Reverse engineering of metabotropic glutamate receptor-dependent long-term depression in the hippocampus

status: publishe

Towards Individualised Model-based Monitoring: From Biology to Technology

One of the main obstacles in applying engineering approaches to biological processes remains dealing with inter- and intra-individual differences. Therefore, it is highly challenging to accurately monitor their individual state (cfr. personalised medicine). The general objective of this PhD is to develop a framework for individualised model-based monitoring for biological processes, as inspired by control engineering concepts. The presented approach addresses four main topics: i) the biological process itself (i.e. bio-process), ii) the process model, iii) model-based features and iv) individualised change detection based on individual thresholds. In order to explore the general objective, six different case studies (cell, embryo, animal, human) were examined: i) individualised monitoring of activity and body weight in the activity-based anorexia rat model, ii) individualised model-based monitoring of interleukin-6 for early detection of infection in pigs, iii) model-based monitoring of heart rate and blood cytokine time series for early detection of infections in critically ill patients, iv) model-based monitoring of mGluR-dependent synaptic plasticity in hippocampal brain slices of rat, v) individualised monitoring of hippocampal theta oscillations and individualised electrical stimulation in the mesencephalic reticular formation for real-time closed-loop suppression of locomotion in rat and vi) individualised model-based monitoring of chicken embryo status during incubation based on eggshell temperature and micro-environmental air temperature. The results showed that the individual bio-processes involved (individual structure, individual dynamics, bio-signals) can be considered as the biological equivalents of clever-designed control engineering components by defining actuator and homeostatic variables for each of the six case studies (case studies i-vi). Although biological processes are known to contain many nonlinearities, compact individual linear models (general Box-Jenkins models) could be used for the specific individualised monitoring applications of the case studies. By using these models we obtained good approximations of the individual bio-process dynamics (case studies ii, iii, iv and vi), since biological systems often show relatively simple responses (expressing the crucial dominant processes that ascertain healthy internal homeostatic or homeodynamic conditions) when exposed to perturbations as illustrated by the bio-processes of the case studies. In addition, we were able to uncover information about the underlying mechanisms/state by applying data-based mechanistic modelling approaches (i.e. case studies iv and vi). Based on the results, we suggest three different model-based features (model parameter changes, changes in model order and changes in the noise model). In addition, more than 20 other generic metrics from the fields of complex systems science, change detection and control engineering were identified that can be used while analysing individual time series (case studies i-vi). This list of metrics can be used for all individual bio-processes in the design of model-based monitoring application. Based on the specific case studies, three possible approaches were proposed for model-based monitoring of bio-processes based on individual thresholds (e.g. case studies v and vi): 1) individual thresholds based on (sub-)population information, 2) individual thresholds based on universal laws and insights from control engineering, complex systems science and biology and 3) individual thresholds based on individual serial baseline measurements, which can be considered as the most individualised way. To conclude, this thesis has led to some innovative individualised monitoring applications based on each of the six specific case studies. Until now the existence of general frameworks for individualised model-based monitoring of biological processes is limited. Each specific case contributed to the development of such general framework inspired by control engineering concepts. The presented general approach could be used in a broad range of application domains, thus stressing the generic power of the suggested framework for individualized model-based monitoring of (complex) bio-processes.status: publishe

An evaluation of the effect of pulse-shape on grey and white matter stimulation in the rat brain

Despite the current success of neuromodulation, standard biphasic, rectangular pulse shapes may not be optimal to achieve symptom alleviation. Here, we compared stimulation efficiency (in terms of charge) between complex and standard pulses in two areas of the rat brain. In motor cortex, Gaussian and interphase gap stimulation (IPG) increased stimulation efficiency in terms of charge per phase compared with a standard pulse. Moreover, IPG stimulation of the deep mesencephalic reticular formation in freely moving rats was more efficient compared to a standard pulse. We therefore conclude that complex pulses are superior to standard stimulation, as less charge is required to achieve the same behavioral effects in a motor paradigm. These results have important implications for the understanding of electrical stimulation of the nervous system and open new perspectives for the design of the next generation of safe and efficient neural implants.status: publishe

Electrical stimulation of the bed nucleus of the stria terminalis reduces anxiety in a rat model

We recently showed that deep brain stimulation (DBS) in the bed nucleus of the stria terminalis (BST) reduces obsessions, compulsions and associated anxiety in patients suffering from severe, treatment-refractory obsessive-compulsive disorder. Here, we investigated the anxiolytic effects of electrical BST stimulation in a rat model of conditioned anxiety, unrelated to obsessions or compulsions. Two sets of stimulation parameters were evaluated. Using fixed settings at 100 Hz, 40 µs and 300 µA (Set A), we observed elevated freezing and startle levels, whereas stimulation at 130 Hz, 220 µs and individually tailored amplitudes (Set B) appeared to reduce freezing. In a follow-up experiment, we evaluated the anxiolytic potential of Set B more extensively, by adding a lesion group and an additional day of stimulation. We found that electrical stimulation significantly reduced freezing, but not to the same extent as lesions. Neither lesions nor stimulation of the BST affected motor behavior or unconditioned anxiety in an open field test. In summary, electrical stimulation of the BST was successful in reducing contextual anxiety in a rat model, without eliciting unwanted motor effects. Our findings underline the therapeutic potential of DBS in the BST for disorders which are hallmarked by pathological anxiety. Further research will be necessary to assess the translatability of these findings to the clinic.Luyck K., Tambuyzer T., Deprez M., Rangarajan J.R., Nuttin B., Luyten L., ''Electrical stimulation of the bed nucleus of the stria terminalis reduces anxiety in a rat model'', Translational psychiatry, vol. 7, article e1033, 8 pp., February 14, 2017.status: publishe

Interleukin-6 dynamics as a basis for an early-warning monitor for sepsis and inflammation in individual pigs

Static interleukin-6 (IL-6) levels of pigs contain considerable individual differences, which obstruct the practical use of IL-6 for disease monitoring purposes. It was hypothesised that interleukin-6 (IL-6) dynamics could be used to quantify these individual differences and carries critical information of the individual pig infection status. Time series of IL-6 responses in 25 pigs were analysed before and after infection by Actinobacillus pleuropneumoniae. The results indicated that amplitude increases of IL-6 fluctuations of individual pigs rather than static IL-6 values should be used as indicator of the infection state. This study shows the added value for IL-6 time series analyses of individual pigs. These results are a first step towards the development of objective individualised methods for monitoring and early detection of sepsis and inflammation processes in pigs by integrating animal response dynamics.publisher: Elsevier articletitle: Interleukin-6 dynamics as a basis for an early-warning monitor for sepsis and inflammation in individual pigs journaltitle: Research in Veterinary Science articlelink: http://dx.doi.org/10.1016/j.rvsc.2014.03.014 content_type: article copyright: Copyright © 2014 Elsevier Ltd. All rights reserved.status: publishe

Rethinking Food Anticipatory Activity in the Activity-Based Anorexia Rat Model

When a rat is on a limited fixed-time food schedule with full access to a running wheel (activity-based anorexia model, ABA), its activity level will increase hours prior to the feeding period. This activity, called food-anticipatory activity (FAA), is a hypothesized parallel to the hyperactivity symptom in human anorexia nervosa. To investigate in depth the characteristics of FAA, we retrospectively analyzed the level of FAA and activities during other periods in ABA rats. To our surprise, rats with the most body weight loss have the lowest level of FAA, which contradicts the previously established link between FAA and the severity of ABA symptoms. On the contrary, our study shows that postprandial activities are more directly related to weight loss. We conclude that FAA alone may not be sufficient to reflect model severity, and activities during other periods may be of potential value in studies using ABA model.status: publishe

DYNAMIC AUTOREGRESSIVE MODELLING OF CRITICAL CARE PATIENTS AS A BASIS FOR HEALTH MONITORING

Real-time modelling techniques could be valuable to continuously evaluate individual critically ill patients and to help the medical staff with estimation of prognosis. This preliminary study examines the possibilities to distinguish survivors from non-survivors on the basis of instabilities in the dynamics of daily measured variables. A data set, containing 140 patients, was generated in the intensive care unit (ICU) of the university hospital of Leuven. First and second order dynamic auto-regression (DAR) models were used to quantify the stability of time series of three physiological variables as a criterion to distinguish survivors from non-survivors. The best results were found for blood urea concentration with true negative fractions of 45/72 (63%) and true positive fractions of 43/68 (62%). The results indicate that the dynamics of time series of laboratory parameters from critically ill patients are indicative for their clinical condition and outcome.status: publishe