Doctoraten 2021

Woon een doctoraat bij of raadpleeg de voorbije verdedigingen

The impact of cadmium in the maize leaf growth zone - Jonas Bertels (01/02/2021)

Jonas Bertels


Much is known about the impact of cadmium (Cd) stress on plants and the plant’s response to this form of abiotic stress. However, it is remarkable that the impact of Cd in the growth zone of monocotyledonous leaves remained largely unstudied. This growth zone hosts the two cellular processes driving growth, i.e. cell division and cell elongation. The aim of my PhD study was to assess the impact of Cd in this maize leaf growth zone at several biological levels.

We have found that Cd inhibited leaf growth mainly because it results in a significant reduction of cell production. Cells were halted at the G1-S transition of the cell cycle, which increased the cell cycle duration. In addition, when exposed to Cd, growing leaves had a lower number of meristematic cells and therefore less cells are contributing to cell division. In addition, we have found that Cd accumulated highest in the meristematic tissue, indicating that it could impact processes therein directly. To reveal these processes, we have performed a transcriptome study. This resulted in a broad range of Cd affected processes, which led me to perform biochemical analyses of several phytohormones, minerals, two oxidative stress related parameters and carbohydrates. We showed that Cd caused an increase in stress hormone levels (i.e. salicylic acid, abscisic acid and 1-aminocyclopropane 1-carboxylic acid (ACC, an ethylene precursor)) and a decrease of growth promoting hormones (i.e. gibberellin 1 and trans-zeatin riboside). For gibberellin 1, we were able to directly link changes in the spatial distribution of this phytohormone to changes in transcript levels of key gibberellin synthesis and degradation genes. Regarding the measured minerals, we mainly found manganese to be the most strongly and consistently Cd affected nutrient. Lipid peroxidation and antioxidant potential were increased throughout the entire maize leaf growth zone, demonstrating that Cd resulted in oxidative stress in all developmental stages. Lastly, we found that carbohydrates were increased under Cd stress, perhaps in response to oxidative or osmotic stress.

During my PhD study, we have also published leafkin, an R package that contains four functions which allow the user to perform all calculations in a kinematic analysis of monocot leaf growth. In addition, it allows cell length profiles and leaf elongation rates to be easily extracted, which in turn can be used in separate analyses.

Development of advanced hyperspectral unmixing methods - Bikram Koirala (18/01/2021)

Bikram Koirala


Hyperspectral cameras collect the reflected light of materials in hundreds of narrow, contiguous spectral bands in the visible, near and shortwave infrared wavelengths to provide a continuous reflectance spectrum for each pixel. Due to the complex interaction of light with materials, these spectra are highly nonlinear mixtures of the reflectances of the material constituents. The general goal of this thesis is to estimate the composition of materials from reflectance spectra.

Mixing models describe the reflectance spectrum of a material as a (nonlinear) mixture of the constituent materials. The main disadvantage of these models is that the model parameters are not properly interpretable in terms of the fractions. Moreover, not all spectra necessarily follow the same particular mixing model.

Alternatively, the complex mixing effects can be learned using supervised machine learning methods. This requires ground truth training data, in the form of the actual compositions (i.e., the spectra and fractions of the constituents). One major drawback of these strategies is that the estimated fractions do not comply with their physical constraints, leading to a loss of the physical meaning of the estimated parameters. Another disadvantage of the learned models is that they cannot perform well in case training and test spectra are obtained under different environmental conditions or by different sensors, causing spectral variability of the acquired spectra.

In this thesis, a hybrid framework was developed that combines the physical interpretability of a model and the flexibility of data-driven approaches. The general idea is to learn the complex relation between the nonlinear spectra and spectra that follow a particular mixing model by utilizing advanced machine learning regression algorithms. Based on this strategy, a number of different nonlinear unmixing methods were developed:

1) A supervised method that learns a mapping between the nonlinear spectra and the linear mixing model.

2) A strategy for the estimation of leaf biochemical parameters from leaf reflectance and transmittance spectra, by learning a mapping to a leaf biochemical model (PROSPECT).

3) A semi-supervised method to reduce the number of training samples required to learn the nonlinearities, and additionally does not require the availability of pure pixels.

4) A robust supervised method for nonlinear spectral unmixing that is invariant to endmember variability.

The impact of long-duration spaceflight on brain structure and function - Steven Jillings (14/01/2021)

Steven Jillings

  • 14/01/2021
  • 17.00 uur
  • Online Doctoraatsverdediging
  • Promotoren: Floris Wuyts, Angelique Van Ombergen, Ben Jeurissen & Athena Demertzi
  • Departement Fysica


Na bijna zestig jaar van bemande ruimtemissies is er veel onderzoek gebeurd naar het effect van ruimtevaart op de mens. Echter, het effect op de hersenen heeft beperkte aandacht gekregen in het verleden. Dit werk beschrijft pionierswerk op vlak van veranderingen in de hersenen als gevolg van langdurige ruimtevaart door de hersenen van Roscosmos kosmonauten te beeldvormen met behulp van nucleaire magnetische resonantie (MRI) via een longitudinale prospectieve studie. Wij onderzochten volumeveranderingen en veranderingen in de composities van hersenweefsel en hersenvocht na ruimtevaart met behulp van structurele MRI, zoals T1-gewogen en diffusie MRI. Wij vonden een grootschalige herverdeling van het hersenvocht rond het brein met vervormingen van de grijze stof als een secundair mechanistisch effect van deze vloeistofverschuiving. We toonden aan dat de hoeveelheid hersenweefsel in enkele motorische regio’s van de hersenen steeg, wijzend op een structurele aanpassing van de hersenen, ook bekend als neuroplasticiteit, dat toelaat om motorische functies aan te passen naar een situatie van gewichtloosheid. Uit de MRI data die werd opgenomen meer dan een half jaar na de ruimtemissie bleek dat de meeste veranderingen die we zien net na de ruimtemissie nog deels aanwezig zijn op langere termijn. We onderzochten ook functionele reorganisatie in het brein na ruimtevaart, wat aantoonde dat de functionele connectiviteit in verschillende hersenregio’s veranderde na ruimtevaart en dat sommige veranderingen tot een half jaar na de ruimtemissie aanhielden, terwijl anderen terugkeerden naar het niveau van voor de ruimtemissie. Dit werk beschrijft ook preliminaire resultaten van twee studies die analoog zijn aan ruimtevaart. In een pilootstudie bij muizen werd het model van hindlimb unloading toegepast, wat een vloeistofverschuiving naar het hoofd teweegbrengt, om zo verder te onderzoeken hoe deze vloeistofverschuiving de hersenen op structurele wijze aantast. Een tweede studie onderzocht verschillen in functionele organisatie in de hersenen van F16 piloten vergeleken met controles, waarbij F16 piloten een model zijn voor blootstelling aan hoge G-krachten en conflicten in inkomende zintuiglijke informatie in de hersenen. In het geheel heeft dit werk geleid tot een grote toename van informatie over structurele en functionele veranderingen in de hersenen na ruimtevaart. In de toekomst trachten we te kunnen vastleggen welke veranderingen ongewenst zijn, zodat we ze kunnen minimaliseren door tegenmaatregelen te ontwikkelen, en welke gewenst zijn, zodat we ze kunnen stimuleren. Op die manier kunnen we de mensheid beter voorbereiden op langere en verdere missies naar de ruimte in de toekomst, zoals een missie naar Mars.

Unlocking the Potential of Plasma Catalysis - Yannick Engelmann (12/01/2021)

Yannick Engelmann


CO2 conversion, CH4 conversion and NH3 synthesis are three essential processes that can help to reduce greenhouse gas emissions. However, these processes typically require harsh reaction conditions when performed thermally, because of the strong chemical bonds of the reactants. Plasma catalysis can provide alternative methods to activating chemical bonds at ambient conditions. Due to the complexity of plasma-catalytic systems, fundamental understanding of the underlying mechanisms is still lacking, impeding the optimization of the technology and holding back its full potential. The aim of this dissertation is to provide fundamental understanding, needed to unlock the full potential of plasma catalysis.

As a tool to acquire the fundamental understanding, we introduced microkinetic modelling to provide detailed information on reaction mechanisms, kinetics and thermodynamics of the processes. In this way, we identified the limitations of thermal processes, but also unraveled if and how plasma-catalytic processes can overcome these limitations. The main difficulty of CO2 hydrogenation is to selectively produce CH3OH at sufficient rates. In plasma catalysis, the contribution of the plasma is twofold: excitation of the reactant molecules, lowering the barrier of dissociation and increasing the conversion rates of the thermal pathways, and generation of reactive radicals and intermediates, allowing new, unique pathways that potentially lead to CH3OH (often in a much faster way).

In the study on the conversion of CH4, we showed the limitations of transition metal catalysts to produce C2-hydrocarbons under thermal conditions. Thermally, the more noble catalysts are not able to dissociate the strong chemical bonds of the CH4 molecule, while the less noble catalysts suffer from cokes formation. In plasma catalysis, dissociation rates on noble catalysts can be increased by vibrationally exciting the reactants, or catalytic dissociation can be avoided by adsorption of plasma-generated radicals. Whether the adsorbed species couple directly to C2-hydrocarbons or undergo further dehydrogenation before coupling, can be controlled by the catalyst binding strength.

Lastly, the potential of the plasma-catalytic NH3 synthesis is locked in the enhanced catalytic rates, caused by plasma-induced excitation and plasma-generated radicals. Again, both vibrationally excited species and plasma-generated radicals are found to improve the NH3 synthesis rates. Due to the contribution of ER reactions, rates are not only increased on noble catalysts, but also on more strongly binding catalysts, making the choice of the catalyst material much less impactful.