Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.
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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 | 0.001 | 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 it