Evidence map›Paper›PMID 25146130›Full record

ArticleJournal of visualized experiments : JoVE2014

Laser nanosurgery of cerebellar axons in vivo.

Anna L Allegra Mascaro, Leonardo Sacconi, Francesco Saverio Pavone

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Time-lapse changes ofNeural regeneration research · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Anna L Allegra MascaroEuropean Laboratory for Non-Linear Spectroscopy, University of Florence; allegra@lens.unifi.it.
Leonardo SacconiEuropean Laboratory for Non-Linear Spectroscopy, University of Florence; National Institute of Optics, National Research Council.
Francesco Saverio PavoneEuropean Laboratory for Non-Linear Spectroscopy, University of Florence; National Institute of Optics, National Research Council; Department of Physics and Astronomy, University of Florence; International Center for Computational Neurophotonics (ICON Foundation).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Only a few neuronal populations in the central nervous system (CNS) of adult mammals show local regrowth upon dissection of their axon. In order to understand the mechanism that promotes neuronal regeneration, an in-depth analysis of the neuronal types that can remodel after injury is needed. Several studies showed that damaged climbing fibers are capable of regrowing also in adult animals. The investigation of the time-lapse dynamics of degeneration and regeneration of these axons within their complex environment can be performed by time-lapse two-photon fluorescence (TPF) imaging in vivo. This technique is here combined with laser surgery, which proved to be a highly selective tool to disrupt fluorescent structures in the intact mouse cortex. This protocol describes how to perform TPF time-lapse imaging and laser nanosurgery of single axonal branches in the cerebellum in vivo. Olivocerebellar neurons are labeled by anterograde tracing with a dextran-conjugated dye and then monitored by TPF imaging through a cranial window. The terminal portion of their axons are then dissected by irradiation with a Ti:Sapphire laser at high power. The degeneration and potential regrowth of the damaged neuron are monitored by TPF in vivo imaging during the days following the injury.

Indexed as

AnimalsAxonsCerebellar CortexLaser TherapyMiceMicroscopy, FluorescenceNanotechnologyNeuronsTime-Lapse Imaging

Identifiers

PMID25146130
PMCPMC4437537

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.