Comparing biological and pathological factors affecting osteocalcin concentrations in archaeological skeletal remains
Bibliographic record
Abstract
Paleoproteomics and the study of ancient proteins has become an important consideration in bioarchaeological research as we seek to understand the relationship between the physical skeleton and its underlying biochemistry. Osteocalcin is an abundant, non-collagenous protein that is accessible archaeologically due to its affinity for hydroxyapatite in bone. Manufactured by the osteoblast cells during normal bone metabolism, osteocalcin is inherently linked to the process of bone remodelling. Clinical studies have consistently shown the impact of biological (i.e., sex and age) and pathological (i.e., disease) factors on osteocalcin concentrations within the body; however, this connection has yet to be fully explored bioarchaeologically. For this study, 46 individuals from the Danish Sct. Albert’s cemetery (CE 1250–1536) were analyzed with cortical bone samples harvested from the femur. Each sample was demineralized and quantified using established paleoproteomic methods (ELISA) and tested for diagenesis using FTIR-ATR. No significant differences were found in the osteocalcin concentrations between adult males and females. However, males had a wider range of osteocalcin variability perhaps explained in part by their increased prevalence of pathological conditions characterized by bone remodelling. Similarly, non-adults had a wide range of osteocalcin variability but there were no significant differences when compared to the adult mean. No correlations were found between osteocalcin concentrations and diagenesis suggesting that the protein can survive across a range of temporal periods and variable burial environments. While no clear pattern emerged between osteocalcin concentrations and biological and/or pathological factors, this study is significant in that it further explores the use of paleoproteomics in bioarchaeological contexts and how we may unite our macroscopic and biochemical assessments of human skeletal remains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.063 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".