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Record W1985268668 · doi:10.1002/bip.20544

The effect of manganese(II) on the structure of DNA/HMGB1/H1 complexes: Electronic and vibrational circular dichroism studies

2006· article· en· W1985268668 on OpenAlexaff
A. M. Polyanichko, Е. В. Чихиржина, Valery Andrushchenko, В. И. Воробьев, H. Wieser

Bibliographic record

VenueBiopolymers · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistryDNACircular dichroismCrystallographyVibrational circular dichroismManganeseMoleculeIonBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The interactions were studied of DNA with the nonhistone chromatin protein HMGB1 and histone H1 in the presence of manganese(II) ions at different protein to DNA and manganese to DNA phosphate ratios by using absorption and optical activity spectroscopy in the electronic [ultraviolet (UV) and electronic circular dichroism ECD)] and vibrational [infrared (IR) and vibrational circular dichroism (VCD)] regions. In the presence of Mn 2+ , the protein–DNA interactions differ from those without the ions and cause prominent DNA compaction and formation of large intermolecular complexes. At the same time, the presence of HMGB1 and H1 also changed the mode of interaction of Mn 2+ with DNA, which now takes place mostly in the major groove of DNA involving N 7 (G), whereas interactions between Mn 2+ and DNA phosphate groups are weakened by histone molecules. Considerable interactions were also detected of Mn 2+ ions with aspartic and glutamic amino acid residues of the proteins. © 2006 Wiley Periodicals, Inc. Biopolymers 83: 182–192, 2006 This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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 score0.009
Threshold uncertainty score0.297

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 head0.218
Teacher spread0.215 · 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

Citations22
Published2006
Admission routes1
Has abstractyes

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