Alleviation of pre-exposure of mouse brain with low-dose C-12(6+) ion or Co-60 gamma-ray on male reproductive endocrine damages induced by subsequent high-dose irradiation

Irradiation has been widely reported to damage organisms by attacking on proteins, nucleic acid and lipids in cells. However, radiation hormesis after low-dose irradiation has become the focus of research in radiobiology in recent years. To investigate the effects of pre-exposure of mouse brain with low-dose C-12(6+) ion or Co-60 gamma (gamma)-ray on male reproductive endocrine capacity induced by subsequent high-dose irradiation, the brains of the B6C3F(1) hybrid strain male mice were irradiated with 0.05 Gy of C-12(6+) ion or Co-60 gamma-ray as the pre-exposure dose, and were then irradiated with 2 Gy as challenging irradiation dose at 4 h after pre-exposure. Serum pituitary gonadotropin hormones, follicle-stimulating hormone (FSH) and luteinizing hormone (LH), testosterone, testis weight, sperm count and shape were measured on the 35th day after irradiation. The results showed that there was a significant reduction in the levels of serum FSH, LH, testosterone, testis weight and sperm count, and a significant increase in sperm abnormalities by irradiation of the mouse brain with 2 Gy of C-12(6+) ion or Co-60 gamma-ray. Moreover, the effects were more obvious in the group irradiated by C-12(6+) ion than in that irradiated by Co-60 gamma-ray. Pre-exposure with low-dose C-12(6+) ion or Co-60 gamma-ray significantly alleviated the harmful effects induced by a subsequent high-dose irradiation.

Comparison of biochemical effects induced by Changle between male and female rats using NMR and ICP-MS techniques

Metabolic profiles caused by rare earth complex were investigated using NMR and ICP-MS techniques. Male and female Wistar rats were treated orally with Changle (A kind of rare earth complex applied in agriculture to raise the production of crops) at dose of 2, 5 and 20 mg (.) kg(-1) body weight/day respectively for 90 d. Urine and serum samples are collected on 90 d. The relative concentrations of important endogenous metabolites in urine and serum are determined from H-1 NMR spectra and the contents of the four rare earth elements ( La, Ce, Pr and Nd) constituting Changle in the serum samples are measured by ICP-MS technique. Changle-induced renal and liver damage in rats is found based on the increase in the amounts of the amino acids, trimethylamine N-oxide, N, N-dimethyglycine, dimethylamine, succinate, aketoglutarate and ethanol as well as rare earth concentrations. The similarities and differentiations are found in the alteration patterns of metabolites and rare earth concentrations in serum.

Breeding behavior under temporal risk of predation in male root voles (Microtus oeconomus)

We examined breeding behavior responses of male root votes (Microtus oeconomus) to temporal risk of predation by using acute and chronic exposure to predator odor. The 2 series of exposure experiments provided 2 types of temporal patterns of risk: continuous safety with a brief period of risk and Sustained risk with a brief period of safety. Male root votes that were acutely exposed to predator odor for I h suppressed their breeding behavior, but bred immediately after exposure to control odor for I h. Those chronically exposed to predator odor for 20 days maintained behavioral suppression during the 1-h period of exposure to control odor. Acutely exposed males did not change their physiological patterns of breeding, but those chronically exposed to predator odor had reduced testosterone concentration and epididymis index. Our results indicate that breeding behavior in a given situation depends on the overall patterns of risk experienced by male root votes, and the acute and chronic stress responses that affect reproduction are responsible for different behavioral responses to the 2 types of temporal patterns of risk. We also discuss the reasons for conflicting results about breeding suppression of votes between previous studies in the laboratory and the field.

Grouping For Recognition

This paper presents a new method of grouping edges in order to recognize objects. This grouping method succeeds on images of both two- and three- dimensional objects. So that the recognition system can consider first the collections of edges most likely to lead to the correct recognition of objects, we order groups of edges based on the likelihood that a single object produced them. The grouping module estimates this likelihood using the distance that separates edges and their relative orientation. This ordering greatly reduces the amount of computation required to locate objects and improves the system's robustness to error.

Color Region Grouping and Shape Recognition with Deformable Models

A new deformable shape-based method for color region segmentation is described. The method includes two stages: over-segmentation using a traditional color region segmentation algorithm, followed by deformable model-based region merging via grouping and hypothesis selection. During the second stage, region merging and object identification are executed simultaneously. A statistical shape model is used to estimate the likelihood of region groupings and model hypotheses. The prior distribution on deformation parameters is precomputed using principal component analysis over a training set of region groupings. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with similarly colored adjacent objects. Furthermore, the recovered parametric shape model can be used directly in object recognition and comparison. Experiments in segmentation and image retrieval are reported.

Deformable Shape Detection and Description via Model-Based Region Grouping

A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with adjacent objects or shadows. The formulation can be used to group image regions based on any image homogeneity predicate; e.g., texture, color, or motion. The recovered shape models can be used directly in object recognition. Experiments with color imagery are reported.

MosaicShape: Stochastic Region Grouping with Shape Prior

A novel method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework and solved by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. By this means, object segmentation and recognition are accomplished simultaneously. Within each sampling move during the simulation process,probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized parallel algorithm by Barbu and Zhu,combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.

Fast Synchronization of Perpetual Grouping in Laminar Visual Cortical Circuits

Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints on which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

Spiking Dynamics during Perceptual Grouping in the Laminar Circuits of Visual Cortex

Grouping of collinear boundary contours is a fundamental process during visual perception. Illusory contour completion vividly illustrates how stable perceptual boundaries interpolate between pairs of contour inducers, but do not extrapolate from a single inducer. Neural models have simulated how perceptual grouping occurs in laminar visual cortical circuits. These models predicted the existence of grouping cells that obey a bipole property whereby grouping can occur inwardly between pairs or greater numbers of similarly oriented and co-axial inducers, but not outwardly from individual inducers. These models have not, however, incorporated spiking dynamics. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity to inducer configurations occur despite irregularities in spike timing across all the interacting cells. Other models have demonstrated spiking dynamics in laminar neocortical circuits, but not how perceptual grouping occurs. The current model begins to unify these two modeling streams by implementing a laminar cortical network of spiking cells whose intracellular temporal dynamics interact with recurrent intercellular spiking interactions to quantitatively simulate data from neurophysiological experiments about perceptual grouping, the structure of non-classical visual receptive fields, and gamma oscillations.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.

Preattentive Texture Segmentation and Grouping by the Boundary Contour System

An improved Boundary Contour System (BCS) neural network model of preattentive vision is applied to two images that produce strong "pop-out" of emergent groupings in humans. In humans these images generate groupings collinear with or perpendicular to image contrasts. Analogous groupings occur in computer simulations of the model. Long-range cooperative and short-range competitive processes of the BCS dynamically form the stable groupings of texture regions in response to the images.

St. Columba, Silnán, and the 'Male Bovine' (VC 2.17)

At Vita Columbae VC 2.17, Adomnán has severely misunderstood a written source which originally described how Columba ordered one party to a dispute, an alleged maleficus ‘evil-doer’ called Silnán, to milk a sick cow in order to settle the dispute by demonstrating that its contaminated milk was the real, hidden cause of the harm which had occasioned the dispute. Adomnán misread a description of a bos maculosus ‘pock-marked bovine’ to refer to a bos masculus ‘male bovine’, and proceeded to misunderstand the story as the description of some form of contest between Columba and a maleficus ‘sorcerer’.

Tryptophan degradation in irritable bowel syndrome: evidence of indoleamine 2,3-dioxygenase activation in a male cohort

Background: Irritable bowel syndrome (IBS) is a common disorder that affects 10–15% of the population. Although characterised by a lack of reliable biological markers, the disease state is increasingly viewed as a disorder of the brain-gut axis. In particular, accumulating evidence points to the involvement of both the central and peripheral serotonergic systems in disease symptomatology. Furthermore, altered tryptophan metabolism and indoleamine 2,3-dioxygenase (IDO) activity are hallmarks of many stress-related disorders. The kynurenine pathway of tryptophan degradation may serve to link these findings to the low level immune activation recently described in IBS. In this study, we investigated tryptophan degradation in a male IBS cohort (n = 10) and control subjects (n = 26). Methods: Plasma samples were obtained from patients and healthy controls. Tryptophan and its metabolites were measured by high performance liquid chromatography (HPLC) and neopterin, a sensitive marker of immune activation, was measured using a commercially available ELISA assay. Results: Both kynurenine levels and the kynurenine:tryptophan ratio were significantly increased in the IBS cohort compared with healthy controls. Neopterin was also increased in the IBS subjects and the concentration of the neuroprotective metabolite kynurenic acid was decreased, as was the kynurenic acid:kynurenine ratio. Conclusion: These findings suggest that the activity of IDO, the immunoresponsive enzyme which is responsible for the degradation of tryptophan along this pathway, is enhanced in IBS patients relative to controls. This study provides novel evidence for an immune-mediated degradation of tryptophan in a male IBS population and identifies the kynurenine pathway as a potential source of biomarkers in this debilitating condition.

Stream segregation on a single electrode as a function of pulse rate in cochlear implant listeners.

While cochlear implants (CIs) usually provide high levels of speech recognition in quiet, speech recognition in noise remains challenging. To overcome these difficulties, it is important to understand how implanted listeners separate a target signal from interferers. Stream segregation has been studied extensively in both normal and electric hearing, as a function of place of stimulation. However, the effects of pulse rate, independent of place, on the perceptual grouping of sequential sounds in electric hearing have not yet been investigated. A rhythm detection task was used to measure stream segregation. The results of this study suggest that while CI listeners can segregate streams based on differences in pulse rate alone, the amount of stream segregation observed decreases as the base pulse rate increases. Further investigation of the perceptual dimensions encoded by the pulse rate and the effect of sequential presentation of different stimulation rates on perception could be beneficial for the future development of speech processing strategies for CIs.