A Separation Principle on Lie Groups

For linear time-invariant systems, a separation principle holds: stable observer and stable state feedback can be designed for the time-invariant system, and the combined observer and feedback will be stable. For non-linear systems, a local separation principle holds around steady-states, as the linearized system is time-invariant. This paper addresses the issue of a non-linear separation principle on Lie groups. For invariant systems on Lie groups, we prove there exists a large set of (time-varying) trajectories around which the linearized observer-controler system is time-invariant, as soon as a symmetry-preserving observer is used. Thus a separation principle holds around those trajectories. The theory is illustrated by a mobile robot example, and the developed ideas are then extended to a class of Lagrangian mechanical systems on Lie groups described by Euler-Poincare equations.Comment: Submitted to IFAC 201

The role of humic-type ligands in the bioavailability and stabilization of dissolved iron in the Western Tropical South Pacific Ocean

The high N2 fixation rate observed in the Lau Basin of the western tropical South Pacific Ocean (WTSP) is fueled by iron (Fe) released from shallow hydrothermal systems. Understanding Fe bioavailability is crucial but the controls on the stability and bioavailability of hydrothermal Fe inputs are still poorly understood. Here, we provide new data on the spatial and vertical distribution of the soluble ubiquitous humic-like ligands (LFeHS) and their associated dissolved Fe (DFe) in the WTSP, including in samples near hydrothermal vents. Our data show that LFeHS are heterogenous ligands with binding sites of both strong and intermediate strengths. These ligands are primarily produced in surface waters and partially mineralized in mesopelagic waters. A substantial fraction of DFe was complexed by LFeHS (mean ~30%). The DFe complexed by LFeHS is likely bioavailable to phytoplankton and LFeHS stabilized Fe released by the mineralization of sinking biomass. However, unsaturation of LFeHS by Fe suggest that part of DFe is not available for complexation with LFeHS. Possible reasons are competition between DFe and other metals, such as dissolved copper, or the inability of LFeHS to access colloidal DFe. The study of two volcanic sites indicates that LFeHS were not produced in these hydrothermal systems. At the active site (DFe ~50 nmol L-1), LFeHS can only partially solubilize the hydrothermal DFe released in this area (1~5.5% of the total DFe). We performed controlled laboratory experiments which show that the observed low solubilization yield result from the inability of LFeHS to solubilize aged Fe oxyhydroxides (FeOx - a kinetically mediated process) and to form stable complexes with Fe(II) species. Our study provides new understanding of the role of LFeHS on the bioavailability and stabilization of hydrothermal DFe

Diagnostic Value of FDG PET-CT Quantitative Parameters and Deauville-Like 5 Point-Scale in Predicting Malignancy of Focal Thyroid Incidentaloma

Objective: To evaluate the diagnostic value of FDG PET-CT metabolic parameters and Deauville-like 5 point-scale to predict malignancy in a population of patients presenting focal thyroid incidentaloma (fTI).Design: This retrospective study included 41 fTI, classified according to cytological and histological data as benign (BL) or malignant lesion (ML). FDG PET-CT semi-quantitative parameters (SUVmax, SUVmean, SUVpeak, MTV, TLG), tumor to liver SUVmean ratio (TLRmax and TLRmean), tumor to blood-pool SUVmean ratio (TBRmax and TBRmean) were calculated. Each fTI was also classified on a Deauville-like 5-point scale (DS) currently used in lymphoma. Comparison between BL and ML was performed for each parameter and a ROC analysis was conducted.Results: All quantitative PET metabolic parameters (SUV parameters, volume based parameters and SUV ratio) were higher in ML compared with BL, yet no significant difference was reported. fTI (uptake) malignancy rate according to DS grades 2, 3, 4, and 5 was, respectively, 25% (1 of 4), 28.6% (2 of 7), 8.3% (1 of 12), and 33.3% (6 of 18) with no significant difference between ML and BL groups. Results of ROC analysis showed that mean TBR had the highest AUC in our cohort (0.66 95%CI [0.41; 0.91]) with a cut-off value of 2.2. Specificity of MTV and TLG was 100% (cut-off values: MTV 9.6 ml, TLG 22.9 g) and their sensitivity was 30 and 40%, respectively.Conclusion: Our study did not highlight any FDG PET/CT parameter predictor of fTI malignancy

Radiotherapy modification based on artificial intelligence and radiomics applied to (18F)-fluorodeoxyglucose positron emission tomography/computed tomography.

peer reviewedOver the last decades, the refinement of radiation therapy techniques has been associated with an increasing interest for individualized radiation therapy with the aim of increasing or maintaining tumor control and reducing radiation toxicity. Developments in artificial intelligence (AI), particularly machine learning and deep learning, in imaging sciences, including nuclear medecine, have led to significant enthusiasm for the concept of "rapid learning health system". AI combined with radiomics applied to (18F)-fluorodeoxyglucose positron emission tomography/computed tomography ([18F]-FDG PET/CT) offers a unique opportunity for the development of predictive models that can help stratify each patient's risk and guide treatment decisions for optimal outcomes and quality of life of patients treated with radiation therapy. Here we present an overview of the current contribution of AI and radiomics-based machine learning models applied to (18F)-FDG PET/CT in the management of cancer treated by radiation therapy

Review. Divergent selection for residual feed intake in the growing pig

To view supplementary material for this article, please visit https:/doi.org/10.1017/S175173111600286XThis review summarizes the results from the INRA (Institut National de la Recherche Agronomique) divergent selection experiment on residual feed intake (RFI) in growing Large White pigs during nine generations of selection. It discusses the remaining challenges and perspectives for the improvement of feed efficiency in growing pigs. The impacts on growing pigs raised under standard conditions and in alternative situations such as heat stress, inflammatory challenges or lactation have been studied. After nine generations of selection, the divergent selection for RFI led to highly significant ( P<0.001) line differences for RFI (−165 g/day in the low RFI (LRFI) line compared with high RFI line) and daily feed intake (−270 g/day). Low responses wereobserved on growth rate (−12.8 g/day, P <0.05) and body composition (+0.9mm backfat thickness, P = 0.57; −2.64% lean meat content, P<0.001) with a marked response on feed conversion ratio (−0.32 kg feed/kg gain, P<0.001). Reduced ultimate pH and increased lightness of the meat ( P<0.001) were observed in LRFI pigs with minor impact on the sensory quality of the meat. These changes in meat quality were associated with changes of the muscular energy metabolism. Reduced maintenance energy requirements (−10% after five generations of selection) and activity (−21% of time standing after six generations of selection) of LRFI pigs greatly contributed to the gain in energy efficiency. However, the impact of selection for RFI on the protein metabolism of the pig remains unclear. Digestibility of energy and nutrients was not affected by selection, neither for pigs fed conventional diets nor for pigs fed high-fibre diets. A significant improvement of digestive efficiency could likely be achieved by selecting pigs on fibre diets. No convincing genetic or blood biomarker has been identified for explaining the differences in RFI, suggesting that pigs have various ways to achieve an efficient use of feed. No deleterious impact of the selection on the sow reproduction performance was observed. The resource allocation theory states that low RFI may reduce the ability to cope with stressors,via the reduction of a buffer compartment dedicated to responses to stress. None of the experiments focussed on the response of pigs to stress or challenges could confirm this theory. Understanding the relationships between RFI and responses to stress and energy demanding processes, as such immunity and lactation, remains a major challenge for a better understanding of the underlying biological mechanisms of the trait and to reconcile the experimental results with the resource allocation theory

Poly(I:C) induces intense expression of c-IAP2 and cooperates with an IAP inhibitor in induction of apoptosis in cancer cells

<p>Abstract</p> <p>Background</p> <p>There is increasing evidence that the toll-like receptor 3 (TLR3) is an interesting target for anti-cancer therapy. Unfortunately, most laboratory investigations about the impact of TLR3 stimulation on human malignant cells have been performed with very high concentrations - 5 to 100 μg/ml - of the prototype TLR3 ligand, poly(I:C). In a previous study focused on a specific type of human carcinoma - nasopharyngeal carcinoma - we have shown that concentrations of poly(I:C) as low as 100 ng/ml are sufficient to induce apoptosis of malignant cells when combined to a pharmacological antagonist of the IAP family based on Smac mimicry.</p> <p>Methods</p> <p>This observation prompted us to investigate the contribution of the IAP family in cell response to poly(I:C) in a variety of human malignant cell types.</p> <p>Results</p> <p>We report a rapid, intense and selective increase in c-IAP2 protein expression observed under stimulation by poly(I:C)(500 ng/ml) in all types of human malignant cells. In most cell types, this change in protein expression is underlain by an increase in c-IAP2 transcripts and dependent on the TLR3/TRIF pathway. When poly(I:C) is combined to the IAP inhibitor RMT 5265, a cooperative effect in apoptosis induction and/or inhibition of clonogenic growth is obtained in a large fraction of carcinoma and melanoma cell lines.</p> <p>Conclusions</p> <p>Currently, IAP inhibitors like RMT 5265 and poly(I:C) are the subject of separate therapeutic trials. In light of our observations, combined use of both types of compounds should be considered for treatment of human malignancies including carcinomas and melanomas.</p

Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.

peer reviewedThe primary objective of the present study was to identify a subset of radiomic features extracted from primary tumor imaged by computed tomography of early-stage non-small cell lung cancer patients, which remain unaffected by variations in segmentation quality and in computed tomography image acquisition protocol. The robustness of these features to segmentation variations was assessed by analyzing the correlation of feature values extracted from lesion volumes delineated by two annotators. The robustness to variations in acquisition protocol was evaluated by examining the correlation of features extracted from high-dose and low-dose computed tomography scans, both of which were acquired for each patient as part of the stereotactic body radiotherapy planning process. Among 106 radiomic features considered, 21 were identified as robust. An analysis including univariate and multivariate assessments was subsequently conducted to estimate the predictive performance of these robust features on the outcome of early-stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. The univariate predictive analysis revealed that robust features demonstrated superior predictive potential compared to non-robust features. The multivariate analysis indicated that linear regression models built with robust features displayed greater generalization capabilities by outperforming other models in predicting the outcomes of an external validation dataset