Retinoic Acids Potentiate BMP9-Induced Osteogenic Differentiation of Mesenchymal Progenitor Cells

As one of the least studied bone morphogenetic proteins (BMPs), BMP9 is one of the most osteogenic BMPs. Retinoic acid (RA) signaling is known to play an important role in development, differentiation and bone metabolism. In this study, we investigate the effect of RA signaling on BMP9-induced osteogenic differentiation of mesenchymal progenitor cells (MPCs).Both primary MPCs and MPC line are used for BMP9 and RA stimulation. Recombinant adenoviruses are used to deliver BMP9, RARalpha and RXRalpha into MPCs. The in vitro osteogenic differentiation is monitored by determining the early and late osteogenic markers and matrix mineralization. Mouse perinatal limb explants and in vivo MPC implantation experiments are carried out to assess bone formation. We find that both 9CRA and ATRA effectively induce early osteogenic marker, such as alkaline phosphatase (ALP), and late osteogenic markers, such as osteopontin (OPN) and osteocalcin (OC). BMP9-induced osteogenic differentiation and mineralization is synergistically enhanced by 9CRA and ATRA in vitro. 9CRA and ATRA are shown to induce BMP9 expression and activate BMPR Smad-mediated transcription activity. Using mouse perinatal limb explants, we find that BMP9 and RAs act together to promote the expansion of hypertrophic chondrocyte zone at growth plate. Progenitor cell implantation studies reveal that co-expression of BMP9 and RXRalpha or RARalpha significantly increases trabecular bone and osteoid matrix formation.Our results strongly suggest that retinoid signaling may synergize with BMP9 activity in promoting osteogenic differentiation of MPCs. This knowledge should expand our understanding about how BMP9 cross-talks with other signaling pathways. Furthermore, a combination of BMP9 and retinoic acid (or its agonists) may be explored as effective bone regeneration therapeutics to treat large segmental bony defects, non-union fracture, and/or osteoporotic fracture

Connecting Network Properties of Rapidly Disseminating Epizoonotics

To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure.Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) 'connectivity', a model that integrated bio-physical concepts (the agent's transmission cycle, road topology) into indicators designed to measure networks ('nodes' or infected sites with short- and long-range links), and 2) 'contacts', which focused on infected individuals but did not assess connectivity.THE CONNECTIVITY MODEL SHOWED FIVE NETWORK PROPERTIES: 1) spatial aggregation of cases (disease clusters), 2) links among similar 'nodes' (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a "20:80" pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads.Geo-temporal constructs of Network Theory's nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable to revise theory and optimize control measures. Prospective studies that consider pre-outbreak predictors, such as connecting networks, are recommended

Neuroimmune crosstalk in the central nervous system and its significance for neurological diseases

The central nervous system (CNS) is now known to actively communicate with the immune system to control immune responses both centrally and peripherally. Within the CNS, while studies on glial cells, especially microglia, have highlighted the importance of this cell type in innate immune responses of the CNS, the immune regulatory functions of other cell types, especially neurons, are largely unknown. How neuroimmune cross-talk is homeostatically maintained in neurodevelopment and adult plasticity is even more elusive. Inspiringly, accumulating evidence suggests that neurons may also actively participate in immune responses by controlling glial cells and infiltrated T cells. The potential clinical application of this knowledge warrants a deeper understanding of the mutual interactions between neurons and other types of cells during neurological and immunological processes within the CNS, which will help advance diagnosis, prevention, and intervention of various neurological diseases. The aim of this review is to address the immune function of both glial cells and neurons, and the roles they play in regulating inflammatory processes and maintaining homeostasis of the CNS.Peer reviewe

A Neuron-Glial Perspective for Computational Neuroscience

International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells

Designing an iPad App to Monitor and Improve Classroom Behavior for Children with ADHD: iSelfControl Feasibility and Pilot Studies

Children with Attention Deficit/Hyperactivity Disorder (ADHD) receive approximately 80% of instruction in the general education classroom, where individualized behavioral management strategies may be difficult for teachers to consistently deliver. Mobile device apps provide promising platforms to manage behavior. This pilot study evaluated the utility of a web-based application (iSelfControl) designed to support classroom behavior management. iSelfControl prompted students every 'Center' (30-minutes) to self-evaluate using a universal token-economy classroom management system focused on compliance, productivity, and positive relationships. Simultaneously, the teacher evaluated each student on a separate iPad. Using Multi Level Modeling, we examined 13 days of data gathered from implementation with 5th grade students (N = 12) at a school for children with ADHD and related executive function difficulties. First, an unconditional growth model evaluated the overall amount of change in aggregated scores over time as well as the degree of systematic variation in scores within and across teacher-student dyads. Second, separate intercepts and slopes were estimated for teacher and student to estimate degree of congruency between trajectories. Finally, differences between teacher and student scores were tested at each time-point in separate models to examine unique 'Center' effects. 51% of the total variance in scores was attributed to differences between dyads. Trajectories of student and teacher scores remained relatively stable across seven time-points each day and did not statistically differ from each other. On any given day, students tended to evaluate their behaviors more positively (entered higher scores for themselves) compared to corresponding teacher scores. In summary, iSelfControl provides a platform for self and teacher evaluation that is an important adjunct to conventional classroom management strategies. The application captured teacher/student discrepancies and significant variations across the day. Future research with a larger, clinically diagnosed sample in multiple classrooms is needed to assess generalizability to a wider variety of classroom settings