Evidence map›Paper›PMID 33958990›Full record

ArticleFrontiers in neuroanatomy2021

Application of the Mirror Technique for Three-Dimensional Electron Microscopy of Neurochemically Identified GABA-ergic Dendrites.

Petra Talapka, Zsolt Kocsis, Lívia Diána Marsi, Vera Etelka Szarvas, Zoltán F Kisvárday

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroanatomy, 2021. 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
0.2field-weighted citation impact, top 52% of its field
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, 3 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Petra TalapkaMTA-DE Neuroscience Research Group, University of Debrecen, Debrecen, Hungary.
Zsolt KocsisDepartment of Anatomy, Histology and Embryology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Lívia Diána MarsiDepartment of Anatomy, Histology and Embryology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Vera Etelka SzarvasDepartment of Anatomy, Histology and Embryology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Zoltán F KisvárdayMTA-DE Neuroscience Research Group, University of Debrecen, Debrecen, Hungary.
University of Debrecen · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the nervous system synaptic input arrives chiefly on dendrites and their type and distribution have been assumed pivotal in signal integration. We have developed an immunohistochemistry (IH)-correlated electron microscopy (EM) method - the "mirror" technique - by which synaptic input to entire dendrites of neurochemically identified interneurons (INs) can be mapped due preserving high-fidelity tissue ultrastructure. Hence, this approach allows quantitative assessment of morphometric parameters of synaptic inputs along the whole length of dendrites originating from the parent soma. The method exploits the fact that adjoining sections have truncated or cut cell bodies which appear on the common surfaces in a mirror fashion. In one of the sections the histochemical marker of the GABAergic subtype, calbindin was revealed in cell bodies whereas in the other section the remaining part of the very same cell bodies were subjected to serial section EM to trace and reconstruct the synaptology of entire dendrites. Here, we provide exemplary data on the synaptic coverage of two dendrites belonging to the same calbindin-D

Indexed as

3D-TEMcalbindindendritic synaptomeelectron microscopyGABA interneuronsmirror technique

Identifiers

PMID33958990
PMCPMC8093522
OpenAlexW3154251878

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.