Aging and bone health in individuals with developmental disabilities,”

Low bone mass density (BMD), a classical age-related health issue and a known health concern for fair skinned, thin, postmenopausal Caucasian women, is found to be common among individuals with developmental/intellectual disabilities (D/IDs). It is the consensus that BMD is decreased in both men and women with D/ID. Maintaining good bone health is important for this population as fractures could potentially go undetected in nonverbal individuals, leading to increased morbidity and a further loss of independence. This paper provides a comprehensive overview of bone health of adults with D/ID, their risk of fractures, and how this compares to the general aging population. We will specifically focus on the bone health of two common developmental disabilities, Down syndrome (DS) and cerebral palsy (CP), and will discuss BMD and fracture rates in these complex populations. Gaining a greater understanding of how bone health is affected in individuals with D/ID could lead to better customized treatments for these specific populations

Stress-Dependent Opioid And Adrenergic Modulation Of Newly Retrieved Fear Memory

Recent studies on the effect of stress on modulation of fear memory in our laboratory have uncovered endogenous opioid and adrenergic based modulation systems, working in concert, that limit the strengthening or weakening of newly acquired fear memory during consolidation under conditions of mild or intense stress, respectively. The present study sought to determine if similar stress-dependent modulation, mediated by endogenous opioid and adrenergic systems, occurs during reconsolidation of newly retrieved fear memory. Rats underwent contextual fear conditioning followed 24 h later by reactivation of fear memory; a retention test was administered the next day. Stress was manipulated by varying duration of recall of fear memory during reactivation. In the first experiment, vehicle or the opioid-receptor blocker naloxone was administered immediately after varied durations (30 or 120 s) of reactivation. The results indicate that (1) reactivation, in the absence of drug, has a marked effect on freezing behavior-as duration of reactivation increases from 30 to 120 s, freezing behavior and presumably fear-induced stress increases and (2) naloxone, administered immediately after 30 s (mild stress) or 120 s (intense stress) of reactivation, enhances or impairs retention, respectively, the next day. In the second experiment, naloxone and the g-adrenergic blocker propranolol were administered either separately or in combination immediately after 120 s (intense stress) reactivation. The results indicate that separate administration of propranolol and naloxone impairs retention, while the combined administration fails to do so. Taken together the results of the two experiments are consistent with a protective mechanism, mediated by endogenous opioid and adrenergic systems working in concert, that limits enhancement and impairment of newly retrieved fear memory during reactivation in a stress-dependent manner. (C) 2013 Elsevier Inc. All rights reserved

VennPlex--a novel Venn diagram program for comparing and visualizing datasets with differentially regulated datapoints.

With the development of increasingly large and complex genomic and proteomic data sets, an enhancement in the complexity of available Venn diagram analytical programs is becoming increasingly important. Current freely available Venn diagram programs often fail to represent extra complexity among datasets, such as regulation pattern differences between different groups. Here we describe the development of VennPlex, a program that illustrates the often diverse numerical interactions among multiple, high-complexity datasets, using up to four data sets. VennPlex includes versatile output features, where grouped data points in specific regions can be easily exported into a spreadsheet. This program is able to facilitate the analysis of two to four gene sets and their corresponding expression values in a user-friendly manner. To demonstrate its unique experimental utility we applied VennPlex to a complex paradigm, i.e. a comparison of the effect of multiple oxygen tension environments (1–20% ambient oxygen) upon gene transcription of primary rat astrocytes. VennPlex accurately dissects complex data sets reliably into easily identifiable groups for straightforward analysis and data output. This program, which is an improvement over currently available Venn diagram programs, is able to rapidly extract important datasets that represent the variety of expression patterns available within the data sets, showing potential applications in fields like genomics, proteomics, and bioinformatics

GIT2 Acts as a Potential Keystone Protein in Functional Hypothalamic Networks Associated with Age-Related Phenotypic Changes in Rats

The aging process affects every tissue in the body and represents one of the most complicated and highly integrated inevitable physiological entities. The maintenance of good health during the aging process likely relies upon the coherent regulation of hormonal and neuronal communication between the central nervous system and the periphery. Evidence has demonstrated that the optimal regulation of energy usage in both these systems facilitates healthy aging. However, the proteomic effects of aging in regions of the brain vital for integrating energy balance and neuronal activity are not well understood. The hypothalamus is one of the main structures in the body responsible for sustaining an efficient interaction between energy balance and neurological activity. Therefore, a greater understanding of the effects of aging in the hypothalamus may reveal important aspects of overall organismal aging and may potentially reveal the most crucial protein factors supporting this vital signaling integration. In this study, we examined alterations in protein expression in the hypothalami of young, middle-aged, and old rats. Using novel combinatorial bioinformatics analyses, we were able to gain a better understanding of the proteomic and phenotypic changes that occur during the aging process and have potentially identified the G protein-coupled receptor/cytoskeletal-associated protein GIT2 as a vital integrator and modulator of the normal aging process

BRET biosensor analysis of receptor tyrosine kinase functionality

Bioluminescence resonance energy transfer (BRET) is an improved version of earlier resonance energy transfer technologies used for the analysis of biomolecular protein interaction. BRET analysis can be applied to many transmembrane receptor classes, however the majority of the early published literature on BRET has focused on G protein-coupled receptor (GPCR) research. In contrast, there is limited scientific literature using BRET to investigate receptor tyrosine kinase (RTK) activity. This limited investigation is surprising as RTKs often employ dimerization as a key factor in their activation, as well as being important therapeutic targets in medicine, especially in the cases of cancer, diabetes, neurodegenerative and respiratory conditions. In this review, we consider an array of studies pertinent to RTKs and other non-GPCR receptor protein-protein signaling interactions; more specifically we discuss receptor-protein interactions involved in the transmission of signaling communication. We have provided an overview of functional BRET studies associated with the receptor tyrosine kinase (RTK) super family involving: neurotrophic receptors (e.g. tropomyosin-related kinase (Trk) and p75 neurotrophin receptor (p75NTR)); insulinotropic receptors (e.g. insulin receptor (IR) and insulin-like growth factor receptor (IGFR)) and growth factor receptors (e.g. ErbB receptors including the EGFR, the fibroblast growth factor receptor (FGFR), the vascular endothelial growth factor receptor (VEGFR) and the c-kit and platelet-derived growth factor receptor (PDGFR)). In addition, we review BRET-mediated studies of other tyrosine kinase-associated receptors including cytokine receptors, i.e. leptin receptor (OB-R) and the growth hormone receptor (GHR). It is clear even from the relatively sparse experimental RTK BRET evidence that there is tremendous potential for this technological application for the functional investigation of RTK biology

Aging and Bone Health in Individuals with Developmental Disabilities

Low bone mass density (BMD), a classical age-related health issue and a known health concern for fair skinned, thin, postmenopausal Caucasian women, is found to be common among individuals with developmental/intellectual disabilities (D/IDs). It is the consensus that BMD is decreased in both men and women with D/ID. Maintaining good bone health is important for this population as fractures could potentially go undetected in nonverbal individuals, leading to increased morbidity and a further loss of independence. This paper provides a comprehensive overview of bone health of adults with D/ID, their risk of fractures, and how this compares to the general aging population. We will specifically focus on the bone health of two common developmental disabilities, Down syndrome (DS) and cerebral palsy (CP), and will discuss BMD and fracture rates in these complex populations. Gaining a greater understanding of how bone health is affected in individuals with D/ID could lead to better customized treatments for these specific populations

Plurigon: three dimensional visualization and classification of high-dimensionality data

High-dimensionality data is rapidly becoming the norm for biomedical sciences and many other analytical disciplines. Not only is the collection and processing time for such data becoming problematic, but it has become increasingly difficult to form a comprehensive appreciation of high-dimensionality data. Though data analysis methods for coping with multivariate data are well-documented in technical fields such as computer science, little effort is currently being expended to condense data vectors that exist beyond the realm of physical space into an easily interpretable and aesthetic form. To address this important need, we have developed Plurigon, a data visualization and classification tool for the integration of high-dimensionality visualization algorithms with a user-friendly, interactive graphical interface. Unlike existing data visualization methods, which are focused on an ensemble of data points, Plurigon places a strong emphasis upon the visualization of a single data point and its determining characteristics. Multivariate data vectors are represented in the form of a deformed sphere with a distinct topology of hills, valleys, plateaus, peaks, and crevices. The gestalt structure of the resultant Plurigon object generates an easily-appreciable model. User interaction with the Plurigon is extensive; zoom, rotation, axial and vector display, feature extraction, and anaglyph stereoscopy are currently supported. With Plurigon and its ability to analyze high-complexity data, we hope to see a unification of biomedical and computational sciences as well as practical applications in a wide array of scientific disciplines. Increased accessibility to the analysis of high-dimensionality data may increase the number of new discoveries and breakthroughs, ranging from drug screening to disease diagnosis to medical literature mining

The effects of aging on the BTBR mouse model of autism spectrum disorder

Autism spectrum disorders (ASD) are complex, heterogeneous neurodevelopmental disorderscharacterized by alterations in social functioning, communicative abilities, and engagement inrepetitive or restrictive behaviors. The process of aging in individuals with autism and relatedneurodevelopmental disorders is not well understood, despite the fact that the number ofindividuals with ASD aged 65 and older is projected to increase by over half a millionindividuals in the next 20 years. To elucidate the effects of aging in the context of a modifiedcentral nervous system, we investigated the effects of age on the BTBR T+tf/j mouse, a wellcharacterized and widely used mouse model that displays an ASD-like phenotype. We found thata reduction in social behavior persists into old age in male BTBR T+tf/j mice. We employedquantitative proteomics to discover potential alterations in signaling systems that could regulateaging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue ofBTBR mice compared to age-matched wild-type controls revealed a significant decrease in brainderived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin,Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to theseproteins, including Neural synaptic plasticity regulation and Neurotransmitter secretionregulation. Taken together, these results contribute to our understanding of the effects of agingon an ASD-like mouse model in regards to both behavior and protein alterations, thoughadditional studies are needed to fully understand the complex interplay underlying aging inmouse models displaying an ASD-like phenotype

<i>Textrous!</i>: Extracting Semantic Textual Meaning from Gene Sets

<div><p>The un-biased and reproducible interpretation of high-content gene sets from large-scale genomic experiments is crucial to the understanding of biological themes, validation of experimental data, and the eventual development of plans for future experimentation. To derive biomedically-relevant information from simple gene lists, a mathematical association to scientific language and meaningful words or sentences is crucial. Unfortunately, existing software for deriving meaningful and easily-appreciable scientific textual ‘tokens’ from large gene sets either rely on controlled vocabularies (Medical Subject Headings, Gene Ontology, BioCarta) or employ Boolean text searching and co-occurrence models that are incapable of detecting indirect links in the literature. As an improvement to existing web-based informatic tools, we have developed <i>Textrous!</i>, a web-based framework for the extraction of biomedical semantic meaning from a given input gene set of arbitrary length. <i>Textrous!</i> employs natural language processing techniques, including latent semantic indexing (LSI), sentence splitting, word tokenization, parts-of-speech tagging, and noun-phrase chunking, to mine MEDLINE abstracts, PubMed Central articles, articles from the Online Mendelian Inheritance in Man (OMIM), and Mammalian Phenotype annotation obtained from Jackson Laboratories. <i>Textrous!</i> has the ability to generate meaningful output data with even very small input datasets, using two different text extraction methodologies (collective and individual) for the selecting, ranking, clustering, and visualization of English words obtained from the user data. <i>Textrous!</i>, therefore, is able to facilitate the output of quantitatively significant and easily appreciable semantic words and phrases linked to both individual gene and batch genomic data.</p></div