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Record W2086133534 · doi:10.1371/journal.pone.0018053

Effect of Different Factors on Proliferation of Antler Cells, Cultured In Vitro

2011· article· en· W2086133534 on OpenAlexaff
Erika Kužmová, Luděk Bartoš, Radim Kotrba, George A. Bubenik

Bibliographic record

VenuePLoS ONE · 2011
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of Guelph
FundersMinisterstvo ZemědělstvíGrantová Agentura České Republiky
KeywordsAntlerIn vitroCell biologyCell growthChemistryBiologyBiochemistryEcology

Abstract

fetched live from OpenAlex

Antlers as a potential model for bone growth and development have become an object of rising interest. To elucidate processes explaining how antler growth is regulated, in vitro cultures have been established. However, until now, there has been no standard method to cultivate antler cells and in vitro results are often opposite to those reported in vivo. In addition, many factors which are often not taken into account under in vitro conditions may play an important role in the development of antler cells. In this study we investigated the effects of the antler growth stage, the male individuality, passaged versus primary cultures and the effect of foetal calf serum concentrations on proliferative potential of mixed antler cell cultures in vitro, derived from regenerating antlers of red deer males (Cervus elaphus). The proliferation potential of antler cells was measured by incorporation of (3)H thymidine. Our results demonstrate that there is no significant effect of the antler growth stage, whereas male individuality and all other examined factors significantly affected antler cell proliferation. Furthermore, our results suggest that primary cultures may better represent in vivo conditions and processes occurring in regenerating antlers. In conclusion, before all main factors affecting antler cell proliferation in vitro will be satisfactorily investigated, results of in vitro studies focused on hormonal regulation of antler growth should be taken with extreme caution.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.037
GPT teacher head0.246
Teacher spread0.209 · 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 designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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