Familial frontotemporal dementia with ubiquitin inclusion bodies and without motor neuron disease.

Frontotemporal dementia (FTD) is the second most common degenerative dementia after Alzheimer's disease and its Lewy body variant. Clinical pathology can be subdivided in three main neuropathological subtypes: frontal lobe dementia, Pick's disease and FTD with motor neuron disease (MND), all characterised by distinct histological features. Until recently the presence of ubiquitin-positive intraneuronal inclusions in the dentate gyrus, and the temporal and frontal cortex was usually associated with the MND type. Such inclusions were also observed in a few sporadic cases of FTD without or with parkinsonism (FTDP) in the absence of MND. We present here clinical, neuropathological and immunohistochemical data about a Swiss FTD family with FTDP-like features but without MND. Spongiosis and mild gliosis were observed in the grey matter. No neurofibrillary tangles, Pick bodies, Lewy bodies, senile plaques or prion-positive signals were present. However, ubiquitin-positive intracytoplasmic inclusions were detected in various structures but predominantly in the dentate gyrus. These observations support the existence of a familial form of FTDP with ubiquitin-positive intracytoplasmic inclusions (Swiss FTDP family).

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

A Topological Approach to Fuzzy Sets

This thesis presents a topological approach to studying fuzzy setsby means of modifier operators. Modifier operators are mathematical models, e.g., for hedges, and we present briefly different approaches to studying modifier operators. We are interested in compositional modifier operators, modifiers for short, and these modifiers depend on binary relations. We show that if a modifier depends on a reflexive and transitive binary relation on U, then there exists a unique topology on U such that this modifier is the closure operator in that topology. Also, if U is finite then there exists a lattice isomorphism between the class of all reflexive and transitive relations and the class of all topologies on U. We define topological similarity relation "≈" between L-fuzzy sets in an universe U, and show that the class LU/ ≈ is isomorphic with the class of all topologies on U, if U is finite and L is suitable. We consider finite bitopological spaces as approximation spaces, and we show that lower and upper approximations can be computed by means of α-level sets also in the case of equivalence relations. This means that approximations in the sense of Rough Set Theory can be computed by means of α-level sets. Finally, we present and application to data analysis: we study an approach to detecting dependencies of attributes in data base-like systems, called information systems.

A mathematical study of fuzzy logic; an algebraic approach

Fuzzy set theory and Fuzzy logic is studied from a mathematical point of view. The main goal is to investigatecommon mathematical structures in various fuzzy logical inference systems and to establish a general mathematical basis for fuzzy logic when considered as multi-valued logic. The study is composed of six distinct publications. The first paper deals with Mattila'sLPC+Ch Calculus. THis fuzzy inference system is an attempt to introduce linguistic objects to mathematical logic without defining these objects mathematically.LPC+Ch Calculus is analyzed from algebraic point of view and it is demonstratedthat suitable factorization of the set of well formed formulae (in fact, Lindenbaum algebra) leads to a structure called ET-algebra and introduced in the beginning of the paper. On its basis, all the theorems presented by Mattila and many others can be proved in a simple way which is demonstrated in the Lemmas 1 and 2and Propositions 1-3. The conclusion critically discusses some other issues of LPC+Ch Calculus, specially that no formal semantics for it is given.In the second paper the characterization of solvability of the relational equation RoX=T, where R, X, T are fuzzy relations, X the unknown one, and o the minimum-induced composition by Sanchez, is extended to compositions induced by more general products in the general value lattice. Moreover, the procedure also applies to systemsof equations. In the third publication common features in various fuzzy logicalsystems are investigated. It turns out that adjoint couples and residuated lattices are very often present, though not always explicitly expressed. Some minor new results are also proved.The fourth study concerns Novak's paper, in which Novak introduced first-order fuzzy logic and proved, among other things, the semantico-syntactical completeness of this logic. He also demonstrated that the algebra of his logic is a generalized residuated lattice. In proving that the examination of Novak's logic can be reduced to the examination of locally finite MV-algebras.In the fifth paper a multi-valued sentential logic with values of truth in an injective MV-algebra is introduced and the axiomatizability of this logic is proved. The paper developes some ideas of Goguen and generalizes the results of Pavelka on the unit interval. Our proof for the completeness is purely algebraic. A corollary of the Completeness Theorem is that fuzzy logic on the unit interval is semantically complete if, and only if the algebra of the valuesof truth is a complete MV-algebra. The Compactness Theorem holds in our well-defined fuzzy sentential logic, while the Deduction Theorem and the Finiteness Theorem do not. Because of its generality and good-behaviour, MV-valued logic can be regarded as a mathematical basis of fuzzy reasoning. The last paper is a continuation of the fifth study. The semantics and syntax of fuzzy predicate logic with values of truth in ana injective MV-algerba are introduced, and a list of universally valid sentences is established. The system is proved to be semanticallycomplete. This proof is based on an idea utilizing some elementary properties of injective MV-algebras and MV-homomorphisms, and is purely algebraic.

Predictions of the MCMI-III personality disorders from NEO-PI-R domains and facets: Comparison between American and Spanish samples

Este estudio ex post facto analiza las relaciones entre las dimensiones y facetas del NEO-PI-R y los 14 trastornos de personalidad del MCMI-III en una muestra no clínica española (N = 674). Se exploran las diferencias y similitudes con los resul- tados de Dyce y O’Connor en una muestra americana con los mismos instrumentos. Como se esperaba, los análisis factoriales de facetas reteniendo cinco factores mostraron un modelo de relaciones muy similar entre ambas muestras, con un coeficiente de la congruencia total de 0,92, y coeficientes de congruencia de factor aceptables, salvo para el factor Apertura (0,68). En consonancia con las predicciones de Widiger y Widiger et al. los porcentajes de correlaciones significativas estaban alrededor de 60% en ambas muestras, y la mayoría coincidían. El análisis de regresión múltiple con dimensiones también reveló un gran parecido entre los resultados americanos y españoles, Neuroticismo fue el predictor más relacionado con los trastornos de personalidad. Se encontraron diferencias en las regresiones por facetas, aunque la varianza explicada fue prácticamente la misma que en las dimensiones. Se discute la validez transcultural y el valor predictivo del NEO-PI-R sobre los trastornos de personalidad del MCMI-III, junto con las ventajas relativas de las facetas sobre las dimensiones.

Validez convergente y estructural del NEO-PI-R : baremos orientativos

El estudio que se presenta se diseñó para estudiar la validez convergen-te y de estructura del NEO-PI-R en una muestra amplia de universitarios y de la población general. Los resultados muestran una robusta estructura de cinco factores y buena validez convergente con los adjetivos bipolares de Goldberg. Se realiza un análisis comparativo de los resultados obtenidos en este estudio con los del estudio original americano y en el estudio normativo realizado en España. Se concluye que las medias de las cinco dimensiones son parecidas al comparar las muestras del estudio actual con el americano, pero muy diferentes respecto al estudio normativo español. Ello es probablemente debido a la naturaleza de las muestras empleadas en el estudio normativo español provenientes de selección de personal, inadecuadas para un estudio normativo. La procedencia de las muestras no afecta la estructura ni la fiabilidad del NEO-PI-R, pero si afecta los baremos obtenidos. A efectos de la interpretación del test en población sana española se proporcionan baremos en percentiles y notas T.

Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

The five and seven factors personality models: differences and similitude between the TCI-R, NEO-FFI-R and ZKPQ-50-CC

The present study tests the relationships between the three frequently used personality models evaluated by the Temperament Character Inventory-Revised (TCI-R), Neuroticism Extraversion Openness Five Factor Inventory – Revised (NEO-FFI-R) and Zuckerman-Kuhlman Personality Questionnaire-50- Cross-Cultural (ZKPQ-50-CC). The results were obtained with a sample of 928 volunteer subjects from the general population aged between 17 and 28 years old. Frequency distributions and alpha reliabilities with the three instruments were acceptable. Correlational and factorial analyses showed that several scales in the three instruments share an appreciable amount of common variance. Five factors emerged from principal components analysis. The first factor was integrated by A (Agreeableness), Co (Cooperativeness) and Agg-Host (Aggressiveness-Hostility), with secondary loadings in C (Conscientiousness) and SD (Self-directiveness) from other factors. The second factor was composed by N (Neuroticism), N-Anx (Neuroticism-Anxiety), HA (Harm Avoidance) and SD (Self-directiveness). The third factor was integrated by Sy (Sociability), E (Extraversion), RD (Reward Dependence), ImpSS (Impulsive Sensation Seeking) and NS (novelty Seeking). The fourth factor was integrated by Ps (Persistence), Act (Activity), and C, whereas the fifth and last factor was composed by O (Openness) and ST (Self- Transcendence). Confirmatory factor analyses indicate that the scales in each model are highly interrelated and define the specified latent dimension well. Similarities and differences between these three instruments are further discussed.

Adding similarity-based reasoning capabilities to a Horn fragment of possibilistic logic with fuzzy constants

PLFC is a first-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quantifiers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded unification among fuzzy constants. However, unification for precise object constants is classical. In order to use PLFC for similarity-based reasoning, in this paper we extend a Horn-rule sublogic of PLFC with similarity-based unification of object constants. The Horn-rule sublogic of PLFC we consider deals only with disjunctive fuzzy constants and it is equipped with a simple and efficient version of PLFC proof method. At the semantic level, it is extended by equipping each sort with a fuzzy similarity relation, and at the syntactic level, by fuzzily “enlarging” each non-fuzzy object constant in the antecedent of a Horn-rule by means of a fuzzy similarity relation.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

Adaptación para adolescentes de la versión española del NEO PI-R (JS NEO)

Este artículo presenta los primeros datos del desarrollo de la versión española para adolescentes, entre 12 y 17 años, del NEO PI-R (JS NEO). Noventa y dos de los 240 ítems fueron modificados con el fin de adaptar el vocabulario de los mismos a este grupo de edad. Las propiedades psicométricas del JS NEO han sido investigadas en una muestra de 2.505 adolescentes. Los resultados muestran cómo la estructura factorial encontrada con el NEO PI-R para adultos se replica en la versión junior. Las fiabilidades de consistencia interna y estabilidad temporal de las escalas fueron adecuadas en la mayor parte de los casos. Además, la correlación entre las escalas de las versiones para adultos (NEO PI-R) y adolescentes (JS NEO) muestran que la versión para adolescentes presenta una validez de constructo adecuada.

Dysfunction in endoplasmic reticulum-mitochondria crosstalk underlies SIGMAR1 loss of function mediated motor neuron degeneration.

Mutations in Sigma 1 receptor (SIGMAR1) have been previously identified in patients with amyotrophic lateral sclerosis and disruption of Sigmar1 in mouse leads to locomotor deficits. However, cellular mechanisms underlying motor phenotypes in human and mouse with disturbed SIGMAR1 function have not been described so far. Here we used a combination of in vivo and in vitro approaches to investigate the role of SIGMAR1 in motor neuron biology. Characterization of Sigmar1(-/-) mice revealed that affected animals display locomotor deficits associated with muscle weakness, axonal degeneration and motor neuron loss. Using primary motor neuron cultures, we observed that pharmacological or genetic inactivation of SIGMAR1 led to motor neuron axonal degeneration followed by cell death. Disruption of SIGMAR1 function in motor neurons disturbed endoplasmic reticulum-mitochondria contacts, affected intracellular calcium signalling and was accompanied by activation of endoplasmic reticulum stress and defects in mitochondrial dynamics and transport. These defects were not observed in cultured sensory neurons, highlighting the exacerbated sensitivity of motor neurons to SIGMAR1 function. Interestingly, the inhibition of mitochondrial fission was sufficient to induce mitochondria axonal transport defects as well as axonal degeneration similar to the changes observed after SIGMAR1 inactivation or loss. Intracellular calcium scavenging and endoplasmic reticulum stress inhibition were able to restore mitochondrial function and consequently prevent motor neuron degeneration. These results uncover the cellular mechanisms underlying motor neuron degeneration mediated by loss of SIGMAR1 function and provide therapeutically relevant insight into motor neuronal diseases.