Metabolomic studies of radiation‐induced apoptosis of human leukocytes by capillary electrophoresis‐mass spectrometry and flow cytometry: Adaptive cellular responses to ionizing radiation
Bibliographic record
Abstract
There is growing interest in the development of new methods for elucidating the biological effects of low-dose exposure to ionizing radiation (IR) on human health. Herein, we introduce a strategy for assessment of the impact of radiation-induced oxidative stress on the intra-cellular metabolism of human leukocytes. Untargeted metabolomic analyses were performed by CE-ESI-MS on irradiated leukocytes exposed to increasing doses of -radiation emitted from a Taylor source, which were subsequently incubated for 44 h to allow for cellular recovery. Flow cytometry with dual fluorescence staining revealed a major shift from early- to late-stage apoptosis associated with cell membrane permeability changes as radiation dosage was increased relative to the control, but with a significant attenuation measured at intermediate dose levels. CE-ESI-MS analysis of filtered white blood cell lysates was also performed to quantify changes associated with 22 intra-cellular metabolites, which were consistently measured in leukocytes across all radiation levels. Preliminary experiments demonstrated that there was an overall depletion in metabolites with extended exposure to IR; however, there was a non-linear upregulation of specific metabolites at the 4 Gy level relative to pre-irradiated levels, notably for arginine, glutamine, creatine, proline and reduced glutathione. Our studies demonstrate that leukocytes require a minimum threshold level of IR to induce a cytoprotective response in metabolism associated with antioxidant defense, energy homeostasis and cell signaling, which is relevant to improved understanding of the mechanisms of oxidative stress in radiobiology and cancer therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".