Overexpression of guanylate cyclase activating protein 2 in rod photoreceptors in vivo leads to morphological changes at the synaptic ribbon

Guanylate cyclase activating proteins are EF-hand containing proteins that confer calcium sensitivity to retinal guanylate cyclase at the outer segment discs of photoreceptor cells. By making the rate of cGMP synthesis dependent on the free intracellular calcium levels set by illumination, GCAPs play a fundamental role in the recovery of the light response and light adaptation. The main isoforms GCAP1 and GCAP2 also localize to the synaptic terminal, where their function is not known. Based on the reported interaction of GCAP2 with Ribeye, the major component of synaptic ribbons, it was proposed that GCAP2 could mediate the synaptic ribbon dynamic changes that happen in response to light. We here present a thorough ultrastructural analysis of rod synaptic terminals in loss-of-function (GCAP1/GCAP2 double knockout) and gain-of-function (transgenic overexpression) mouse models of GCAP2. Rod synaptic ribbons in GCAPs−/− mice did not differ from wildtype ribbons when mice were raised in constant darkness, indicating that GCAPs are not required for ribbon early assembly or maturation. Transgenic overexpression of GCAP2 in rods led to a shortening of synaptic ribbons, and to a higher than normal percentage of club-shaped and spherical ribbon morphologies. Restoration of GCAP2 expression in the GCAPs−/− background (GCAP2 expression in the absence of endogenous GCAP1) had the striking result of shortening ribbon length to a much higher degree than overexpression of GCAP2 in the wildtype background, as well as reducing the thickness of the outer plexiform layer without affecting the number of rod photoreceptor cells. These results indicate that preservation of the GCAP1 to GCAP2 relative levels is relevant for maintaining the integrity of the synaptic terminal. Our demonstration of GCAP2 immunolocalization at synaptic ribbons at the ultrastructural level would support a role of GCAPs at mediating the effect of light on morphological remodeling changes of synaptic ribbons.

Influence of thymol and silver nanoparticles on the degradation of poly(lactic acid) based nanocomposites: thermal and morphological properties

Biopolymers, such as poly(lactic acid) (PLA), have been proposed as environmentally-friendly alternatives in applications such as food packaging. In this work, silver nanoparticles and thymol were used as active additives in PLA matrices, combining the antibacterial activity of silver with the antioxidant performance of thymol. The combined action of both additives influenced PLA thermal degradation in ternary systems. DSC results showed that the addition of thymol resulted in a clear decrease of the glass transition temperature (Tg) of PLA, suggesting its plasticizing effect in PLA matrices. Slight modifications in mechanical properties of dog-bone bars were also observed after the addition of the active components, especially in the elastic modulus. FESEM analyses showed the good distribution of active additives through the PLA matrix, obtaining homogenous surfaces and highlighting the presence of silver nanoparticles successfully embedded into the bulk matrix. Degradation of these PLA-based nanocomposites with thymol and silver nanoparticles in composting conditions indicated that the inherent biodegradable character of this biopolymer was improved after this modification. The obtained nanocomposites showed suitable properties to be used as biodegradable active-food packaging systems with antioxidant and antimicrobial effects.

Trajectory-Based Morphological Operators: A Model for Efficient Image Processing

Mathematical morphology has been an area of intensive research over the last few years. Although many remarkable advances have been achieved throughout these years, there is still a great interest in accelerating morphological operations in order for them to be implemented in real-time systems. In this work, we present a new model for computing mathematical morphology operations, the so-called morphological trajectory model (MTM), in which a morphological filter will be divided into a sequence of basic operations. Then, a trajectory-based morphological operation (such as dilation, and erosion) is defined as the set of points resulting from the ordered application of the instant basic operations. The MTM approach allows working with different structuring elements, such as disks, and from the experiments, it can be extracted that our method is independent of the structuring element size and can be easily applied to industrial systems and high-resolution images.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

Physiological and Morphological Similarities between the Octodon Degus Retina and the Human Retina

Octodon degus is a rodent with diurnal crepuscular activity. Here we compare the function and morphology of the retina of this diurnal rodent with the retinas of nocturnal rodents and humans.

A new boundary-based morphological model

Mathematical morphology addresses the problem of describing shapes in an n-dimensional space using the concepts of set theory. A series of standardized morphological operations are defined, and they are applied to the shapes to transform them using another shape called the structuring element. In an industrial environment, the process of manufacturing a piece is based on the manipulation of a primitive object via contact with a tool that transforms the object progressively to obtain the desired design. The analogy with the morphological operation of erosion is obvious. Nevertheless, few references about the relation between the morphological operations and the process of design and manufacturing can be found. The non-deterministic nature of classic mathematical morphology makes it very difficult to adapt their basic operations to the dynamics of concepts such as the ordered trajectory. A new geometric model is presented, inspired by the classic morphological paradigm, which can define objects and apply morphological operations that transform these objects. The model specializes in classic morphological operations, providing them with the determinism inherent in dynamic processes that require an order of application, as is the case for designing and manufacturing objects in professional computer-aided design and manufacturing (CAD/CAM) environments. The operators are boundary-based so that only the points in the frontier are handled. As a consequence, the process is more efficient and more suitable for use in CAD/CAM systems.

Morphological classification of microtidal sand and gravel beaches

A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.