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Record W2053261923 · doi:10.3168/jds.2014-8444

Short communication: Factors affecting hair cortisol concentrations in lactating dairy cows

2014· article· en· W2053261923 on OpenAlexafffund
T.A. Burnett, A.M.L. Madureira, B.F. Silper, Audrey Nadalin, A.M. Tahmasbi, D. M. Veira, R.L.A. Cerri

Bibliographic record

VenueJournal of Dairy Science · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsSalivaFecesBlood samplingAnimal scienceBreedBlood collectionHydrocortisoneEndocrinologyInternal medicineBiologyChemistryMedicine

Abstract

fetched live from OpenAlex

Cortisol has long been used as a marker of the stress response in animals. Cortisol can be analyzed from different media, most notably from the blood, saliva, and feces; however, the collection of cortisol from some of these media requires invasive procedures or excessive handling of the animals. Furthermore, it is not possible to capture long-term increases in circulating concentrations of cortisol from the blood, saliva, or feces. Hair cortisol has been found to be a reliable alternative for measuring chronic stress. With this emerging measure, appropriate sampling methodology must be developed and validated. The aim of this study was to determine the effects of hair color, sampling location, and processing method on cortisol concentrations in hair from lactating black and white Holstein cows (n=18). Furthermore, we aimed to measure the hair growth rates at different body locations (n=12) and test hair cortisol levels when resampled over short intervals (n=37). Both black- and white-colored hair was collected from the shoulder, top line, hip, and tail switch of Holsteins; due to breed characteristics only white hair was harvested from the tail switch. All samples were cleaned with water and isopropanol, and then ground in a ball mill or finely cut with scissors once dry. Cortisol was extracted with methanol before being measured using a commercially available ELISA kit. Concentrations of cortisol were greater in white than in black hair (7.8 ± 1.1 vs. 3.8 ± 1.1 pg/mg). When only white samples were analyzed, hair from the tail switch had more cortisol than hair from the shoulder (11.0 ± 1.2 vs. 6.2 ± 1.2 pg/mg), whereas no difference was found when compared with the hip and top line. Samples ground with a ball mill had greater concentrations of cortisol extracted than those minced with scissors (10.4 ± 1.2 vs. 4.7 ± 1.2 pg/mg). The growth rate of hair was significantly greater at the tail switch compared with the hip and shoulder (0.51 ± 0.05 vs. 0.04 ± 0.05 vs. 0.03 ± 0.05 mm/d). When hair was collected every 3 wk after calving, a tendency was detected for multiparous cows to have greater concentrations of hair cortisol and significantly greater concentrations of cortisol on d 0 and 21 after calving compared with d 42, 84, and 126. In Holsteins, the hair on the tail switch is always white, grows more rapidly than other sites, and is sensitive enough to capture changes in cortisol over intervals as short as 3 wk, making it the ideal location for measuring hair cortisol.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.300
Teacher spread0.280 · 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

Citations132
Published2014
Admission routes2
Has abstractyes

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