![]() A major difficulty, however, is that it is currently not possible to predict quantitatively how developmental processes occurring at the molecular and subcellular levels determine the morphology of the entire dendritic arbor. Many molecules that participate in dendrite morphogenesis have been identified: transcription factors ( 17) extracellular matrix and integrins ( 18, 19) actin-associated proteins ( 20) microtubule motors such as dynein and kinesin ( 21, 22) microtubule regulators such as spastin ( 23), katanin ( 24), and γ-tubulin ( 25) and microRNAs such as bantam ( 14). Class IV cells are ideal for studying branching morphogenesis because they grow rapidly over 5 days of larval development, their branches are noncrossing due to self-avoidance mediated by the Down’s syndrome cell adhesion molecule ( 11– 13) and other molecules ( 14, 15), and they can be visualized using cell-specific labeling ( 7, 16). These nociceptive neurons form a highly branched meshwork just under the cuticle that senses puncture of the larva by the ovipositor barbs of parasitic wasps and initiates avoidance behaviors ( 9, 10). To investigate these rules, we have focused on dendrite morphogenesis in class IV dendritic arborization neurons in Drosophila, a model system for dendritogenesis ( 7, 8). While many molecules have been shown to play crucial roles in shaping dendrites, the underlying rules by which molecular interactions generate branched morphologies are not understood. These principles may generalize to branching of other neuronal cell types, as well as to branching at the subcellular and tissue levels. By incorporating these measured dynamics into an agent-based computational model, we showed that the complex and highly variable dendritic morphologies of these cells are a consequence of the stochastic dynamics of their dendrite tips. To elucidate these principles, we visualized the growth of dendrites throughout larval development of Drosophila sensory neurons and found that the tips of dendrites undergo dynamic instability, transitioning rapidly and stochastically between growing, shrinking, and paused states. However, the underlying principles by which molecular interactions generate branched morphologies are not understood. Many molecules have been shown to play crucial roles in shaping and maintaining dendrite morphology. Altered dendritic morphology is associated with neuronal diseases. Textrect (elpos,radx=.094,rady=.The highly ramified arbors of neuronal dendrites provide the substrate for the high connectivity and computational power of the brain. Textrect (elpos,radx=.094,rady=.05,lab=paste("Not Consented\n",nconsented)) Textrect (elpos,radx=.094,rady=.05,lab=paste("Consented\n",consented)) Textrect (elpos,radx=.094,rady=.05,lab=paste("Not Interested\n",ninterested)) ![]() Textrect (elpos,radx=.094,rady=.05,lab=paste("Interested\n",interested)) Textrect (elpos,radx=.094,rady=.05,lab=paste("Screening \n Incomplete\n",screened-(neligible eligible))) Textrect (elpos,radx=.094,rady=.05,lab=paste("Not Eligible\n",neligible)) Textrect (elpos,radx=.094,rady=.05,lab=paste("Eligible\n",eligible)) Textrect (elpos,radx=.094,rady=.05,lab=paste("Screened\n",screened)) It probably is not as nice as the one you show, but it has the main idea. I did what skullkey suggests here and then I cooked up this. I had an similar request for these types of charts every week.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |