Transcriptional and Secretomic Profiling of Epidermal Cells Exposed to Alpha Particle Radiation
Bibliographic record
Abstract
Alpha (α)-particle emitters are probable isotopes to be used in a terrorist attack. The development of biological assessment tools to identify those who have handled these difficult to detect materials would be an asset to our current forensic capacity. In this study, for the purposes of biomarker discovery, human keratinocytes were exposed to α-particle and X-radiation (0.98 Gy/h at 0, 0.5, 1.0, 1.5 Gy) and assessed for differential gene and protein expression using microarray and Bio-Plex technology, respectively. Secretomic analysis of supernatants showed expression of two pro-inflammatory cytokines (IL-13 and PDGF-bb) to be exclusively affected in α-particle exposed cells. The highest dose of α-particle radiation modulated a total of 67 transcripts (fold change>|1.5|, (False discovery rate) FDR<0.05) in exposed cells. Several genes which responded with high expression levels (>2 fold) included KIF20A, NEFM, C7orf10, HIST1H2BD, BMP6, and HIST1H2AC. Among the high expressing genes, five (CCNB2, BUB1, NEK2, CDC20, AURKA) were also differentially expressed at the medium (1.0 Gy) dose however, these genes were unmodulated following exposure to X-irradiation. Networks of these genes clustered around tumor protein-53 and transforming growth factor-beta signaling. This study has identified some potential gene /protein responses and networks that may be validated further to confirm their specificity and potential to be signature biomarkers of α-particle exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".