Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/143439
Title: Follicular Fluid
Author: Brinca, Ana Teresa
Ramalhinho, Ana Cristina
Sousa, Ângela
Oliani, António Hélio
Breitenfeld , Luiza
Passarinha, Luís A.
Gallardo, Eugénia
Keywords: human follicular fluid
metabolomics
polycystic ovary syndrome (PCOS)
reproduction
Medicine (miscellaneous)
Biochemistry, Genetics and Molecular Biology(all)
SDG 3 - Good Health and Well-being
Issue Date: 27-May-2022
Citation: Brinca, A. T., Ramalhinho, A. C., Sousa, Â., Oliani, A. H., Breitenfeld , L., Passarinha, L. A., & Gallardo, E. (2022). Follicular Fluid: A Powerful Tool for the Understanding and Diagnosis of Polycystic Ovary Syndrome. Biomedicines, 10(6), 1-27. Article 1254. https://doi.org/10.3390/biomedicines10061254
Abstract: Polycystic ovary syndrome (PCOS) represents one of the leading causes of anovulatory infertility and affects 5% to 20% of women worldwide. Until today, both the subsequent etiology and pathophysiology of PCOS remain unclear, and patients with PCOS that undergo assisted reproductive techniques (ART) might present a poor to exaggerated response, low oocyte quality, ovarian hyperstimulation syndrome, as well as changes in the follicular fluid metabolites pattern. These abnormalities originate a decrease of Metaphase II (MII) oocytes and decreased rates for fertilization, cleavage, implantation, blastocyst conversion, poor egg to follicle ratio, and increased miscarriages. Focus on obtaining high-quality embryos has been taken into more consideration over the years. Nowadays, the use of metabolomic analysis in the quantification of proteins and peptides in biological matrices might predict, with more accuracy, the success in assisted reproductive technology. In this article, we review the use of human follicular fluid as the matrix in metabolomic analysis for diagnostic and ART predictor of success for PCOS patients.
Description: The Associate Laboratory Institute for Health and Bioeconomy–i4HB (project LA/P/0140/2020), which are financed by National Funds from FCT/MCTES. This work was supported by operation Centro-01-0145-FEDER-000019-C4-Centro de Competências em Cloud Computing, cofinanced by the European Regional Development Fund (ERDF) through the Programa Operacional Regional do Centro (Centro 2020), in the scope of the Sistema de Apoio à Investigação Científica e Tecnológica-Programas Integrados de IC&DT. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Peer review: yes
URI: http://hdl.handle.net/10362/143439
DOI: https://doi.org/10.3390/biomedicines10061254
ISSN: 2227-9059
Appears in Collections:FCT: DQ - Artigos em revista internacional com arbitragem científica

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