Machine Learning and Statistical Analysis of Complex Mathematical Models: An Application to Epilepsy

The electroencephalogram (EEG) is a commonly used tool for studying the emergent electrical rhythms of the brain. It has wide utility in psychology, as well as bringing a useful diagnostic aid for neurological conditions such as epilepsy. It is of growing importance to better understand the emergence of these electrical rhythms and, in the case of diagnosis of neurological conditions, to find mechanistic differences between healthy individuals and those with a disease. Mathematical models are an important tool that offer the potential to reveal these otherwise hidden mechanisms. In particular Neural Mass Models (NMMs), which describe the macroscopic activity of large populations of neurons, are increasingly used to uncover large-scale mechanisms of brain rhythms in both health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite they are considered low-dimensional in comparison to micro-scale neural network models, with regards to understanding the relationship between parameters and dynamics NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. We need alternative methods to characterise the dynamics of NMMs in high dimensional parameter spaces. The primary aim of this thesis is to develop a method to explore and analyse the high dimensional parameter space of these mathematical models. We develop an approach based on statistics and machine learning methods called decision tree mapping (DTM). This method is used to analyse the parameter space of a mathematical model by studying all the parameters simultaneously. With this approach, the parameter space can efficiently be mapped in high dimension. We have used measures linked with this method to determine which parameters play a key role in the output of the model. This approach recursively splits the parameter space into smaller subspaces with an increasing homogeneity of dynamics. The concepts of decision tree learning, random forest, measures of importance, statistical tests and visual tools are introduced to explore and analyse the parameter space. We introduce formally the theoretical background and the methods with examples. The DTM approach is used in three distinct studies to: • Identify the role of parameters on the dynamic model. For example, which parameters have a role in the emergence of seizure dynamics? • Constrain the parameter space, such that regions of the parameter space which give implausible dynamic are removed. • Compare the parameter sets to fit different groups. How does the thalamocortical connectivity of people with and without epilepsy differ? We demonstrate that classical studies have not taken into account the complexity of the parameter space. DTM can easily be extended to other fields using mathematical models. We advocate the use of this method in the future to constrain high dimensional parameter spaces in order to enable more efficient, person-specific model calibration

Method development for [11C]carbon monoxide radiochemistry

Positron emission tomography (PET) is a non-invasive molecular imaging technique that has found extensive utility in biomedical research and in drug development. A fundamental pre-requisite for PET is the tracer, which is a biologically relevant molecule, labeled with a short-lived radionuclide. One of the most attractive radionuclides for PET is carbon-11 (11C) that has a half-life of only 20 minutes (11C, t1/2=20.3 min). This radionuclide can be introduced via transition-metal mediated carbonylation with [11C]carbon monoxide ([11C]CO), a reaction that has found utility in the production of a wide range of drug-like molecules and radioligands. Transition-metal mediated 11C-carbonylation is typically performed at high pressure and high temperature due to the poor solubility of [11C]CO in organic solvents and its high dilution in inert gas. Because of its radioactive nature, chemical processes with 11C not only need to be fast, but also need to be automated inside a lead-shielded fume cupboard to ensure operator safety. The current PhD thesis aimed to develop novel and simplified methods for the introduction of 11C into one of the most abundant functional groups in bioactive molecules, namely the carbonyl group. Paper I describes the development of a new stainless-steel loop method for 11C-carbonylation reactions, in which a thin film of reagents is created on the interior surface of the loop. This operation creates a large surface area, which facilitates exchange between the liquid and gas phase and thus enhances trapping and incorporation of [11C]CO into target compounds via reactive palladium complexes. The method was applied to a set of test compounds and proved to be useful to provide 11C-labeled amides, esters and carboxylic acids with good to excellent yields. As a proof of concept, the histamine‐3 receptor radioligand [11C]AZ13198083, the oncology drug [11C]olaparib, the dopamine D2 receptor radioligands [11C]raclopride and [11C]FLB457 were produced using the same method. To allow tracers labeled by 11C-carbonylation to be used in studies of human physiology and pathophysiology, Paper II described the development of a new automated system for [11C]CO radiochemistry that complies with all regulations associated with such studies (e.g. good manufacturing practice (GMP)). The aim was to develop the first commercially available [11C]CO system with the purpose of making [11C]CO radiochemistry accessible to the wider PET community. Following development and optimization of each part of the GMP system, the [11C]CO synthesizer was successfully used to produce the histamine type-3 radioligand, [11C]AZ13198083. In Paper III, a novel and simple method for the synthesis of 11C-labeled primary amides was developed. This process consists on the Pd-mediated 11C-aminocarbonylation of aryl halides via intermediate electrophilic aroyl-DMAP-salts (DMAP – 4-dimethylaminopyridine). The method provided a range of substrates with good to excellent yields and was finally successfully applied to the radiolabeling of the two cancer drugs [11C]niraparib and [11C]veliparib for preclinical studies. To conclude, a variety of new methodologies have been described for 11C-labeling carbonyl groups that have the potential to be widely implemented in the development of new tracer molecules for PET imaging

Expression of MHC II genes

Innate and adaptive immunity are connected via antigen processing and presentation (APP), which results in the presentation of antigenic peptides to T cells in the complex with the major histocompatibility (MHC) determinants. MHC class II (MHC II) determinants present antigens to CD4+ T cells, which are the main regulators of the immune response. Their genes are transcribed from compact promoters that form first the MHC II enhanceosome, which contains DNA-bound activators and then the MHC II transcriptosome with the addition of the class II transactivator (CIITA). CIITA is the master regulator of MHC II transcription. It is expressed constitutively in dendritic cells (DC) and mature B cells and is inducible in most other cell types. Three isoforms of CIITA exist, depending on cell type and inducing signals. CIITA is regulated at the levels of transcription and post-translational modifications, which are still not very clear. Inappropriate immune responses are found in several diseases, including cancer and autoimmunity. Since CIITA regulates the expression of MHC II genes, it is involved directly in the regulation of the immune response. The knowledge of CIITA will facilitate the manipulation of the immune response and might contribute to the treatment of these diseases

Interpretation of palaeomonsoon dynamics on the Eastern Tibetan Plateau from a 10 kyr peat record of dust deposition and regional atmospheric model simulations

The Holocene evolution of the Asian monsoon remains poorly constrained due to the lack of information on past wind trajectories and intensities in central Asia. Mineral dust mobilized from aeolian deposits, transported by atmospheric currents and deposited in environmental archives such as peatlands, offers the potential to elucidate past changes in monsoon dynamics. This thesis examines the history of palaeomonsoon circulation in central Asia during the Holocene through the study of the fluxes and sources of dust deposited in a peatland on the eastern Tibetan Plateau, and the use of this record to constrain numerical simulations of dust transport. Different Asian dust sources capable of providing material to the peat deposit were characterized geochemically to establish a framework of provenance tracers for their identification. Rare earth element-based proxies were shown to be effective geochemical tracers to distinguish between them. These proxies were measured in a 9,500 year old peat core from Hongyuan to reconstruct the history of mineral dust deposition in this region. Results suggest that the deposits of northern and northwestern China dominated dust input to the peat throughout the Holocene and particularly during the last 5 kyr, with earlier deposition also governed by high local contributions. All geochemical proxies indicate that the northern sources dominated between 3.1-2.7 and 1.7-0.9 kyr BP, accompanied by a large increase in dust fluxes. These changes are interpreted as a strengthening of the East Asian winter monsoon, in agreement with other studies in the region. Annual fluxes and sources simulated with a regional atmosphere-chemistry/aerosol climate model show good agreement with the geochemical data. These results provide the first uninterrupted interpretation of atmospheric circulation patterns in central Asia during the Holocene and confirm the potential of peatlands as reliable repositories of dust deposition and as high-quality datasets against which regional model simulations can be evaluated

Technical and Economic Analysis of a Residential Heat Pump with Photovoltaic Solar Panels in Self-Consumption for Space Heating, Cooling and DHW Production

Two different thermodynamic systems for space heating, cooling, and domestic hot water production coupled to photovoltaic panels have been studied. The aim is to assess the PV electricity self-consumption variation with the heat storage volume and the applied control strategy. Each system has been studied using a 1D unsteady state modelisation software to simulate its performance in a house complying with the French building code (RT2012) having a DHW demand according to ErP’s load profile M and with Paris weather data. The main parameters studied are the electricity consumption of the thermodynamic system, the seasonal performance factor (SPF), the self-consumption ratio, the self-production ratio, the coverage ratio and the Return on Investment. The results show that the seasonal efficiency can be doubled thanks to the optimization of the PV electricity self-consumption, which results in a return on investment lower than 15 years

IS GLUTATHIONE TRANSFERASE (GST) ACTIVITY IN POSIDONIA OCEANICA A STRESS RESPONSE TO MERCURY EXPOSURE?

International audienceToday, efficient monitoring of the environment is increasingly depend on the use of bio-indicator species. Marine phanerogams, and in particular Posidonia oceanica, would appear to be potentially valuable bioindicators of metal pollutants. Although correlations have been found between the mercury levels accumulated in the plant tissue and the concentrations of this metal in the water column, it would be of interest to identify early signs of the stress response induced by this xenobiotic. Thus, mercury concentrations and GST activity in Posidonia oceanica (L.) Delile from contaminated and pristine sites were measured. These results demonstrate that an increase in mercury level is correlated with an increase in GST activity, particularly in the sheaths of P. oceanica shoots. The sites contaminated by mercury were also those sites for which the highest enzyme activity was recorded. An even better correlation was found between the mercury levels and GST activity, if a 2 mo lag in the effect of mercury on GST activity is assumed

The Synergy between Organ-on-a-Chip and Artificial Intelligence for the Study of NAFLD: From Basic Science to Clinical Research

Non-alcoholic fatty liver affects about 25% of global adult population. On the long-term, it is associated with extra-hepatic compliances, multiorgan failure, and death. Various invasive and non-invasive methods are employed for its diagnosis such as liver biopsies, CT scan, MRI, and numerous scoring systems. However, the lack of accuracy and reproducibility represents one of the biggest limitations of evaluating the effectiveness of drug candidates in clinical trials. Organ-on-chips (OOC) are emerging as a cost-effective tool to reproduce in vitro the main NAFLD’s pathogenic features for drug screening purposes. Those platforms have reached a high degree of complexity that generate an unprecedented amount of both structured and unstructured data that outpaced our capacity to analyze the results. The addition of artificial intelligence (AI) layer for data analysis and interpretation enables those platforms to reach their full potential. Furthermore, the use of them do not require any ethic and legal regulation. In this review, we discuss the synergy between OOC and AI as one of the most promising ways to unveil potential therapeutic targets as well as the complex mechanism(s) underlying NAFLD

Evolution and Vitality of Seagrasses in a Mediterranean Lagoon

International audienceDespite their registration on the list of the Ramsar convention sites, the Mediterranean lagoons rarely beneficiate of an effective protection, and are particularly sensitive to environmental quality. A control of these wetlands needs the creation of an inventory of knowledge for the concerned environment. In this perspective, the seagrass beds were followed up in the coastal lagoon of Urbino (Corse, France) since 1990. A cartographic study was carried out by remote sensing of aerial photography. Temporal evolution of the seagrass beds (Cymodocea nodosa principally) allows to determine the vitality of these structures. A comparison of the surface areas occupied by Cymodocea nodosa, between 1990 and 1999, did not allow seeing any significant evolution. However, some variations appear like biotopes all more fragile and coveted as the Mediterranean coastal fringe is straight and is the privileged site of appear in the localization of the beds, due to the modification of environmental conditions in the lagoon