Evidence map›Paper›PMID 36747698›Full record

ArticlebioRxiv : the preprint server for biology2023

Three-dimensional imaging and quantification of mouse ovarian follicles via optical coherence tomography.

Marcello Magri Amaral, Aixia Sun, Yilin Li, Chao Ren, Anh Blue Truong, Saumya Nigam, Zexu Jiao, Ping Wang, Chao Zhou

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Marcello Magri AmaralBiomedical Engineering Department, Washington University in St Louis, 1 Brookings Dr, St Louis, MO, USA.
Aixia SunPrecision Health Program, Michigan State University, East Lansing, MI, USA.
Yilin LiBiomedical Engineering Department, Washington University in St Louis, 1 Brookings Dr, St Louis, MO, USA.
Chao RenBiomedical Engineering Department, Washington University in St Louis, 1 Brookings Dr, St Louis, MO, USA.
Anh Blue TruongBiomedical Engineering Department, Washington University in St Louis, 1 Brookings Dr, St Louis, MO, USA.
Saumya NigamPrecision Health Program, Michigan State University, East Lansing, MI, USA.
Zexu JiaoDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, Tx, USA.
Ping WangPrecision Health Program, Michigan State University, East Lansing, MI, USA.
Chao ZhouBiomedical Engineering Department, Washington University in St Louis, 1 Brookings Dr, St Louis, MO, USA.
Washington University in St. Louis · USMichigan State University · USThe University of Texas Southwestern Medical Center · US

Funding

High throughput optical coherence tomography (OCT)-based imaging platform for label-free, non-invasive characterization of 3D tumor spheroids.R01EB025209 · NIBIB · WASHINGTON UNIVERSITY · PI ZHOU, CHAO · 2017 to 2021
$1.4M
NIBIB NIH HHS R01 EB025209
6 · The paper itself

Abstract

Ovarian tissue cryopreservation has been successfully applied worldwide for fertility preservation. Correctly selecting the ovarian tissue with high follicle loading for freezing and reimplantation increases the likelihood of restoring ovarian function, but it is a challenging process. In this work, we explore the use of three-dimensional spectral-domain optical coherence tomography (SD-OCT) to identify different follicular stages, especially primary follicles, compare the identifications with H&E images, and measure the size and age-related follicular density distribution differences in mice ovaries. We use the thickness of the layers of granulosa cells to differentiate primordial and primary follicles from secondary follicles. The measured dimensions and age-related follicular distribution agree well with histological images and physiological aging. Finally, we apply attenuation coefficient map analyses to significantly improve the image contrast and the contrast-to-noise ratio (p < 0.001), facilitating follicle identification and quantification. We conclude that SD-OCT is a promising method to noninvasively evaluate ovarian follicles.

Identifiers

PMID36747698
PMCPMC9900855
OpenAlexW4317776055

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.