Localization of NG2 immunoreactive neuroglia cells in the rat locus coeruleus and their plasticity in response to stress

The locus coeruleus (LC) nucleus modulates adaptive behavioural responses to stress and dysregulation of LC neuronal activity is implicated in stress-induced mental illnesses. The LC is composed primarily of noradrenergic neurons together with various glial populations. A neuroglia cell-type largely unexplored within the LC is the NG2 cell. NG2 cells serve primarily as oligodendrocyte precursor cells throughout the brain. However, some NG2 cells are in synaptic contact with neurons suggesting a role in information processing. The aim of this study was to neurochemically and anatomically characterise NG2 cells within the rat LC. Furthermore, since NG2 cells have been shown to proliferate in response to traumatic brain injury, we investigated whether such NG2 cells plasticity also occurs in response to emotive insults such as stress. Immunohistochemistry and confocal microscopy revealed that NG2 cells were enriched within the pontine region occupied by the LC. Close inspection revealed that a sub-population of NG2 cells were located within unique indentations of LC noradrenergic somata and were immunoreactive for the neuronal marker NeuN whilst NG2 cell processes formed close appositions with clusters immunoreactive for the inhibitory synaptic marker proteins gephyrin and the GABA-A receptor alpha3-subunit, on noradrenergic dendrites. In addition, LC NG2 cell processes were decorated with vesicular glutamate transporter 2 immunoreactive puncta. Finally, ten days of repeated restraint stress significantly increased the density of NG2 cells within the LC. The study demonstrates that NG2 IR cells are integral components of the LC cellular network and they exhibit plasticity as a result of emotive challenges

Classification as an Approach To Requirements Analysis

Oassification schemes have proven immensely useful in computerized systems for problem solving in the physical and biological sciences. A typical example is found in the medical domain where various taxonomies have been created for diseases, symptOms, laboratory tests, drugs, and so forth. These taxonomies may be used for characterizing specific clinical situations in expert systems that assist physicians and other health professionals in diagnosis and treatment. Oassification can be divided into several phases. The activities in the first phase are to find a category structure which can fit observations. This phase is called "cluster analysis", or "typology", "learning", "clumping", "regionalization", etc., or "classification (construction)" in our paper, depending on the field to which it is applied. There are many approaches to this cluster analysis. These include approaches such as numerical taxonomy and conceptual clustering. Once this category structure has been established, the next phase is to classify new observations, that is, recognize them as members of one category or another. There are two different situations for the activities in this phase: 1) when the category structure is completely known, this kind of activity is called "classification", "indexing", or "classifying" in this paper, and 2) if category structure is partly known or only part of the information of the observation is known, this kind of activity is called "discriminant analysis" [AND73] [GOR81]. Oancey [CLA84] has characterized classification problem solving as making a selection from a set of pre-enumerated solutions (in contrast to constructing new solutions). If the problem solver has a priori knowledge of existing solutions and is able to relate these to the problem description by data abstraction and refinement, then the problem can be solved using classification. Other artificial intelligence researchers, especially those investigating machine learning, have developed new techniques such as conceptual clustering [MIC86] (in contrast to numerical/statistical clustering), which might be used for developing classification schemes for problem solving

Lunar sample analysis

Results are presented from an extensive series of new high resolution scanning electron microscope studies of the very primative group of meteorites known as unequilibrated chondrites. These include quantitative analyses of micrometer sized phases and interpretation in terms of relevant phase equilibria. Several new meteorite minerals including high chromium metal, have been discovered

Realising context-sensitive mobile messaging

Mobile technologies aim to assist people as they move from place to place going about their daily work and social routines. Established and very popular mobile technologies include short-text messages and multimedia messages with newer growing technologies including Bluetooth mobile data transfer protocols and mobile web access.Here we present new work which combines all of the above technologies to fulfil some of the predictions for future context aware messaging. We present a context sensitive mobile messaging system which derives context in the form of physical locations through location sensing and the co-location of people through Bluetooth familiarity

A multi-agent system to manage users and spaces in a adaptive environment system

This paper, deals with the actual problem of manage user preferences and local specifications on an IoT adaptive system, namely using a multi agent system to achieve a Smart Environment System. On a new era of interaction between persons and physical spaces, users want those spaces smartly adapt to their preferences in a transparent way. To achieve that, new approaches are needed. In this project we develop a multi agent system architecture with different layers to achieve a solution that entails all the proposed objectives.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Using jason framework to develop a multi-agent system to manage users and spaces in an adaptive environment system

Manage user preferences and local specifications on an IoT adaptive system is a actual problem. This paper uses Jason framework to develop a multi agent system to achieve a Smart Environment System, and supports interaction between persons and physical spaces, that users want to smartly adapt to their preferences in a transparent way. This work proposes a new approach, that has been developed using a multi agent system architecture with different layers to achieve a solution that entails all the proposed objectives.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Cerebellar Development and Plasticity: Perspectives for Motor Coordination Strategies, for Motor Skills, and for Therapy

The role of the mammalian cerebellum ranges from motor coordination, sensory-motor integration, motor learning, and timing to nonmotor functions such as cognition. In terms of motor function, the development of the cerebellum is of particular interest because animal studies show that the development of the cerebellar cortical circuitry closely parallels motor coordination. Ultrastructural analysis of the morphological development of the cerebellar circuitry, coupled with the temporal and spatial identification of the neurochemical substrates expressed during development, will help to elucidate their roles in the establishment of the cerebellar circuitry and hence motor activity. Furthermore, the convenience of a number of naturally occurring mouse mutations has allowed a functional dissection of the various cellular elements that make up the cerebellar circuitry. This understanding will also help in the approach to possible therapies of pathologies arising during development because tile cerebellum is especially prone to such perturbation because of its late development

Spatiotemporal distribution of GABA_A receptor subunits within Layer II of mouse medial entorhinal cortex:implications for grid cell excitability

GABAergic parvalbumin-expressing (PV+) interneurons provide powerful inhibitory modulation of grid cells in layer II of the medial entorhinal cortex (MEC LII). However, the molecular machinery through which PV+ cells regulate grid cell activity is poorly defined. PV+ interneurons impart inhibitory modulation primarily via GABA-A receptors (GABAARs). GABAARs are pentameric ion channels assembled from a repertoire of 19 subunits. Multiple subunit combinations result in a variety of receptor subtypes mediating functionally diverse postsynaptic inhibitory currents. Whilst the broad expression patterns of GABAAR subunits within the EC have been reported, those expressed by individual MEC LII cell types, in particular grid cells candidates, stellate and pyramidal cells, are less well described. Stellate and pyramidal cells are distinguished by their selective expression of reelin (RE+) and calbindin (CB+) respectively. Thus, the overall aim of this study was to provide a high resolution analysis of the major (α and γ) GABAAR subunits expressed in proximity to somato-dendritic PV+ boutons, on RE+ and CB+ cells, using immunohistochemistry, confocal microscopy and quantitative RT-PCR (qPCR). Clusters immunoreactive for the α1 and γ2 subunits decorated the somatic membranes of both RE+ and CB+ cells and were predominantly located in apposition to clusters immunoreactive for PV and vesicular GABA transporter (VGAT), suggesting expression in GABAergic synapses innervated by PV interneurons. Although intense α2 subunit-immunopositive clusters were evident in hippocampal fields located in close proximity to the EC, no specific signal was detected in MEC LII RE+ and CB+ profiles. Immunoreactivity for the α3 subunit was detected in all RE+ somata. In contrast, only a sub-population of CB+ cells was α3 immunopositive. These included CB-α3 cells which were both PV+ and PV−. Furthermore, α3 subunit mRNA and immunofluorescence decreased significantly between P 15 and P 25, a period implicated in the functional maturation of grid cells. Finally, α5 subunit immunoreactivity was detectable only on CB+ cells, not on RE+ cells. The present data demonstrates that physiologically distinct GABAAR subtypes are selectively expressed by CB+ and RE+ cells. This suggests that PV+ interneurons could utilize distinct postsynaptic signaling mechanisms to regulate the excitability of these different, candidate grid cell sub-populations

Manage comfort preferences conflicts using a multi-agent system in an adaptive environment system

Managing comfort preferences conflicts of the different users and locals on an IoT adaptive system is a actual problem, this paper proposes a protocol and hierarchical rules to develop a multi-agent system to achieve a Adaptive Environment System that solves the management of conflicts in an autonomous way for the users and interdependent of the user schedules and routines.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Classification as an Approach To Requirements Analysis

Oassification schemes have proven immensely useful in computerized systems for problem solving in the physical and biological sciences. A typical example is found in the medical domain where various taxonomies have been created for diseases, symptOms, laboratory tests, drugs, and so forth. These taxonomies may be used for characterizing specific clinical situations in expert systems that assist physicians and other health professionals in diagnosis and treatment. Oassification can be divided into several phases. The activities in the first phase are to find a category structure which can fit observations. This phase is called "cluster analysis", or "typology", "learning", "clumping", "regionalization", etc., or "classification (construction)" in our paper, depending on the field to which it is applied. There are many approaches to this cluster analysis. These include approaches such as numerical taxonomy and conceptual clustering. Once this category structure has been established, the next phase is to classify new observations, that is, recognize them as members of one category or another. There are two different situations for the activities in this phase: 1) when the category structure is completely known, this kind of activity is called "classification", "indexing", or "classifying" in this paper, and 2) if category structure is partly known or only part of the information of the observation is known, this kind of activity is called "discriminant analysis" [AND73] [GOR81]. Oancey [CLA84] has characterized classification problem solving as making a selection from a set of pre-enumerated solutions (in contrast to constructing new solutions). If the problem solver has a priori knowledge of existing solutions and is able to relate these to the problem description by data abstraction and refinement, then the problem can be solved using classification. Other artificial intelligence researchers, especially those investigating machine learning, have developed new techniques such as conceptual clustering [MIC86] (in contrast to numerical/statistical clustering), which might be used for developing classification schemes for problem solving