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      Is FSH combined with equine chorionic gonadotropin able to modify lipid metabolism in bovine superstimulated antral follicles?

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          Abstract

          Lipid metabolism is essential for ensuring oocyte maturation and embryo development. β-Oxidized fatty acids (FA) are a potent source of energy for cells, particularly for bovine somatic follicular cells. Superstimulatory protocols using follicle stimulating hormone (FSH) or FSH combined with equine chorionic gonadotropin (eCG) are capable of stimulating the follicular microenvironment and drive the expression of biomarker genes associated with lipid metabolism in the cumulus-oocyte complex (COC) for better embryo development. In this study, we assesed the effects of FSH and FSH/eCG protocols on the expression of genes related to lipid metabolism in bovine granulosa cells (GCs). Further, we measured triglyceride levels in follicular fluid (FF) obtained from both superstimulatd and non-superstimulated cows (synchronized cows). In summary, superstimulation with gonadotropins maintained the TG levels in bovine FF and ensured GCs mRNA abundance of ACSL1, ACSL3, ACSL6, SCD, ELOVL5, ELOVL6, FASN, FADS2, and SREBP1. We, however, found the abundance of CPTIB mRNA to be lower in GCs obtained from cows subjected to FSH/eCG protocols than synchronized cows. In conclusion, the findings of this study showed that ovarian superstimulation around the preovulatory phase has a mild impact on the lipid metabolism in GCs.

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          A new mathematical model for relative quantification in real-time RT-PCR.

          M. Pfaffl (2001)
          Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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            Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data.

            Quantification of mRNAs using real-time polymerase chain reaction (PCR) by monitoring the product formation with the fluorescent dye SYBR Green I is being extensively used in neurosciences, developmental biology, and medical diagnostics. Most PCR data analysis procedures assume that the PCR efficiency for the amplicon of interest is constant or even, in the case of the comparative C(t) method, equal to 2. The latter method already leads to a 4-fold error when the PCR efficiencies vary over just a 0.04 range. PCR efficiencies of amplicons are usually calculated from standard curves based on either known RNA inputs or on dilution series of a reference cDNA sample. In this paper we show that the first approach can lead to PCR efficiencies that vary over a 0.2 range, whereas the second approach may be off by 0.26. Therefore, we propose linear regression on the Log(fluorescence) per cycle number data as an assumption-free method to calculate starting concentrations of mRNAs and PCR efficiencies for each sample. A computer program to perform this calculation is available on request (e-mail: bioinfo@amc.uva.nl; subject: LinRegPCR).
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              The Various Roles of Fatty Acids

              Lipids comprise a large group of chemically heterogeneous compounds. The majority have fatty acids (FA) as part of their structure, making these compounds suitable tools to examine processes raging from cellular to macroscopic levels of organization. Among the multiple roles of FA, they have structural functions as constituents of phospholipids which are the “building blocks” of cell membranes; as part of neutral lipids FA serve as storage materials in cells; and FA derivatives are involved in cell signalling. Studies on FA and their metabolism are important in numerous research fields, including biology, bacteriology, ecology, human nutrition and health. Specific FA and their ratios in cellular membranes may be used as biomarkers to enable the identification of organisms, to study adaptation of bacterial cells to toxic compounds and environmental conditions and to disclose food web connections. In this review, we discuss the various roles of FA in prokaryotes and eukaryotes and highlight the application of FA analysis to elucidate ecological mechanisms. We briefly describe FA synthesis; analyse the role of FA as modulators of cell membrane properties and FA ability to store and supply energy to cells; and inspect the role of polyunsaturated FA (PUFA) and the suitability of using FA as biomarkers of organisms.
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                Author and article information

                Contributors
                Role: conceptualizationRole: methodologyRole: formal analysisRole: data curationRole: softwareRole: writing original draft preparationRole: visualizationRole: investigation
                Role: investigation
                Role: investigation
                Role: investigation
                Role: investigation
                Role: investigation
                Role: conceptualizationRole: methodologyRole: formal analysisRole: funding acquisitionRole: supervisionRole: writing review and editing
                Journal
                Anim Reprod
                Anim Reprod
                ar
                Animal Reproduction
                Colégio Brasileiro de Reprodução Animal
                1806-9614
                1984-3143
                05 July 2024
                2024
                : 21
                : 2
                : e20230063
                Affiliations
                [1 ] originalDepartamento de Biofísica e Farmacologia, Instituto de Biociências, Universidade Estadual Paulista “Júlio de Mesquita Filho”, Botucatu, SP, Brasil
                [2 ] originalDepartamento de Ciência Animal, Universidade do Oeste Paulista, Presidente Prudente, SP, Brasil
                [3 ] originalDepartamento de Química e Bioquímica, Instituto de Biociências, Universidade Estadual Paulista “Júlio de Mesquita Filho”, Botucatu, SP, Brasil
                Author notes
                [* ]Corresponding author: castilho.anthony@ 123456gmail.com

                Conflicts of interest: The authors have no conflict of interest to declare.

                Author information
                http://orcid.org/0000-0001-9858-1306
                http://orcid.org/0000-0002-9859-0576
                http://orcid.org/0000-0002-7957-1660
                http://orcid.org/0000-0002-4280-9575
                http://orcid.org/0000-0001-5963-5930
                http://orcid.org/0000-0001-9137-7783
                http://orcid.org/0000-0003-1666-7021
                Article
                arAO20230063_EN 00205
                10.1590/1984-3143-AR2023-0063
                11253788
                39021495
                bbecad83-d242-44ea-be80-9af48c49260d
                Copyright © The Author(s).

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 May 2023
                : 31 July 2023
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 37
                Funding
                Funded by: FAPESP
                Award ID: 2013/11480-3
                Award ID: 2015/04505-5
                Funded by: CAPES
                Award ID: 001
                Categories
                Original Article

                triglycerides,follicle microenvironment,superovulation,gene expression,bovine

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