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Surface modification effect on contrast agent efficiency for X-ray based spectral photon-counting scanner/luminescence imaging: from fundamental study to in vivo proof of concept
No full textInternational audienceX-Ray imaging techniques are among the most widely used modalities in medical imaging and their constant evolution has led to the emergence of new technologies. The new generation of computed tomography (CT) systems – spectral photonic counting CT (SPCCT) and X-ray luminescence optical imaging – are examples of such powerful techniques. With these new technologies the rising demand for new contrast agents has led to extensive research in the field of nanoparticles and the possibility to merge the modalities appears to be highly attractive. In this work, we propose the design of lanthanide-based nanocrystals as a multimodal contrast agent with the two aforementioned technologies, allowing SPCCT and optical imaging at the same time. We present a systematic study on the effect of the Tb3+ doping level and surface modification on the generation of contrast with SPCCT and the luminescence properties of GdF3:Tb3+ nanocrystals (NCs), comparing different surface grafting with organic ligands and coatings with silica to make these NCs bio-compatible. A comparison of the luminescence properties of these NCs with UV revealed that the best results were obtained for the Gd0.9Tb0.1F3 composition. This property was confirmed under X-ray excitation in microCT and with SPCCT. Moreover, we could demonstrate that the intensity of the luminescence and the excited state lifetime are strongly affected by the surface modification. Furthermore, whatever the chemical nature of the ligand, the contrast with SPCCT did not change. Finally, the successful proof of concept of multimodal imaging was performed in vivo with nude mice in the SPCCT taking advantage of the so-called color K-edge imaging method
Back to the future – 20 years of progress and developments in photonic microscopy and biological imaging
No full textInternational audienceIn 2023, the ImaBio consortium (imabio-cnrs.fr), an interdisciplinary life microscopy research group at the Centre National de la Recherche Scientifique, celebrated its 20th anniversary. ImaBio contributes to the biological imaging community through organization of MiFoBio conferences, which are interdisciplinary conferences featuring lectures and hands-on workshops that attract specialists from around the world. MiFoBio conferences provide the community with an opportunity to reflect on the evolution of the field, and the 2023 event offered retrospective talks discussing the past 20 years of topics in microscopy, including imaging of multicellular assemblies, image analysis, quantification of molecular motions and interactions within cells, advancements in fluorescent labels, and laser technology for multiphoton and label-free imaging of thick biological samples. In this Perspective, we compile summaries of these presentations overviewing 20 years of advancements in a specific area of microscopy, each of which concludes with a brief look towards the future. The full presentations are available on the ImaBio YouTube channel (youtube.com/@gdrimabio5724)
Dynamique hors d'équilibre d'un gaz de Bosons unidimensionnel étudiée via la mesure spatialement résolue de la distribution des quasiparticules
No full textThis manuscript describes theoretical and experimental studies on characterizing one dimensionnal (1D) bose gas. To produce such a system, a Rubidium gas est trapped in a very transversally confining magnetic potential produced by an atom chip. Contrary to thermodynamic systems reaching an equilibrium described by several macroscopic parameters (pressure, temperature), this system relaxes towards a more complex state described by a function called the rapidity distribution. This function can be accessed experimentally : the rapidity distribution corresponds to the asymptotic atomic velocity distribution after a 1D expansion of the atoms. This quantity can also be extracted by studying the 1D expansion with the Generalized Hydrodynamic, an emerging theory with a lot of interest recently, specially conceived for studying these systems.A first study detailed in this manuscript consisted in characterizing 1D expansion of the gas. The evolution of the density profile and the evolution of phase fluctuations were analyzed and found to be compatible with theoretical predictions. A second project involved adding a spatial selection tool to produce non-equilibrium situations and to locally probe the rapidity distribution of the system. These measurements were performed on initial equilibrium and out of equilibrium situations. They are well understood with the predictions of Generalized Hydrodynamics.Cette thèse présente des études théoriques et expérimentales sur la caractérisation de gaz de bosons unidimensionnels (1D). Pour produire de tels systèmes, un gaz de Rubidium est placé dans un piège magnétique très confinant transversalement, produit par une puce atomique.Contrairement aux systèmes thermodynamiques atteignant un équilibre caractérisé par quelques variables d'état (pression, température), ce système relaxe dans un état plus complexe décrit par une fonction appelée distribution de rapidités. Cette grandeur est accessible expérimentalement : la distribution de rapidités est la distribution asymptotique des vitesses des atomes après une expansion de ces derniers dans le guide 1D. Cette fonction peut aussi être extraite en étudiant la dynamique de l'expansion unidimensionnelle grâce à l'hydrodynamique généralisée, une théorie émergente suscitant beaucoup d'attentions, spécialement développée pour l'étude de ces systèmes.Une première étude détaillée dans ce manuscrit a été de caractériser les expansions longitudinales unidimensionnelles des gaz de bosons 1D. L'évolution des profils de densité ainsi que des fluctuations de phase ont été analysées et sont en accord avec les prédictions théoriques.Un deuxième projet a été la mise en place d'un outil de sélection spatial permettant à la fois de produire des situations hors équilibre ainsi qu'à sonder localement la distribution de rapidités. Ces mesures ont été réalisées sur des gaz à l'équilibre et hors-équilibre. Les mesures sont notamment cohérentes avec les prédictions de la théorie hydrodynamique généralisée
Comprendre les réponses des nanoparticules mono- et bi-métalliques d'Au et de Ni à un chauffage rapide.
No full textInternational audienceNanoparticle assembly, alloying and fragmentation are fundamental processes with significant implications in various fields such as catalysis, materials science, and nanotechnology. Understanding these processes under fast heating conditions is crucial for tailoring nanoparticle properties and optimizing their applications. For this, we employ molecular dynamics simulations to obtain atomic-level insights into nanoparticle behavior. The performed simulations reveal intricate details of sintering, alloying and fragmentation mechanisms shedding light on the underlying physical phenomena governing these processes. The calculation results help to visualize nanoparticle evolution upon undercritical and supercritical heating elucidating not only the role of temperature, but also of nanoparticle sizes and composition. In particular, it is shown that surface tension and surface energy play important roles not only in nanoparticle melting but also in its fragmentation. When the added energy exceeds a critical threshold, the nanoparticle begins to experience alternating compression and expansion. If the tensile stress surpasses the material's strength limit, fragmentation becomes prominent. For very small particles (with radius smaller than ∼10 nm), this occurs more rapidly, whereas sub-nano-cavitation precedes the final fragmentation in larger particles, which behave more like droplets. Interestingly, this effect depends on composition in the case of AuNi alloy nanoparticles, as expected from the phase diagrams and excess energy. The heating level required to overcome the mixing barrier is also determined and is shown to play an important role in the evolution of AuNi nanoparticles, in addition to their size. Furthermore, our findings provide insights into controlling nanoparticle synthesis for various applications in numerous nanotechnological domains, such as catalysis, sensors, material analysis, as well as deseas diagnostics and treatment. This study bridges the gap between experimental observations and theoretical predictions paving the way for designing advanced nanomaterials with enhanced functionalities.L'assemblage, l'alliage et la fragmentation des nanoparticules sont des processus fondamentaux ayant des implications significatives dans divers domaines tels que la catalyse, la science des matériaux et la nanotechnologie. Comprendre ces processus dans des conditions de chauffage rapide est crucial pour adapter les propriétés des nanoparticules et optimiser leurs applications. Pour cela, nous utilisons des simulations de dynamique moléculaire afin d'obtenir des informations à l'échelle atomique sur le comportement des nanoparticules. Les simulations réalisées révèlent des détails complexes des mécanismes de frittage, d'alliage et de fragmentation, éclairant les phénomènes physiques sous-jacents régissant ces processus. Les résultats des calculs aident à visualiser l'évolution des nanoparticules lors d'un chauffage sous-critique et supercritique, en mettant en lumière non seulement le rôle de la température, mais aussi celui de la taille et de la composition des nanoparticules. En particulier, il est démontré que la tension de surface et l'énergie de surface jouent un rôle important non seulement dans la fusion des nanoparticules, mais aussi dans leur fragmentation. Lorsque l'énergie ajoutée dépasse un seuil critique, la nanoparticule commence à subir une compression et une expansion alternées. Si la contrainte de traction dépasse la limite de résistance du matériau, la fragmentation devient prépondérante. Pour les très petites particules (d'un rayon inférieur à environ 10 nm), cela se produit plus rapidement, tandis que la sub-cavitation précède la fragmentation finale dans les particules plus grandes, qui se comportent davantage comme des gouttelettes. Fait intéressant, cet effet dépend de la composition dans le cas des nanoparticules d'alliage AuNi, comme prévu par les diagrammes de phase et l'énergie excédentaire. Le niveau de chauffage nécessaire pour surmonter la barrière de mélange est également déterminé et joue un rôle important dans l'évolution des nanoparticules AuNi, en plus de leur taille. En outre, nos résultats fournissent des informations sur le contrôle de la synthèse des nanoparticules pour diverses applications dans de nombreux domaines nanotechnologiques, tels que la catalyse, les capteurs, l'analyse des matériaux, ainsi que le diagnostic et le traitement des maladies. Cette étude comble le fossé entre les observations expérimentales et les prédictions théoriques, ouvrant la voie à la conception de nanomatériaux avancés aux fonctionnalités améliorées
Pheno-morphological screening and acoustic sorting of 3D multicellular aggregates using drop millifluidics
No full textAbstract Three-dimensional multicellular aggregates like organoids and spheroids have become essential tools to study the biological mechanisms involved in the progression of diseases. In cancer research, they are now widely used as in vitro models for drug testing. However, their analysis still relies on tedious manual procedures, which hinders their routine use in large-scale biological assays. Here, we introduce a novel drop millifluidic approach to screen and sort large populations containing over one thousand multicellular aggregates. Our system utilizes real-time image processing to detect pheno-morphological traits in cellular aggregates. They are then encapsulated in millimetric drops, actuated on-demand using the acoustic radiation force. We demonstrate the performance of our system by sorting spheroids with uniform sizes from a heterogeneous population, and by isolating organoids from spheroids with different phenotypes. We anticipate that this work offers the potential to standardize drug testing on multicellular aggregates, which promises accelerated progress in biomedical research
Prospects for extreme light sources at the CERN accelerator complex
No full textInternational audienceThe unique parameter space of CERN’s ultra-relativistic particle beams offers tremendous opportunities for extreme light production at photon energies ranging from the Soft X-rays to γ-rays when paired to state-of-the-art high-power lasers.</jats:p
User Environment Detection Using Long Short-Term Memory Autoencoder
No full textInternational audienceMobile networks are rapidly expanding, and there is an increasing demand for seamless connectivity. Detecting whether a user is indoors or outdoors is pivotal in optimizing network performance and enhancing user experience. This paper proposes a semi-supervised learning method using a Long Short-Term Memory Autoencoder (LSTM-AE) that detects the user's environment. It uses mobile network radio signal data of real users. The LSTM Autoencoder learns to capture the underlying structure of the data and identify patterns that distinguish indoor from outdoor environments. Three key features are used to train the model: Reference Signal Received Power (RSRP), Channel Quality Indicator (CQI), and Timing Advance (TA). Results show that the LSTM-AE model achieves a high accuracy of 84% and an F1 score of 89%. In our approach, we achieve a substantial reduction of 34.14% in the requirement for labeled data compared to traditional methods that primarily rely on fully supervised learning. By diminishing the dependence on labour-intensive and time-consuming data labelling processes, this improvement significantly enhances the overall efficiency of the machine-learning process
Influence of Manufacturing Parameters on the Steady State Radiation Response of Radiation Sensitive Optical Fibers
No full textInternational audienc
Understanding and Exploiting the Optical Properties of Laser-Induced Quasi-Random Plasmonic Metasurfaces
No full textInternational audienceLaser-induced structural colors have the potential for industrial implementation thanks to their versatility, efficiency, cost-effectiveness, and simplicity. However, the quasi-random nature of the nanoparticle (NP) distributions produced by lasers has made the understanding of their optical properties tricky and the confidence in their reproducibility limited. In this article, we demonstrate the potential of nanosecond lasers to control the diffraction, dichroism, and colors of random plasmonic metasurfaces while explaining the origin of their optical properties through electromagnetic simulations. The optical properties are first linked to the geometrical parameters of self-organized gratings that are induced by laser either on the surface by topographic modulation or below the surface by the growth of organized NPs. These two kinds of gratings are perpendicular to each other and exhibit different periods. The article unravels the main mechanisms that shape the spectral properties of these laser-induced NP gratings. Electromagnetic simulations evidence the role of hybrid resonances resulting from the far-field coupling of metallic NPs despite their size dispersion and relative disorder. They also demonstrate the impact of near-field coupling that leads to the hybridization of plasmonic modes of some particle pairs closely packed along the grating lines in these laser-induced structures. The article shows how the two kinds of self-organized gratings influence the diffraction and dichroism. Imperfections of laser-induced metasurfaces bring singular properties that do not exist in perfectly regular samples. They are used here to print faithful color images in different modes of observation and to use diffraction or dichroism as a security featur
Shrinkage MMSE estimators of covariances beyond the zero-mean and stationary variance assumptions
No full textInternational audienceWe tackle covariance estimation in low-sample scenarios, employing a structured covariance matrix with shrinkage methods. These involve convexly combining a low-bias/highvariance empirical estimate with a biased regularization estimator, striking a bias-variance trade-off. Literature provides optimal settings of the regularization amount through risk minimization between the true covariance and its shrunk counterpart. Such estimators were derived for zero-mean statistics with i.i.d. diagonal regularization matrices accounting for the average sample variance solely. We extend these results to regularization matrices accounting for the sample variances both for centered and noncentered samples. In the latter case, the empirical estimate of the true mean is incorporated into our shrinkage estimators. Introducing confidence weights into the statistics also enhance estimator robustness against outliers. We compare our estimators to other shrinkage methods both on numerical simulations and on real data to solve a detection problem in astronomy