Title Promoter Affiliations Abstract "Cognitive assessment platform (CAP): Capturing physiological interaction parameters of caregivers during stressful ICU interventions, towards the development of dynamic caregivers' assistant interfaces (CAI)." "Kristof Vaes, Guido De Bruyne" "Laboratory Experimental Medicine and Pediatrics (LEMP), Product development" "An intensive care unit (ICU) is a safety critical environment where caregivers' activities are crucial to human lives. Adverse events, defined as injuries or complications that are provoked by a medical human error rather than the patient's underlying disease, occur in about one-third of cases in adult ICU patients and the risk of error is cumulative. The risk factors of adverse events include high nursing workload, caregivers' sleep deprivation or fatigue, communication failure, a high patient-to-nurse ratio and poor management. Work-related stress with the accompanying emotions provoked specifically in ICU is well documented. Nonetheless, only few studies have utilized physiological measures regarding research conducted on stress on medical caregivers.Within this project, it is aimed to develop a cognitive assessment platform (CAP) which comprises wearable sensors to enable monitoring of physiological parameters and location in real-time of caregivers within an ICU. This allows creating cognitive states of caregivers, linked to time and place. Workload, fatigue and stress are the monitored cognitive states, as they are the most significant threats towards patient safety. This innovative approach will allow us to correlate the cognitive states of caregivers with specific locations at the ICU, TISS-28, tasks and episodes during their working day and night, which will provide new insights and better understanding of the workflow of the ICU caregivers. Ultimately, this research may provide rich opportunities for examination and discovery in optimising the workflow of ICU caregivers." "iNNOCENS: data driven clinical decision support for improved neonatal care." "Kris Laukens" "Laboratory Experimental Medicine and Pediatrics (LEMP), ADReM Data Lab (ADReM)" "Analysis of patient related vital parameters generated in a continuous manner on a neonatal intensive care department offers the opportunity to develop computational models that can predict care-related complications. This project aims to develop a machine learning model that can predict acquired brain injury of prematurity. The model can than be implemented to generate bedside visualizations in the context of a self-learning digital early warning system." "Using molecular proximity to refine synapse quantification in neuronal cultures." "Alfonso Gerardo Garcia" "Laboratory of cell biology and histology" "Synapses are specialized connections between neuronal cells that determine the wiringpatterns, which are essential for memory and cognition. Synaptic dysfunction is a commonpathological hallmark of neurodevelopmental and - degenerative conditions. Thus, accurateand reliable quantification of synaptic state and number in neuronal networks is crucial. Inprevious work, we have shown that primary neuronal cultures from rodents preserve manymorphological and functional properties of in vivo neuronal networks and can be used toevaluate the impact of chemo-genetic perturbations on synaptic state. However, the largenumber of synapses on the one hand, and the variable specificity of existing microscopytechniques on the other hand, makes synapse quantification in these cultures a balancing actbetween accuracy and throughput. To improve both, we propose to make use of a novelmethod, termed Proximity Ligation Assay (PLA), that can directly visualize molecularinteractions using a standard fluorescence microscope. To do so, we will first identify anoptimal set of trans-synaptic protein interactors. Then, we will validate the PLA technique anduse it to measure synapse density after application of targeted perturbations. By applying PLAto trans-synaptic proteins, we aim at detecting true synapses with superior specificity. Thisshould enhance the sensitivity with which we can detect changes in synapse density, andtherefore it has the potential to accelerate the identification of synaptic modulators in ourongoing screening efforts." "Elucidating the role of alternative trans-splicing in the mRNA abundance regulation of Leishmania." "Bart Cuypers" "ADReM Data Lab (ADReM)" "Leishmania is a genus of protozoan parasites that cause the disease leishmaniasis in humans and a wide array of vertebrate animals. The parasite exhibits a remarkable gene expression system where genes lack individual RNA polymerase II promoters and are therefore not individually controllable by transcription factors. Instead, genes are transcribed constitutively in long polycistronic units of functionally unrelated genes and co-transcriptionally processed to individual mRNAs per gene during a process called 'trans-splicing'. During trans-splicing, mRNAs receive a fixed 39 nucleotide sequence at their 5' end called 'spliced-leader'. The location where this spliced-leader is added is variable, resulting in different possible transcript lengths for a single gene (alternative trans-splicing). The abundance of mRNA per gene appears to be regulated entirely post-transcriptionally, however, it is currently unclear how this occurs. This project aims to determine the role of alternative trans-splicing in the mRNA abundance regulation of Leishmania. As this process determines the length of the transcript, we hypothesise that it affect the abundance of a transcript by altering its stability and/or included regulatory motifs. For the first time, we will make use of long read mRNA sequencing (PacBio) to study the changes in transcript repertoires during different life stages of Leishmania donovani. Additionally, we aim to identify the motifs and/or RNA structural patterns which regulate the location and usage frequency of alternative trans-splicing and polyadenylation sites. This will be investigated making use of state-of-the art pattern finding and classification approaches." "Sequencing DNA of museum specimens to uncover the genetic basis of rapid adaptation to heavy fishing." "Hannes Svardal" "Systemic Physiological and Ecotoxicological Research (SPHERE)" "We currently lack a detailed understanding of how organisms rapidly adapt genetically to environmental changes. However, gaining such an understanding is key in evaluating and predicting human impact on nature, can uncover the genetic basis of adaptive traits, and give insight into fundamental evolutionary processes. To address this, we will dissect the genetic factors contributing to rapid adaptation in Lake Malawi cichlid fish populations following ~40 years of extremely heavy fishing. We have already collected and whole-genome sequenced 96 samples from present day weakly and heavily fished populations. Analysis of these samples suggested overall very close relatedness between populations, but identified the presence of candidate genomic regions of high genetic divergence between weakly and heavily fished populations. Here we suggest to sequence the genomes of museum specimens (an innovative technique sometimes referred to as ""museomics"") from the same populations before the onset of heavy fishing and during fishing. Samples are available through established collaborations with the British Museum of Natural History, the Monkey Bay Fisheries Research Station in Malawi, and Prof. Erik Verheyen (University of Antwerp and Royal Belgian Institute of Natural Sciences). Comparing the genetic composition of historic populations with the present-day genetic composition (after 40 years of heavy fishing) will enable us to identify candidate genes conferring adaptation to fishing. We have performed a pilot study, which suggests that the museum specimens used in this study yield sufficient DNA for genome sequencing. We also have recently established breeding colonies of the same fish populations at the University of Antwerp, which will allow us in future projects to follow up phenotypic changes related to the genetic adaptations identified here. This project will yield important data and results to support an ERC starting grant application by the applicant on this study system that aims to dissect the links between genotypes, phenotypes and selective pressures in rapid human-induced evolution." "Shifting rainfall regimes: a multi-scale analysis of ecosystem response (REGIME SHIFT)." "Ivan Nijs" "ADReM Data Lab (ADReM), Integrated Molecular Plant Physiology Research (IMPRES), Plant and Ecosystems (PLECO) - Ecology in a time of change" "Recent climate change research reveals a novel and significant trend: weather patterns at mid-latitudes, such as in temperate western Europe, are getting more persistent. With respect to rainfall, this means longer droughts, but also longer periods with excessive rain. No comprehensive study has hitherto investigated the ecological consequences of such regime shifts. Can ecosystems adapt, or will the alternation between drought stress and soil water saturation exhaust them? Will this select for communities with novel trait combinations and more volatile species dynamics? And will these novel systems still be robust in the face of further changes in the environment? This study explores the potential impact of the ongoing shift in the frequency of dry/wet cycles at multiple, connected levels of biological organization. It does so in a new, large-scale set-up at UAntwerp built in the framework of the developing European infrastructure for ecosystem research 'AnaEE'. The design simulates changes in rainfall and associated temperature changes in the open air, using a gradient with eight precipitation regimes so that non-linearity and tipping points can be discerned with great precision. The project scope ranges from plants to soil biota such as bacteria and fungi, and from metabolism and genetic regulation assessed with bioinformatics to ecosystem processes. This multi-scale approach explicitly acknowledges the interwoven nature of ecosystems, with knowledge of molecular and cellular changes being instrumental to mechanistically explain the whole-system-scale effects on productivity, greenhouse gas fluxes and biodiversity dynamics. Different experiments are planned each year: (i) year 1 features a gradient in alternating dry/wet cycles, from 1 to 60 days, across a full growing season; (ii) year 2 focuses on legacy effects and the importance of changes of soil communities; (iii) year 3 matches precipitation regimes to corresponding temperature regimes to study the impact of drought-associated warming (an important natural feedback that can greatly increase plant stress). A series of connected, hypothesis-driven measurements is carried out, which will be integrated using structural equation modelling (path analysis) and ecosystem modelling. The project team has successfully collaborated in the past, and the complementary expertise brought together here should yield both significantly increased understanding of key processes as well as new avenues to climate change impact mitigation." "Establishing a computational classification framework for tumour-specific T-cells." "Pieter Meysman" "ADReM Data Lab (ADReM)" "This project aims to construct a computational framework to predict which T-cells can react to a tumour-associated epitope. Key problems that will be investigated are the optimal feature representation as well as the most performant classification strategy. As a proof-of-concept, we will apply the framework on a unique dataset generated by combining a tetramer assay with single cell sequencing." "Data-based modeling of recovery from mastitis in dairy cows" "Ben Aernouts" "Electrical Engineering Technology (ESAT), Geel Campus, Division of Mechatronics, Biostatistics and Sensors (MeBioS), Bioengineering Technology, Geel Campus" "The prevention, detection and treatment of mastitis forms the basis for the contemporary udder-health management. After detection and startup of treatment, recovery; being the suppression of the causal pathogen (bacteriological healing), the disappearance of clinical symptoms and the regeneration of the udder tissue (clinical healing) isn't objetively monitored. Due to lack of information about this recovery, it is impossible for the dairy farmer to estimate the effectiveness of the treatment and to adjust the duration of treatment and further support. This results in excessive antibiotic use in the case of a too long treatment and, on the other hand, the absence of complete recovery by too short or suboptimal treatment.In previously conducted studies, two models were developed to estimate and monitor the severity of the infection and the inflammatory response in mastitis, as well as the recovery:1) A production model that makes it possible to accurately calculate the milk losses by mastitis at quarterly level2) A recovery model based on (historical) animal data and dairy production- & quality records currently available on modern dairy farms.In this project, these models are optimized and validated on Flemish dairy farms so that this knowledge can be used to improve the udder-health." "Rapid vaccine development through immunoinformatics ans immunisequencing." "Kris Laukens" "Centre for Health Economics Research and Modelling of Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), ADReM Data Lab (ADReM)" "Vaccines are used to stimulate the immune system in its defense against pathogens and cancer. Vaccine development involves extensive clinical trials that study the changes in antibodies and immune cells in response to the vaccine to determine their efficacy and safety. This is often an extensive and costly process, with a high failure rate. This project aims to develop a computational framework for use within vaccine clinical trials to make the process more efficient, more rapid and more accurate. The basis of this framework is the new immunological and molecular insights that have been gained through the advent of immunosequencing and immune-informatics technologies, and it builds further upon a successful collaboration between immunologists and data scientists." "Computational investigations of the catalytic mechanism of Staphylococcus aureus transglycosylase: design and chemical synthesis of novel mechanism-based inhibitors." "Hans De Winter" "Medicinal Chemistry (UAMC)" "Bacterial resistance against current medications is a growing problem that will pose significant health problems in the near future. Penicillins are a class of antibiotics that exert there effect by blocking the biosynthesis of the bacterial cell wall by means of inhibition of the transpeptidase protein, an enzyme responsible for the synthesis of the essential glycan chains in the cell wall. An alternative approach to inhibit the growth of the bacterial cell wall would be by inhibition of the transglycosylase enzyme, a protein involved in the polymerisation of the sugar chains that make up the backbone of these glycan chains. Currently there are no medications on the market or in clinical trials that have a mechanism of action of glycosyltransferase inhibition, but it has been shown that blocking the normal function of this enzyme leads to inhibition of bacterial cell growth. The main objective of the current project is to identify potent inhibitors against this transglycosylase enzyme using large-scale molecular dynamics simulations to study the catalytic mechanism of action and kinetics in large detail. Results of these simulations will be used to propose novel chemical compounds that will be synthesized through a collaboration with the University of Leuven. Biochemical testing of the antibacterial effects of these compounds will be performed at the University of Liège."