Effects of thermal exposure on bone surface characteristics and DNA recovery
Bibliographic record
Abstract
In forensic cases involving burned human remains, DNA analysis and anthropological techniques are often required to aid identification. There are gaps in the literature regarding how cremation affects DNA preservation and skeletal integrity. This preliminary study aimed to examine how increasing temperature exposures impact DNA recovery and bone surface morphology. Using domestic pig ( Sus scrofa ) rib bones as a model and a muffle furnace, bones were exposed to temperatures ranging from 100 °C to 800 °C for 30 min. The resulting changes in colour and surface texture were observed both macroscopically and microscopically. DNA was extracted using the Applied Biosystems PrepFiler Express™ BTA Forensic DNA Extraction Kit on the AutoMate Express™ Forensic DNA Extraction System and quantified using a NanoDrop™ One UV–Vis Spectrophotometer. Bone colour changes followed an expected pattern, starting with the natural beige, transitioning to black at 350 °C, and then becoming lighter until reaching white at 800 °C. Microscopic observations showed the presence of surface striations at temperatures below 275 °C and the presence of porosity at temperatures above 275 °C. Bones with a black, grey, or white colour and visible porosity were observed in conjunction with a decrease in the amount of DNA. All the bone samples had DNA amounts exceeding 250 ng, suggesting potential suitability for short tandem repeat (STR) polymerase chain reaction (PCR) amplification. This study furthers our understanding of the impacts of cremation on DNA recovery and bone surface integrity to aid assessment and management of remains. • Visual changes in bone from heat exposure may reflect DNA recovery potential. • DNA was successfully recovered from bones burned at temperatures up to 800 °C. • DNA recovery decreased in black, grey, and white cremated bones. • Increased cancellous bone exposure suggested lower DNA recoverability.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".