Evidence map›Paper›PMID 32190666›Full record

ArticleBioMed research international2020

Fast Localization and Sectioning of Mouse Locus Coeruleus.

Song Cao, Juan Li, Jie Yuan, Dexin Zhang, Tian Yu

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 43% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  5. Review
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.

Song CaoDepartment of Pain Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000 Guizhou, China.ORCID https://orcid.org/0000-0003-4619-9441
Juan LiDepartment of Pain Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000 Guizhou, China.
Jie YuanDepartment of Pain Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000 Guizhou, China.
Dexin ZhangDepartment of Pain Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000 Guizhou, China.
Tian YuGuizhou Key Laboratory of Anesthesia and Organ Protection, Zunyi Medical University, Zunyi, 563002 Guizhou, China.ORCID https://orcid.org/0000-0003-4378-0935
Zunyi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The locus nucleus (LC) is a multifunctional nucleus which is also the source of norepinephrine in the brain. To date, there is no simple and easy method to locate the small LC in brain sectioning. Here we report a fast, accurate, and easy-to-follow protocol for the localization of mice LC in frozen sectioning. After fixation and dehydration, the intact brains of adult mice were placed on a horizontal surface and vertically cut along the posterior margin of the bilateral cerebral cortex. In the coronal cutting plane, the aqueduct of midbrain can be seen easily with the naked eyes. After embedding the cerebellum part with optimal cutting temperature (OCT) compound, coronal brain slices were cut from the cutting plane, within 1 mm, the aqueduct of midbrain disappeared and the fourth ventricle appeared, then the brain slices contained LC and were collected. From the first collection, at ~200

Indexed as

AnimalsBrainCerebral CortexCryoultramicrotomyFemaleFluorescent Antibody TechniqueHistocytological Preparation TechniquesImmunohistochemistryLocus CoeruleusMaleMesencephalonMiceMice, Inbred C57BLNorepinephrineTyrosine 3-MonooxygenaseNorepinephrineTyrosine 3-Monooxygenase

Identifiers

PMID32190666
PMCPMC7071797
OpenAlexW3009089534

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.