Rheological profiles of DNA extracts from forensic bloodstain samples
Bibliographic record
Abstract
Rheology can be used to probe the differences in physical properties and in-solution behaviours of synthetic and biological polymers, like deoxyribonucleic acid (DNA). Large fragments of highly concentrated genomic and phage DNA have been characterized using rheology; however, this amount and size of DNA are atypical in DNA extracted from forensic evidence. To determine the applicability of rheology for the analysis of dilute concentrations of short DNA fragments expected from forensic specimens (low molecular weight DNA at concentrations in the ng/µL range), we conducted an optimization experiment in which we varied the size, concentration, and conformation of synthetic DNA in various solvents and polymer matrices. We found that incorporating DNA into an alginate-based, ionically crosslinked hydrogel produced the greatest differences in rheological profiles from synthetic DNA comprised of different physical properties. The conformation and size of encapsulated DNA provided significantly different responses during dynamic oscillatory measurements (p<0.05). Additionally, a time since deposition (TSD) study was performed using rotational and oscillatory tests to understand the changes in DNA extracts from bloodstains left to degrade for up to 19 months. DNA extracted from all timepoints could be detected and quantified for the tested temperature conditions (-20°C, 4°C, 22°C). Statistical analyses revealed moderate correlations between the rheological responses of DNA-containing materials and TSD (r = -0.57 to r = 0.62). Our results highlight the viability of rheology as a technique for the analysis of dilute DNA oligos and DNA extracts, and as a complementary technique for the determination of bloodstain TSD.
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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) | 0.001 | 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 | 0.001 | 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".