Differential sampling for genetic analyses of Treponema pallidum and for radiocarbon dating in archaeological bone
Bibliographic record
Abstract
OBJECTIVE: Molecular recovery of T. pallidum DNA in dry bone poses methodological challenges. Here we evaluate recovery success from a molecularly confirmed co-infection with yaws (T. pallidum pertenue) and plague (Y. pestis). MATERIALS: Pulverised bone from three pathological anatomical elements from individual AGU007 excavated from Aguonų street, Vilnius, Lithuania was used for DNA analysis. Three additional anatomical elements from individual AGU007 were used to obtain radiocarbon dates. METHODS: High-throughput sequencing of bulk DNA content followed by computational analysis. DNA sequencing and genomic analysis following molecular enrichment for T. pallidum. Radiocarbon dating combined with computational molecular dating. RESULTS: T. pallidum and Y. pestis DNA were identified in a cranial fragment from individual AGU007. Radiocarbon dates from this individual combined with another narrowed the temporal range to the latter part of the 15th century at the 2-sigma level. CONCLUSIONS: Detection of T. pallidum DNA in multiple skeletal elements from an individual confirmed to have an active yaws infection at time of death gave further insight into preferred sampling locations for molecular detection of treponemal infections. While the highest molecular recovery came from teeth, the parietal bone provided adequate recovery. SIGNIFICANCE: This research indicates that sampling for molecular analysis of T. pallidum infections should include (if available) one tooth and one lesion indicative of active infection at the time of death. Accommodating radiocarbon date probability distributions and Bayesian inference has the potential to increase molecular dating precision. LIMITATIONS: T. pallidum DNA preservation is not predictable across the skeleton. SUGGESTIONS FOR FURTHER RESEARCH: We encourage ethical and minimalist sampling strategies for further research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".