Thermomechanical responses of microfluidic cantilever capture DNA melting and properties of DNA premelting states using picoliters of DNA solution
Bibliographic record
Abstract
Melting or thermal denaturation of a DNA molecule and the different bubble-rich, premelting DNA states that serve as a precursor for DNA thermal denaturation are vital events in DNA thermophysics. In this study, we employ cantilever-based sensing to firstly pinpoint the occurrence of DNA melting and identify the temperature Tm characterizing the melting. Very importantly, this sensing is carried out with an extremely small volume (∼picoliters) of DNA sample with the cantilever demonstrating an extremely high sensitivity on the order of mJ/g⋅K corresponding to pico-Joules of energy input. Secondly, this same large sensitivity of the cantilever is used to quantify the hitherto unknown thermophysical properties of the bubble-rich DNA premelting states. In fact, for both the melting and premelting states, the cantilever provides a framework to calculate the specific heat capacity and the storage and loss moduli of the cantilever-DNA-solution system, thereby establishing a platform for quantifying DNAs' thermo-mechanical behavior.
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 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) | 0.000 | 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 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".