Publications by authors named "A Gokhale"
The emerging picture of G protein-coupled receptor function suggests that the global signaling response is an integrated sum of a multitude of individual receptor responses, each regulated by their local protein environment. The beta 2 adrenergic receptor (B2AR) has long served as an example receptor in the development of this model. But the mechanism and the identity of the protein-protein interactions that govern the availability of receptors competent for signaling remains incompletely characterized.
View Article and Find Full Text PDFArticle Synopsis
- Rare inherited diseases caused by mutations in copper transporters (CTR1) lead to copper deficiency, which can cause severe neurological issues like seizures and neurodegeneration in infants.
- The study explores how neuronal cells react to copper deficiency using various genetic model systems, showing that the absence of CTR1 leads to disrupted cellular functions and a shift toward glycolysis.
- Key findings reveal that the activation of the mTORC1-S6K signaling pathway serves as a protective mechanism to enhance protein synthesis in response to copper deficiency, helping to mitigate some of the detrimental effects on neurons.
Objective: This report describes a root cause analysis of incorrect provider assignments and a standardized workflow developed to improve the clarity and accuracy of provider assignments.
Materials And Methods: A multidisciplinary working group involving housestaff was assembled. Key drivers were identified using value stream mapping and fishbone analysis.
We propose and analyze a continuous-time firing-rate neural network, the positive firing-rate competitive network (PFCN), to tackle sparse reconstruction problems with non-negativity constraints. These problems, which involve approximating a given input stimulus from a dictionary using a set of sparse (active) neurons, play a key role in a wide range of domains, including, for example, neuroscience, signal processing, and machine learning. First, by leveraging the theory of proximal operators, we relate the equilibria of a family of continuous-time firing-rate neural networks to the optimal solutions of sparse reconstruction problems.
View Article and Find Full Text PDF