Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Genetic transformation of sweet oranges with the D4E1 gene driven by the AtPP2 promoter

The objective of this work was to produce transgenic 'Pêra' and 'Valência' sweet orange plants using the D4E1 gene driven by the Arabidopsis thaliana phloem protein (AtPP2) promoter and to quantify transgene expression in different transformation events. Genetic transformation experiments were carried out with epicotyl segments co‑cultivated with Agrobacterium tumefaciens. Six plants from 'Pêra' sweet orange and seven plants from 'Valência' sweet orange were confirmed as different transgenic events by means of the polymerase chain reaction (PCR) and the Southern blot techniques. Transgene expression was quantified using real‑time quantitative PCR. D4E1 gene expression levels vary from 5 up to 50 times among different transformation events.

In vivo Structural Imaging of the Cerebellum, the Contribution of Ultra-High Fields.

This review covers some of the contributions to date from cerebellar imaging studies performed at ultra-high magnetic fields. A short overview of the general advantages and drawbacks of the use of such high field systems for imaging is given. One of the biggest advantages of imaging at high magnetic fields is the improved spatial resolution, achievable thanks to the increased available signal-to-noise ratio. This high spatial resolution better matches the dimensions of the cerebellar substructures, allowing a better definition of such structures in the images. The implications of the use of high field systems is discussed for several imaging sequences and image contrast mechanisms. This review covers studies which were performed in vivo in both rodents and humans, with a special focus on studies that were directed towards the observation of the different cerebellar layers.

Hes1 is a critical but context-dependent mediator of canonical Notch signaling in lymphocyte development and transformation.

Although canonical Notch signaling regulates multiple hematopoietic lineage decisions including T cell and marginal zone B cell fate specification, the downstream molecular mediators of Notch function are largely unknown. We showed here that conditional inactivation of Hes1, a well-characterized Notch target gene, in adult murine bone marrow (BM) cells severely impaired T cell development without affecting other Notch-dependent hematopoietic lineages such as marginal zone B cells. Competitive mixed BM chimeras, intrathymic transfer experiments, and in vitro culture of BM progenitors on Delta-like-expressing stromal cells further demonstrated that Hes1 is required for T cell lineage commitment, but dispensable for Notch-dependent thymocyte maturation through and beyond the beta selection checkpoint. Furthermore, our data strongly suggest that Hes1 is essential for the development and maintenance of Notch-induced T cell acute lymphoblastic leukemia. Collectively, our studies identify Hes1 as a critical but context-dependent mediator of canonical Notch signaling in the hematopoietic system.

Structural changes induced by daily music listening in the recovering brain after middle cerebral artery stroke: a voxel-based morphometry study

Music is a highly complex and versatile stimulus for the brain that engages many temporal, frontal, parietal, cerebellar, and subcortical areas involved in auditory, cognitive, emotional, and motor processing. Regular musical activities have been shown to effectively enhance the structure and function of many brain areas, making music a potential tool also in neurological rehabilitation. In our previous randomized controlled study, we found that listening to music on a daily basis can improve cognitive recovery and improve mood after an acute middle cerebral artery stroke. Extending this study, a voxel-based morphometry (VBM) analysis utilizing cost function masking was performed on the acute and 6-month post-stroke stage structural magnetic resonance imaging data of the patients (n = 49) who either listened to their favorite music [music group (MG), n = 16] or verbal material [audio book group (ABG), n = 18] or did not receive any listening material [control group (CG), n = 15] during the 6-month recovery period. Although all groups showed significant gray matter volume (GMV) increases from the acute to the 6-month stage, there was a specific network of frontal areas [left and right superior frontal gyrus (SFG), right medial SFG] and limbic areas [left ventral/subgenual anterior cingulate cortex (SACC) and right ventral striatum (VS)] in patients with left hemisphere damage in which the GMV increases were larger in the MG than in the ABG and in the CG. Moreover, the GM reorganization in the frontal areas correlated with enhanced recovery of verbal memory, focused attention, and language skills, whereas the GM reorganization in the SACC correlated with reduced negative mood. This study adds on previous results, showing that music listening after stroke not only enhances behavioral recovery, but also induces fine-grained neuroanatomical changes in the recovering brain.

Malignancy transformation of chronic osteomyelitis: description of 6 cases of Marjolin's ulcers

Marjolin's ulcer describes any malignant transformation of a chronic inflammatory lesion. In the majority of cases, a squamous cell carcinoma is diagnosed. Malignant transformation occurs usually after a long period of latency of chronic infection; it takes approximately 35 years on average. There are no typical clinical presentations, but several indirect signs may suggest the malignant transformation, such as increased or changed discharge, pathologic fracture, a slow-growing exophytic mass, or other suggestive signs of malignant transformation, which should prompt to biopsy for histological exam. The diagnosis of chronic osteomyelitis should not prevent to search for carcinoma. We present six patients with chronic osteomyelitis that developed well-differentiated squamous cell carcinoma. All patients were older than 50 years (mean 60 years, range 52-77 years). Five Marjolin's ulcers were located on the lower limb and one on the arm. The average time of the chronic discharging osteomyelitis before diagnosis of carcinoma ranged between 12 and 40 years. All patients were treated by amputation of the affected limb. None had metastasis, and one patient developed local recurrence and received palliative treatment. Our study emphasizes that Marjolin's ulcer should be considered as a rare but significant long-term complication of chronic osteomyelitis. The finding of microorganisms should not prevent from further diagnostic procedures by histopathological examination so that the correct surgical treatment can be performed.

Local alignment refinement using structural assessment.

Homology modeling is the most commonly used technique to build a three-dimensional model for a protein sequence. It heavily relies on the quality of the sequence alignment between the protein to model and related proteins with a known three dimensional structure. Alignment quality can be assessed according to the physico-chemical properties of the three dimensional models it produces.In this work, we introduce fifteen predictors designed to evaluate the properties of the models obtained for various alignments. They consist of an energy value obtained from different force fields (CHARMM, ProsaII or ANOLEA) computed on residue selected around misaligned regions. These predictors were evaluated on ten challenging test cases. For each target, all possible ungapped alignments are generated and their corresponding models are computed and evaluated.The best predictor, retrieving the structural alignment for 9 out of 10 test cases, is based on the ANOLEA atomistic mean force potential and takes into account residues around misaligned secondary structure elements. The performance of the other predictors is significantly lower. This work shows that substantial improvement in local alignments can be obtained by careful assessment of the local structure of the resulting models.

Predicting human resting-state functional connectivity from structural connectivity

In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks-including their spatial statistics and their persistence across time-can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.

Financial Analysis of the Pulp and Paper Industry: Performance and value creation of the world's pulp and paper companies

Tutkimuksen tavoitteena on analysoida 74 sellu- ja paperiyrityksen taloudellista suorituskykyä kannattavuutta, maksuvalmiutta, vakavaraisuutta ja arvonluontikykyä kuvaavilla tunnusluvuilla. Tutkimuksen teoriaosa esittelee liiketoiminta-analyysin välineet, jonka jälkeen esitellään taloudelliset tunnusluvut. Empiriaosassa käydään läpi vuoden 2005 tunnusluvut yritystasolla. Jotta voidaan tarkastella tunnuslukujen muutoksia pitkällä aikavälillä, yritykset ryhmitellään maantieteellisen sijainnin sekä liiketoimintaorientaation mukaan. Tutkimus on kuvaileva. Tunnusluvuista voidaan todeta sellu- ja paperiteollisuudessa meneillään oleva toimialan rakennemuutos. Eteläamerikkalaiset yritykset, jotka hyötyvät uudesta ja kustannustehokkaasta raaka-aineesta, ovat siirtyneet lähemmäs arvonluontia, kun taas suurin osa pohjoisamerikkalaisista yrityksistä, jotka olivat toimialan johtavia arvonluojia, ovat nyt arvon tuhoajia. Toimiala kärsii myös alhaisesta kannattavuudesta, joka vaikuttaa eniten pohjoisamerikkalaisiin yrityksiin. Samaan aikaan eteläamerikkalaiset yritykset ovat nostaneet kannattavuuttaan, mikä puolestaan korostaa meneillään olevaa muutosta.

Multimodal MRI analysis of structural and functional networks in the human brain : application to two clinical studies : driving abilities under THC intoxication and early white matter changes in FXTAS

Les approches multimodales dans l'imagerie cérébrale non invasive sont de plus en plus considérées comme un outil indispensable pour la compréhension des différents aspects de la structure et de la fonction cérébrale. Grâce aux progrès des techniques d'acquisition des images de Resonance Magnetique et aux nouveaux outils pour le traitement des données, il est désormais possible de mesurer plusieurs paramètres sensibles aux différentes caractéristiques des tissues cérébraux. Ces progrès permettent, par exemple, d'étudier les substrats anatomiques qui sont à la base des processus cognitifs ou de discerner au niveau purement structurel les phénomènes dégénératifs et développementaux. Cette thèse met en évidence l'importance de l'utilisation d'une approche multimodale pour étudier les différents aspects de la dynamique cérébrale grâce à l'application de cette approche à deux études cliniques: l'évaluation structurelle et fonctionnelle des effets aigus du cannabis fumé chez des consommateurs réguliers et occasionnels, et l'évaluation de l'intégrité de la substance grise et blanche chez des jeunes porteurs de la prémutations du gène FMR1 à risque de développer le FXTAS (Fragile-X Tremor Ataxia Syndrome). Nous avons montré que chez les fumeurs occasionnels de cannabis, même à faible concentration du principal composant psychoactif (THC) dans le sang, la performance lors d'une tâche visuo-motrice est fortement diminuée, et qu'il y a des changements dans l'activité des trois réseaux cérébraux impliqués dans les processus cognitifs: le réseau de saillance, le réseau du contrôle exécutif, et le réseau actif par défaut (Default Mode). Les sujets ne sont pas en mesure de saisir les saillances dans l'environnement et de focaliser leur attention sur la tâche. L'augmentation de la réponse hémodynamique dans le cortex cingulaire antérieur suggère une augmentation de l'activité introspective. Une investigation des ef¬fets au niveau cérébral d'une exposition prolongée au cannabis, montre des changements persistants de la substance grise dans les régions associées à la mémoire et au traitement des émotions. Le niveau d'atrophie dans ces structures corrèle avec la consommation de cannabis au cours des trois mois précédant l'étude. Dans la deuxième étude, nous démontrons des altérations structurelles des décennies avant l'apparition du syndrome FXTAS chez des sujets jeunes, asymptomatiques, et porteurs de la prémutation du gène FMR1. Les modifications trouvées peuvent être liées à deux mécanismes différents. Les altérations dans le réseau moteur du cervelet et dans la fimbria de l'hippocampe, suggèrent un effet développemental de la prémutation. Elles incluent aussi une atrophie de la substance grise du lobule VI du cervelet et l'altération des propriétés tissulaires de la substance blanche des projections afférentes correspondantes aux pédoncules cérébelleux moyens. Les lésions diffuses de la substance blanche cérébrale peu¬vent être un marquer précoce du développement de la maladie, car elles sont liées à un phénomène dégénératif qui précède l'apparition des symptômes du FXTAS. - Multimodal brain imaging is becoming a leading tool for understanding different aspects of brain structure and function. Thanks to the advances in Magnetic Resonance imaging (MRI) acquisition schemes and data processing techniques, it is now possible to measure different parameters sensitive to different tissue characteristics. This allows for example to investigate anatomical substrates underlying cognitive processing, or to disentangle, at a pure structural level degeneration and developmental processes. This thesis highlights the importance of using a multimodal approach for investigating different aspects of brain dynamics by applying this approach to two clinical studies: functional and structural assessment of the acute effects of cannabis smoking in regular and occasional users, and grey and white matter assessment in young FMR1 premutation carriers at risk of developing FXTAS. We demonstrate that in occasional smokers cannabis smoking, even at low concentration of the main psychoactive component (THC) in the blood, strongly decrease subjects' performance on a visuo-motor tracking task, and globally alters the activity of the three brain networks involved in cognitive processing: the Salience, the Control Executive, and the Default Mode networks. Subjects are unable to capture saliences in the environment and to orient attention to the task; the increase in Hemodynamic Response in the Anterior Cingulate Cortex suggests an increase in self-oriented mental activity. A further investigation on long term exposure to cannabis, shows a persistent grey matter modification in brain regions associated with memory and affective processing. The degree of atrophy in these structures also correlates with the estimation of drug use in the three months prior the participation to the study. In the second study we demonstrate structural changes in young asymptomatic premutation carriers decades before the onset of FXTAS that might be related to two different mechanisms. Alteration of the cerebellar motor network and of the hippocampal fimbria/ fornix, may reflect a potential neurodevelopmental effect of the premutation. These include grey matter atrophy in lobule VI and modification of white matter tissue property in the corresponding afferent projections through the Middle Cerebellar Peduncles. Diffuse hemispheric white matter lesions that seem to appear closer to the onset of FXTAS and be related to a neurodegenerative phenomenon may mark the imminent onset of FXTAS.