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Biomolecular Damage Induced by Ionizing Radiation: The Direct and Indirect Effects of Low-Energy Electrons on DNA

2015· review· en· W2106456081 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Physical Chemistry · 2015
Typereview
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchOffice of ScienceU.S. Department of Energy
KeywordsDNA damageIonizing radiationRadiation damageDNAIrradiationBiomoleculeElectronMaterials scienceRadiationNanotechnologyBiophysicsChemistryChemical physicsBiologyPhysicsBiochemistryOptics

Abstract

fetched live from OpenAlex

Many experimental and theoretical advances have recently allowed the study of direct and indirect effects of low-energy electrons (LEEs) on DNA damage. In an effort to explain how LEEs damage the human genome, researchers have focused efforts on LEE interactions with bacterial plasmids, DNA bases, sugar analogs, phosphate groups, and longer DNA moieties. Here, we summarize the current understanding of the fundamental mechanisms involved in LEE-induced damage of DNA and complex biomolecule films. Results obtained by several laboratories on films prepared and analyzed by different methods and irradiated with different electron-beam current densities and fluencies are presented. Despite varied conditions (e.g., film thicknesses and morphologies, intrinsic water content, substrate interactions, and extrinsic atmospheric compositions), comparisons show a striking resemblance in the types of damage produced and their yield functions. The potential of controlling this damage using molecular and nanoparticle targets with high LEE yields in targeted radiation-based cancer therapies is also discussed.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.773
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.311
Teacher spread0.301 · 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