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Record W3208273004 · doi:10.1111/rda.14035

Ultrasonographic observation in combination with progesterone monitoring for detection of ovulation in Labrador Retrievers

2021· article· en· W3208273004 on OpenAlexaboutno aff
Mei Tsuchida, Nako Komura, Tatsuya Yoshihara, Yuta Kawasaki, Daichi Sakurai, Hiroshi Suzuki

Bibliographic record

VenueReproduction in Domestic Animals · 2021
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsOvulationFollicleFollicular phaseCorpus luteumEstrous cycleInternal medicineOvarian follicleEndocrinologyAndrologyBiologyMedicineOvaryHormone

Abstract

fetched live from OpenAlex

Although it is well known that the ovulation occurs during a period of time after LH surge in dogs, there are few reports of observing the entire process of development, ovulation and luteinization of each follicle. This study aimed to detect the ovulation kinetics by ultrasonography in combination with progesterone monitoring and therefore identify the time-range of the ovulation process in a dog. Daily transabdominal ultrasonography and progesterone monitoring were conducted for 24 natural oestrus cycles of Labrador Retrievers. Ovarian follicles were observed as anechoic structure with contours before ovulation. Ovulation (follicular collapse) was defined as when follicles became cloudy and contours obscure by transabdominal ultrasonography. Ultrasound imaging was capable of identifying the day of ovulation for 94.7% (178/188) of the follicles through the appearance of collapsed follicle or corpus luteum. Ovulation was observed between LH 0 (the day of LH surge) and LH 5, with 48.0%, 33.5% and 15.0% for LH 2, LH 3 and LH 1, respectively. The total number of ovulations on LH 2 and LH 3 accounted for 81.5% (141/173) of the total ovulation in 24 cycles examined. Ovulation occurred in 12 cycles for 2 d and for 3 d in 12 cycles. Seventeen cycles (70.8%) with multiple days of ovulation showed the largest number of ovulations on LH 2. The average follicle diameter 3 d before the LH surge was less than 5 mm, then exceeded 5 mm 2 d before the LH surge. The average follicle diameter at the time of ovulation (follicular collapse) was 6.1 ± 1.0 mm (n = 118). On the day before ovulation, the average diameters of the follicles ovulated on LH 1, LH 2 and LH 3 were 5.0 ± 0.7 mm, 5.8 ± 1.2 mm and 6.2 ± 1.3 mm, respectively. There was a significant difference in the follicle diameter between LH1 and LH2 (p < .001), LH2 and LH3 (p < .05), and LH1 and LH3 (p < .001). Suggesting that it is difficult to estimate the ovulation day based on follicle size. This study showed that combination of ultrasonography with progesterone monitoring could follow follicular development, ovulation and luteinization of the ovary in Labrador Retrievers. The direct visualization of the ovulation was achieved in a non-invasive, labour-friendly way. Furthermore, the time-range of the ovulation process was clarified in a dog. These results may contribute to an accurate understanding of the optimum timing of mating and improved breeding efficiency, including artificial insemination and embryo transfer for Labrador Retrievers.

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 score0.389
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.081
GPT teacher head0.334
Teacher spread0.253 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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