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Circulating Concentrations of Progesterone and Estrogen in Weddell Seals During the Breeding Period and Early Pregnancy

2016· article· en· W4389034020 on OpenAlexaff
Amy L. Kirkham, Michelle R. Shero, Robert McCorkell, Shannon Atkinson, Jennifer M. Burns

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsRadioimmunoassayLactationPregnancyGestationAnimal scienceSeasonal breederEndocrine systemEndocrinologyEstrogenBiologyGestation periodWeaningInternal medicineHormoneMedicineEcology

Abstract

fetched live from OpenAlex

Weddell seals ( Leptonychotes weddellii ) experience a synchronized annual reproductive cycle. Females give birth in the austral spring (October‐November) and are bred towards the end of lactation in November and December; following a brief period of embryonic diapause, active gestation begins. To examine endocrine dynamics during the breeding period and early gestation, we handled adult, post‐parturient Weddell seals with known pupping dates ~1 week prior to weaning (29–44 days post‐partum, n=32) in mid‐November to mid‐December (Nov/Dec) and approximately 60 days later, mid‐January to mid‐February (Jan/Feb). A second group of previously parous females that did not pup in the current season (non‐parturient) were also handled at equivalent dates (n=21). Seals were weighed, body composition (lipid as %body mass) was determined using isotopic dilution, and serum progesterone concentrations were measured using commercial radioimmunoassays validated for use in Weddell seals. Total estrogens were also measured by validated radioimmunoassay in a representative subset of animals. In Jan/Feb, transrectal ultrasonography was used to determine pregnancy status. Serum progesterone concentrations in Nov/Dec study animals fell into two distinct groups: a low‐concentration group, with values ranging from 0.80 to 2.50 ng•mL −1 (mean±SEM = 1.65±0.08 ng•mL −1 , n=26), and a high‐concentration group, with values between 20.60 and 146.40 ng•mL −1 (59.76±6.40 ng•mL −1 , n=27). Total estrogens were elevated in low progesterone seals (163.59±12.98 pg•mL −1 , n=8) relative to those with high progesterone (95.71 ±12.09 pg•mL −1 , n= 4) (t‐test, p value= 0.004). As elevated progesterone concentrations indicate that ovulation has occurred, we examined the likelihood that animals’ progesterone levels were in the high group using binomial logistic regressions to determine what factors may influence ovulation timing in Weddell seals. Females that did not give birth were more likely to exhibit high progesterone at later calendar dates, with no detectable effects of mass or condition. Relative to non‐parturient seals, post‐parturient seals exhibited low progesterone later in the season. The likelihood of high progesterone increased with calendar date as well as days since parturition in these females, suggesting seals that give birth later in the pupping period ovulate at fewer days post‐partum than those that give birth early. All Jan/Feb study animals had progesterone levels greater than 10 ng•mL −1 , and there were no differences in progesterone (85.17±7.89ng•mL −1 , n=48) or estrogen concentrations (57.70± 2.95 pg•mL −1 , n=12) between females that were detectably pregnant and those that were not. This study shows that timing of ovulation in post‐parturient Weddell seals is not driven solely by parturition date, and that circulating progesterone and estrogen concentrations are not likely clear indicators of early pregnancy in this species. Support or Funding Information This research was funded by NSF award ANT‐1246463 to JMB and JWT and by an Institutional Development Award (IDeA) from the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number P20GM103395. The content is solely the responsibility of the authors and does not necessarily reflect the official views of the NIH.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2016
Admission routes1
Has abstractyes

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