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Record W2775133519 · doi:10.1071/rdv30n1ab4

4 Relationship Between Ovarian Vascularity, Cumulus–Oocyte Morphology and Luteal Development in Four-Month-Old Calves After FSH Stimulation

2017· article· en· W2775133519 on OpenAlexaff
S. Caunce, Ana Rita Tavares Krause, F. C. F. Dias, Gregory P. Adams, Jaswant Singh

Bibliographic record

VenueReproduction Fertility and Development · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVascularityLuteal phaseFollicular phaseFollicleMedicineEstrous cycleInternal medicineEndocrinologyAndrologyPathology

Abstract

fetched live from OpenAlex

The objectives of this study were to determine the effect of LH on the blood flow to the ovaries of 4-month-old calves after 2 FSH stimulation protocols, and to examine the relationship between ovarian vascularity after superstimulation to the morphology of the cumulus–oocyte complexes (COC) and luteal function. We hypothesise that ovarian vascularity (detected by 3-dimensional (3D) analysis of Doppler ultrasound cineloops) will increase in response to LH, and the magnitude of change in vascularity would be predictive of (1) a greater proportion of expanded COC, (2) greater development of luteal tissue volume and vascularity at 3 and 7 days after follicle aspiration, and (3) higher levels of plasma progesterone. Ovarian superstimulation was initiated at the beginning of an induced follicular wave in 4-month-old beef calves (n = 16), and beef cattle >16 months of age (control group, adults; n = 8) using either a traditional 4-day or an extended 7-day FSH protocol (n = 8 calves and n = 4 controls per group). Power Doppler ultrasound cineloops were recorded immediately before (i.e. 12 h after the last FSH treatment) and 24 h after LH treatment (before ultrasound-guided follicular aspiration for oocyte collection) to assess ovarian vascularity, and 3 and 7 days after follicular aspiration to assess luteal tissue volume and vascularity. Video segments were analysed in Fiji and Imaris software to obtain the 3D ovarian vascularity index (ratio of blood flow volume to tissue volume). The ovarian vascularity index tended to increase >1.7-fold in response to exogenous LH in both prepubertal calves (pre-LH 1.5 ± 0.4% v. post-LH 2.6 ± 0.7%; P = 0.08) and adult cattle (pre-LH 2.2 ± 0.6% v. post-LH 4.7 ± 0.9%; P = 0.07). Calves with a recovery of >75% of expanded COC had a higher ovarian vascularity index (10.7 ± 2.6% v. 4.8 ± 1.6%; P = 0.06) and luteal vascularity index (15.7 ± 4.5% v. 5.7 ± 2.1%; P < 0.05) 7 days after aspiration than those with <75% expanded COC. Calves in the 7-day FSH protocol had >10-fold higher concentration of plasma progesterone on Day 3 (12.7 ± 7.3 ng mL-1v. 1.2 ± 0.4 ng mL-1; P < 0.05) and Day 5 (50.6 ± 28.0 ng mL-1v. 4.5 ± 1.0 ng mL-1; P < 0.05), and ~2-fold higher luteal vascularity index at 7 days after follicle aspiration (13.7 ± 4.6% v. 7.7 ± 2.8%; P < 0.05) than calves in the 4-day FSH protocol, whereas no difference (P > 0.05) was found in control (adult) animals. In conclusion, there was an increase in ovarian vascularity resulting from LH treatment in prepubertal calves and adult cattle. A greater proportion of expansion of COC at 24 h after LH treatment (an indicator of follicular maturation) was related to higher ovarian and luteal vascularity on Day 7 after collection in prepubertal calves, but not in adults. Luteal vascularity on Day 3 was reflective of plasma progesterone concentration, and prepubertal calves in the 7-day FSH protocol had greater plasma progesterone than calves in the 4-day FSH protocol. The use of FSH in calves allows a greater number of follicles for oocyte collection as it does in adult cattle. Research was supported by an NSERC grant.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.073
GPT teacher head0.278
Teacher spread0.205 · 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 designObservational
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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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