the mGlu5 receptor in a disordered system marked by dopamine dysfunction. We further explored epigenetic mechanisms contributing to heritable transmission of a psychosis-like phenotype in a novel heritable model of drug abuse vulnerability in psychosis.

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Objectives: Evidence on the optimal frequency of laboratory testing during outpatient parenteral antimicrobial therapy (OPAT) is lacking. Therefore, we investigated how often and when laboratory abnormalities occur during OPAT and which factors are associated with these abnormalities.

Methods: We performed a multicenter cohort study in four Dutch hospitals among adult patients receiving OPAT and collected routinely obtained laboratory test results.

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  • Diuretic resistance is when medications that help remove extra fluid from the body don’t work well, which can lead to worse health outcomes for patients with heart problems. Researchers looked at how urine sodium levels (how much sodium is in urine) can help adjust these medications to make them more effective.
  • The study included 143 patients with heart failure, and they found that those with low urine sodium levels also had other health issues. They measured urine sodium two hours after giving medicine to patients and looked at how this affected hospital visits and overall survival after 90 days.
  • The results showed that low urine sodium was common and often found in patients with serious heart and kidney problems,
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Intermediate-length repeat expansions in ATAXIN-2 (ATXN2) are the strongest genetic risk factor for amyotrophic lateral sclerosis (ALS). At the molecular level, ATXN2 intermediate expansions enhance TDP-43 toxicity and pathology. However, whether this triggers ALS pathogenesis at the cellular and functional level remains unknown.

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Real-world data (RWD) has the potential to revolutionize healthcare by offering valuable insights into patient outcomes and treatment efficacy. However, leveraging RWD effectively presents challenges, including its inherent limitations, diverse stakeholders, and insufficient data management pipelines. A proposed framework advocates three essential elements: adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable), stakeholder engagement and education, and highlighting the need for inclusive, pragmatic federated hybrid pipelines.

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  • * Machine learning models were applied to predict confirmed disability progression after two years, achieving a ROC-AUC score of 0.71, indicating moderate accuracy, while historical disability was found to be a stronger predictor than treatment or relapse history.
  • * The research followed strict guidelines and made its coding accessible for others to facilitate future benchmarking in predicting disability progression in MS patients.
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Water-table maps are fundamental to hydrogeological studies and a manual, hand-drawn method is still commonly used to produce them. Despite this, the accuracy and variability of such maps have received little attention in international literature. In a unique experiment, 63 groundwater professionals drew water-table equipotential contours based on the same dataset of point measurements and were asked to infer flow directions and predict groundwater elevations at predefined locations.

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Background: The integrity and reliability of clinical research outcomes rely heavily on access to vast amounts of data. However, the fragmented distribution of these data across multiple institutions, along with ethical and regulatory barriers, presents significant challenges to accessing relevant data. While federated learning offers a promising solution to leverage insights from fragmented data sets, its adoption faces hurdles due to implementation complexities, scalability issues, and inclusivity challenges.

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  • * The initiative has formed four working groups aimed at enhancing research, clinical management, eHealth, and healthcare system reforms, ensuring a collaborative effort among patients, caregivers, and other stakeholders.
  • * As it progresses, the initiative plans to boost the use of eHealth tools and passive PROs in research and clinical settings, while also refining statistical methods in clinical trials and fostering alignment among industry, regulatory bodies, and health policymakers regarding PROs in MS healthcare.
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Antihypertensive drugs do not qualify as optimal candidates for therapeutic drug monitoring (TDM), given their obvious physiological effect, the absence of a clear relationship between drug concentrations and pharmacodynamic outcomes and their wide therapeutic range. However, since non-adherence is a major challenge in hypertension management, using drug concentrations can be of value to identify non-adherence as a first step towards better blood pressure control. In this article we discuss the key challenges associated with measuring and interpreting antihypertensive drug concentrations that are important when TDM is used to improve non-adherence.

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Objective: To assess the impact of personalized feedback on therapy adherence testing results on quality of life and beliefs about medication in patients with resistant hypertension, as well as to identify patient-oriented predictors of therapy adherence.

Methods: This study was a prespecified post hoc analysis of the multicenter randomized controlled trial Resistant HYpertension: MEasure to ReaCh Targets (RHYME-RCT). Patients were randomized to a personalized feedback conversation on measured antihypertensive drug levels additional to standard-of-care, or standard-of-care only.

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Background: Hypertension, a significant risk factor for cardiovascular diseases, demands proactive management as cardiovascular diseases remain the leading cause of death worldwide. Reducing systolic and diastolic blood pressure levels below recommended reference values of <140/90 mmHg can lead to a significant reduction of the risk of CVD and all-cause mortality. However, treatment of hypertension can be difficult and the presence of comorbidities could further complicate this treatment.

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Rationale: Antipsychotic medications that are used to treat psychosis are often limited in their efficacy by high rates of severe side effects. Treatment success in schizophrenia is further complicated by high rates of comorbid nicotine use. Dopamine D heteroreceptor complexes have recently emerged as targets for the development of more efficacious pharmaceutical treatments for schizophrenia.

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Introduction: The primary objective of the core data set is to reduce heterogeneity and promote harmonization among data sources in EM, thereby reducing the time needed to execute real life data collection efforts. Recently, a group led by the Multiple Sclerosis Data Alliance has developed a core data set for collecting real-world data on multiple sclerosis (MS) globally. Our objective was to adapt this global data set to the needs of Latin America, so that it can be implemented by the registries already developed and in the process of development in the region.

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Objective: Osteoarthritis (OA) is characterized by articular cartilage erosion, pathological subchondral bone changes, and signs of synovial inflammation and pain. We previously identified p[63-82], a bone morphogenetic protein 7 (BMP7)-derived bioactive peptide that attenuates structural cartilage degeneration in the rat medial meniscal tear-model for posttraumatic OA. This study aimed to evaluate the cartilage erosion-attenuating activity of p[63-82] in a different preclinical model for OA (anterior cruciate ligament transection-partial medial meniscectomy [anterior cruciate ligament transection (ACLT)-pMMx]).

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The combination of physical equations with deep learning is becoming a promising methodology for bioprocess digitalization. In this paper, we investigate for the first time the combination of long short-term memory (LSTM) networks with first principles equations in a hybrid workflow to describe human embryonic kidney 293 (HEK293) culture dynamics. Experimental data of 27 extracellular state variables in 20 fed-batch HEK293 cultures were collected in a parallel high throughput 250 mL cultivation system in an industrial process development setting.

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Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system, causing increased vulnerability to infections and disability among young adults. Ever since the outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infections, there have been concerns among people with MS (PwMS) about the potential interactions between various disease-modifying therapies and COVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) was initiated in 2020 with the aim of addressing these concerns.

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Article Synopsis
  • - As of September 2022, a lack of standardized core data elements for multiple sclerosis (MS) hindered effective data sharing and collaboration in healthcare and research.
  • - A global task force of 20 experts developed a core dataset of 44 variables in eight categories to improve data consistency from real-world data sources, which includes demographic information, disease history, MRI results, and treatment details.
  • - The resulting MS Data Alliance Core Dataset aims to assist newly formed and existing registries, promoting data harmonisation and improving research outcomes in the field of MS.
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Purpose: Hypertension significantly contributes to cardiovascular diseases and premature deaths. Effective treatment is crucial to reduce cardiovascular risks, but poor adherence to antihypertensive drugs is a major issue. Numerous studies attempted to investigate interventions for identifying non-adherence, but often failed to address the issue effectively.

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