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Record W1980291434 · doi:10.1071/rdv27n1ab176

176 BLOOD FLOW TO THE CORPUS LUTEUM AND PREOVULATORY FOLLICLE AFTER OVULATION INDUCTION DURING FIRST VERSUS SECOND WAVE IN WATER BUFFALO

2014· article· en· W1980291434 on OpenAlexaff
S. Caunce, D. Dadarwal, P. S. Brar, Jaswant Singh

Bibliographic record

VenueReproduction Fertility and Development · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCorpus luteumOvulationFollicleFollicular phaseLuteolysisArtificial inseminationLuteal phaseEstrous cycleInternal medicineOvaryEndocrinologyMedicineOvarian follicleAndrologyBiologyHormonePregnancy

Abstract

fetched live from OpenAlex

The objective of the study was to compare the blood flow to the corpus luteum (CL) and the preovulatory follicle in dairy buffalo (Bubalus bubalis) when ovulation was induced during the first (low to increasing progesterone levels) versus the second (luteal progesterone levels) follicular wave. We hypothesised that the wall of the first-wave dominant follicle will be less vascular compared with that of the second-wave follicle. The study was conducted during the summer months in Punjab, India. Ovulation was synchronized with prostaglandin F2a (PGF) IM followed by gonadotropin-releasing hormone (GnRH) IM 48 h later (Day 0) and buffaloes were randomised to first wave (FW; n = 6) and second wave (SW; n = 7) groups. FW group was given PGF on Days 6.5 and 7, and GnRH on Day 9.5 followed by AI (14–16 h after GnRH). The SW group was given GnRH on Day 7 (to induce ovulation of first-wave dominant follicle without luteolysis and synchronous emergence of next wave), PGF on Days 13.5 and 14, GnRH on Day 16.5 followed by artificial insemination. Transrectal colour Doppler ultrasonography (MyLab5 Vetwith 7.5 MHz transducer, Esaote S.p.A, Genoa, Italy) was performed daily and 20-s cineloops of each ovary were recorded under standardized gain controls. Images from the cineloops were processed using Fiji (ImageJ, National Institutes of Health, Bethesda, MD, USA) to calculate the area of blood flow (coloured area = vascular area, grey scale area = tissue area, and their ratio) for the preovulatory follicle (on the day before ovulation) and luteal tissue (on the day of PGF injection and 4 days post-ovulation). Data were analysed by t-test from the animals that ovulated one day before (n = 3) or the day of AI (n = 6) and had a functional CL at day 5 post-AI (FW n = 5, SW n = 4). FW follicles ovulated on 8.6 ± 0.3 days from wave emergence compared with SW follicles on 10.0 ± 0.6 days (P < 0.05) but were similar in size (i.e. follicular area on the day before ovulation did not differ between groups; P = 0.5). There was no difference in the blood flow area in the wall of preovulatory follicles (P = 0.4). Vascular area of follicles was strongly correlated with their diameter (r = 0.87). Follicles >13.5 mm in diameter had more blood flow in their wall than smaller follicles (P < 0.01). FW had a tendency (P = 0.07) for smaller luteal area on the day of PGF treatment (FW = 171 ± 24 mm2; SW = 332 ± 81 mm2) and tended (P = 0.06) to have less vascular area in the CL compared to SW group (FW = 30 ± 6 mm2; SW = 67 ± 17 mm2). There was no difference (P = 0.5) between the groups for vascular to CL area ratio. The area of luteal tissue and blood flow to the CL at Day 4 post-ovulation did not differ between the groups (P = 0.4). The diameter of the preovulatory follicle (11.6–15.7 mm) was not correlated with the cross-sectional area of developing CL at Day 4 post-ovulation (r = 0.09). In conclusion, vascularity to preovulatory follicles originating from the first wave v. second wave did not differ and preovulatory follicles =13.5 mm were more vascular than smaller follicles. Research was funded by NSERC; the first author was funded by scholarships from WCVM and GADVASU.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.198
Teacher spread0.178 · 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
Published2014
Admission routes1
Has abstractyes

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