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Record W7037787878

Factors influencing cellular radiosensitivity and survival curve analysis.

2024· dissertation· en· W7037787878 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsnot available
FundersCanada Research ChairsNortheastern States Research Cooperative
KeywordsRadiosensitivityBystander effectSurvival analysisIonizing radiationRadiobiologyPopulationEnd pointCell survivalDose–response relationship
DOInot available

Abstract

fetched live from OpenAlex

Investigating variance in radiosensitivity amongst cell populations contributes to the overall improvement in our understanding of the effects of low dose ionizing radiation. The aim of this thesis was to investigate factors influencing radiosensitivity through analysis of survival curves. The radiation-induced bystander effect and low dose hyperradiosensitivty were observed to help elucidate relationships between these phenomena. First heterogeneity of a cell population was investigated and seven clonal lines of an HCT 116 p53 wild type cell line were derived. Survival curves with a wide range of dose points (0.5 to 15 Gy) were developed and curves were fitted with the linear- quadratic and multi-target models. The McMaster Taylor Radiobiology Cesium-137 source was used for all irradiations in this thesis. Here it was evident that the multi- target model provided a better fit and further analysis revealed a relationship between the curve shoulder and toxicity of bystander effect signals. Clonal lines with a large shoulder size did not show evidence of the radiation induced bystander effect. Since the lowest dose point in curves was 0.5 Gy, a more focused look was taken in the low dose range. iii Survival curves were again produced for all clonal lines adding data to now include six dose points in the low dose region (below 0.5 Gy). Survival curves were re-analyzed with this extensive data set including doses from 0.01 to 15 Gy and now instances of hyperradiosensitivty were evident in all cell lines. The linear-quadratic model did not provide a meaningful fit to the data and so the induced-repair model was used and found to be appropriate in low doses. It was concluded that whether the radiation-induced bystander effect was produced or not, low dose effects such as hyperradiosensitivity may contribute to the overall radiosensitivity of a cell line. Finally, sex of the cell line was investigated using four cell lines. Of the four cell lines, two were included as controls for radiosensitivity. These two cell lines were null for the protein Artemis which assists in the repair of double strand DNA breaks. Thus, when this protein is not functioning as normal, radiosensitivity is induced in the cell line. Through medium transfer bystander effect assays a greater reduction in cell survival was observed in the normal female cell line compared to the normal male cell line. In conclusion, this thesis contributes to the understanding of low dose effects and non-targeted effects of ionizing radiation. Understanding these mechanisms both separately and in combination may contribute to the betterment of radiation therapies and radiation protection.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.201
Teacher spread0.184 · 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 designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

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