Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Ochratoxin A at nanomolar concentration perturbs the homeostasis of neural stem cells in highly differentiated but not in immature three-dimensional brain cell cultures.

Ochratoxin A (OTA), a fungal contaminant of basic food commodities, is known to be highly cytotoxic, but the pathways underlying adverse effects at subcytotoxic concentrations remain to be elucidated. Recent reports indicate that OTA affects cell cycle regulation. Therefore, 3D brain cell cultures were used to study OTA effects on mitotically active neural stem/progenitor cells, comparing highly differentiated cultures with their immature counterparts. Changes in the rate of DNA synthesis were related to early changes in the mRNA expression of neural stem/progenitor cell markers. OTA at 10nM, a concentration below the cytotoxic level, was ineffective in immature cultures, whereas in mature cultures it significantly decreased the rate of DNA synthesis together with the mRNA expression of key transcriptional regulators such as Sox2, Mash1, Hes5, and Gli1; the cell cycle activator cyclin D2; the phenotypic markers nestin, doublecortin, and PDGFRα. These effects were largely prevented by Sonic hedgehog (Shh) peptide (500ngml(-1)) administration, indicating that OTA impaired the Shh pathway and the Sox2 regulatory transcription factor critical for stem cell self-renewal. Similar adverse effects of OTA in vivo might perturb the regulation of stem cell proliferation in the adult brain and in other organs exhibiting homeostatic and/or regenerative cell proliferation.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

Dysregulated activation of the CXCR4/CXCL12 Axisand its role in the malignant phenotype of neural crest-derived neuroblastoma tumours

Résumé: Le neuroblastome (NB) est un néoplasme dévastateur de la petite enfance, pour lequel il n'existe pas encore de traitement efficace. Les chimiokines et leurs récepteurs ont été impliqués dans la croissance des tumeurs et la formation de métastases, et en particulier, il a été rapporté que l'axe CXCR4/CXCL12 dirigeait le guidage, ainsi que l'invasion des cellules cancéreuses vers des organes spécifiques. Notre étude avait pour objectif d'analyser le rôle de CxCR4 exogène dans le comportement malin du NB, en étudiant la croissance des cellules tumorales, leur capacité de survie, de migration et d'invasion in vitro et en validant ces résultats grâce à un modèle orthotopique murin de la progression tumorale du NB in vivo. La surexpression de CXCR4 dans les cellules faiblement métastatiques IGR-NB8 n'exprimant pas CXCR4, a augmenté la mobilité des cellules vers CXCL12 in vitro. De plus, les cellules surexprimant CXCR4 ont été moins affectées par la privation de sérum que les cellules contrôles. Le volume des tumeurs chez les animaux greffés de manière orthotopique avec les cellules NB8-CXCR4-C3 était significativement plus élevé que celui des tumeurs issues des cellules contrôles NB8-E6 au moment du sacrifice des animaux. Cependant, aucune induction des métastases n'a été observée. La lignée cellulaire IGR-N91, aux propriétés invasives et métastatiques in vivo, exprime constitutivement des quantités modérées de CXCR4. La surexpression du récepteur dans cette lignée a accéléré la croissance tumorale in vivo, mais n'a pas augmenté pas l'occurrence des métastases. Les cellules IGR-N91, dans lesquelles l'expression de CXCR4 a été éteinte, suite à l'introduction de shRNA stable contre CXCR4, a présenté une croissance cellulaire plus lente, in vitro et in vivo. Afin d'identifier les gènes et les voies de signalisation impliqués dans les effets dépendants de CXCR4-CXCL12 dans le NB, des analyses du profil d'expression des gènes ont été effectuées sur les lignées cellulaires transfectées ou non (contrôle). Trois clones contrôles ont été comparés à 3 clones surexprimant CXCR4 pour chacune des lignées (IGR-NB8 et IGR-N91). Les analyses biostatiques ont identifié 10 gènes induits, dont CXCR4, et 31 gènes réprimés, communs entre tous les clones surexprimant CXCR4. Ces observations démontrent que la surexpression de CXCR4 dans le NB stimule la croissance, la survie et la migration chémotactique des cellules tumorales, mais est insuffisante pour induire ou augmenter leurs capacités invasives et métastatiques. Les voies de signalisation activées suite à la surexpression de CXCR4 et identifiées à travers le profil global de l'expression des gènes pourraient être des cibles intéressantes pour le développement de drogues capables d'inhiber la croissance tumorale. Abstact: Neuroblastoma (NB) is a devastating childhood neoplasm for which there is not yet an efficient treatment. Chemokines and their receptors have been involved in tumour growth and metastasis, and in particular the CXCR4/CXCL12 axis has been reported to mediate organ-specific cancer cells homing and invasion. The purpose of the study was to investigate the role of ectopic CXCR4 in the malignant behaviour of NB by studying tumour cell growth, survival, migration, and invasion in vitro and by validating these results using a murine orthotopic model of NB tumour progression in vivo. CXCR4 overexpression in the low metastatic, CXCR4-negative IGR-NB8 cells resulted in CXCL12-mediated chemotaxis in vitro. Furthermore, CXCR4 overexpressing cells were less affected by serum deprivation than mock-transduced cells. In vivo studies revealed that, at sacrifice, volumes of tumours developing in mice with orthotopically implanted NB8-CXCR4-C3 cells, were significantly increased compared to NB8-E6 control tumours. However, no induction of metastases was observed. The in vivo invasive and metastatic cell line IGR-N91 cell line constitutively expresses moderate levels of CXCR4. Overexpression of CXCR4 enhanced in vivo tumour growth but did not increase the occurrence of metastases. IGR-N91 cells where CXCR4 has been knocked-down by stable shRNA grew slower in vitro and in vivo. To identify genes and pathways involved in the CXCR4/CXCL12-mediated effects in NB expression, profiles analyses (Affymetrix) were performed on transduced and control cell lines. Three mock-transduced clones were compared to three CXCR4 overexpressing clones of either cell line IGR-NB8 and IGR-N91. Biostatistical analysis identified 10 commonly upregulated genes (including CXCR4) and 31 downregulated genes common to all CXCR4 overexpressing clones. These observations demonstrate that overexpression of CXCR4 in NB stimulates tumour cell growth, survival, and chemotactic migration but is not sufficient to induce or enhance invasive and metastatic capacities. Activated pathways upon CXCR4 overexpression, identified through global gene expression profiling may be interesting targets for drugs inhibiting tumour growth.

Similarity measure based classification

Luokittelujärjestelmää suunniteltaessa tarkoituksena on rakentaa systeemi, joka pystyy ratkaisemaan mahdollisimman tarkasti tutkittavan ongelma-alueen. Hahmontunnistuksessa tunnistusjärjestelmän ydin on luokitin. Luokittelun sovellusaluekenttä on varsin laaja. Luokitinta tarvitaan mm. hahmontunnistusjärjestelmissä, joista kuvankäsittely toimii hyvänä esimerkkinä. Myös lääketieteen parissa tarkkaa luokittelua tarvitaan paljon. Esimerkiksi potilaan oireiden diagnosointiin tarvitaan luokitin, joka pystyy mittaustuloksista päättelemään mahdollisimman tarkasti, onko potilaalla kyseinen oire vai ei. Väitöskirjassa on tehty similaarisuusmittoihin perustuva luokitin ja sen toimintaa on tarkasteltu mm. lääketieteen paristatulevilla data-aineistoilla, joissa luokittelutehtävänä on tunnistaa potilaan oireen laatu. Väitöskirjassa esitetyn luokittimen etuna on sen yksinkertainen rakenne, josta johtuen se on helppo tehdä sekä ymmärtää. Toinen etu on luokittimentarkkuus. Luokitin saadaan luokittelemaan useita eri ongelmia hyvin tarkasti. Tämä on tärkeää varsinkin lääketieteen parissa, missä jo pieni tarkkuuden parannus luokittelutuloksessa on erittäin tärkeää. Väitöskirjassa ontutkittu useita eri mittoja, joilla voidaan mitata samankaltaisuutta. Mitoille löytyy myös useita parametreja, joille voidaan etsiä juuri kyseiseen luokitteluongelmaan sopivat arvot. Tämä parametrien optimointi ongelma-alueeseen sopivaksi voidaan suorittaa mm. evoluutionääri- algoritmeja käyttäen. Kyseisessä työssä tähän on käytetty geneettistä algoritmia ja differentiaali-evoluutioalgoritmia. Luokittimen etuna on sen joustavuus. Ongelma-alueelle on helppo vaihtaa similaarisuusmitta, jos kyseinen mitta ei ole sopiva tutkittavaan ongelma-alueeseen. Myös eri mittojen parametrien optimointi voi parantaa tuloksia huomattavasti. Kun käytetään eri esikäsittelymenetelmiä ennen luokittelua, tuloksia pystytään parantamaan.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

Prediction of crude protein and classification of the growth stage of wheat plant samples from NIR spectra

Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples : all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.

Modelling bird species richness with neural networks for forest landscape management in NE Spain

Para preservar la biodiversidad de los ecosistemas forestales de la Europa mediterránea en escenarios actuales y futuros de cambio global mediante una gestión forestal sostenible es necesario determinar cómo influye el medio ambiente y las propias características de los bosques sobre la biodiversidad que éstos albergan. Con este propósito, se analizó la influencia de diferentes factores ambientales y de estructura y composición del bosque sobre la riqueza de aves forestales a escala 1 × 1 km en Cataluña (NE de España). Se construyeron modelos univariantes y multivariantes de redes neuronales para respectivamente explorar la respuesta individual a las variables y obtener un modelo parsimonioso (ecológicamente interpretable) y preciso. La superficie de bosque (con una fracción de cabida cubierta superior a 5%), la fracción de cabida cubierta media, la temperatura anual y la precipitación estival medias fueron los mejores predictores de la riqueza de aves forestales. La red neuronal multivariante obtenida tuvo una buena capacidad de generalización salvo en las localidades con una mayor riqueza. Además, los bosques con diferentes grados de apertura del dosel arbóreo, más maduros y más diversos en cuanto a su composición de especies arbóreas se asociaron de forma positiva con una mayor riqueza de aves forestales. Finalmente, se proporcionan directrices de gestión para la planificación forestal que permitan promover la diversidad ornítica en esta región de la Europa mediterránea.