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Two Modes of Auditory Hair Cell Loss following Acoustic Overstimulation in the Avian Inner Ear

Authors: T, Nakagawa; H, Yamane; S, Shibata; M, Takayama; K, Sunami; Y, Nakai;

Two Modes of Auditory Hair Cell Loss following Acoustic Overstimulation in the Avian Inner Ear

Abstract

To determine the type of cell death occurring and how the removal of damaged cells proceeds following overstimulation, we examined chick basilar papillae using an in situ DNA nick end labeling method and transmission electron microscopy. Two distinct modes of hair cell loss were identified. First, hair cells which had not progressed into typical cell death processes, apoptosis or necrosis, were deleted by extrusion from the epithelium just after sound exposure. Second, hair cells manifested degeneration through the process of apoptosis, then further deterioration within the epithelium after the beginning of the process of hair cell regeneration. The latter mode may contribute to the following repair processes.

Keywords

Acoustic Stimulation, Cell Death, Hearing Loss, Noise-Induced, Cell Movement, Hair Cells, Auditory, Animals, Epithelial Cells, Chickens, Basilar Membrane

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
31
Average
Top 10%
Top 10%
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