Morphological Functions to Quantify Three-Dimensional Tomograms of Macropore Structure in a Vineyard Soil with Two Different Management Regimes

Soil tomography and morphological functions built over Minkowski functionals were used to describe the impact on pore structure of two soil management practices in a Mediterranean vineyard. Soil structure controls important physical and biological processes in soil–plant–microbial systems. Those processes are dominated by the geometry of soil pore structure, and a correct model of this geometry is critical for understanding them. Soil tomography has been shown to provide rich three-dimensional digital information on soil pore geometry. Recently, mathematical morphological techniques have been proposed as powerful tools to analyze and quantify the geometrical features of porous media. Minkowski functionals and morphological functions built over Minkowski functionals provide computationally efficient means to measure four fundamental geometrical features of three-dimensional geometrical objects, that is, volume, boundary surface, mean boundary surface curvature, and connectivity. We used the threshold and the dilation and erosion of three-dimensional images to generate morphological functions and explore the evolution of Minkowski functionals as the threshold and as the degree of dilation and erosion changes. We analyzed the three-dimensional geometry of soil pore space with X-ray computed tomography (CT) of intact soil columns from a Spanish Mediterranean vineyard by using two different management practices (conventional tillage versus permanent cover crop of resident vegetation). Our results suggested that morphological functions built over Minkowski functionals provide promising tools to characterize soil macropore structure and that the evolution of morphological features with dilation and erosion is more informative as an indicator of structure than moving threshold for both soil managements studied.

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

Parallel sets and morphological measurements of CT images of soil pore structure in a vineyard

Important physical and biological processes in soil-plant-microbial systems are dominated by the geometry of soil pore space, and a correct model of this geometry is critical for understanding them. We analyze the geometry of soil pore space with the X-ray computed tomography (CT) of intact soil columns. We present here some preliminary results of our investigation on Minkowski functionals of parallel sets to characterize soil structure. We also show how the evolution of Minkowski morphological measurements of parallel sets may help to characterize the influence of conventional tillage and permanent cover crop of resident vegetation on soil structure in a Spanish Mediterranean vineyard.

Coupled Nonlinear Ginzburg-Landau and Mechanics Model for Martensitic Transformations in Polycrystals

Las transformaciones martensíticas (MT) se definen como un cambio en la estructura del cristal para formar una fase coherente o estructuras de dominio multivariante, a partir de la fase inicial con la misma composición, debido a pequeños intercambios o movimientos atómicos cooperativos. En el siglo pasado se han descubierto MT en diferentes materiales partiendo desde los aceros hasta las aleaciones con memoria de forma, materiales cerámicos y materiales inteligentes. Todos muestran propiedades destacables como alta resistencia mecánica, memoria de forma, efectos de superelasticidad o funcionalidades ferroicas como la piezoelectricidad, electro y magneto-estricción etc. Varios modelos/teorías se han desarrollado en sinergia con el desarrollo de la física del estado sólido para entender por qué las MT generan microstructuras muy variadas y ricas que muestran propiedades muy interesantes. Entre las teorías mejor aceptadas se encuentra la Teoría Fenomenológica de la Cristalografía Martensítica (PTMC, por sus siglas en inglés) que predice el plano de hábito y las relaciones de orientación entre la austenita y la martensita. La reinterpretación de la teoría PTMC en un entorno de mecánica del continuo (CM-PTMC) explica la formación de los dominios de estructuras multivariantes, mientras que la teoría de Landau con dinámica de inercia desentraña los mecanismos físicos de los precursores y otros comportamientos dinámicos. La dinámica de red cristalina desvela la reducción de la dureza acústica de las ondas de tensión de red que da lugar a transformaciones débiles de primer orden en el desplazamiento. A pesar de las diferencias entre las teorías estáticas y dinámicas dado su origen en diversas ramas de la física (por ejemplo mecánica continua o dinámica de la red cristalina), estas teorías deben estar inherentemente conectadas entre sí y mostrar ciertos elementos en común en una perspectiva unificada de la física. No obstante las conexiones físicas y diferencias entre las teorías/modelos no se han tratado hasta la fecha, aun siendo de importancia crítica para la mejora de modelos de MT y para el desarrollo integrado de modelos de transformaciones acopladas de desplazamiento-difusión. Por lo tanto, esta tesis comenzó con dos objetivos claros. El primero fue encontrar las conexiones físicas y las diferencias entre los modelos de MT mediante un análisis teórico detallado y simulaciones numéricas. El segundo objetivo fue expandir el modelo de Landau para ser capaz de estudiar MT en policristales, en el caso de transformaciones acopladas de desplazamiento-difusión, y en presencia de dislocaciones. Comenzando con un resumen de los antecedente, en este trabajo se presentan las bases físicas de los modelos actuales de MT. Su capacidad para predecir MT se clarifica mediante el ansis teórico y las simulaciones de la evolución microstructural de MT de cúbicoatetragonal y cúbicoatrigonal en 3D. Este análisis revela que el modelo de Landau con representación irreducible de la deformación transformada es equivalente a la teoría CM-PTMC y al modelo de microelasticidad para predecir los rasgos estáticos durante la MT, pero proporciona una mejor interpretación de los comportamientos dinámicos. Sin embargo, las aplicaciones del modelo de Landau en materiales estructurales están limitadas por su complejidad. Por tanto, el primer resultado de esta tesis es el desarrollo del modelo de Landau nolineal con representación irreducible de deformaciones y de la dinámica de inercia para policristales. La simulación demuestra que el modelo propuesto es consistente fcamente con el CM-PTMC en la descripción estática, y también permite una predicción del diagrama de fases con la clásica forma ’en C’ de los modos de nucleación martensítica activados por la combinación de temperaturas de enfriamiento y las condiciones de tensión aplicada correlacionadas con la transformación de energía de Landau. Posteriomente, el modelo de Landau de MT es integrado con un modelo de transformación de difusión cuantitativa para elucidar la relajación atómica y la difusión de corto alcance de los elementos durante la MT en acero. El modelo de transformaciones de desplazamiento y difusión incluye los efectos de la relajación en borde de grano para la nucleación heterogenea y la evolución espacio-temporal de potenciales de difusión y movilidades químicas mediante el acoplamiento de herramientas de cálculo y bases de datos termo-cinéticos de tipo CALPHAD. El modelo se aplica para estudiar la evolución microstructural de aceros al carbono policristalinos procesados por enfriamiento y partición (Q&P) en 2D. La microstructura y la composición obtenida mediante la simulación se comparan con los datos experimentales disponibles. Los resultados muestran el importante papel jugado por las diferencias en movilidad de difusión entre la fase austenita y martensita en la distibución de carbono en las aceros. Finalmente, un modelo multi-campo es propuesto mediante la incorporación del modelo de dislocación en grano-grueso al modelo desarrollado de Landau para incluir las diferencias morfológicas entre aceros y aleaciones con memoria de forma con la misma ruptura de simetría. La nucleación de dislocaciones, la formación de la martensita ’butterfly’, y la redistribución del carbono después del revenido son bien representadas en las simulaciones 2D del estudio de la evolución de la microstructura en aceros representativos. Con dicha simulación demostramos que incluyendo las dislocaciones obtenemos para dichos aceros, una buena comparación frente a los datos experimentales de la morfología de los bordes de macla, la existencia de austenita retenida dentro de la martensita, etc. Por tanto, basado en un modelo integral y en el desarrollo de códigos durante esta tesis, se ha creado una herramienta de modelización multiescala y multi-campo. Dicha herramienta acopla la termodinámica y la mecánica del continuo en la macroescala con la cinética de difusión y los modelos de campo de fase/Landau en la mesoescala, y también incluye los principios de la cristalografía y de la dinámica de red cristalina en la microescala. ABSTRACT Martensitic transformation (MT), in a narrow sense, is defined as the change of the crystal structure to form a coherent phase, or multi-variant domain structures out from a parent phase with the same composition, by small shuffles or co-operative movements of atoms. Over the past century, MTs have been discovered in different materials from steels to shape memory alloys, ceramics, and smart materials. They lead to remarkable properties such as high strength, shape memory/superelasticity effects or ferroic functionalities including piezoelectricity, electro- and magneto-striction, etc. Various theories/models have been developed, in synergy with development of solid state physics, to understand why MT can generate these rich microstructures and give rise to intriguing properties. Among the well-established theories, the Phenomenological Theory of Martensitic Crystallography (PTMC) is able to predict the habit plane and the orientation relationship between austenite and martensite. The re-interpretation of the PTMC theory within a continuum mechanics framework (CM-PTMC) explains the formation of the multivariant domain structures, while the Landau theory with inertial dynamics unravels the physical origins of precursors and other dynamic behaviors. The crystal lattice dynamics unveils the acoustic softening of the lattice strain waves leading to the weak first-order displacive transformation, etc. Though differing in statics or dynamics due to their origins in different branches of physics (e.g. continuum mechanics or crystal lattice dynamics), these theories should be inherently connected with each other and show certain elements in common within a unified perspective of physics. However, the physical connections and distinctions among the theories/models have not been addressed yet, although they are critical to further improving the models of MTs and to develop integrated models for more complex displacivediffusive coupled transformations. Therefore, this thesis started with two objectives. The first one was to reveal the physical connections and distinctions among the models of MT by means of detailed theoretical analyses and numerical simulations. The second objective was to expand the Landau model to be able to study MTs in polycrystals, in the case of displacive-diffusive coupled transformations, and in the presence of the dislocations. Starting with a comprehensive review, the physical kernels of the current models of MTs are presented. Their ability to predict MTs is clarified by means of theoretical analyses and simulations of the microstructure evolution of cubic-to-tetragonal and cubic-to-trigonal MTs in 3D. This analysis reveals that the Landau model with irreducible representation of the transformed strain is equivalent to the CM-PTMC theory and microelasticity model to predict the static features during MTs but provides better interpretation of the dynamic behaviors. However, the applications of the Landau model in structural materials are limited due its the complexity. Thus, the first result of this thesis is the development of a nonlinear Landau model with irreducible representation of strains and the inertial dynamics for polycrystals. The simulation demonstrates that the updated model is physically consistent with the CM-PTMC in statics, and also permits a prediction of a classical ’C shaped’ phase diagram of martensitic nucleation modes activated by the combination of quenching temperature and applied stress conditions interplaying with Landau transformation energy. Next, the Landau model of MT is further integrated with a quantitative diffusional transformation model to elucidate atomic relaxation and short range diffusion of elements during the MT in steel. The model for displacive-diffusive transformations includes the effects of grain boundary relaxation for heterogeneous nucleation and the spatio-temporal evolution of diffusion potentials and chemical mobility by means of coupling with a CALPHAD-type thermo-kinetic calculation engine and database. The model is applied to study for the microstructure evolution of polycrystalline carbon steels processed by the Quenching and Partitioning (Q&P) process in 2D. The simulated mixed microstructure and composition distribution are compared with available experimental data. The results show that the important role played by the differences in diffusion mobility between austenite and martensite to the partitioning in carbon steels. Finally, a multi-field model is proposed by incorporating the coarse-grained dislocation model to the developed Landau model to account for the morphological difference between steels and shape memory alloys with same symmetry breaking. The dislocation nucleation, the formation of the ’butterfly’ martensite, and the redistribution of carbon after tempering are well represented in the 2D simulations for the microstructure evolution of the representative steels. With the simulation, we demonstrate that the dislocations account for the experimental observation of rough twin boundaries, retained austenite within martensite, etc. in steels. Thus, based on the integrated model and the in-house codes developed in thesis, a preliminary multi-field, multiscale modeling tool is built up. The new tool couples thermodynamics and continuum mechanics at the macroscale with diffusion kinetics and phase field/Landau model at the mesoscale, and also includes the essentials of crystallography and crystal lattice dynamics at microscale.

Human AML1/MDS1/EVI1 fusion protein induces an acute myelogenous leukemia (AML) in mice: A model for human AML

The human t(3;21)(q26;q22) translocation is found as a secondary mutation in some cases of chronic myelogenous leukemia during the blast phase and in therapy-related myelodysplasia and acute myelogenous leukemia. One result of this translocation is a fusion between the AML1, MDS1, and EVI1 genes, which encodes a transcription factor of approximately 200 kDa. The role of the AML1/MDS1/EVI1 (AME) fusion gene in leukemogenesis is largely unknown. In this study, we analyzed the effect of the AME fusion gene in vivo by expressing it in mouse bone marrow cells via retroviral transduction. We found that mice transplanted with AME-transduced bone marrow cells suffered from an acute myelogenous leukemia (AML) 5–13 mo after transplantation. The disease could be readily transferred into secondary recipients with a much shorter latency. Morphological analysis of peripheral blood and bone marrow smears demonstrated the presence of myeloid blast cells and differentiated but immature cells of both myelocytic and monocytic lineages. Cytochemical and flow cytometric analysis confirmed that these mice had a disease similar to the human acute myelomonocytic leukemia. This murine model for AME-induced AML will help dissect the molecular mechanism of AML and the molecular biology of the AML1, MDS1, and EVI1 genes.

Modifications of retinal neurons in a mouse model of retinitis pigmentosa

Animal models of retinitis pigmentosa include the rd mouse, in which a mutation of a rod-specific phosphodiesterase leads to the rapid loss of photoreceptors during the early postnatal life. Very little is known about changes occurring in inner retinal neurons after photoreceptor loss. These changes are important in view of the possibility of restoring vision in retinas with photoreceptor degeneration by means of cell transplantation or direct stimulation of inner layers. In this paper, we show that bipolar and horizontal cells of the rd mouse retina undergo dramatic morphological modifications accompanying photoreceptor loss, demonstrating a dependence of second order neurons on these cells. While describing modifications of the rd retina, we also provide quantitative information about neurons of the wild-type mouse retina, useful for future studies on genetically altered animals.

Farnesyltransferase inhibitors induce dramatic morphological changes of KNRK cells that are blocked by microtubule interfering agents

Farnesyltransferase inhibitors (FTIs) exhibit the remarkable ability to inhibit transformed phenotypes of a variety of human cancer cell lines and to block the growth of cancer cells in a number of animal model systems. In this paper, we report that the addition of FTI to v-K-ras- transformed NRK cells (KNRK) results in dramatic morphological changes. Within 24 h after the addition of FTI, the round morphology of KNRK cells was changed to an elongated (flattened and spread out) morphology resembling those of untransformed NRK cells. No morphological effects were seen when similar concentrations of FTI were added to NRK cells. Phalloidin staining showed that FTI treatment did not restore the disrupted actin cytoskeleton in KNRK cells. In contrast, FTI addition resulted in the appearance of extensive microtubule networks in KNRK cells. The addition of a low concentration (1.2 nM) of vincristine or vinblastine, agents that interfere with microtubule dynamics, blocked the FTI-induced morphological changes in KNRK cells. In contrast, cytochalasin B, which interferes with actin polymerization, did not block the morphological changes. The FTI-induced morphological changes were associated with a decrease in the percentage of cells in S-phase, and the addition of 1.2 nM vincristine did not have additional effects on cell cycle progression. A higher concentration (12 nM) of vincristine caused synergistic effect with FTI to enrich dramatically KNRK cells in G2/M phase. These results suggest that FTI affects cell morphology and that microtubule dynamics are involved in these processes.

Targeted disruption of the Kcnq1 gene produces a mouse model of Jervell and Lange– Nielsen Syndrome

KCNQ1 encodes KCNQ1, which belongs to a family of voltage-dependent K+ ion channel proteins. KCNQ1 associates with a regulatory subunit, KCNE1, to produce the cardiac repolarizing current, IKs. Loss-of-function mutations in the human KCNQ1 gene have been linked to Jervell and Lange–Nielsen Syndrome (JLNS), a disorder characterized by profound bilateral deafness and a cardiac phenotype. To generate a mouse model for JLNS, we created a line of transgenic mice that have a targeted disruption in the Kcnq1 gene. Behavioral analysis revealed that the Kcnq1−/− mice are deaf and exhibit a shaker/waltzer phenotype. Histological analysis of the inner ear structures of Kcnq1−/− mice revealed gross morphological anomalies because of the drastic reduction in the volume of endolymph. ECGs recorded from Kcnq1−/− mice demonstrated abnormal T- and P-wave morphologies and prolongation of the QT and JT intervals when measured in vivo, but not in isolated hearts. These changes are indicative of cardiac repolarization defects that appear to be induced by extracardiac signals. Together, these data suggest that Kcnq1−/− mice are a potentially valuable animal model of JLNS.

Morphological abnormalities in the brains of estrogen receptor β knockout mice

Estrogen receptor β (ERβ) is expressed at high levels in both neurons and glial cells of the central nervous system. The development of ERβ knockout (BERKO) mice has provided a model to study the function of this nuclear receptor in the brain. We have found that the brains of BERKO mice show several morphological abnormalities. There is a regional neuronal hypocellularity in the brain, with a severe neuronal deficit in the somatosensory cortex, especially layers II, III, IV, and V, and a remarkable proliferation of astroglial cells in the limbic system but not in the cortex. These abnormalities are evident as early as 2 mo of age in BERKO mice. As BERKO mice age, the neuronal deficit becomes more pronounced, and, by 2 yr of age, there is degeneration of neuronal cell bodies throughout the brain. This is particularly evident in the substantia nigra. We conclude that ERβ is necessary for neuronal survival and speculate that this gene could have an important influence on the development of degenerative diseases of the central nervous system, such as Alzheimer's disease and Parkinson's disease, as well as those resulting from trauma and stroke in the brain.

Parkinson's disease and gastrointestinal dysfunctions: morphological, neurochemical and functional modifications of the enteric nervous system associated with central dopaminergic impairment

Parkinson’s disease (PD) is frequently associated with gastrointestinal (GI) symptoms, mostly represented by abdominal distension, constipation and defecatory dysfunctions. Despite GI dysfunctions have a major impact on the clinical picture of PD, there is currently a lack of information on the neurochemical, pathological and functional correlates of GI dysmotility associated with PD. Moreover, there is a need of effective and safe pharmacological therapies for managing GI disturbances in PD patients. The present research project has been undertaken to investigate the relationships between PD and related GI dysfunctions by means of investigations in an animal model of PD induced by intranigral injection of 6-hydroxydopamine (6-OHDA). The use of the 6-OHDA experimental model of PD in the present program has allowed to pursue the following goals: 1) to examine the impact of central dopaminergic denervation on colonic excitatory cholinergic and tachykininergic neuromotility by means of molecular, histomorphologic and functional approaches; 2) to elucidate the role of gut inflammation in the onset and progression of colonic dysmotility associated with PD, characterizing the degree of inflammation and oxidative damage in colonic tissues, as well as identifying the immune cells involved in the production of pro-inflammatory cytokines in the gut; 3) to evaluate the impact of chronic treatment with L-DOPA plus benserazide on colonic neuromuscular activity both in control and PD animals. The results suggest that central nigrostriatal dopaminergic denervation is associated with an impaired excitatory cholinergic neurotransmission and an enhanced tachykininergic control, resulting in a dysregulated smooth muscle motor activity, which likely contributes to the concomitant decrease in colonic transit rate. These motor alterations might result from the occurrence of a condition of gut inflammation associated with central intranigral denervation. The treatment with L-DOPA/BE following central dopaminergic neurodegeneration can restore colonic motility, likely through a normalization of the cholinergic enteric neurotransmission, and it can also improve the colonic inflammation associated with central dopaminergic denervation.

Correlation between SD-OCT, immunocytochemistry and functional findings in an animal model of retinal degeneration

Purpose: The P23H rhodopsin mutation is an autosomal dominant cause of retinitis pigmentosa (RP). The degeneration can be tracked using different anatomical and functional methods. In our case, we evaluated the anatomical changes using Spectral-Domain Optical Coherence Tomography (SD-OCT) and correlated the findings with retinal thickness values determined by immunocytochemistry.Methods: Pigmented rats heterozygous for the P23H mutation, with ages between P18 and P180 were studied. Function was assessed by means of optomotor testing and ERGs. Retinal thicknesses measurements, autofluorescence and fluorescein angiography were performed using Spectralis OCT. Retinas were studied by means of immunohistochemistry. Results: Between P30 and P180, visual acuity decreased from 0.500 to 0.182 cycles per degree (cyc/deg) and contrast sensitivity decreased from 54.56 to 2.98 for a spatial frequency of 0.089 cyc/deg. Only cone-driven b-wave responses reached developmental maturity. Flicker fusions were also comparable at P29 (42 Hz). Double flash-isolated rod-driven responses were already affected at P29. Photopic responses revealed deterioration after P29.A reduction in retinal thicknesses and morphological modifications were seen in OCT sections. Statistically significant differences were found in all evaluated thicknesses. Autofluorescence was seen in P23H rats as sparse dots. Immunocytochemistry showed a progressive decrease in the outer nuclear layer (ONL), and morphological changes. Although anatomical thickness measures were significantly lower than OCT values, there was a very strong correlation between the values measured by both techniques.Conclusions: In pigmented P23H rats, a progressive deterioration occurs in both retinal function and anatomy. Anatomical changes can be effectively evaluated using SD-OCT and immunocytochemistry, with a good correlation between their values, thus making SD-OCT an important tool for research in retinal degeneration.

Type A aortic dissection model to improve endovascular research and technologies.

OBJECTIVE Type A aortic dissection is a life-threatening disease requiring immediate surgical treatment. With emerging catheter-based technologies, endovascular stent-graft implantation to treat aneurysms and dissections has become a standardized procedure. However, endovascular treatment of the ascending aorta remains challenging. Thus we designed an ascending aortic dissection model to allow simulation of endovascular treatment. METHODS Five formalin-fixed human aortas were prepared. The ascending aorta was opened semicircularly in the middle portion and the medial layer was separated from the intima. The intimal tube was readapted using running monofilament sutures. The preparations were assessed by 128-slice computed tomography. A bare-metal stent was implanted for thoracic endovascular aortic repair in 4 of the aortic dissection models. RESULTS Separation of the intimal and medial layer of the aorta was considered to be sufficient because computed tomography showed a clear image of the dissection membrane in each aorta. The dissection was located 3.9 ± 1.4 cm proximally from the aortic annulus, with a length of 4.6 ± 0.9 cm. Before stent implantation, the mean distance from the intimal flap to the aortic wall was measured as 0.63 ± 0.163 cm in the ascending aorta. After stent implantation, this distance decreased to 0.26 ± 0.12 cm. CONCLUSION This model of aortic dissection of the ascending human aorta was reproducible with a comparable pathological and morphological appearance. The technique and model can be used to evaluate new stent-graft technologies to treat type A dissection and facilitate training for surgeons.

Morphological variability of Globorotalia menardii in DSDP Sites 68-502 and 68-503

Variability in the test of Globorotalia menardii during the past 8 million years has been investigated at DSDP Site 502A (Caribbean Sea) and DSDP Site 503A (Eastern Equatorial Pacific). Measurements were made of spire height (delta x), maximum diameter (delta y), the tangent angles of the upper and lower peripheral keels (phi 1, phi 2, respectively), the number of chambers in the final whorl, and the area of the silhouette in keel view. Four morphotypes alpha, beta, gamma, and delta were distinguished. Morphotype alpha was found in strata ranging in age from the Late Miocene through the Holocene. It shows a continuous increase in delta x and delta y until the Late Pleistocene. During and after the final closure of the ancient Central American Seaway (between 2.4 Ma and 1.8 Ma) there was a rapid increase in the area of the test in keel view. At the Caribbean Sea site, morphotype beta evolved during the past 0.22 Ma. It is less inflated than alpha and has a more delicate test. In the morphospace of delta x vs. delta y, morphotypes alpha and beta can be distinguished by a separation line delta y = 3.2 * delta x - 160 (delta x and delta y in µm). Plots of morphotype alpha are below that line, those of beta are above it. Morphotype alpha is taken to be Globorotalia menardii menardii Parker, Jones & Brady (1865) and includes G. menardii 'A' Bolli (1970). Morphotype beta is identified as G. menardii cultrata (d'Orbigny). Morphotypes gamma and delta are extinct Upper Miocene to Pliocene forms which evolved from morphotype alpha. They have a narrower phi 1 angle and more chambers (>=7) than morphotype alpha commonly with 5 to 6 chambers (7 in transitional forms). In contemporaneous samples morphotype delta can be distinguished from gamma by a smaller value of phi 1 and 8 or more chambers in the final whorl. Morphotype gamma is taken to be G. limbata (Fornasini, 1902) and includes the junior synonym G. menardii 'B' Bolli (1970). Morphotype delta is G. multicamerata Cushman & Jarvis (1930). With the exception of the Late Pleistocene development of G. menardii cultrataonly in the Caribbean the morphological changes of G. menardii at DSDP Sites 502A and 503A are similar. The development from the ancestral G. menardii menardii of the G. limbata - G. multicamerata lineage during the Pliocene and of G. menardii cultrata during the Late Pleistocene suggests responses at the two sites to a changing palaeoceanography during and after the formation of the Isthmus of Panama.

Biogenesis of caveolae: a structural model for caveolin-induced domain formation

Caveolae are striking morphological features of the plasma membrane of mammalian cells. Caveolins, the major proteins of caveolae, play a crucial role in the formation of these invaginations of the plasma membrane; however, the precise mechanisms involved are only just starting to be unravelled. Recent studies suggest that caveolae are stable structures first generated in the Golgi complex. Their formation and exit from the Golgi complex is associated with caveolin oligomerisation, acquisition of detergent insolubility, and association with cholesterol. Modelling of caveolin-membrane interactions together with in vitro studies of caveolin peptides are providing new insights into how caveolin-lipid interactions could generate the unique architecture of the caveolar domain.

Investigating the use of sweet sorghum as a model for sugar accumulation in sugarcane

This paper outlines a current investigation of sugar accumulation in sweet sorghum to assist in understanding and simplifying this complex trait in sugarcane. A recombinant inbred line (RIL) sorghum population, between a sweet and a grain sorghum, has been developed and phenotyped for various morphological and agronomic traits related to grain yield, biomass and stem sugar content. A genetic linkage map will be constructed for the sweet sorghum population with the objective of identifying genomic regions associated with sucrose accumulation in sweet sorghum. This will lead to further work, including comparative mapping in sugarcane, to identify the extent to which sweet sorghum can be used as a model for investigating sugar accumulation in sugarcane.