Identification of Key Proteins in Human Epithelial Cells Responding to Bystander Signals From Irradiated Trout Skin
Bibliographic record
Abstract
Radiation-induced bystander signaling has been found to occur in live rainbow trout fish (Oncorhynchus mykiss). This article reports identification of key proteomic changes in a bystander reporter cell line (HaCaT) grown in low-dose irradiated tissue-conditioned media (ITCM) from rainbow trout fish. In vitro explant cultures were generated from the skin of fish previously exposed to low doses (0.1 and 0.5 Gy) of X-ray radiation in vivo. The ITCM was harvested from all donor explant cultures and placed on recipient HaCaT cells to observe any change in protein expression caused by the bystander signals. Proteomic methods using 2-dimensional (2D) gel electrophoresis and mass spectroscopy were employed to screen for novel proteins expressed. The proteomic changes measured in HaCaT cells receiving the ITCM revealed that exposure to 0.5 Gy induced an upregulation of annexin A2 and cingulin and a downregulation of Rho-GDI2, F-actin-capping protein subunit beta, microtubule-associated protein RP/EB family member, and 14-3-3 proteins. The 0.1 Gy dose also induced a downregulation of Rho-GDI2, hMMS19, F-actin-capping protein subunit beta, and microtubule-associated protein RP/EB family member proteins. The proteins reported may influence apoptotic signaling, as the results were suggestive of an induction of cell communication, repair mechanisms, and dysregulation of growth signals.
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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) | 0.001 | 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".