ReviewFrontiers in cell and developmental biology2021
Ovary Development: Insights From a Three-Dimensional Imaging Revolution.
Review in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- Polycystic ovary syndrome (PCOS): current insights, emerging therapeutics, and future treatment strategies.Inflammopharmacology · 2026Review
- OoCount: a machine-learning-based approach to mouse ovarian follicle counting and classification†.Biology of reproduction · 2025Article
- Three-dimensional visualisation of human ovarian follicles using a whole-mount immunolabelling and optical tissue clearing method.Reproduction & fertility · 2025Article
- Single-cell-scale spatial transcriptome of the developing and adult mouse ovary.bioRxiv : the preprint server for biology · 2025Article
- Studying ovarian aging and its health impacts: modern tools and approaches.Genes & development · 2025Review
- Quercetin diminishes the apoptotic pathway of magnetite nanoparticles in rats' ovary: Antioxidant status and hormonal profiles.Environmental analysis, health and toxicology · 2024Article
- Beyond defence: Immune architects of ovarian health and disease.Seminars in immunopathology · 2024Review
- Rescue of follicle development after oocyte-induced ovary dysfunction and infertility in a model of POI.Frontiers in cell and developmental biology · 2023Article
- Article
- Review
- Aging conundrum: A perspective for ovarian aging.Frontiers in endocrinology · 2022Review
- Effects of PInternational journal of molecular sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The ovary is an indispensable unit of female reproduction and health. However, the study of ovarian function in mammals is hindered by unique challenges, which include the desynchronized development of oocytes, irregular distribution and vast size discrepancy of follicles, and dynamic tissue remodeling during each hormonal cycle. Overcoming the limitations of traditional histology, recent advances in optical tissue clearing and three-dimensional (3D) visualization offer an advanced platform to explore the architecture of intact organs at a single cell level and reveal new relationships and levels of organization. Here we summarize the development and function of ovarian compartments that have been delineated by conventional two-dimensional (2D) methods and the limits of what can be learned by these approaches. We compare types of optical tissue clearing, 3D analysis technologies, and their application to the mammalian ovary. We discuss how 3D modeling of the ovary has extended our knowledge and propose future directions to unravel ovarian structure toward therapeutic applications for ovarian disease and extending female reproductive lifespan.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.