Evidence map›Paper›PMID 29782020›Full record

ArticleJournal of visualized experiments : JoVE2018

Whole Mount Immunofluorescence and Follicle Quantification of Cultured Mouse Ovaries.

Vera D Rinaldi, Jordana C Bloom, John C Schimenti

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In one paragraph

Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

3 authors.

Vera D RinaldiDepartment of Biomedical Sciences, Cornell University; vdr4@cornell.edu.
Jordana C BloomDepartment of Molecular Biology and Genetics, Cornell University.
John C SchimentiDepartment of Biomedical Sciences, Cornell University; Department of Molecular Biology and Genetics, Cornell University.

Funding

Genetics of recombination/genomic instability in miceR01GM045415 · NIGMS · JACKSON LABORATORY · PI SCHIMENTI, JOHN C · 1992 to 2016
$4.9M
Research and Career Training in Vertebrate Developmental GenomicsT32HD057854 · NICHD · CORNELL UNIVERSITY · PI SCHIMENTI, JOHN C · 2010 to 2020
$1.3M
Broad wavelength range Zeiss 780 NLO/confocal system for the Cornell Imaging CoreS10OD018516 · OD · CORNELL UNIVERSITY · PI ZIPFEL, WARREN R · 2014 to 2014
$834k
NICHD NIH HHS T32 HD057854NIGMS NIH HHS R01 GM045415NIH HHS S10 OD018516
6 · The paper itself

Abstract

Research in the field of mammalian reproductive biology often involves evaluating the overall health of ovaries and testes. Specifically, in females, ovarian fitness is often assessed by visualizing and quantifying follicles and oocytes. Because the ovary is an opaque three-dimensional tissue, traditional approaches require laboriously slicing the tissue into numerous serial sections in order to visualize cells throughout the entire organ. Furthermore, because quantification by this method typically entails scoring only a subset of the sections separated by the approximate diameter of an oocyte, it is prone to inaccuracy. Here, a protocol is described that instead utilizes whole organ tissue clearing and immunofluorescence staining of mouse ovaries to visualize follicles and oocytes. Compared to more traditional approaches, this protocol is advantageous for visualizing cells within the ovary for numerous reasons: 1) the ovary remains intact throughout sample preparation and processing; 2) small ovaries, which are difficult to section, can be examined with ease; 3) cellular quantification is more readily and accurately achieved; and 4) the whole organ imaged.

Indexed as

AnimalsCell Culture TechniquesFemaleFluorescent Antibody TechniqueMiceOvarian Follicle

Identifiers

PMID29782020
PMCPMC6101098

What OpenQuestion holds

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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.