Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

Classification of current anticancer immunotherapies.

During the past decades, anticancer immunotherapy has evolved from a promising therapeutic option to a robust clinical reality. Many immunotherapeutic regimens are now approved by the US Food and Drug Administration and the European Medicines Agency for use in cancer patients, and many others are being investigated as standalone therapeutic interventions or combined with conventional treatments in clinical studies. Immunotherapies may be subdivided into "passive" and "active" based on their ability to engage the host immune system against cancer. Since the anticancer activity of most passive immunotherapeutics (including tumor-targeting monoclonal antibodies) also relies on the host immune system, this classification does not properly reflect the complexity of the drug-host-tumor interaction. Alternatively, anticancer immunotherapeutics can be classified according to their antigen specificity. While some immunotherapies specifically target one (or a few) defined tumor-associated antigen(s), others operate in a relatively non-specific manner and boost natural or therapy-elicited anticancer immune responses of unknown and often broad specificity. Here, we propose a critical, integrated classification of anticancer immunotherapies and discuss the clinical relevance of these approaches.

A new classification of the Turkish terranes and sutures and its implication for the paleotectonic history of the region

The Turkish part of the Tethyan realm is represented by a series of terranes juxtaposed through Alpine convergent movements and separated by complex suture zones. Different terranes can be defined and characterized by their dominant geological background. The Pontides domain represents a segment of the former active margin of Eurasia, where back-arc basins opened in the Triassic and separated the Sakarya terrane from neighbouring regions. Sakarya was re-accreted to Laurasia through the Balkanic mid-Cretaceous orogenic event that also affected the Rhodope and Strandja zones. The whole region from the Balkans to the Caucasus was then affected by a reversal of subduction and creation of a Late Cretaceous arc before collision with the Anatolian domain in the Eocene. If the Anatolian terrane underwent an evolution similar to Sakarya during the Late Paleozoic and Early Triassic times, both terranes had a diverging history during and after the Eo-Cimmerian collision. North of Sakarya, the Küre back-arc was closed during the Jurassic, whereas north of the Anatolian domain, the back-arc type oceans did not close before the Late Cretaceous. During the Cretaceous, both domains were affected by ophiolite obduction, but in very different ways: north directed diachronous Middle to Late Cretaceous mélange obduction on the Jurassic Sakarya passive margin; Senonian synchronous southward obduction on the Triassic passive margin of Anatolia. From this, it appears that the Izmir-Ankara suture, currently separating both terranes, is composite, and that the passive margin of Sakarya is not the conjugate margin of Anatolia. To the south, the Cimmerian Taurus domain together with the Beydağları domain (part of the larger Greater Apulian terrane), were detached from north Gondwana in the Permian during the opening of the Neotethys (East-Mediterranean basin). The drifting Cimmerian blocks entered into a soft collision with the Anatolian and related terranes in the Eo-Cimmerian orogenic phase (Late Triassic), thus suturing the Paleotethys. At that time, the Taurus plate developed foreland-type basins, filled with flysch-molasse deposits that locally overstepped the lower plate Taurus terrane and were deposited in the opening Neotethys to the south. These olistostromal deposits are characterized by pelagic Carboniferous and Permian material from the Paleotethys suture zone found in the Mersin mélange. The latter, as well as the Antalya and Mamonia domains are represented by a series of exotic units now found south of the main Taurus range. Part of the Mersin exotic material was clearly derived from the former north Anatolian passive margin (Huğlu-type series) and re-displaced during the Paleogene. This led us to propose a plate tectonic model where the Anatolian ophiolitic front is linked up with the Samail/Baër-Bassit obduction front found along the Arabian margin. The obduction front was indented by the Anatolian promontory whose eastern end was partially subducted. Continued slab roll-back of the Neotethys allowed Anatolian exotics to continue their course southwestward until their emplacement along the Taurus southern margin (Mersin) and up to the Beydağları promontory (Antaya-Mamonia) in the latest Cretaceous-Paleocene. The supra-subduction ocean opening at the back of the obduction front (Troodos-type Ocean) was finally closed by Eocene north-south shortening between Africa and Eurasia. This brought close to each other Cretaceous ophiolites derived from the north of Anatolia and those obducted on the Arabian promontory. The latter were sealed by a Maastrichtian platform, and locally never affected by Alpine tectonism, whereas those located on the eastern Anatolian plate are strongly deformed and metamorphosed, and affected by Eocene arc magmatism. These observations help to reconstruct the larger frame of the central Tethyan realm geodynamic evolution.

Enchondromatosis revisited: New classification with molecular basis.

The so-called "enchondromatoses" are skeletal disorders defined by the presence of ectopic cartilaginous tissue within bone tissue. The clinical and radiographic features of the different enchondromatoses are distinct, and grouping them does not reflect a common pathogenesis but simply a similar radiographic appearance and thus the need for a differential diagnosis. Recent advances in the understanding of their molecular and cellular bases confirm the heterogeneous nature of the different enchondromatoses. Some, like Ollier disease, Maffucci disease, metaphyseal chondromatosis with hydroxyglutaric aciduria, and metachondromatosis are produced by a dysregulation of chondrocyte proliferation, while others (such as spondyloenchondrodysplasia or dysspondyloenchondromatosis) are caused by defects in structure or metabolism of cartilage or bone matrix. In other forms (e.g., the dominantly inherited genochondromatoses), the basic defect remains to be determined. The classification, proposed by Spranger and associates in 1978 and tentatively revised twice, was based on the radiographic appearance, the anatomic sites involved, and the mode of inheritance. The new classification proposed here integrates the molecular genetic advances and delineates phenotypic families based on the molecular defects. Reference radiographs are provided to help in the diagnosis of the well-defined forms. In spite of advances, many cases remain difficult to diagnose and classify, implying that more variants remain to be defined at both the clinical and molecular levels. © 2012 Wiley Periodicals, Inc.

Validation of tissue modelization and classification techniques in T1-weighted MR brain images

We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

Typing less common ovarian tumors: A training tool based on a pattern-based algorithm applied to a set of 20 virtual slides.

Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.

Prognosis in Duke's B colorectal carcinoma: the Jass classification revisited.

OBJECTIVE: To assess whether Jass staging enhances prognostic prediction in Dukes' B colorectal carcinoma. DESIGN: A historical cohort observational study. SETTING: A university tertiary care centre, Switzerland. SUBJECTS: 108 consecutive patients. INTERVENTIONS: Curative resection of Dukes' B colorectal carcinoma between January 1985 and December 1988, Patients with familial adenomatous polyposis; hereditary non-polyposis colorectal cancer; Crohns' disease; ulcerative colitis and synchronous and recurrent tumours were excluded. A comparable group of 155 consecutive patients with Dukes' C carcinoma were included for reference purposes. MAIN OUTCOME MEASURES: Disease free and overall survival for Dukes' B and overall survival for Dukes' C tumours. RESULTS: Dukes' B tumours in Jass group III or with an infiltrated margin had a significantly worse disease-free survival (p = 0.001 and 0.0001, respectively) and those with infiltrated margins had a significantly worse overall survival (p = 0.002). Overall survival among those with Dukes' B Jass III and Dukes' B with infiltrated margins was no better than overall survival among all patients with Dukes' C tumours. CONCLUSION: Jass staging and the nature of the margin of invasion allow patients undergoing curative surgery for Dukes' B colorectal carcinoma to be separated into prognostic groups. A group of patients with Dukes' B tumours whose prognosis is inseparable from those with Dukes' C tumours can be identified, the nature of the margin of invasion being used to classify a larger number of patients.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Multi-source composite kernels for urban image classification

This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

Aggregation invariance in general clustering approaches

General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Management of Pharyngeal Fistulas After Anterior Cervical Spine Surgery: A Treatment Algorithm for Severe Complications.

STUDY DESIGN:: Retrospective database- query to identify all anterior spinal approaches. OBJECTIVES:: To assess all patients with pharyngo-cutaneous fistulas after anterior cervical spine surgery. SUMMARY OF BACKGROUND DATA:: Patients treated in University of Heidelberg Spine Medical Center, Spinal Cord Injury Unit and Department of Otolaryngology (Germany), between 2005 and 2011 with the diagnosis of pharyngo-cutaneous fistulas. METHODS:: We conducted a retrospective study on 5 patients between 2005 and 2011 with PCF after ACSS, their therapy management and outcome according to radiologic data and patient charts. RESULTS:: Upon presentation 4 patients were paraplegic. 2 had PCF arising from one piriform sinus, two patients from the posterior pharyngeal wall and piriform sinus combined and one patient only from the posterior pharyngeal wall. 2 had previous unsuccessful surgical repair elsewhere and 1 had prior radiation therapy. In 3 patients speech and swallowing could be completely restored, 2 patients died. Both were paraplegic. The patients needed an average of 2-3 procedures for complete functional recovery consisting of primary closure with various vascularised regional flaps and refining laser procedures supplemented with negative pressure wound therapy where needed. CONCLUSION:: Based on our experience we are able to provide a treatment algorithm that indicates that chronic as opposed to acute fistulas require a primary surgical closure combined with a vascularised flap that should be accompanied by the immediate application of a negative pressure wound therapy. We also conclude that particularly in paraplegic patients suffering this complication the risk for a fatal outcome is substantial.