Evidence map›Paper›PMID 37508859›Full record

ReviewBioengineering (Basel, Switzerland)2023

Bioengineered 3D Ovarian Models as Paramount Technology for Female Health Management and Reproduction.

Julieta S Del Valle, Susana M Chuva de Sousa Lopes

Open access · goldAbstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 16 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

2 authors at 1 institution in 2 countries.

Julieta S Del ValleDepartment of Anatomy and Embryology, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands.
Susana M Chuva de Sousa LopesDepartment of Anatomy and Embryology, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands.ORCID 0000-0003-3866-2803
Leiden University Medical Center · NL

Funding

European Research Council ERC-CoG-2016-725722
6 · The paper itself

Abstract

Ovarian dysfunction poses significant threats to the health of female individuals. Ovarian failure can lead to infertility due to the lack or inefficient production of fertilizable eggs. In addition, the ovary produces hormones, such as estrogen and progesterone, that play crucial roles not only during pregnancy, but also in maintaining cardiovascular, bone, and cognitive health. Decline in estrogen and progesterone production due to ovarian dysfunction can result in menopausal-associated syndromes and lead to conditions, such as osteoporosis, cardiovascular disease, and Alzheimer's disease. Recent advances in the design of bioengineered three-dimensional (3D) ovarian models, such as ovarian organoids or artificial ovaries, have made it possible to mimic aspects of the cellular heterogeneity and functional characteristics of the ovary in vitro. These novel technologies are emerging as valuable tools for studying ovarian physiology and pathology and may provide alternatives for fertility preservation. Moreover, they may have the potential to restore aspects of ovarian function, improving the quality of life of the (aging) female population. This review focuses on the state of the art of 3D ovarian platforms, including the latest advances modeling female reproduction, female physiology, ovarian cancer, and drug screening.

Indexed as

artificial ovaryin vitro folliculogenesisovarian cancerovarian organoidpersonalized medicinepluripotent stem cellsreproductive biologytissue engineeringtumoroids

Identifiers

PMID37508859
PMCPMC10376580
OpenAlexW4384340731

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.