Des substrats SERS, élaborés selon une approche simple et à moindre coût, ont été étudiéspour la détection sans marqueurs d’ADN en vue d’applications dans le domaine du diagnostic médical.Un protocole de réduction photocatalytique assistée chimiquement conduisant à des hétérostructuresAg°/TiO2 a été optimisé. Nohttp://star.theses.fr/editeur.jsp?tefId=58411&action=save#droitsus avons montré en quoi l’utilisation d’un agent encapsulant et d’uneprocédure de nucléation-croissance permettent de contrôler la formation et l’agrégation de NPs Ag° à lasurface de couches minces TiO2. L’agrégation contrôlée des NPs conduit à des points chauds induisantune très forte amplification de l’effet SERS. Les performances des substrats SERS ont tout d’abord étévalidées par détection Raman de la molécule modèle R6G. Des études de fond, portant sur la détectionde polybases dérivées des quatre nucléobases constituant la structure de l’ADN, adénine, cytosine,guanine et thymine, ont ensuite été réalisées. Le potentiel de détection des hétérostructures Ag°/TiO2 apermis l’indexation quasi-intégrale des bandes Raman des quatre polybases étudiées, modifiées ou nonavec des groupements NH2, et nous a permis de discuter des effets d’accrochage, d’orientation etd’agencement des molécules d’ADN sur les substrats SERS. Des études complémentaires ont finalementconfirmé le potentiel de nos hétérostructures en fournissant différents aperçus sur l’hybridation despolybases et l’association de différentes polybases sur un même substrat SERS. / SERS substrates, elaborated through a simple and low-cost procedure, have been studied forthe label-free detection of DNA in the view of applications in the medical diagnostic field. A chemicallyassisted photocatalytic reduction protocol leading to an Ag°/TiO2 heterostructure has been optimized.We have shown how the use of an encapsulating agent and a nucleation-growth procedure enable tocontrol the formation and aggregation of Ag° NPs at the surface of TiO2 thin films. The controlledaggregation of NPs leads to hot points inducing a very strong amplification of the SERS effect.Performances of the SERS substrate have first been evaluated through the Raman detection of the R6Gmodel molecule. Thorough studies dealing with the detection of polybases derived from the fournucleobases constituting the DNA structure, adenine, cytosine, guanine, and thymine, have then beenconducted. The detection potential of the Ag°/TiO2 heterostructure enabled a nearly exhaustiveindexation of the Raman bands for the four studied polybases, modified or not with NH2 groups, and todiscuss on binding, orientation, and ordering effects of the DNA molecules on the SERS substrate.Complementary studies finally enabled us to confirm the potential of our heterostructure by providingdifferent insights on the polybase hybridization and the association of different polybases on a sameSERS substrate.

abstract: Detection of molecular interactions is critical for understanding many biological processes, for detecting disease biomarkers, and for screening drug candidates. Fluorescence-based approach can be problematic, especially when applied to the detection of small molecules. Various label-free techniques, such as surface plasmon resonance technique are sensitive to mass, making it extremely challenging to detect small molecules. In this thesis, novel detection methods for molecular interactions are described. First, a simple detection paradigm based on reflectance interferometry is developed. This method is simple, low cost and can be easily applied for protein array detection. Second, a label-free charge sensitive optical detection (CSOD) technique is developed for detecting of both large and small molecules. The technique is based on that most molecules relevant to biomedical research and applications are charged or partially charged. An optical fiber is dipped into the well of a microplate. It detects the surface charge of the fiber, which does not decrease with the size (mass) of the molecule, making it particularly attractive for studying small molecules. Third, a method for mechanically amplification detection of molecular interactions (MADMI) is developed. It provides quantitative analysis of small molecules interaction with membrane proteins in intact cells. The interactions are monitored by detecting a mechanical deformation in the membrane induced by the molecular interactions. With this novel method small molecules and membrane proteins interaction in the intact cells can be detected. This new paradigm provides mechanical amplification of small interaction signals, allowing us to measure the binding kinetics of both large and small molecules with membrane proteins, and to analyze heterogeneous nature of the binding kinetics between different cells, and different regions of a single cell. Last, by tracking the cell membrane edge deformation, binding caused downstream event – granule secretory has been measured. This method focuses on the plasma membrane change when granules fuse with the cell. The fusion of granules increases the plasma membrane area and thus the cell edge expands. The expansion is localized at the vesicle release location. Granule size was calculated based on measured edge expansion. The membrane deformation due to the granule release is real-time monitored by this method. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

Ce travail présente une méthode originale de détection et de quantification, sans étape de marquage, de la proportion de bases libres contenues dans des acides nucléiques. La spectrométrie de diffusion Raman exaltée de surface (DRES ou SERS en anglais) nous a permis d’obtenir la signature spectrale spécifique des nucléotides caractéristiques des ARN (adénosine, cytosine, guanosine et uridine), en utilisant des colloïdes d’argent comme substrat-DRES et des ajouts de MgCl2 comme agent d’agrégation. Les conditions de détection ont été optimisées pour établir un protocole de quantification de la proportion des nucléobases non-appariées par spectrométrie DRES. Les limites de détection obtenues sont de l’ordre de quelques dizaines de picomoles. L’amélioration de la reproductibilité des mesures par spectrométrie DRES passe par le contrôle précis des temps de réaction (adsorption et agrégation), qui peut être contrôlé grâce à l’utilisation de plateformes microfluidiques adaptées. Nous avons mis en œuvre deux types de plateformes microfluidiques, l’une basée sur des écoulements monophasiques et l’autre sur la génération de gouttes. Les espèces à analyser sont contenus dans les gouttes, permettant la détection in situ par spectrométrie DRES des divers nucléotides. / This work deals with the development of an original label-free method for free bases proportions detection and quantification of nucleic acids. The surface enhanced Raman spectroscopy (SERS) allowed obtaining the specific spectral signature of characteristic nucleotides of RNA (adenosine, cytosine, guanosine and uridine), using silver colloids as SERS substrate and MgCl2 addition as aggregating agent. Then, the condition detection have optimizing to establish a label-free quantification protocol of free nucleobases proportion by SERS spectroscopy. The detection limits obtained are order of few picomoles. The reproducibility improvement of SERS detection requires the precise control of time reaction (adsorption and aggregation), which could be control thanks to microfluidic chips use. We have implemented two different microfluidic chips, one based on single-phase flows and one other based on droplets generation. The analyzed species are containing in droplets, allowing in situ detection by spectroscopy SERS of various nucleotides.

Laser application in the field of biological and medical sciences has significantly grown, thereby strengthening the field of Biophotonics. Research conducted in Biophotonics focuses on the concept of using light especially in the visible and near infrared regions of the electromagnetic radiation for the evaluation of living systems. In this thesis new discoveries are presented about low level laser therapy, optical trapping, transmission spectroscopy, luminescence spectroscopy and structured illumination microscopy (SIM), displaying the impact each technique has on HIV infected cells. The results showed that the irradiation of HIV-1 infected TZM-bl cells with low power red laser reduces HIV-1 infection. The outcomes of this study further proved that when irradiation is used in conjunction with efavirenz, an antiretroviral drug, HIV-1 infection could be reduced to undetectable levels in TZM-bl cells. Through the coupling of transmission spectroscopy with optical trapping, and separately, use of luminescence spectroscopy, label free diagnosis of HIV in infected cell samples was achieved. This finding affirms that HIV-1 infection can be detected in a label free manner when using laser based techniques. Furthermore, the photoluminescence spectrometer system was employed to generate a decay curve, which was necessary so as to have some understanding on lifetime of the luminescent signal in infected TZM-bl cells. Finally, in order to confirm that indeed TZM-bl cells were infected, an established super-resolution microscopy system SIM was used to detect HIV-1 infection in TZM-bl cells. Indeed in the infected cells viral molecules p24 and gp41 were detected through SIM, while they were not detected in uninfected cells. In future studies, super resolution microscopy would be coupled to an optical trapping system in order to confirm that each trapped cells is whether infected or uninfected so as to improve HIV diagnosis. / College of Science, Engineering and Technology / Ph. D. (Science, Engineering and Technology)

Computer vision object detection is the task of detecting and identifying objects present in an image or a video sequence. Models based on artificial convolutional neural networks are commonly used as detector models. Object detection precision and inference efficiency are crucial for surveillance-based applications. A decrease in the detector model complexity as well as in the complexity of the post-processing computations promotes increased inference efficiency. Modern object detectors for surveillance applications usually make use of a regression algorithm and bounding box priors referred to as anchor boxes to compute bounding box proposals, and the proposal selection algorithm contributes to the computational cost at inference. In this study, an anchor-free and low complexity deep learning detector model was implemented within a surveillance applications setting, and was evaluated and compared to a reference baseline state-of-the-art anchor-based object detector. A key-point-based detector model (CenterNet), predicting Gaussian distribution based object centers, was selected for the evaluation against the baseline. The surveillance applications adapted anchor-free detector exhibited a factor 2.4 lower complexity than the baseline detector. Further, a significant redistribution to shorter post-processing times was demonstrated at inference for the anchor-free surveillance adapted CenterNet detector, giving a modal values factor 0.6 of the baseline detector post-processing time. Furthermore, the surveillance adapted CenterNet model was shown to outperform the baseline in terms of detection precision for several surveillance applications relevant classes and for objects of smaller spatial scale.