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Record W1988966398 · doi:10.1071/rdv20n1ab241

241 STRATEGIES TO IMPROVE GLUTATHIONE CONTENT OF <i>IN VITRO</i> -MATURED BOVINE OOCYTES

2007· article· en· W1988966398 on OpenAlexaboutno aff
Eliza Curnow, John P. Ryan, DM Saunders, Eric Hayes

Bibliographic record

VenueReproduction Fertility and Development · 2007
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsGlutathioneBlastocystOocyteAndrologyIn vitro maturationChemistryFetal bovine serumOogenesisHuman fertilizationBiologyEmbryogenesisIn vitroBiochemistryEmbryoEnzymeMedicineAnatomyCell biology

Abstract

fetched live from OpenAlex

Glutathione is the main non-enzymatic defense against oxidative stress and a critical part of oocyte maturation and normal fertilization. Our aim was to test different strategies to manipulate cellular glutathione (GSH) content of bovine in-vitro -matured (IVM) oocytes and study the development of embryos produced from such oocytes. The reducing agents lipoic acid (LA, intracellular) and dihydrolipoic acid (DHLA, extracellular) were compared to the cell-permeable reduced glutathione (GSH) donor glutathione ethyl ester (OET) for their effect on oocyte GSH content, oocyte maturation, and blastocyst development (OET only). Reagents were purchased from Sigma (St. Louis, MO, USA) unless stated otherwise. Cumulus–oocyte complexes (COCs) were aspirated from abattoir-derived ovaries and matured for 24 h in a humidified atmosphere of 6% CO2 at 38.5°C in modified tissue culture medium (mTCM199) supplemented with 2% (LA, DHLA) or 10% (OET) fetal calf serum (FCS; Gibco, Grand Island, NY, USA), 0.1 IU bLH and 0.1 IU bFSH (Sioux Biochemicals, Sioux City, IA, USA). COCs were matured in the presence of either LA (100 µm) or DHLA (100 µm) alone or in combination with L-cystine (CYS; 0.6 mm), CYS alone, or OET at 1, 3, and 5 mm. COCs matured under control and experimental conditions were denuded of cumulus cells (40 IU hyaluronidase) and scored for maturity. GSH content of MII oocytes was determined by colorimetric assay (Northwest Life Science Specialties, LLC, Vancouver, WA, USA). Oocytes matured in OET were inseminated with frozen/thawed bull sperm (2 × 106 mL-1), cultured to the blastocyst stage (COOK bovine medium, COOK Australia, Brisbane, Queensland, Australia), and subjected to differential cell count (propidium iodide/Hoechst). GSH levels (mean ± SEM) and developmental data (percentage) are expressed for n = 18–73 oocytes or embryos and were analyzed by ANOVA or chi-square test (significance, P = 0.05). LA alone failed to increase oocyte GSH content over 2% FCS control levels (6.98 ± 0.22 pmol/oocyte v . 5.26 ± 0.4 pmol/oocyte). DHLA alone significantly increased oocyte GSH content (9.64 ± 0.8 pmol/oocyte) compared to both LA and controls (10% FCS; 4.78 ± 0.36 pmol/oocyte). CYS alone (10.18 ± 0.58 pmol/oocyte) or in combination with LA (10.84 ± 0.37 pmol/oocyte) or DHLA (9.75 ± 0.66 pmol/oocyte) significantly increased GSH compared to controls. GSH content of MII oocytes matured in 5 mm OET (8.35 ± 0.35 pmol/oocyte) was significantly higher compared to control (5.07 ± 0.32 pmol/oocyte), 1 mm (4.21 ± 0.18 pmol/oocyte), and 3 mm (7.12 ± 0.35 pmol/oocyte) OET treatments. Maturation rates of oocytes were significantly reduced in 2% FCS (51.1–72%) compared to 10% FCS (90.5%). OET treatment (1–5 mm) did not significantly alter maturation rate compared to control (75–89.8%). Blastocyst development of IVM oocytes treated with 1 mm OET (22.5%) was significantly lower compared to 3 mm (42.3%) and 5 mm (41.1%) OET but not to control (33.6%). Blastocysts from IVM oocytes treated with 5 mm OET had significantly higher cell counts compared to controls (126 ± 6.4 cells v . 100.8 ± 5.2 cells). Bovine IVM is a valuable model for testing the efficacy of various strategies to increase oocyte cellular GSH. Both strategies improve oocyte GSH levels, and an increase in blastocyst cell number occurred with GSH donor treatment (5 mm OET).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.281
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2007
Admission routes1
Has abstractyes

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