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Record W7001416663

Investigations on age and breed-associated differences in energy intake,\ngrowth rate, body composition, haematological and biochemical values of\nLabrador Retrievers and Miniature Schnauzers fed different dietary levels of\nvitamin A

2018· dissertation· en· W7001416663 on OpenAlexaboutno aff

Bibliographic record

VenueRefubium (Universitätsbibliothek der Freien Universität Berlin) · 2018
Typedissertation
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsBody weightEnergy metabolismBreedEnergy requirementEnergy expenditureVitamin
DOInot available

Abstract

fetched live from OpenAlex

Balanced nutrition ensuring adequate intakes of energy, protein, minerals and\nvitamins is essential for the optimal development of young dogs. An adequate\nenergy supply of growing dogs is critical in controlling the growth rate.\nResearch in rodents indicates that dietary vitamin A impacts energy\nutilisation; the potential impact on the energy metabolism in dogs and\nconsequently on the energy intake, body composition and growth velocity in\ngrowing dogs however remains unclear. The literature survey in Chapter 2\nindicates that the definition of healthy growth is difficult and\ncontroversial. The assessment of ideal body condition of growing dogs is more\ndifficult compared to adult animals because increased energy intake results in\nincreased growth rate, but not necessarily in increased body fat mass.\nGuidance values for energy intake and body weight development do exist,\nhowever considerable variability can be observed between breeds. The overview\nof studies investigating breed and age related changes in haematological and\nblood chemical values during growth clearly shows that prominent changes\noccur. Therefore results obtained from puppies have to be interpreted with\ncare to correctly assess the health status as values may deviate from values\nfound in adult dogs. Chapter 3 explains the main aims and hypotheses of this\nthesis. The main work of the current thesis consists of two published\nmanuscripts summarized in Chapter 4 and 5. In the first manuscript the\npossible effects of different dietary vitamin A concentrations on energy\nintake, growth rate and body composition in Labrador Retriever and Miniature\nSchnauzer puppies have been evaluated. However, based on the well-documented\nhigh tolerance of dogs to dietary vitamin A levels up to 104.8 μmol retinol\n(100 000 IU vitamin)/4184 kJ (1000 kcal) it was hypothesized that energy\nintake and accumulation of body fat would be unaffected (Chapter 4). This was\nconfirmed by the results of our study. Given the findings of Morris et al\n(2012), vitamin A was not considered as a factor in the evaluation of the\nhaematological and biochemical data in the second manuscript (Chapter 5). The\nmain interest of the second manuscript was to increase the knowledge on breed,\nsex and age effects and their interaction during the first year of life. The\nevaluation shows that age and breed-related changes in haematological and\nblood chemical test results are evident in young Labrador Retriever and\nMiniature Schnauzer dogs. The results confirm the need for age-specific\nreference ranges for the interpretation of clinical data obtained from young\npuppies. The potential effects of dietary vitamin A as well as growth related\nalterations in body tissue and metabolism are discussed in Chapter 6 together\nwith the results obtained from this study. In conclusion, the results of the\ncurrent study suggest that unlike to rodents dietary vitamin A does not affect\nenergy utilization, growth rate or body composition in dogs. The underlying\nbiochemical mechanisms however remain unclear and require further\nclarification. With regards to haematological and blood chemical parameters\nthe study showed marked age and breed related changes illustrating growth\nrelated alterations in body tissue and metabolism during the first year of\nlife. The early growth phase clearly appears to be most critical and needs to\nbe investigated in more depth to ease interpretation of clinical data obtained\nfrom young puppies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.271
Teacher spread0.224 · 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.

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
Published2018
Admission routes1
Has abstractyes

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