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Record W2018589283 · doi:10.1504/ijlr.2006.007902

Radiation-induced bystander effects: do they provide evidence for an adaptive response?

2005· article· en· W2018589283 on OpenAlexaff
Carmel Mothersill, Colin Seymour

Bibliographic record

VenueInternational Journal of Low Radiation · 2005
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsMcMaster University
FundersScience Foundation Ireland
KeywordsBystander effectAdaptive responsePopulationIonizing radiationApoptosisHormesisStressorBiologyToxicologyCell biologyCancer researchMedicineImmunologyIrradiationNeuroscienceOxidative stressPhysicsGeneticsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

In this paper, our current knowledge of the mechanisms underlying the induction of bystander effects by low dose low LET ionising radiation is reviewed and the question of how bystander effects may be related to observed adaptive responses or other protective effects of low doses exposures is considered. Bystander effects appear to be the result of a generalised stress response in tissues or cells. The signals may be produced by all exposed cells but the response may require a quoram in order to be expressed. The major response involving low LET radiation exposure discussed in the existing literature is a death response. This has many characteristics of apoptosis but is p53 independent. While a death response might appear to be adverse, the position is argued in this paper that it is in fact protective and removes damaged cells from the population. Since many cell populations carry damaged cells without being exposed to radiation (so called 'background damage'), it is possible that low doses exposures cause removal of cells damaged by agents other than the test dose of radiation. This mechanism would lead to the production of 'U-shaped' dose response curves. In this scenario, the level of 'adaptive' or beneficial response will be related to the background damage carried by the cell population. This model may be important when attempting to predict the consequences of mixed exposures involving radiation and other environmental stressors.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.033
GPT teacher head0.368
Teacher spread0.335 · 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 designObservational
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

Citations2
Published2005
Admission routes1
Has abstractyes

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