例如:"lncRNA", "apoptosis", "WRKY"

Genetically targeted 3D visualisation of Drosophila neurons under Electron Microscopy and X-Ray Microscopy using miniSOG.

Sci Rep. 2016 Dec 13;6:38863
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
{{ author.authorName }}{{getOrganisationIndexOf(author)}} {{ author.authorName }}{{getOrganisationIndexOf(author)}}
+ et al

[No authors listed]

Author information
  • {{index+1}} {{ organisation }}

摘要


Large dimension, high-resolution imaging is important for neural circuit visualisation as neurons have both long- and short-range patterns: from axons and dendrites to the numerous synapses at terminal endings. Electron Microscopy (EM) is the favoured approach for synaptic resolution imaging but how such structures can be segmented from high-density images within large volume datasets remains challenging. Fluorescent probes are widely used to localise synapses, identify cell-types and in tracing studies. The equivalent EM approach would benefit visualising such labelled structures from within sub-cellular, cellular, tissue and neuroanatomical contexts. Here we developed genetically-encoded, electron-dense markers using miniSOG. We demonstrate their ability in 1) labelling cellular sub-compartments of genetically-targeted neurons, 2) generating contrast under different EM modalities, and 3) segmenting labelled structures from EM volumes using computer-assisted strategies. We also tested non-destructive X-ray imaging on whole Drosophila brains to evaluate contrast staining. This enabled us to target specific regions for EM volume acquisition.

KEYWORDS: {{ getKeywords(articleDetailText.words) }}

基因功能


  • {{$index+1}}.{{ gene }}

图表


原始数据


 保存测序数据
Sample name
Organism Experiment title Sample type Library instrument Attributes
{{attr}}
{{ dataList.sampleTitle }}
{{ dataList.organism }} {{ dataList.expermentTitle }} {{ dataList.sampleType }} {{ dataList.libraryInstrument }} {{ showAttributeName(index,attr,dataList.attributes) }}

文献解读