Effects of lipid extraction and ultrafiltration on stable carbon and nitrogen isotopic compositions of fish bone collagen
Bibliographic record
Abstract
RATIONALE: Fish bone collagen isotopic measurements are increasingly important in palaeodietary and paleoenvironmental studies yet differences in the chemical and physical properties of fish relative to other vertebrate bones are rarely considered. Lipid content in fish bone, which can exceed 50%, may underlie the poor collagen integrity criteria typically observed in archaeological studies. METHODS: We compare stable carbon and nitrogen isotopic and elemental compositions of bone collagen prepared using four different methods from a wide range of modern fish species to: (1) assess the extent to which lipid content influences bone collagen δ(13) C and δ(15) N values, and (2) evaluate the relative efficacy of chemical (2:1 chloroform/methanol) and physical (30 kDa ultrafilters) methods for removing lipids from bones. RESULTS: Lower δ(13) C values were observed when the lipid content exceeded 5% of the initial bone mass. The lipid content did not influence the δ(15) N values. 30 kDa ultrafiltration, a common pretreatment for purifying archaeological collagen, removed fewer lipids and was associated with reduced collagen yields (37% loss) as well as altered amino acid compositions. In contrast, collagen prepared using a 2:1 chloroform/methanol lipid extraction step resulted in significantly improved collagen yields, elemental compositions, and isotopic measurements relative to a control treatment. CONCLUSIONS: The chemical lipid extraction method (2:1 chloroform/methanol) performed significantly better than the physical lipid extraction method (30 kDa ultrafilters). Given the high quantities of lipids in fish bones we recommend the inclusion of a chemical lipid extraction step when isolating collagen from modern and archaeological fish bones. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".