Gross morphology and topography of the digestive apparatus in rheas (Rhea americana americana)

Rodrigues M.N., Oliveira G.B., Silva R.S.S, Tivane C.T., Albuquerque J.F.G., Miglino M.A. & Oliveira M.F. 2012. [Gross morphology and topography of the digestive apparatus in rheas (Rhea americana americana).] Macroscopia e topografia do aparelho digestorio de emas (Rhea americana americana). Pesquisa Veterinaria Brasileira 32(7):681-686. Departamento de Cirurgia, Faculdade de Medicina Veterinaria e Zootecnia, Universidade de Sao Paulo, Cidade Universitaria, Av. Prof. Dr. Orlando Marques de Paiva 87, Sao Paulo, SP 05508270, Brazil. E-mail: marcio_medvet@hotmail.com Rheas are birds belonging to the ratites group and, among ostriches and emus, are the largest birds currently alive. In this work we studied the macroscopic aspects of rheas' digestive tract in order to provide important information to a better understanding of these birds' eating habits as well their anatomy. Twenty young animals aging between two and six months from the Centre for Wild Animals Multiplication (Cemas, scientific breeding license form Ibama no.1478912) were used. After dissection it was observed that their tongue was small and presented a rhomboid form, being disposed on the oral cavity floor, and inserted in its base by a frenulum. The esophagus was a rectilinear tube with elastic aspect and longitudinal elastic fibers, without dilation, which gives it an absence of crop. The proventriculus presented a fusiform form and the gastric ventricle showed and slightly oval form when filled, and was internally coated with a thick gastric cuticle. The small intestine was composed of three distinct regions: duodenum, jejunum and ileum. The duodenum had a light gray color and showed a "U" curved shaped. The jejunum was dark green, long and composed of several short loops arranged above each other. The ileum had a gray color and was connected with the jejunum. In ventral line to the rectum and cloaca, the ileum extended cranially, dorsally to the ascending duodenum. The large intestine was composed of two caeca, one right and one left, and colon-rectum and ileum were continuous with the cloaca. The structures of the rhea digestive tract resemble those described in the literature regarding to its shape and topography, even though rhea's caeca are well developed and relatively long.

Strategie di personalizzazione della terapia di resincronizzazione cardiaca

Solo il 60% dei candidati alla resincronizzazione cardiaca risponde in termini di rimodellamento ventricolare inverso che è il più forte predittore di riduzione della mortalità e delle ospedalizzazioni. Due cause possibili della mancata risposta sono la programmazione del dispositivo e i limiti dell’ approccio transvenoso. Nel corso degli anni di dottorato ho effettuato tre studi per ridurre il numero di non responder. Il primo studio valuta il ritardo interventricolare. Al fine di ottimizzare le risorse e fornire un reale beneficio per il paziente ho ricercato la presenza di predittori di ritardo interventricolare diverso dal simultaneo, impostato nella programmazione di base. L'unico predittore è risultato essere l’ intervallo QRS> 160 ms, quindi ho proposto una flow chart per ottimizzare solo i pazienti che avranno nella programmazione ottimale un intervallo interventricolare non simultaneo. Il secondo lavoro valuta la fissazione attiva del ventricolo sinistro con stent. I dislocamenti, la soglia alta di stimolazione del miocardio e la stimolazione del nervo frenico sono tre problematiche che limitano la stimolazione biventricolare. Abbiamo analizzato più di 200 angiografie per vedere le condizioni anatomiche predisponenti la dislocazione del catetere. Prospetticamente abbiamo deciso di utilizzare uno stent per fissare attivamente il catetere ventricolare sinistro in tutti i pazienti che presentavano le caratteristiche anatomiche favorenti la dislocazione. Non ci sono più state dislocazioni, c’è stata una migliore risposta in termini di rimodellamento ventricolare inverso e non ci sono state modifiche dei parametri elettrici del catetere. Il terzo lavoro ha valutato sicurezza ed efficacia della stimolazione endoventricolare sinistra. Abbiamo impiantato 26 pazienti giudicati non responder alla terapia di resincronizzazione cardiaca. La procedura è risultata sicura, il rischio di complicanze è simile alla stimolazione biventricolare classica, ed efficace nell’arrestare la disfunzione ventricolare sinistra e / o migliorare gli effetti clinici in un follow-up medio.

Studio anatomico dei muscoli della spalla e del braccio in Pernis apivorus, Accipiter gentilis ed Accipiter nisus

Recentemente, vari ricercatori si sono concentrati sulle proprietà funzionali dei muscoli, sulla meccanica e sulla cinematica legata al volo, ma senza la possibilità di consultare un’adeguata letteratura poiché assente o incompleta. Si è quindi ritenuto utile studiare la miologia della regione della spalla e del braccio di specie non in precedenza esaminate e che mostrassero differenti stili di volo, al fine di creare una base di informazioni per futuri studi funzionali. Tutte le specie prese in esame sono membri della famiglia degli Accipitridae e nello specifico si sono selezionati: il Falco pecchiaiolo (Pernis apivorus Linnaeus, 1758), l’Astore comune (Accipiter gentilis Linnaeus, 1758) e lo Sparviero eurasiatico (Accipiter nisus Linnaeus, 1758). Questi animali attuano stili di volo differenti e sono stati pertanto scelti per capire se diverse performance di volo potessero indurre una differenziazione dell’apparato muscolare. La comparazione dei dati raccolti durante questo studio con quelli presenti in letteratura in altre specie aviarie ha evidenziato che, mentre alcuni muscoli non sembrano andare incontro a grandi modificazioni nei rapaci, altri invece presentano una grande eterogeneità. In particolare, grazie alle caratteristiche dei diversi muscoli, si è potuto raggruppare questi ultimi in base a possibili funzioni comuni: a) muscoli che concorrono a stabilizzare l’ala rispetto al tronco e che assorbono le forze generate durante il volo; b) muscoli con possibile ruolo nel controllo della rotazione dell’omero; c) muscoli con possibile funzione propriocettiva. Il presente studio ha inoltre evidenziato, nei muscoli esaminati, alcune similitudini e molteplici peculiarità anatomiche non precedentemente segnalate in letteratura. Si ritiene che questo studio macroscopico possa rappresentare un punto di partenza per futuri studi microscopici o elettrofisiologici, a dimostrazione dell’importanza della dissezione quale primo strumento di indagine.

Aortic arch morphometry in living humans

Anatomical features of the aortic arch such as its steepness, the take-off angles and the distances between its supra-aortic branches can influence the feasibility and difficulty of interventional and/or surgical maneuvers. These anatomical characteristics were assessed by means of 3D multiplanar reconstruction of thoracic angio-computed tomography scans of 92 living patients (79 males, 13 females, mean age 69.4 ± 9.9 years) carried out for various indications (gross pathology of the thoracic aorta excluded). There was a significant variation of all measured parameters between the subjects - a standard aortic arch (i.e. with all measured parameters within 2 SD) does not seem to exist. There were no significant differences between genders but some of the parameters correlated significantly to age.

Robotics in ear, nose and throat (ENT) surgery

The three main classes of robotics in ear, nose and throat (ENT) surgery (telemanipulation, image-guided functional servoing, and computer numerical control) are discussed and important examples of applications are described to show both technological and clinical developments. As access to many anatomical features of the head requires very small and compact tools to accurately perform procedures, examples are give in ear surgery where manipulation of the minute ossicles requires fine, dexterous movements.

High Resolution Vascular Imaging of the Rat Spine using Liposomal Blood Pool MR Agent

High resolution, vascular magnetic resonance imaging of the spine region in small animals poses several challenges. The small anatomical features, extravascular diffusion, and the low signal-to-noise ratio limit the use of conventional contrast agents. We hypothesize that a long circulating, intravascular liposomal-encapsulated MR contrast agent (liposomal-Gd) would facilitate visualization of small anatomical features of the perispinal vasculature not visible with conventional contrast agent (Gd-DTPA).

Motile response patterns and ultrastructural observations of the isolated outer hair cell

The tonotopic organization of the mammalian cochlea is accompanied by structural gradients which include the somatic lengths of outer hair cells (OHCs). These receptors rest upon the vibrating portion of the basilar membrane and have been reported to exhibit motile responses following chemical and electrical stimulation. These movements were examined in detail in this dissertation. It was found that isolated OHCs cultured in vitro respond to chemical depolarization with slow tonic movements, and to electrical waveforms with bi-directional, frequency following movements extending from DC to at least 10 kHz.^ Slow contractions were also elicited following electrical stimulation, bath incubation in carbachol (a cholinergic agonist), and increases in extracellular K+ concentration as little as 50 mM.^ Isolated OHCs display anatomical features which are remarkable when contrasted with those prepared from intact receptor organs. A complex structure located between the cuticular plate and the nuclear membrane was consistently observed and was examined by serial cross-sections which revealed a network of non-membrane bound densities. This corresponded to a granular complex seen at the light microscope level. The complex was composed of dense regions of organelles, striated structures embedded within the core, and a circumferential network of microtubules residing in the peri-nuclear portion of the cell. In cells which had lost their nuclear attachment to the terminal synaptic body, the granular complex could be made to contract without effecting any change in cellular length, implying that the complex may be the driving force behind certain aspects of the motile response.^ Most cells displayed movements which revealed asymmetries analogous to those reported for OHC receptor potentials in vivo. The contraction phase (for longer cells) was shown to have a small time constant (approximately 400 microseconds) and saturated with limited displacements. The expansion phase had time constants as large as 1.3 milliseconds but yielded displacements as much as 60 percent larger than those seen for contractions.^ Additional waveform characteristics seen in the in vivo response could be emulated either by biasing the cell's resting length with either direct current, triggering contractions via large electrical displacements, or incubation with depolarizing compounds.^ Alternatively, short (20-30 um) cells revealed more linear response characteristics to the probe stimulus. Partial saturation was achieved and revealed a DC component which was opposite in polarity to that seen in longer cells. (Abstract shortened with permission of author.) ^

Senile scleral plaques imaged with enhanced depth optical coherence tomography

PURPOSE Senile scleral plaques (SSP) are sharply demarcated greyish areas located just anterior to the insertions of the horizontal rectus muscles and thus are frequently encountered during transscleral intravitreal injections. The aim of this study was to characterize SSP using enhanced depth imaging spectral domain anterior segment optical coherence tomography (OCT) in a cohort of patients attending intravitreal injection clinics. METHODS Prospective cross-sectional study of 380 patients attending the clinic for intravitreal injections at the Department of Ophthalmology at the Bern University Hospital. Thirty-two patients with SSP were identified and the anatomical features were assessed using anterior segment OCT. RESULTS In our patient cohort, we found a SSP prevalence of 8.2%. Senile scleral plaques were easily identifiable using anterior segment OCT and were found at the insertion sites of the horizontal recti muscles. The mean horizontal diameter was 2.2 mm (±760 μm SD), the mean vertical diameter was 3.3 mm (±144 μm SD), and the average surface area was 5.3 mm(2) (±0.4 mm(2) SD). The mean senile scleral plaque thickness was 0.6 mm (±149 μm SD). The mean distance from the limbus was 2.24 mm for nasally located SSP and 3.22 mm for temporally located SSP. CONCLUSION SSP are frequently encountered during intravitreal injections as they are located just anterior to the insertion sites of the horizontal recti muscles. Because the scleral stroma is rarefied and due to calcifications within SSP, these areas should be avoided when performing multiple intravitreal injections as this may result in rupture of the sclera.

A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes

Standard stereotaxic reference systems play a key role in human brain studies. Stereotaxic coordinate systems have also been developed for experimental animals including non-human primates, dogs, and rodents. However, they are lacking for other species being relevant in experimental neuroscience including sheep. Here, we present a spatial, unbiased ovine brain template with tissue probability maps (TPM) that offer a detailed stereotaxic reference frame for anatomical features and localization of brain areas, thereby enabling inter-individual and cross-study comparability. Three-dimensional data sets from healthy adult Merino sheep (Ovis orientalis aries, 12 ewes and 26 neutered rams) were acquired on a 1.5 T Philips MRI using a T1w sequence. Data were averaged by linear and non-linear registration algorithms. Moreover, animals were subjected to detailed brain volume analysis including examinations with respect to body weight (BW), age, and sex. The created T1w brain template provides an appropriate population-averaged ovine brain anatomy in a spatial standard coordinate system. Additionally, TPM for gray (GM) and white (WM) matter as well as cerebrospinal fluid (CSF) classification enabled automatic prior-based tissue segmentation using statistical parametric mapping (SPM). Overall, a positive correlation of GM volume and BW explained about 15% of the variance of GM while a positive correlation between WM and age was found. Absolute tissue volume differences were not detected, indeed ewes showed significantly more GM per bodyweight as compared to neutered rams. The created framework including spatial brain template and TPM represent a useful tool for unbiased automatic image preprocessing and morphological characterization in sheep. Therefore, the reported results may serve as a starting point for further experimental and/or translational research aiming at in vivo analysis in this species.

Central and peripheral defects in motor units of the diaphragm of spinal muscular atrophy mice.

Spinal muscular atrophy (SMA) is characterized by motoneuron loss and muscle weakness. However, the structural and functional deficits that lead to the impairment of the neuromuscular system remain poorly defined. By electron microscopy, we previously found that neuromuscular junctions (NMJs) and muscle fibres of the diaphragm are among the earliest affected structures in the severe mouse SMA model. Because of certain anatomical features, i.e. its thinness and its innervation from the cervical segments of the spinal cord, the diaphragm is particularly suitable to characterize both central and peripheral events. Here we show by immunohistochemistry that, at postnatal day 3, the cervical motoneurons of SMA mice receive less stimulatory synaptic inputs. Moreover, their mitochondria become less elongated which might represent an early stage of degeneration. The NMJs of the diaphragm of SMA mice show a loss of synaptic vesicles and active zones. Moreover, the partly innervated endplates lack S100 positive perisynaptic Schwann cells (PSCs). We also demonstrate the feasibility of comparing the proteomic composition between diaphragm regions enriched and poor in NMJs. By this approach we have identified two proteins that are significantly upregulated only in the NMJ-specific regions of SMA mice. These are apoptosis inducing factor 1 (AIFM1), a mitochondrial flavoprotein that initiates apoptosis in a caspase-independent pathway, and four and a half Lim domain protein 1 (FHL1), a regulator of skeletal muscle mass that has been implicated in several myopathies.

Morphological descriptions from the recent bivalve of the genus Calyptogena (Vesicomyidae)

The genus Calyptogena (Bivalvia: Vesicomyidae) comprises highly specialized bivalves living in symbiosis with sulphur-oxidizing bacteria in reducing habitats. In this study, the genus is revised using shell and anatomical features. The work is based on type material, as well as on the extensive collection of vesicomyids obtained during twelve expeditions to the Pacific and Indian Oceans. Nine Recent species are ascribed to the genus Calyptogena, four of which are new: C. pacifica Dall, 1891, C. fausta Okutani, Fujikura & Hashimoto, 1993, C. rectimargo Scarlato, 1981, C. valdiviae (Thiele & Jaeckel, 1931), C. gallardoi Sellanes & Krylova, 2005, C. goffrediae n. sp., C. starobogatovi n. sp., C. makranensis n. sp. and C. costaricana n. sp. The characteristic features of Calyptogena are: shell up to 90 mm in length, elongate-elliptical or elongate; presence of escutcheon; presence of broad posterior ramus (3b) of right subumbonal cardinal tooth as well as right posterior nymphal ridge; absence of pallial sinus as a result of attachment of intersiphonal septal retractor immediately adjacent to ventral surface of posterior adductor; absence of processes on inner vulva of inhalant siphon; presence of inner demibranch only, with descending and ascending lamellae with interlamellar septa not divided into separate tubes. The most closely related taxa to Calyptogena are probably the genus Isorropodon Sturany, 1896, and the group of species represented by 'Calyptogena' phaseoliformis Métivier, Okutani & Ohta, 1986. These groups have several characters in common, namely absence of pallial sinus, presence of single inner pair of demibranchs and absence of processes on inner vulva of inhalant siphon. The worldwide distribution of the genus Calyptogena suggests that methane seeps at continental margins are the major dispersal routes and that speciation was promoted by geographical isolation. Recent species diversity and fossil records indicate that the genus originated in the Pacific Ocean. Sufficient data to discuss the distribution at species level exist only for C. pacifica, which has a remarkably narrow bathymetric range. Published studies on the physiology of C. pacifica suggest that adaptation to a specific geochemical environment has led to coexisting vesicomyid genera. The bacteria-containing gill of C. pacifica and other Calyptogena species is one of the most specialized in the family Vesicomyidae and may reflect these ecological adaptations.

Intra-annual patterns of tracheid size in the Mediterranean tree Juniperus thurifera as an indicator of seasonal water stress

Because climate can affect xylem cell anatomy, series of intra-annual cell anatomical features have the potential to retrospectively supply seasonal climatic information. In this study, we explored the ability to extract information about water stress conditions from tracheid features of the Mediterranean conifer Juniperus thurifera L. Tracheidograms of four climatic years from two drought-sensitive sites in Spain were compared to evaluate whether it is possible to link intra-annual cell size patterns to seasonal climatic conditions. Results indicated site-specific anatomical adjustment such as smaller and thicker tracheids at the dryer site but also showed a strong climatic imprint on the intra-annual pattern of tracheid size. Site differences in cell size reflected expected structural adjustments against cavitation failures. Differences between intra-annual patterns, however, indicated a response to seasonal changes in water availability whereby cells formed under drought conditions were smaller and thicker, and vice versa. This relationship was more manifest and stable at the dryer site

Contributions to Bayesian network learning with applications to neuroscience

Neuronal morphology is a key feature in the study of brain circuits, as it is highly related to information processing and functional identification. Neuronal morphology affects the process of integration of inputs from other neurons and determines the neurons which receive the output of the neurons. Different parts of the neurons can operate semi-independently according to the spatial location of the synaptic connections. As a result, there is considerable interest in the analysis of the microanatomy of nervous cells since it constitutes an excellent tool for better understanding cortical function. However, the morphologies, molecular features and electrophysiological properties of neuronal cells are extremely variable. Except for some special cases, this variability makes it hard to find a set of features that unambiguously define a neuronal type. In addition, there are distinct types of neurons in particular regions of the brain. This morphological variability makes the analysis and modeling of neuronal morphology a challenge. Uncertainty is a key feature in many complex real-world problems. Probability theory provides a framework for modeling and reasoning with uncertainty. Probabilistic graphical models combine statistical theory and graph theory to provide a tool for managing domains with uncertainty. In particular, we focus on Bayesian networks, the most commonly used probabilistic graphical model. In this dissertation, we design new methods for learning Bayesian networks and apply them to the problem of modeling and analyzing morphological data from neurons. The morphology of a neuron can be quantified using a number of measurements, e.g., the length of the dendrites and the axon, the number of bifurcations, the direction of the dendrites and the axon, etc. These measurements can be modeled as discrete or continuous data. The continuous data can be linear (e.g., the length or the width of a dendrite) or directional (e.g., the direction of the axon). These data may follow complex probability distributions and may not fit any known parametric distribution. Modeling this kind of problems using hybrid Bayesian networks with discrete, linear and directional variables poses a number of challenges regarding learning from data, inference, etc. In this dissertation, we propose a method for modeling and simulating basal dendritic trees from pyramidal neurons using Bayesian networks to capture the interactions between the variables in the problem domain. A complete set of variables is measured from the dendrites, and a learning algorithm is applied to find the structure and estimate the parameters of the probability distributions included in the Bayesian networks. Then, a simulation algorithm is used to build the virtual dendrites by sampling values from the Bayesian networks, and a thorough evaluation is performed to show the model’s ability to generate realistic dendrites. In this first approach, the variables are discretized so that discrete Bayesian networks can be learned and simulated. Then, we address the problem of learning hybrid Bayesian networks with different kinds of variables. Mixtures of polynomials have been proposed as a way of representing probability densities in hybrid Bayesian networks. We present a method for learning mixtures of polynomials approximations of one-dimensional, multidimensional and conditional probability densities from data. The method is based on basis spline interpolation, where a density is approximated as a linear combination of basis splines. The proposed algorithms are evaluated using artificial datasets. We also use the proposed methods as a non-parametric density estimation technique in Bayesian network classifiers. Next, we address the problem of including directional data in Bayesian networks. These data have some special properties that rule out the use of classical statistics. Therefore, different distributions and statistics, such as the univariate von Mises and the multivariate von Mises–Fisher distributions, should be used to deal with this kind of information. In particular, we extend the naive Bayes classifier to the case where the conditional probability distributions of the predictive variables given the class follow either of these distributions. We consider the simple scenario, where only directional predictive variables are used, and the hybrid case, where discrete, Gaussian and directional distributions are mixed. The classifier decision functions and their decision surfaces are studied at length. Artificial examples are used to illustrate the behavior of the classifiers. The proposed classifiers are empirically evaluated over real datasets. We also study the problem of interneuron classification. An extensive group of experts is asked to classify a set of neurons according to their most prominent anatomical features. A web application is developed to retrieve the experts’ classifications. We compute agreement measures to analyze the consensus between the experts when classifying the neurons. Using Bayesian networks and clustering algorithms on the resulting data, we investigate the suitability of the anatomical terms and neuron types commonly used in the literature. Additionally, we apply supervised learning approaches to automatically classify interneurons using the values of their morphological measurements. Then, a methodology for building a model which captures the opinions of all the experts is presented. First, one Bayesian network is learned for each expert, and we propose an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts is induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts is built. A thorough analysis of the consensus model identifies different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types can be defined by performing inference in the Bayesian multinet. These findings are used to validate the model and to gain some insights into neuron morphology. Finally, we study a classification problem where the true class label of the training instances is not known. Instead, a set of class labels is available for each instance. This is inspired by the neuron classification problem, where a group of experts is asked to individually provide a class label for each instance. We propose a novel approach for learning Bayesian networks using count vectors which represent the number of experts who selected each class label for each instance. These Bayesian networks are evaluated using artificial datasets from supervised learning problems. Resumen La morfología neuronal es una característica clave en el estudio de los circuitos cerebrales, ya que está altamente relacionada con el procesado de información y con los roles funcionales. La morfología neuronal afecta al proceso de integración de las señales de entrada y determina las neuronas que reciben las salidas de otras neuronas. Las diferentes partes de la neurona pueden operar de forma semi-independiente de acuerdo a la localización espacial de las conexiones sinápticas. Por tanto, existe un interés considerable en el análisis de la microanatomía de las células nerviosas, ya que constituye una excelente herramienta para comprender mejor el funcionamiento de la corteza cerebral. Sin embargo, las propiedades morfológicas, moleculares y electrofisiológicas de las células neuronales son extremadamente variables. Excepto en algunos casos especiales, esta variabilidad morfológica dificulta la definición de un conjunto de características que distingan claramente un tipo neuronal. Además, existen diferentes tipos de neuronas en regiones particulares del cerebro. La variabilidad neuronal hace que el análisis y el modelado de la morfología neuronal sean un importante reto científico. La incertidumbre es una propiedad clave en muchos problemas reales. La teoría de la probabilidad proporciona un marco para modelar y razonar bajo incertidumbre. Los modelos gráficos probabilísticos combinan la teoría estadística y la teoría de grafos con el objetivo de proporcionar una herramienta con la que trabajar bajo incertidumbre. En particular, nos centraremos en las redes bayesianas, el modelo más utilizado dentro de los modelos gráficos probabilísticos. En esta tesis hemos diseñado nuevos métodos para aprender redes bayesianas, inspirados por y aplicados al problema del modelado y análisis de datos morfológicos de neuronas. La morfología de una neurona puede ser cuantificada usando una serie de medidas, por ejemplo, la longitud de las dendritas y el axón, el número de bifurcaciones, la dirección de las dendritas y el axón, etc. Estas medidas pueden ser modeladas como datos continuos o discretos. A su vez, los datos continuos pueden ser lineales (por ejemplo, la longitud o la anchura de una dendrita) o direccionales (por ejemplo, la dirección del axón). Estos datos pueden llegar a seguir distribuciones de probabilidad muy complejas y pueden no ajustarse a ninguna distribución paramétrica conocida. El modelado de este tipo de problemas con redes bayesianas híbridas incluyendo variables discretas, lineales y direccionales presenta una serie de retos en relación al aprendizaje a partir de datos, la inferencia, etc. En esta tesis se propone un método para modelar y simular árboles dendríticos basales de neuronas piramidales usando redes bayesianas para capturar las interacciones entre las variables del problema. Para ello, se mide un amplio conjunto de variables de las dendritas y se aplica un algoritmo de aprendizaje con el que se aprende la estructura y se estiman los parámetros de las distribuciones de probabilidad que constituyen las redes bayesianas. Después, se usa un algoritmo de simulación para construir dendritas virtuales mediante el muestreo de valores de las redes bayesianas. Finalmente, se lleva a cabo una profunda evaluaci ón para verificar la capacidad del modelo a la hora de generar dendritas realistas. En esta primera aproximación, las variables fueron discretizadas para poder aprender y muestrear las redes bayesianas. A continuación, se aborda el problema del aprendizaje de redes bayesianas con diferentes tipos de variables. Las mixturas de polinomios constituyen un método para representar densidades de probabilidad en redes bayesianas híbridas. Presentamos un método para aprender aproximaciones de densidades unidimensionales, multidimensionales y condicionales a partir de datos utilizando mixturas de polinomios. El método se basa en interpolación con splines, que aproxima una densidad como una combinación lineal de splines. Los algoritmos propuestos se evalúan utilizando bases de datos artificiales. Además, las mixturas de polinomios son utilizadas como un método no paramétrico de estimación de densidades para clasificadores basados en redes bayesianas. Después, se estudia el problema de incluir información direccional en redes bayesianas. Este tipo de datos presenta una serie de características especiales que impiden el uso de las técnicas estadísticas clásicas. Por ello, para manejar este tipo de información se deben usar estadísticos y distribuciones de probabilidad específicos, como la distribución univariante von Mises y la distribución multivariante von Mises–Fisher. En concreto, en esta tesis extendemos el clasificador naive Bayes al caso en el que las distribuciones de probabilidad condicionada de las variables predictoras dada la clase siguen alguna de estas distribuciones. Se estudia el caso base, en el que sólo se utilizan variables direccionales, y el caso híbrido, en el que variables discretas, lineales y direccionales aparecen mezcladas. También se estudian los clasificadores desde un punto de vista teórico, derivando sus funciones de decisión y las superficies de decisión asociadas. El comportamiento de los clasificadores se ilustra utilizando bases de datos artificiales. Además, los clasificadores son evaluados empíricamente utilizando bases de datos reales. También se estudia el problema de la clasificación de interneuronas. Desarrollamos una aplicación web que permite a un grupo de expertos clasificar un conjunto de neuronas de acuerdo a sus características morfológicas más destacadas. Se utilizan medidas de concordancia para analizar el consenso entre los expertos a la hora de clasificar las neuronas. Se investiga la idoneidad de los términos anatómicos y de los tipos neuronales utilizados frecuentemente en la literatura a través del análisis de redes bayesianas y la aplicación de algoritmos de clustering. Además, se aplican técnicas de aprendizaje supervisado con el objetivo de clasificar de forma automática las interneuronas a partir de sus valores morfológicos. A continuación, se presenta una metodología para construir un modelo que captura las opiniones de todos los expertos. Primero, se genera una red bayesiana para cada experto y se propone un algoritmo para agrupar las redes bayesianas que se corresponden con expertos con comportamientos similares. Después, se induce una red bayesiana que modela la opinión de cada grupo de expertos. Por último, se construye una multired bayesiana que modela las opiniones del conjunto completo de expertos. El análisis del modelo consensuado permite identificar diferentes comportamientos entre los expertos a la hora de clasificar las neuronas. Además, permite extraer un conjunto de características morfológicas relevantes para cada uno de los tipos neuronales mediante inferencia con la multired bayesiana. Estos descubrimientos se utilizan para validar el modelo y constituyen información relevante acerca de la morfología neuronal. Por último, se estudia un problema de clasificación en el que la etiqueta de clase de los datos de entrenamiento es incierta. En cambio, disponemos de un conjunto de etiquetas para cada instancia. Este problema está inspirado en el problema de la clasificación de neuronas, en el que un grupo de expertos proporciona una etiqueta de clase para cada instancia de manera individual. Se propone un método para aprender redes bayesianas utilizando vectores de cuentas, que representan el número de expertos que seleccionan cada etiqueta de clase para cada instancia. Estas redes bayesianas se evalúan utilizando bases de datos artificiales de problemas de aprendizaje supervisado.

Anatomía comparada de la madera de Cupressaceae y su correspondencia con los estudios de filogenia

La familia Cupressaceae incluye un total de 133 especies agrupadas en 30 géneros, 17 de los cuales son monospecíficos. Esta familia se encuentra representada en todos los continentes salvo en la Antártida. Sus especies se distribuyen en distintas regiones climáticas, y en altitudes que varían desde el nivel del mar hasta los 5.000 m. La falta de descripción anatómica de muchos de los géneros y especies de Cupressaceae es notable, así como la contradicción que aparece entre distintas investigaciones sobre las características anatómicas de la madera descritas para cada especie. Este estudio describe la anatomía de la madera de Cupressaceae y analiza las características que podrían representar sinapomorfías de los clados delimitados en los estudios filogenéticos. Siguiendo los métodos tradicionales de preparación y descripción de la madera a nivel microscópico, se ha estudiado la madera de 113 especies de los 30 géneros de Cupressaceae. Para ello se han empleado muestras de madera de origen trazable, procedentes de colecciones de madera de distintas instituciones internacionales. Se ha empleado una robusta filogenia molecular para la reconstrucción de los caracteres ancestrales. La anatomía de la madera de los 30 géneros de Cupressaceae, pone de manifiesto la gran homogeneidad de la familia, caracterizada por la presencia de traqueidas axiales sin engrosamientos helicoidales, parénquima radial con paredes horizontales lisas, punteaduras del campo de cruce de tipo cupresoide y la carencia de canales resiníferos fisiológicos. Además, todos presentan parénquima axial (salvo Neocallitropsis, Thuja y Xanthocyparis), punteaduras radiales areoladas con toro definido (salvo Thuja y Thujopsis), siendo habitual la presencia de punteaduras areoladas en las paredes tangenciales de la madera tardía, y verrugosidades en la cara interna de las traqueidas (salvo Ca. macleayana, Libocedrus, Papuacedrus y Neocallitropsis). Los radios leñosos son homogéneos y están compuestos de parénquima radial (con la presencia de traqueidas radiales en algunas especies de Cupressus, Sequoia, Thujopsis y X. nootkatensis) con paredes finales lisas o lisas y noduladas (exclusivamente noduladas en Cal. macrolepis, C. bakeri y en la mayoría de especies de Juniperus), y el rango de altura de los radios leñosos se encuentra entre 5 y 15 células. Se consideran posibles sinapomorfismos de Cupressaceae la presencia de verrugosidades en la cara interna de las traqueidas, la presencia de traqueidas axiales sin engrosamientos helicoidales, la presencia de parénquima axial, la presencia de radios leñosos homogéneos (compuestos únicamente de parénquima radial), la tipología de las paredes horizontales del parénquima radial, las punteaduras del campo de cruce de tipo cupresoide y la ausencia de canales resiníferos fisiológicos, pero lo que realmente diferencia a este grupo de coníferas es la simultaneidad de todos estos caracteres en sus maderas. Como sinapomorfías específicas por clados se proponen: la ausencia de toro definido y muescas en el borde de las punteaduras en Thuja-Thujopsis, la existencia de extensiones de toro en Diselma-Fitzroya-Widdringtonia; la presencia de engrosamientos callitroides en Callitris-Actinostrobus; la presencia de espacios intercelulares y las muescas en el borde de las punteaduras en el clado formado por el género Juniperus y las especies de Cupressus en la región oriental; la presencia de paredes finales del parénquima radial tanto lisas como noduladas en los clados formados por el género Xanthocyparis y las especies de Cupressus en la región occidental y en Fitzroya-Diselma; y por último, la presencia de punteaduras del campo de cruce de tipo taxodioide en los clados taxodioid y sequoioid. ABSTRACT The Cupressaceae family comprises 133 species grouped into 30 genera, 17 of which are monotypic. The family is represented in all continents except Antarctica. Its species are distributed in various climate zones and at altitudes from sea level to 5,000 m. There is a considerable lack of anatomical descriptions for many genera and species of Cupressaceae and much contradiction between studies about the wood anatomical features described for each species. This study describes the wood anatomy of Cupressaceae and analyses the features that could represent synapomorphies of the clades recovered in phylogenetic studies. Following the traditional methods of preparation and description of wood at microscopic level, a study was made of the wood of 113 species of the 30 Cupressaceae genera. The study samples had traceable origins and came from wood collections held at various international institutions. A robust molecular phylogeny was used for ancestral state reconstruction. The wood anatomy of the 30 genera of the Cupressaceae shows the high homogeneity of the family, which is characterised by the presence of axial tracheids without helical thickenings, smooth horizontal walls of ray parenchyma cells, cupressoid cross-field pits, and the absence of physiological resin canals. In addition, they all have axial parenchyma (except Neocallitropsis, Thuja and Xanthocyparis), a warty layer on the inner wall of the tracheids (except Ca. macleayana, Libocedrus, Papuacedrus and Neocallitropsis) and tracheid pitting in radial walls with a well defined torus (except Thuja and Thujopsis); tracheid pitting in the tangential walls of the latewood is common. Rays are homogeneous and are composed of ray parenchyma (with the presence of ray tracheids in some species of Cupressus, Sequoia, Thujopsis and X. nootkatensis), with smooth end walls or both smooth and nodular end walls (exclusively nodular in Cal. macrolepis, C. bakeri and most Juniperus species), and ray height range is 5 to 15 cells. Possible synapomorphies of Cupressaceae are the presence of a warty layer on the inner layer of the tracheids, axial tracheids without helical thickenings, the presence of axial parenchyma, homogeneous rays (composed exclusively of ray parenchyma), the typology of the horizontal walls of ray parenchyma cells, cupressoid cross-field pits and the absence of physiological resin canals, but what truly differentiates this group of softwoods is the co-occurrence of all these features in their wood. The following are proposed as clade-specific synapomorphies: absence of a well-defined torus and presence of pits with notched borders in Thuja-Thujopsis, torus extensions in Diselma-Fitzroya-Widdringtonia; callitroid thickenings in Callitris-Actinostrobus; intercellular spaces and pits with notched borders in the clade formed by the genus Juniperus and the species of Cupressus in the eastern region; smooth and nodular ray parenchyma end walls in the clades formed by the genus Xanthocyparis and the species of Cupressus in the western region and in Fitzroya-Diselma, and taxodioid cross-field pits in the taxodioid and sequoioid clades.

Quantitative methods in neuropathology

The last decade has seen a considerable increase in the application of quantitative methods in the study of histological sections of brain tissue and especially in the study of neurodegenerative disease. These disorders are characterised by the deposition and aggregation of abnormal or misfolded proteins in the form of extracellular protein deposits such as senile plaques (SP) and intracellular inclusions such as neurofibrillary tangles (NFT). Quantification of brain lesions and studying the relationships between lesions and normal anatomical features of the brain, including neurons, glial cells, and blood vessels, has become an important method of elucidating disease pathogenesis. This review describes methods for quantifying the abundance of a histological feature such as density, frequency, and 'load' and the sampling methods by which quantitative measures can be obtained including plot/quadrat sampling, transect sampling, and the point-quarter method. In addition, methods for determining the spatial pattern of a histological feature, i.e., whether the feature is distributed at random, regularly, or is aggregated into clusters, are described. These methods include the use of the Poisson and binomial distributions, pattern analysis by regression, Fourier analysis, and methods based on mapped point patterns. Finally, the statistical methods available for studying the degree of spatial correlation between pathological lesions and neurons, glial cells, and blood vessels are described.