Micro-object pose estimation with sim-to-real transfer learning using small dataset

International audience<span style="color: rgb(34, 34, 34); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Oxygen-Sans, Ubuntu, Cantarell, &quot;Helvetica Neue&quot;, sans-serif; font-size: 18px;"&gtThree-dimensional (3D) pose estimation of micro/nano-objects isessential for the implementation of automatic manipulation inmicro/nano-robotic systems. However, out-of-plane pose estimationof a micro/nano-object is challenging, since the images aretypically obtained in 2D using a scanning electron microscope (SEM)or an optical microscope (OM). Traditional deep learning basedmethods require the collection of a large amount of labeled datafor model training to estimate the 3D pose of an object from amonocular image. Here we present a sim-to-real learning-to-matchapproach for 3D pose estimation of micro/nano-objects. Instead ofcollecting large training datasets, simulated data is generated toenlarge the limited experimental data obtained in practice, whilethe domain gap between the generated and experimental data isminimized via image translation based on a generative adversarialnetwork (GAN) model. A learning-to-match approach is used to mapthe generated data and the experimental data to a low-dimensionalspace with the same data distribution for different pose labels,which ensures effective feature embedding. Combining the labeleddata obtained from experiments and simulations, a new trainingdataset is constructed for robust pose estimation. The proposedmethod is validated with images from both SEM and OM, facilitatingthe development of closed-loop control of micro/nano-objects withcomplex shapes in micro/nano-robotic systems.</span&g

Development and Validation of a Bedside Score to Predict Early Death in Cancer of Unknown Primary Patients

BACKGROUND: We have investigated predictors of 90-day-mortality in a large cohort of non-specific cancer of unknown primary patients. METHODS: Predictors have been identified by univariate and then logistic regression analysis in a single-center cohort comprising 429 patients (development cohort). We identified four predictors that produced a predictive score that has been applied to an independent multi-institutional cohort of 409 patients (validation cohort). The score was the sum of predictors for each patient (0 to 4). RESULTS: The 90-day-mortality-rate was 33 and 26% in both cohorts. Multivariate analysis has identified 4 predictors for 90-day-mortality: performance status>1 (OR = 3.03, p = 0.001), at least one co-morbidity requiring treatment (OR = 2.68, p = 0.004), LDH>1.5 x the upper limit of normal (OR = 2.88, p = 0.007) and low albumin or protein levels (OR = 3.05, p = 0.007). In the development cohort, 90-day-mortality-rates were 12.5%, 32% and 64% when the score was [0-1], 2 and [3]-[4], respectively. In the validation cohort, risks were 13%, 25% and 62% according to the same score values. CONCLUSIONS: We have validated a score that is easily calculated at the beside that estimates the 90-days mortality rate in non-specific CUP patients. This could be helpful to identify patients who would be better served with palliative care rather than aggressive chemotherapy

Reward Versus Nonreward Sensitivity of the Medial Versus Lateral Orbitofrontal Cortex Relates to the Severity of Depressive Symptoms

BackgroundThe orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.MethodsActivations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.ResultsThe medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).ConclusionsActivations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Microrobot hélicoïdal sans fil évoluant dans une puce microfluidique pour des applications comme capteur de force.

Microfluidic chips that could perform chemical and biological processes on a few centimeter square footprint have been an active area of research in the past decades. Among other advantages, this platform offers a closed and controllable environment that allows reproducible measurements and avoids external contamination. However, such closed environments prevent the use of tethered probes to measure or apply a specific force on an element inside the microfluidic chip. Therefore we propose to use a helical rotating microrobot inside a microfluidic chip to answer this need. The proposed microrobots are designed with 3D laser lithography, and have a helical shape of 5.5 µm in diameter and around 50 µm length. A thin ferromagnetic layer is deposited on these microrobots which allows us to propel and control them with a homogenous external rotating magnetic field.The first challenge is the stable integration of these microrobots inside microfluidic environments. Therefore, in this thesis we first proved that these microrobots can use their own mobility to integrate themselves selectively (one by one) inside a microfluidic chip through a microchannel connected to an open reservoir. For this, we have developed a 3D motion where the microrobot evolves in the fluid and two different 2D motions where it evolves on a surface. By switching easily from one motion to another, the microrobots can use the different advantages of each motion to get sufficient mobility required for this integration. We named our microrobot design Roll-To-Swimm (RTS) in reference to this characteristic.Then in order to use a microrobot as on-chip force sensor, a precise characterization of the force generated by the helical shape is necessary for each RTS. A characterization method is proposed, where the different environment parameters (parasite flow, temperature gradient and impact of near surfaces on the flow) are controlled precisely thanks to the microfluidic environment. The characterization shows that the force range of the RTS is between 10 and 45 piconewton with a maximum error of 38 %. We also conclude that the main component of this error (73 %) is due to the evolution of the RTS magnetization. Therefore the efforts to reduce this error should first focus on the magnetization property of the RTS. This error can also be temporarily reduced by characterizing the RTS just before its use in another experiment.Finally, we present three different proofs of concept to demonstrate that our characterization method brings helical microrobots closer to potential on-chip force sensing applications. Firstly, we show that it is possible to measure the diminution of the RTS force when it is pushing a micro spherical bead. This is essential toward applying force on an object with this RTS or to use beads as an interface between the RTS and the surface to measure friction forces. A microbead with 10 µm in diameter at the tip of the RTS reduces it propulsion of 6 %.Secondly, we use the RTS characterization to measure local flow speed. We demonstrate this feature by measuring flow profiles in fluid channels. We show the potential use for of microrobot control by proposing an automatic control of the RTS that adapts the motion to the measured flow. This control has been tested experimentally with different flow conditions. Thirdly, we use the characterization of the RTS to perform numerical simulations in order to find a control strategy in small microchannels. Indeed we demonstrate that for microchannels below 20 times the RTS diameter, the channel walls have an impact on the RTS motions. The model of this simulation has been validated by comparing this result with experimental data. Finally we propose a control scheme for maintaining the RTS centered in a curved microchannel by only using a 2D image feedback.Au cours des dernières décennies, l'étude des puces microfluidiques capables d'exécuter des processus chimiques et biologiques sur quelques centimètres carrés a été un domaine de recherche actif. De telles plateformes offrent un environnement fermé et contrôlable qui permet une mesure reproductible et évite toute contamination externe. Cependant, ces environnements sont fermés, ce qui empêche l'utilisation de sondes de mesure ou d'effecteurs fixés à l'extérieur de la puce microfluidique. Pour répondre à ce besoin, nous proposons d'utiliser des microrobots rotatifs hélicoïdaux évoluant dans un fluide. Les microrobots proposés sont conçus grâce à la lithographie 3D par laser. Ils présentent une forme hélicoïdale de 5.5 µm de diamètre et environ 50 µm de longueur. Une couche mince ferromagnétique déposée sur ces microrobots permet de les propulser et de les contrôler grâce à un champ magnétique tournant homogène.Le premier défi est l'intégration stable de microrobots à l'intérieur d'un environnement microfluidique. Dans cette thèse, nous avons donc d'abord prouvé que ces microrobots peuvent utiliser leur propre mobilité pour s'intégrer individuellement à l'intérieur d'une puce microfluidique en utilisant un microcanal relié à un réservoir ouvert. Pour cela, nous avons développé un mouvement 3D où le microrobot évolue dans le fluide et deux mouvements 2D où il évolue sur une surface. En passant facilement d'un mouvement à l'autre, les microrobots peuvent utiliser les différents avantages de chaque mouvement pour obtenir une mobilité suffisante à cette intégration. Nous avons nommé ce modèle de microrobot "Roll-to-Swimm"(RTS).Ensuite, pour utiliser un microrobot comme capteur de force sur puce microfluidique, il est nécessaire de caractériser la force générée par l'hélice de chaque RTS. Une méthode de caractérisation est proposée, dans laquelle les différents paramètres d'environnement tels que le flux parasite, le gradient de température et l'impact des surfaces, sont contrôlées avec précision grâce à l'environnement microfluidique. Nous en concluons que le modèle de microrobot "RTS" peut appliquer une force de 10 à 45 piconewton avec une erreur maximale de 38 %. La composante principale de cette erreur (73 %) est due à l'évolution de l'aimantation du RTS. Par conséquent, les efforts visant à réduire cette erreur doivent d'abord se concentrer sur la propriété de magnétisation du RTS. Cette erreur peut également être temporairement réduite en caractérisant la RTS juste avant son utilisation dans une expérience.Enfin, nous présentons trois preuves de concept pour démontrer que notre méthode de caractérisation rapproche les microrobots hélicoïdaux des applications potentielles. Tout d'abord, nous mesurons la diminution de la force du RTS lorsqu'il pousse une microbille. Cette mesure est essentielle pour connaitre la force appliquée par le RTS sur un objet ou pour mesurer l'état de surface en utilisant des billes comme interface. Une microbille de 10 µm de diamètre à la pointe du RTS réduit la propulsion de 6 %. Deuxièmement, nous utilisons la caractérisation du RTS pour mesurer la vitesse locale de l'écoulement dans un canal. Puis nous proposons d'utiliser cette mesure de vitesse pour le contrôle du microrobot grâce à un contrôle automatique du RTS qui adapte le type de mouvement en fonction de la vitesse de l'écoulement. Ce contrôle a été testé expérimentalement avec différentes conditions d'écoulement. Troisièmement, nous utilisons la caractérisation du RTS pour effectuer des simulations numériques afin de trouver une stratégie de contrôle dans des microcanaux de taille inférieure à 20 fois le diamètre du RTS. Le modèle de cette simulation a été validé en comparant ces résultats avec des données expérimentales. Finalement, nous proposons un système de contrôle permettant de maintenir le RTS centré à l'intérieur de microcanaux courbes évoluant en 3D, en utilisant seulement une acquisition d'image en 2D

Top–down modulation of human early visual cortex after stimulus offset supports successful postcued report

Modulations of sensory processing in early visual areas are thought to play an important role in conscious perception. To date, most empirical studies focused on effects occurring before or during visual presentation. By contrast, several emerging theories postulate that sensory processing and conscious visual perception may also crucially depend on late top-down influences, potentially arising after a visual display. To provide a direct test of this, we performed an fMRI study using a postcued report procedure. The ability to report a target at a specific spatial location in a visual display can be enhanced behaviorally by symbolic auditory postcues presented shortly after that display. Here we showed that such auditory postcues can enhance target-specific signals in early human visual cortex (V1 and V2). For postcues presented 200 msec after stimulus termination, this target-specific enhancement in visual cortex was specifically associated with correct conscious report. The strength of this modulation predicted individual levels of performance in behavior. By contrast, although later postcues presented 1000 msec after stimulus termination had some impact on activity in early visual cortex, this modulation no longer related to conscious report. These results demonstrate that within a critical time window of a few hundred milliseconds after a visual stimulus has disappeared, successful conscious report of that stimulus still relates to the strength of top-down modulation in early visual cortex. We suggest that, within this critical time window, sensory representation of a visual stimulus is still under construction and so can still be flexibly influenced by top-down modulatory processes