Our data suggest that the VEGF gene may play a role in the development of RA

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Synapses grow, prune, and remodel throughout development, experience, and disease. This structural plasticity can destabilize information transfer in the nervous system. However, neural activity remains stable throughout life, implying that adaptive countermeasures exist that maintain neurotransmission within proper physiological ranges. Aberrant synaptic structure and function have been associated with a variety of neural diseases, including Fragile X syndrome, autism, and intellectual disability. We have screened 300 mutants in Drosophila larvae of both sexes for defects in synaptic growth at the neuromuscular junction, identifying 12 mutants with severe reductions or enhancements in synaptic growth. Remarkably, electrophysiological recordings revealed that synaptic strength was unchanged in all but one of these mutants compared with WT. We used a combination of genetic, anatomical, and electrophysiological analyses to illuminate three mechanisms that stabilize synaptic strength despite major disparities in synaptic growth. These include compensatory changes in (1) postsynaptic neurotransmitter receptor abundance, (2) presynaptic morphology, and (3) active zone structure. Together, this characterization identifies new mutants with defects in synaptic growth and the adaptive strategies used by synapses to homeostatically stabilize neurotransmission in response.This study reveals compensatory mechanisms used by synapses to ensure stable functionality during severe alterations in synaptic growth using the neuromuscular junction of Drosophila melanogaster as a model system. Through a forward genetic screen, we identify mutants that exhibit dramatic undergrown or overgrown synapses yet express stable levels of synaptic strength, with three specific compensatory mechanisms discovered. Thus, this study reveals novel insights into the adaptive strategies that constrain neurotransmission within narrow physiological ranges while allowing considerable flexibility in overall synapse number. More broadly, these findings provide insights into how stable synaptic function may be maintained in the nervous system during periods of intensive synaptic growth, pruning, and remodeling.

This study presents an improved discrete Kalman filter for simultaneously estimating both all state variables and the unknown road roughness input for a vehicle suspension control system that plays a key role in the ride quality and handling performance while driving the vehicle. The suspension system is influenced by the road roughness input, which causes undesirable vibrations associated with vehicle instability. It is therefore important to estimate the road roughness and state variables information when designing the model-based controller for the vehicle suspension control system associated with the vehicle’s vertical dynamics. However, the implementation of conventional estimation theories for the suspension control system is challenging because the road roughness acts as an unknown input and is difficult to be measured or estimated while driving. This study presents an improved Kalman filter with unknown input, which can simultaneously estimate the state variables and road roughness without any prior information about the vehicle suspension control system. The proposed road roughness input estimator is evaluated by using an in-vehicle test bed with a laser-type profilometer. Finally, the state estimation performance of the proposed estimator for a vehicle suspension control system is validated by using CarSim software.