Understanding the determinants and improving detection of bone fragility in female chickens
Bibliographic record
Abstract
Each year, in Canada, about 25 million commercial laying hens produce more than nine billion eggs, providing affordable, nutrient-dense food for consumers. However, studies have reported up to 97% fracture prevalence in these commercial flocks by the end of their lives, which poses a major welfare concern and has a detrimental impact on the sustainability of the egg- farming industry. Providing increased opportunities for physical activity by housing design is currently the main strategy used to improve welfare and bone health in commercial hens. My research investigates how genetics and experience of physical activity during youth influence bone structure, bone mechanical behaviour, and bone mechanoadaptation, and validates common methods of fracture detection and severity assessment. All studies examine chickens of two commercially relevant genetic strains, who were raised in several different styles of housing that allow for varying types and amounts of physical activity.First, I characterized the in vivo mechanical behaviour of the tibiotarsi of young chickens during habitual activities, using strain gauge sensors to measure strains engendered in vivo. I found that the tibiotarsus undergoes a complex strain environment and that torsion is the predominant source of mechanical strain. Genetic strain and loading history both influenced the in vivo mechanical behaviour of the bone, with sedentary chickens exhibiting higher in vivo mechanical strain levels compared to those with a more active loading history. These findings provide important context to interpreting bone structural and material properties as determinants of these in vivo strains, and directly informed my third study investigating the bone’s mechanoresponse to controlled loading.Next, I sought to characterize whole bone mechanical behaviour due to axial compressive loading and assess its correlation to bone material and structural properties. I created finite element models mimicking our axial compressive loading model, with either heterogeneous or homogeneous tissue mineral density-derived elastic moduli, and correlated the simulated engendered stresses to measures of bone structure along the length of the bone. I found that mineral density heterogeneity did not influence stress magnitudes or patterns along the bone length, and I identified a set of structural parameters with a strong negative correlation to engendered stress levels. These findings inform future interpretations of the effect of interventions that aim toxviimprove tissue mineral density as a means to improve bone stiffness and provide a set of candidate stiffening structural parameters that can be targeted by genetic selection.In a third study, I performed in vivo controlled loading over a 2-week period to study the bone mechanoresponse, using a load waveform protocol that has been shown to successfully elicit bone formation in murine models. Applied load levels were set to engender mechanical strains above the measured habitual levels from my first study. I found that loaded limbs had impaired bone structure and decreased bone surface undergoing formation, compared to non-loaded limbs. These results indicate that the mechanoresponse is different in chickens compared to murine models; future studies are warranted to investigate the osteogenic components of load stimuli in chickens.My last study focuses on adult chickens during the laying phase and sought to cross- validate commonly used methods of keel bone damage detection and severity assessment. Chickens underwent in vivo palpation to categorize them as either having or lacking fracture(s). Then, bones were radiographed, given a fracture severity score based on this image, and scored again based on visual inspection of the keel. Then, palpation and radiograph scores were correlated against the dissected keel scores. I found that although palpation lacks precision and accuracy, it was still more highly correlated to dissected fracture scores than the radiograph scores.Overall, the findings from this thesis inform about the determinants of bone health in young female chickens, and what detection and outcome measures of bone health are meaningful and informative in this group. This research also contributes to the general pool of knowledge on bone biomechanics and mechanobiology in birds, and towards understanding bone’s form-function relationship
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".