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Jin hui Chen

Researcher at Washington University in St. Louis

Publications -  8
Citations -  894

Jin hui Chen is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Slit & Axon guidance. The author has an hindex of 3, co-authored 3 publications receiving 864 citations. Previous affiliations of Jin hui Chen include Chinese Academy of Sciences.

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Vertebrate Slit, a Secreted Ligand for the Transmembrane Protein Roundabout, Is a Repellent for Olfactory Bulb Axons

TL;DR: The isolation of vertebrate homologs of the Drosophila slit gene are reported and it is shown that Slit protein binds to the transmembrane protein Roundabout (Robo), establishing a ligand-receptor relationship between two molecules important for neural development and suggesting a role for Slit in olfactory bulb axon guidance.
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The mouse SLIT family: secreted ligands for ROBO expressed in patterns that suggest a role in morphogenesis and axon guidance.

TL;DR: It is demonstrated that the mouse SLIT1 protein can bind ROBO1, a transmembrane receptor implicated in axon guidance, and the unique expression pattern in limb and other organs indicates additional potential functions of the Slit gene family.
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The N-terminal leucine-rich regions in Slit are sufficient to repel olfactory bulb axons and subventricular zone neurons.

TL;DR: The results indicate that the same LRRs are sufficient for guiding both axon projection and neuronal migration and suggest that the other regions in the Slit proteins may be involved in regulating the diffusion and distribution of theSlit proteins.
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Conformal optical black hole for cavity

TL;DR: In this paper , an optical black hole (OBH) cavity based on transformation optics is proposed and demonstrated, where the radiation loss of all WGMs in OBH cavity is completely inhibited by an infinite wide potential barrier, and the WGM field outside the cavity is revealed to follow $1/r^\alpha$ decay rule based on conformal mapping.
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Towards integrated mode-division demultiplexing spectrometer by deep learning

TL;DR: In this paper , an ultracompact mode-division demultiplexing spectrometer that includes branched waveguide structures and graphene-based photodetectors is proposed, which realizes simultaneously spectral dispersing and light fields detecting.