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Record W1599889823 · doi:10.5772/23295

Calorimetric Investigations of Non-Viral DNA Transfection Systems

2011· book-chapter· en· W1599889823 on OpenAlexaff
Tranum Kaur, Naser Tavakoli, Roderick Slavcev, Shawn Wettig

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTransfectionDNAVirologyComputational biologyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Although the structural and energetic forces involved in DNA condensation have been studied for years, this area has experienced a resurgence of interest in recent years with respect to developing gene therapy protocols to combat a variety of human diseases. Despite an intense effort to study the mechanism(s) of DNA condensation using a variety of techniques such as microscopic, light scattering, fluorescence, and calorimetric techniques the precise details of the energetics of DNA nanoparticle formation and how these complexes assemble is not well understood at present. Isothermal titration calorimetry (ITC) has become an important technique for studying the binding energetics of biological processes, including protein-protein binding, protein-carbohydrate binding, protein-lipid binding, antigen-antibody binding, DNA-protein binding, and the DNA-lipid binding that is at the heart of non-viral transfection vectors. Given the large informational content of thermodynamic data (such as binding constants, stoichiometry, enthalpies of interaction, etc.) it is not surprising that ITC is being used for the elucidation of the binding mechanism of DNA with surfactants or lipids used in non-viral gene delivery vectors. This is described in more detail in this Chapter.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score1.000

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 integrity0.0010.000
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 head0.024
GPT teacher head0.232
Teacher spread0.208 · 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.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations5
Published2011
Admission routes1
Has abstractyes

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