Recente incidenten met ransomware tonen aan dot veel organisaties hun informatiebeveiliging nog niet op orde hebben. Informatiebeveiliging op orde brengen vraagt naast technische middelen ook om beleid en informatiebeveiligingsbewustzijn bij medewerkers. Deze combinatie betekent dot het een illusie is te denken dot organisaties van de ene op de andere dog hun informatiebeveiliging op orde kunnen hebben. Er is behoefte aan een model waarlangs organisaties stappen kunnen zetten om hun informatiebeveiliging op orde te brengen. Linkedin: https://www.linkedin.com/in/herman-de-bruine-b0aa9b4/ https://www.linkedin.com/in/fabio-lucero-garau-04836080/ https://www.linkedin.com/in/marcelspruit/
Handleiding voor studenten die een rapport of scriptie moeten schrijven over het omgaan met bronnen. Wanneer en hoe geef je door jou geraadpleegde boeken, rapporten, websites, films en dergelijke weer in je rapport/scriptie?
De behoefte om informatie te ordenen zodat ze 'beheersbaar' wordt, resulteert vaak in een top-down aanpak zoals bibliotheeksystemen die kennen. Betrekkelijk nieuw is de bottom-up aanpak, metadatering gebaseerd op het sociale aspect van consensus. Sybilla Poortman en Gerard Bierens zoomen in op de achtergronden van folksonomy en nemen de nieuwe 'sociale' tools onder de loep met aandacht voor toepassingsmogelijkheden in de bibliotheekomgeving. En ook: folksonomy versus taxonomie, samen door één deur of ieder een eigen ingang?
Every year the police are confronted with an ever increasing number of complex cases involving missing persons. About 100 people are reported missing every year in the Netherlands, of which, an unknown number become victims of crime, and presumed buried in clandestine graves. Similarly, according to NWVA, several dead animals are also often buried illegally in clandestine graves in farm lands, which may result in the spread of diseases that have significant consequences to other animals and humans in general. Forensic investigators from both the national police (NP) and NWVA are often confronted with a dilemma: speed versus carefulness and precision. However, the current forensic investigation process of identifying and localizing clandestine graves are often labor intensive, time consuming and employ classical techniques, such as walking sticks and dogs (Police), which are not effective. Therefore, there is an urgent request from the forensic investigators to develop a new method to detect and localize clandestine graves quickly, efficiently and effectively. In this project, together with practitioners, knowledge institutes, SMEs and Field labs, practical research will be carried out to devise a new forensic investigation process to identify clandestine graves using an autonomous Crime Scene Investigative (CSI) drone. The new work process will exploit the newly adopted EU-wide drone regulation that relaxes a number of previously imposed flight restrictions. Moreover, it will effectively optimize the available drone and perception technologies in order to achieve the desired functionality, performance and operational safety in detecting/localizing clandestine graves autonomously. The proposed method will be demonstrated and validated in practical operational environments. This project will also make a demonstrable contribution to the renewal of higher professional education. The police and NVWA will be equipped with operating procedures, legislative knowledge, skills and technological expertise needed to effectively and efficiently performed their forensic investigations.
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).
The missing link in diagnostic testing for rheumatoid arthritis (RA) is an agglutination assay, easy to perform and dedicated to decentralized testing. Approximately 75% of RA patients produce autoantibodies to citrullinated proteins (ACPA), which can be detected using an agglutination-based diagnostic test. Such a diagnostic test will be cheaper, less laborious and faster than current tests and does not require sophisticated equipment. Novio Catalpa is developing this alternative test for ACPA in collaboration with Radboud University. To develop this test, specifically tagged and citrullinated nanobodies are needed, but the production is still challenging. Current methods for the production of ACPA diagnostics involve chemical synthesis, in which a variety of toxic chemicals are used in each step. The alternative assay involves nanobodies fused with RA-biomarker target entities, which can be completely produced by ‘green synthesis’ in the yeast Pichia pastoris using the expertise of HAN BioCentre. The yeast P. pastoris has proven to be able to produce nanobodies and is a fast and cost-effective platform that often results in high protein yields. Goal of the project is therefore to determine the feasibility and best green route to produce purified nanobodies tagged with citrullinated ACPA targets that can be used for developing an agglutination assay for RA. P. pastoris does not produce endogenous PAD enzymes which are needed for citrullination of the nanobodies in order to be able to use it in a RA agglutination test. Therefore, PAD enzymes from other sources need to be tested and applied. The project results will be directly used by Novio Catalpa to further develop the innovative test for RA. This project will contribute to and finally result in a single-step agglutination assay suitable for both point-of-care testing and automation in clinical laboratories.
