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Record W2801069307 · doi:10.1063/1.5010916

Effective and absolute cross sections for low-energy (1-30 eV) electron interactions with condensed biomolecules

2018· article· en· W2801069307 on OpenAlexafffund
Yi Zheng, Léon Sanche

Bibliographic record

VenueApplied Physics Reviews · 2018
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsIonizing radiationRadiationAbsorbed doseElectronBrachytherapyScatteringRange (aeronautics)BiomoleculeRadiation therapyDosimetryPhysicsMonte Carlo methodNuclear medicineMaterials scienceIrradiationMedical physicsNuclear physicsNanotechnologyOpticsMedicine

Abstract

fetched live from OpenAlex

Ionizing radiation is intensively used for therapeutic [e.g., radiotherapy, brachytherapy, and targeted radionuclide therapy (TRT)], as well as for diagnostic medical imaging purposes. In these applications, the radiation dose given to the patient should be known and controlled. In conventional cancer treatments, absorbed dose calculations rely essentially on scattering cross sections (CSs) of the primary high-energy radiation. In more sophisticated treatments, such as combined radio- and chemo-therapy, a description of the details of energy deposits at the micro- and nano-scopic level is preferred to relate dose to radiobiological effectiveness or to evaluate doses at the biomolecular level, when radiopharmaceuticals emitting short-range radiation are delivered to critical molecular components of cancer cells (e.g., TRT). These highly radiotoxic compounds emit large densities of low-energy electrons (LEEs). More generally, LEE (0-30 eV) are emitted in large numbers by any type of high-energy radiation; i.e., about 30 000 per MeV of deposited primary energy. Thus, to optimize the effectiveness of several types of radiation treatments, the energy deposited by LEEs must be known at the level of the cell, nucleus, chromosome, or DNA. Such local doses can be evaluated by Monte Carlo (MC) calculations, which account event-by-event, for the slowing down of all generations of particles. In particular, these codes require as input parameters absolute LEE CSs for elastic scattering, energy losses, and direct damage to vital cellular molecules, particularly DNA, the main target of radiation therapy. In the last decade, such CSs have emerged in the literature. Furthermore, a method was developed to transform relative yields of damages into absolute CSs by measuring specific parameters in the experiments. In this review article, we first present a general description of dose calculations in biological media via MC simulation and give an overview of the CSs available from theoretical calculations and gas-phase experiments. The properties of LEE scattering in the gas-phase are then compared to those in the condensed phase. The remaining portion of the article is devoted to condensed-phase CSs. We provide absolute LEE scattering CSs for electronic, vibrational, and phonon excitation of biomolecules as well as for dissociative electron attachment, electron intra- and inter-molecular stabilization, and bond dissociation, including strand breaks and degradation product formation. The biomolecules are O2, CO2, H2O, DNA bases, sugar and phosphate unit analogs, oligonucleotides, plasmid DNA, and the amino acid tryptophan. CSs for strand breaks in radiosensitizing and chemotherapeutic molecules bond or not to a short DNA strand are also listed. The principle of each experimental technique and mathematical methods utilized to generate all condensed-phase CSs are briefly explained. The mechanisms responsible for the magnitudes of the CSs are 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.014
GPT teacher head0.325
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2018
Admission routes2
Has abstractyes

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