Ultraviolet Light (UV) Regulation of the TNF Family Decoy Receptors DcR2 and DcR3 in Human Keratinocytes
Bibliographic record
Abstract
BACKGROUND: Several additional members of the tumor necrosis factor (TNF) receptor family were recently identified. The existence of such receptors, which may play distinct and unique regulatory roles, suggests that complex regulatory mechanisms are involved in apoptosis. OBJECTIVE: This study examines the expression of several members of the TNF receptor family in human keratinocytes exposed to ultraviolet B (UVB) irradiation. METHODS: Human keratinocytes were exposed to increasing doses of UVB, total RNA was harvested, and a quantitative RNase protection assay was performed. RESULTS: Decoy receptor-3 (DcR3), a nonfunctional receptor that binds to Fas ligand (FasL), was constitutively expressed at high level in keratinocytes but decreased rapidly in cells exposed to UVB. Decoy receptor-2 (DcR2), a nonfunctional receptor that binds to TNF-related apoptosis-inducing ligand (TRAIL)/APO-2L, showed the opposite expression pattern. DcR2 was undetectable in unirradiated keratinocytes and was markedly up-regulated after exposure to UVB. Although the response showed significant delays at higher UVB doses, the patterns observed for DcR3 and DcR2 were consistent in this set of experiments. CONCLUSION: We conclude that UVB regulates expression of these two TNF decoy receptors in keratinocytes. This pathway may represent a novel mechanism for regulation of apoptosis in the skin.
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 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".