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Record W1998345117 · doi:10.1021/jp808253t

Helix−Coil Transition of DNA Monitored by Pressure Perturbation Calorimetry

2009· article· en· W1998345117 on OpenAlexaff
Gamal Rayan, Alekos Tsamaloukas, Robert B. Macgregor, Heiko Heerklotz

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnthalpyAqueous solutionCalorimetryChemistryElectromagnetic coilHelix (gastropod)Heat capacityMolar volumeAnalytical Chemistry (journal)ThermodynamicsCrystallographyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We report the first use of pressure perturbation calorimetry (PPC) to characterize the heat-induced helix-coil transition of DNA polymers. The alternating copolymer poly[d(A-T)] was studied in aqueous solutions containing 5.2 and 18.2 mM Na+; it exhibited helix-coil transition temperatures of 33.6 and 44.7 degrees C, respectively. The transition is accompanied by a negative molar volume change, DeltaV) -2.6 and -2.1 mL/mol (base pair), respectively, and an increase in the coefficient of thermal expansion, Deltaalpha=+5x10(-4) K(-1) (at both ionic strengths). These values are consistent with a greater hydration of the coil form. The larger water-accessible surface area of the coil causes more water molecules to assume a bound, more densely packed structure that then gradually decreases with increasing temperature, leading to a larger value of R. The magnitude of the volume changes detected by PPC were larger than those deduced from high-pressure UV spectroscopy, shedding light on the effect of pressure on DeltaV. The shape of the PPC peak was nearly identical to the shape of the DSC peak, providing direct evidence for the correlation between the molar volume change and enthalpy change for the helix to coil transition of DNA.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.003
GPT teacher head0.215
Teacher spread0.212 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations32
Published2009
Admission routes1
Has abstractyes

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