Loneliness among young adults is a growing concern worldwide, posing serious health risks. While the human ecological framework explains how various factors such as socio-demographic, social, and built environment characteristics can affect this feeling, still, relatively little is known about the effect of built environment characteristics on the feelings of loneliness that young people experience in their daily life activities. This research investigates the relationship between built environment characteristics and emotional state loneliness in young adults (aged 18–25) during their daily activities. Leveraging the Experience Sampling Method, we collected data from 43 participants for 393 personal experiences during daily activities across different environmental settings. The findings of a mixed-effects regression model reveal that built environment features significantly impact emotional state loneliness. Notably, activity location accessibility, social company during activities, and walking activities all contribute to reducing loneliness. These findings can inform urban planners and municipalities to implement interventions that support youngsters’ activities and positive experiences to enhance well-being and alleviate feelings of loneliness in young adults. Specific recommendations regarding the built environment are (1) to create spaces that are accessible, (2) create spaces that are especially accessible by foot, and (3) provide housing with shared facilities for young adults rather than apartments/studios.
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Matrix-assisted laser desorption/ionisation time of-flight mass spectrometry (MALDI-TOF MS) is a fast and reliable method for the identification of bacteria from agar media. Direct identification from positive blood cultures should decrease the time to obtaining the result. In this study, three different processing methods for the rapid direct identification of bacteria from positive blood culture bottles were compared. In total, 101 positive aerobe BacT/ALERT bottles were included in this study. Aliquots from all bottles were used for three bacterial processing methods, i.e. the commercially available Bruker's MALDI Sepsityper kit, the commercially available Molzym's MolYsis Basic5 kit and a centrifugation/washing method. In addition, the best method was used to evaluate the possibility of MALDI application after a reduced incubation time of 7 h of Staphylococcus aureus- and Escherichia coli-spiked (1,000, 100 and 10 colony-forming units [CFU]) aerobe BacT/ALERT blood cultures. Sixty-six (65%), 51 (50.5%) and 79 (78%) bottles were identified correctly at the species level when the centrifugation/washing method, MolYsis Basic 5 and Sepsityper were used, respectively. Incorrect identification was obtained in 35 (35%), 50 (49.5%) and 22 (22%) bottles, respectively. Gram-positive cocci were correctly identified in 33/52 (64%) of the cases. However, Gram-negative rods showed a correct identification in 45/47 (96%) of all bottles when the Sepsityper kit was used. Seven hours of pre-incubation of S. aureus- and E. coli-spiked aerobe BacT/ALERT blood cultures never resulted in reliable identification with MALDI-TOF MS. Sepsityper is superior for the direct identification of microorganisms from aerobe BacT/ALERT bottles. Gram-negative pathogens show better results compared to Gram-positive bacteria. Reduced incubation followed by MALDI-TOF MS did not result in faster reliable identification.
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).
Routine neuropathology diagnostic methods are limited to histological staining techniques or directed PCR for pathogen detection and microbial cultures of brain abscesses are negative in one-third of the cases. Fortunately, due to improvements in technology, metagenomic sequencing of a conserved bacterial gene could provide an alternative diagnostic method. For histopathological work up, formalin-fixed paraffin-embedded (FFPE) tissue with highly degraded nucleic acids is the only material being available. Innovative amplicon-specific next-generation sequencing (NGS) technology has the capability to identify pathogens based on the degraded DNA within a few hours. This approach significantly accelerates diagnostics and is particularly valuable to identify challenging pathogens. This ensures optimal treatment for the patient, minimizing unnecessary health damage. Within this project, highly conserved primers in a universal PCR will be used, followed by determining the nucleotide sequence. Based on the obtained data, it is then precisely determined which microorganism(s) is/are responsible for the infection, even in cases of co-infection with multiple pathogens. This project will focus to answer the following research question; how can a new form of rapid molecular diagnostics contribute to the identification of microbial pathogens in CNS infections? The SME partner Molecular Biology Systems B.V. (MBS) develops and sells equipment for extremely rapid execution of the commonly used PCR. In this project, the lectorate Analysis Techniques in the Life Sciences (Avans) will, in collaboration with MBS, Westerdijk Institute (WI-KNAW) and the Institute of Neuropathology (Münster, DE) establish a new molecular approach for fast diagnosis within CNS infections using this MBS technology. This enables the monitoring of infectious diseases in a fast and user-friendly manner, resulting in an improved treatment plan.
