MTADV 5-MER peptide suppresses chronic inflammations as well as autoimmune pathologies and unveils a new potential target-Serum Amyloid A.

Despite the existence of potent anti-inflammatory biological drugs e.g., anti-TNF and anti IL-6 receptor antibodies, for treating chronic inflammatory and autoimmune diseases, these are costly and not specific. Cheaper oral available drugs remain an unmet need. Expression of the acute phase protein Serum Amyloid A (SAA) is dependent on release of pro-inflammatory cytokines IL-1, IL-6 and TNF-α during inflammation. Conversely, SAA induces pro-inflammatory cytokine secretion, including Th17, leading to a pathogenic vicious cycle and chronic inflammation. 5- MER peptide (5-MP) MTADV (methionine-threonine-alanine-aspartic acid-valine), also called Amilo-5MER, was originally derived from a sequence of a pro-inflammatory CD44 variant isolated from synovial fluid of a Rheumatoid Arthritis (RA) patient. This human peptide displays an efficient anti-inflammatory effects to ameliorate pathology and clinical symptoms in mouse models of RA, Inflammatory Bowel Disease (IBD) and Multiple Sclerosis (MS). Bioinformatics and qRT-PCR revealed that 5-MP, administrated to encephalomyelytic mice, up-regulates genes contributing to chronic inflammation resistance. Mass spectrometry of proteins that were pulled down from an RA synovial cell extract with biotinylated 5-MP, showed that it binds SAA. 5-MP disrupted SAA assembly, which is correlated with its pro-inflammatory activity. The peptide MTADV (but not scrambled TMVAD) significantly inhibited the release of pro-inflammatory cytokines IL-6 and IL-1β from SAA-activated human fibroblasts, THP-1 monocytes and peripheral blood mononuclear cells. 5-MP suppresses the pro-inflammatory IL-6 release from SAA-activated cells, but not from non-activated cells. 5-MP could not display therapeutic activity in rats, which are SAA deficient, but does inhibit inflammations in animal models of IBD and MS, both are SAA-dependent, as shown by others in SAA knockout mice. In conclusion, 5-MP suppresses chronic inflammation in animal models of RA, IBD and MS, which are SAA-dependent, but not in animal models, which are SAA-independent

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience

Bistable Percepts in the Brain: fMRI Contrasts Monocular Pattern Rivalry and Binocular Rivalry

The neural correlates of binocular rivalry have been actively debated in recent years, and are of considerable interest as they may shed light on mechanisms of conscious awareness. In a related phenomenon, monocular rivalry, a composite image is shown to both eyes. The subject experiences perceptual alternations in which the two stimulus components alternate in clarity or salience. The experience is similar to perceptual alternations in binocular rivalry, although the reduction in visibility of the suppressed component is greater for binocular rivalry, especially at higher stimulus contrasts. We used fMRI at 3T to image activity in visual cortex while subjects perceived either monocular or binocular rivalry, or a matched non-rivalrous control condition. The stimulus patterns were left/right oblique gratings with the luminance contrast set at 9%, 18% or 36%. Compared to a blank screen, both binocular and monocular rivalry showed a U-shaped function of activation as a function of stimulus contrast, i.e. higher activity for most areas at 9% and 36%. The sites of cortical activation for monocular rivalry included occipital pole (V1, V2, V3), ventral temporal, and superior parietal cortex. The additional areas for binocular rivalry included lateral occipital regions, as well as inferior parietal cortex close to the temporoparietal junction (TPJ). In particular, higher-tier areas MT+ and V3A were more active for binocular than monocular rivalry for all contrasts. In comparison, activation in V2 and V3 was reduced for binocular compared to monocular rivalry at the higher contrasts that evoked stronger binocular perceptual suppression, indicating that the effects of suppression are not limited to interocular suppression in V1

On the Origin of the Functional Architecture of the Cortex

The basic structure of receptive fields and functional maps in primary visual cortex is established without exposure to normal sensory experience and before the onset of the critical period. How the brain wires these circuits in the early stages of development remains unknown. Possible explanations include activity-dependent mechanisms driven by spontaneous activity in the retina and thalamus, and molecular guidance orchestrating thalamo-cortical connections on a fine spatial scale. Here I propose an alternative hypothesis: the blueprint for receptive fields, feature maps, and their inter-relationships may reside in the layout of the retinal ganglion cell mosaics along with a simple statistical connectivity scheme dictating the wiring between thalamus and cortex. The model is shown to account for a number of experimental findings, including the relationship between retinotopy, orientation maps, spatial frequency maps and cytochrome oxidase patches. The theory's simplicity, explanatory and predictive power makes it a serious candidate for the origin of the functional architecture of primary visual cortex

The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas

This article explores the notion that Freudian constructs may have neurobiological substrates. Specifically, we propose that Freud’s descriptions of the primary and secondary processes are consistent with self-organized activity in hierarchical cortical systems and that his descriptions of the ego are consistent with the functions of the default-mode and its reciprocal exchanges with subordinate brain systems. This neurobiological account rests on a view of the brain as a hierarchical inference or Helmholtz machine. In this view, large-scale intrinsic networks occupy supraordinate levels of hierarchical brain systems that try to optimize their representation of the sensorium. This optimization has been formulated as minimizing a free-energy; a process that is formally similar to the treatment of energy in Freudian formulations. We substantiate this synthesis by showing that Freud’s descriptions of the primary process are consistent with the phenomenology and neurophysiology of rapid eye movement sleep, the early and acute psychotic state, the aura of temporal lobe epilepsy and hallucinogenic drug states

Development, calibration and validation of a greenhouse tomato model: 1. Description of the model.

A dynamic crop growth model, TOMGRO, for an indeterminate tomato variety is presented. The model describes the phenological development and increase in dry weight of various organs (roots, stem nodes, leaves and fruits) from planting till maturity under variable environmental conditions. Phenological development is governed by genetic plant properties and environmental conditions (e.g. air temperature and CO2 level) and expressed in a plastochron index, i.e. the current stem node number. Total dry matter accumulation is based on a quantitative description of the carbon balance, including gross CO2 assimilation, maintenance respiration and growth respiration. Partitioning of dry matter increase over the various organs is governed by their relative sink strengh, defined on the basis of a genetically determined ‘potential’ growth rate, achieved under non-limiting carbohydrate supply. The model is both schematic and modular in set-up. This means it can be adapted easily and most of its subroutines can be replaced easily by others if better descriptions become available. It can also be combined with a more comprehensive model describing greenhouse climate and appears robust for use in procedures of economic optimization of climate conditions in greenhouses or for management purposes

Development, calibration and validation of a greenhouse tomato model: 2. Field calibration and validation.

The tomato crop growth model described in part I of this study has been parameterized on the basis of the results of experiments conducted in greenhouses in the northern Negev of Israel. Iterative procedures were applied to derive the parameters for the functional responses of various processes to temperature, radiation intensity and carbon dioxide concentration. The model was subsequently validated on the basis of the results of completely independent experiments. It is shown that the model accounts for the major phenomena observed under greenhouse conditions, and may be used, therefore, with confidence to examine the effects of environmental conditions and management practices on tomato fruit yield. It may also form the basis of decision support systems, aiming at recommendations for crop management. To improve its performance and range of applicability, further development of the model is necessary, including more morphological detail, as well as effects of other environmental factors

Development, calibration and validation of a greenhouse tomato model: 2. Field calibration and validation.

The tomato crop growth model described in part I of this study has been parameterized on the basis of the results of experiments conducted in greenhouses in the northern Negev of Israel. Iterative procedures were applied to derive the parameters for the functional responses of various processes to temperature, radiation intensity and carbon dioxide concentration. The model was subsequently validated on the basis of the results of completely independent experiments. It is shown that the model accounts for the major phenomena observed under greenhouse conditions, and may be used, therefore, with confidence to examine the effects of environmental conditions and management practices on tomato fruit yield. It may also form the basis of decision support systems, aiming at recommendations for crop management. To improve its performance and range of applicability, further development of the model is necessary, including more morphological detail, as well as effects of other environmental factors

Development, calibration and validation of a greenhouse tomato model: 1. Description of the model.

A dynamic crop growth model, TOMGRO, for an indeterminate tomato variety is presented. The model describes the phenological development and increase in dry weight of various organs (roots, stem nodes, leaves and fruits) from planting till maturity under variable environmental conditions. Phenological development is governed by genetic plant properties and environmental conditions (e.g. air temperature and CO2 level) and expressed in a plastochron index, i.e. the current stem node number. Total dry matter accumulation is based on a quantitative description of the carbon balance, including gross CO2 assimilation, maintenance respiration and growth respiration. Partitioning of dry matter increase over the various organs is governed by their relative sink strengh, defined on the basis of a genetically determined ‘potential’ growth rate, achieved under non-limiting carbohydrate supply. The model is both schematic and modular in set-up. This means it can be adapted easily and most of its subroutines can be replaced easily by others if better descriptions become available. It can also be combined with a more comprehensive model describing greenhouse climate and appears robust for use in procedures of economic optimization of climate conditions in greenhouses or for management purposes