Frédéric Schmidt

Antitumor activity of pyridocarbazole and benzopyridoindole derivatives that inhibit protein kinase CK2.

The alkyloid compound ellipticine derived from the berrywood tree is a topoisomerase II poison that is used in ovarian and breast cancer treatment. In this study, we report the identification of ellipticine derivatives and their tetracyclic angular benzopyridoindole analogues as novel ATP-competitive inhibitors of the protein kinase CK2. In vitro and in vivo assays showed that these compounds have a good pharmacologic profile, causing a marked inhibition of CK2 activity associated with cell cycle arrest and apoptosis in human cancer cells. Further, in vivo assays demonstrate antitumor activity in a mouse xenograft model of human glioblastoma. Finally, crystal structures of CK2-inhibitor complex provide structural insights on the molecular basis of CK2 inhibition. Our work lays the foundation for development of clinically useful CK2 inhibitors derived from a well-studied scaffold with suitable pharmacokinetics parameters.

New potent dual inhibitors of CK2 and Pim kinases: discovery and structural insights

Protein kinase casein kinase 2 (CK2) is a serine/threonine kinase with evidence of implication in growth dysregulation and apoptosis resistance, making it a relevant target for cancer therapy. Several CK2 inhibitors have been developed showing variable efficiency, emphasizing the need to expand the chemical diversity of those inhibitors. We report the identification and characterization of 2,8‐difurandicarboxylic acid derivatives as a new class of nanomolar ATP‐competitive inhibitors. Selectivity profiling pointed out proviral insertion Moloney virus kinases (Pim kinases) as the only other kinases that are significantly inhibited. By combining structure‐activity relationship analysis with structural determination, we were able to determine the binding mode of these inhibitors for both kinases and to explain their strong inhibitory potency. Essential chemical features necessary for activity on both kinases were then identified. The described compounds are not cell permeable: however, they could provide a lead for developing novel inhibitors usable also in vivo. Given the similar but not redundant pathophysiological functions of CK2 and Pim family members, such inhibitors would provide new attractive leads for targeted cancer therapy. This work highlights that 2 functionally related kinases from different kinome branches display exquisite sensitivity to a common inhibitor.—López‐Ramos, M., Prudent, R., Moucadel, V., Sautel, C. F., Barette, C., Lafanechère, L., Mouawad, L., Grierson, D., Schmidt, F., Florent, J.‐C., Filippakopoulos, P., Bullock, A. N., Knapp, S., Reiser, J.‐B., Cochet, C. New potent dual inhibitors of CK2 and Pim kinases: discovery and structural insights. FASEB J. 24, 3171–3185 (2010). www.fasebj.org

Implementation Strategies for Hyperspectral Unmixing Using Bayesian Source Separation

Bayesian positive source separation (BPSS) is a useful unsupervised approach for hyperspectral data unmixing, where numerical nonnegativity of spectra and abundances has to be ensured, such as in remote sensing. Moreover, it is sensible to impose a sum-to-one (full additivity) constraint to the estimated source abundances in each pixel. Even though nonnegativity and full additivity are two necessary properties to get physically interpretable results, the use of BPSS algorithms has so far been limited by high computation time and large memory requirements due to the Markov chain Monte Carlo calculations. An implementation strategy that allows one to apply these algorithms on a full hyperspectral image, as it is typical in earth and planetary science, is introduced. The effects of pixel selection and the impact of such sampling on the relevance of the estimated component spectra and abundance maps, as well as on the computation times, are discussed. For that purpose, two different data sets have been used: a synthetic one and a real hyperspectral image from Mars.

Surface reflectance of Mars observed by CRISM/MRO : 2. Estimation of surface photometric properties in Gusev Crater and Meridiani Planum

The present article proposes an approach to analyze the photometric properties of the surface materials from multi-angle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on-board the Mars Reconnaissance Orbiter. We estimate photometric parameters using Hapke model in a Bayesian inversion framework. This work also represents a validation of the atmospheric correction provided by the Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO) proposed in the companion article.The latter algorithm retrieves photometric curves of surface materials in reflectance units after removing the aerosol contribution. This validation is done by comparing the estimated photometric parameters to those obtained from in situ measurements by Panoramic Camera instrument at the Mars Exploration Rover (MER)-Spirit and MER-Opportunity landing sites. Consistent photometric parameters with those from in situ measurements are found, demonstrating that MARS-ReCO gives access to accurate surface reflectance. Moreover the assumption of a non-Lambertian surface as included in MARS-ReCO is shown to be significantly more precise to estimate surface photometric properties from space in comparison to methods based on a Lambertian surface assumption. In the future, the presented method will allow us to map from orbit the surface bidirectional reflectance and the related photometric parameters in order to characterize the Martian surface.

Intercomparison and Validation of Techniques for Spectral Unmixing of Hyperspectral Images: A Planetary Case Study

As the volume of hyperspectral data for planetary exploration increases, efficient yet accurate algorithms are decisive for their analysis. In this paper, the capability of spectral unmixing for analyzing hyperspectral images from Mars is investigated. For that purpose, we consider the Russell megadune observed by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and the High-Resolution Imaging Science Experiment (HiRISE) instruments. In late winter, this area of Mars is appropriate for testing linear unmixing techniques because of the geographical coexistence of seasonal CO2 ice and defrosting dusty features that is not resolved by CRISM. Linear unmixing is carried out on a selected CRISM image by seven state-of-the-art approaches based on different principles. Three physically coherent sources with an increasing fingerprint of dust are recognized by the majority of the methods. Processing of HiRISE imagery allows the construction of a ground truth in the form of a reference abundance map related to the defrosting features. Validation of abundances estimated by spectral unmixing is carried out in an independent and quantitative manner by comparison with the ground truth. The quality of the results is estimated through the correlation coefficient and average error between the reconstructed and reference abundance maps. Intercomparison of the selected linear unmixing approaches is performed. Global and local comparisons show that misregistration inaccuracies between the HiRISE and CRISM images represent the major source of error. We also conclude that abundance maps provided by three methods out of seven are generally accurate, i.e., sufficient for a planetary interpretation.

Palladium-catalyzed synthesis of 2,3-disubstituted 5-azaindoles via heteroannulation reaction and of 2-substituted 5-azaindoles through domino sila-Sonogashira/5-endo cyclization.

A general and efficient procedure for the synthesis of 2,3-disubstituted 5-azaindoles through the palladium-catalyzed heteroannulation of 4-acetamido-3-iodopyridines and diaryl-, dialkyl-, or arylalkylalkynes is described along with a study of the reaction regioselectivity. The preparation of 2-monosubstituted 5-azaindoles via sila-Sonogashira/5-endo cyclization is also reported. These methods allowed us to prepare 36 diversely substituted 5-azaindoles in good yields.

Realistic uncertainties on Hapke model parameters from photometric measurement

Abstract The single particle phase function describes the manner in which an average element of a granular material diffuses the light in the angular space usually with two parameters: the asymmetry parameter b describing the width of the scattering lobe and the backscattering fraction c describing the main direction of the scattering lobe. Hapke proposed a convenient and widely used analytical model to describe the spectro-photometry of granular materials. Using a compilation of the published data, Hapke (Hapke, B. [2012]. Icarus 221, 1079–1083) recently studied the relationship of b and c for natural examples and proposed the hockey stick relation (excluding b > 0.5 and c > 0.5 ). For the moment, there is no theoretical explanation for this relationship. One goal of this article is to study a possible bias due to the retrieval method. We expand here an innovative Bayesian inversion method in order to study into detail the uncertainties of retrieved parameters. On Emission Phase Function (EPF) data, we demonstrate that the uncertainties of the retrieved parameters follow the same hockey stick relation, suggesting that this relation is due to the fact that b and c are coupled parameters in the Hapke model instead of a natural phenomena. Nevertheless, the data used in the Hapke (Hapke, B. [2012]. Icarus 221, 1079–1083) compilation generally are full Bidirectional Reflectance Diffusion Function (BRDF) that are shown not to be subject to this artifact. Moreover, the Bayesian method is a good tool to test if the sampling geometry is sufficient to constrain the parameters (single scattering albedo, surface roughness, b , c , opposition effect). We performed sensitivity tests by mimicking various surface scattering properties and various single image-like/disk resolved image, EPF-like and BRDF-like geometric sampling conditions. The second goal of this article is to estimate the favorable geometric conditions for an accurate estimation of photometric parameters in order to provide new constraints for future observation campaigns and instrumentations.

Formation of recurring slope lineae on Mars by rarefied gas-triggered granular flows

Active dark flows known as recurring slope lineae have been observed on the warmest slopes of equatorial Mars. The morphology, composition and seasonality of the lineae suggest a role of liquid water in their formation. However, internal and atmospheric sources of water appear to be insufficient to sustain the observed slope activity. Experimental evidence suggests that under the low atmospheric pressure at the surface of Mars, gas can flow upwards through porous Martian soil due to thermal creep under surface regions heated by the Sun, and disturb small particles. Here we present numerical simulations to demonstrate that such a dry process involving the pumping of rarefied gas in the Martian soil due to temperature contrasts can explain the formation of the recurring slope lineae. In our simulations, solar irradiation followed by shadow significantly reduces the angle of repose due to the resulting temporary temperature gradients over shaded terrain, and leads to flow at intermediate slope angles. The simulated flow locations are consistent with observed recurring slope lineae that initiate in rough and bouldered terrains with local shadows over the soil. We suggest that this dry avalanche process can explain the formation of the recurring slope lineae on Mars without requiring liquid water or CO2 frost activity. Transient streaks on Martian slopes have been attributed to liquid water. Simulations show that a dry avalanche process involving the flow of gas in the Martian soil due to temperature contrasts can instead explain these recurring features.

Minerals detection for hyperspectral images using adapted linear unmixing: LinMin

Minerals detection over large volume of spectra is the challenge addressed by current hyperspectral imaging spectrometer in Planetary Science. Instruments such OMEGA (Mars Express), CRISM (Mars Reconnaissance Orbiter), M (Chandrayaan-1), VIRTIS (Rosetta) and many more, have been producing very large datasets since one decade. We propose here a fast supervised detection algorithm called LinMin, in the framework of linear unmixing, with innovative arrangement in order to treat non-linear cases due to radiative transfer in both atmosphere and surface. We use reference laboratory and synthetic spectral library. Additional spectra are used in order to mimic the effect of Martian aerosols, grain size, and observation geometry discrepancies between reference and observed spectra. The proposed algorithm estimates the uncertainty on “mixing coefficient” from the uncertainty of observed spectra. Both numerical and observational tests validate the approach. Fast parallel implementation of the best algorithm (IPLS) on Graphics Processing Units (GPU) allows to significantly reduce the computation cost by a factor of ̃40.

On the unmixing of MEx/OMEGA hyperspectral data

Abstract This paper presents a comparative study of three different types of estimators used for supervised linear unmixing of two MEx/OMEGA hyperspectral cubes. The algorithms take into account the constraints of the abundance fractions, in order to get physically interpretable results. Abundance maps show that the Bayesian maximum a posteriori probability (MAP) estimator proposed in Themelis and Rontogiannis (2008) outperforms the other two schemes, offering a compromise between complexity and estimation performance. Thus, the MAP estimator is a candidate algorithm to perform ice and minerals detection on large hyperspectral datasets.