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Micro-CT X-rays do not fragment DNA in preserved bird skins

2012· article· en· W1589668425 on OpenAlexaff
Ursula M. Paredes, Robert Prŷs‐Jones, Mark Adams, Jim J. Groombridge, Samit Kundu, Paul‐Michael Agapow, Richard L. Abel

Bibliographic record

VenueJournal of Zoological Systematics & Evolutionary Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsBiologyDNAFragmentation (computing)DNA fragmentationZoologyEvolutionary biologyGeneticsEcology

Abstract

fetched live from OpenAlex

Most zoological systematics studies are currently based on morphological features, molecular traits or a combination of both to reconstruct animals’ phylogenetic history. Increasingly, morphological studies of museum specimens are using X-ray computed tomography to visualize internal morphology, because of its ‘non-destructive’ nature. However, it is not known whether CT can fragment the size of DNA extracted from museum specimens, as has been demonstrated to occur in living cells. This question is of paramount importance for collections based research because X-rays may reduce the amount of data obtainable from specimens. In our study, we tested whether exposure of museum bird skins to typical CT X-ray energies (for visualization of the skeleton) increased DNA strand fragmentation, a key factor for the success of downstream molecular applications. For the present study, we extracted DNA from shavings of 24 prepared and dried bird skins (100+ years) footpads before and after CT scanning. The pre- and post-CT fragmentation profiles were assessed using a capillary electrophoresis high-precision instrument (Agilent Bioanalyzer). Comparison of the most common strand length in each DNA sample (relative mass) revealed no significant difference unexposed and exposed tissue (paired t-test p = 0.463). In conclusion, we found no further quantifiable degradation of DNA strand length under standard X-ray exposure obtained from our bird skins sample. Differences in museum preservation techniques probably had a greater effect on variation of pre-CT DNA fragmentation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0260.002

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.

Opus teacher head0.130
GPT teacher head0.349
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2012
Admission routes1
Has abstractyes

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