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Krishnagopal, S.

Publications and source records attributed to Krishnagopal, S..

2 recordsLinked to original sources

A novel maxillofacial technique to deliver drugs to the visual pathway, the optic nerve and the retina using the glymphatic system.

The blood neural barriers are formidable barriers that prevent delivery of drugs into the eye and the brain. Currently, large biologics are used for treating many diseases of the eye and the brain. But the blood retinal barrier and the blood brain barrier prevent entry of these useful drugs into the eye and the brain respectively. Hence, there is a need for a drug delivery technique to bypass these natural barriers. Bevacizumab (Avastin) is a full length humanized monoclonal antibody with a molecular weight of 149kda. It binds to circulating vascular endothelial growth factor A and prevents interaction with vascular endothelial growth receptors. This results in blocking endothelial response and tumor vascularization. Bevacizumab is used to prevent choroidal neovascularization in age related macular degeneration and to prevent retinal neovascularization in diabetic retinopathy. It is also used for treating certain types of brain cancer. But it crosses neither the blood retinal barrier nor the blood brain barrier. This in vivo mouse study assessed the delivery of a commercial formulation of bevacizumab into the retina of mice using different ocular techniques like topical drops, subconjunctival injection, intravitreal injection and a novel maxillofacial technique. The objective was to assess whether the novel maxillofacial drug delivery technique could deliver drugs into the retina and to compare the efficacy of the maxillofacial technique with the mentioned ocular techniques. The distribution of bevacizumab was further compared with retinoschisin which is a small protein with a molecular weight of 24kda. Intravitreal injection and maxillofacial technique were effective in delivering drugs into the retina. In addition, the maxillofacial technique could target the brain including regions involved in the visual pathway and the optic nerve. The glymphatic pathway could also be targeted for drug delivery. Drug was also detected in the contralateral optic nerve and retina. Based on our study findings, we propose a new concept to explain the presence of the drug in the contralateral eye. We propose that after maxillofacial drug delivery, early distribution of the drug can occur in the CSF at the optic chiasma from the brain via the glymphatic system. In the case of the intravitreal injection, the drug from the experimental eye may be cleared through the glymphatic pathway of the ipsilateral optic nerve into the CSF surrounding the nerve. The crossover of the ipsilateral optic nerve fibers at the optic chiasma can result in further distribution of the drug in the CSF at the optic chiasma. From the region of the optic chiasma, the drug can distribute into the CSF surrounding the contralateral optic nerve. The drug can be then distributed into the contralateral optic nerve through the glymphatic pathway and be delivered into the contralateral eye. The drug can be further cleared into the aqueous of the contralateral eye through the anterior clearance pathway.

neuroscience↗

A rapid and efficient learning rule for biological neural circuits

The dominant view in neuroscience is that changes in synaptic weights underlie learning. It is unclear, however, how the brain is able to determine which synapses should change, and by how much. This uncertainty stands in sharp contrast to deep learning, where changes in weights are explicitly engineered to optimize performance. However, the main tool for that, backpropagation, has two problems. One is neuro-science related: it is not biologically plausible. The other is inherent: networks trained with this rule tend to forget old tasks when learning new ones. Here we introduce the Dendritic Gated Network (DGN), a variant of the Gated Linear Network, which offers a biologically plausible alternative to backpropagation. DGNs combine dendritic gating (whereby interneurons target dendrites to shape neuronal responses) with local learning rules to yield provably efficient performance. They are significantly more data efficient than conventional artificial networks, and are highly resistant to forgetting. Consequently, they perform well on a variety of tasks, in some cases better than backpropagation. Importantly, DGNs have structural and functional similarities to the cerebellum, a link that we strengthen by using in vivo two-photon calcium imaging to show that single interneurons suppress activity in individual dendritic branches of Purkinje cells, a key feature of the model. Thus, DGNs leverage targeted dendritic inhibition and local learning - two features ubiquitous in the brain - to achieve fast and efficient learning.

neuroscience↗