Retinoid X receptor α downregulation is required for tail and caudal spinal cord regeneration in the adult newt
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Some adult vertebrate species, such as newts, axolotls and zebrafish, have the ability to regenerate their central nervous system (CNS). However, the factors that establish a permissive CNS environment for correct morphological and functional regeneration in these species are not well understood. Recent evidence supports a role for retinoid signaling in the intrinsic ability of neurons, in these regeneration-competent species, to regrow after CNS injury. Previously, we demonstrated that a specific retinoic acid receptor (RAR) subtype, RARβ, mediates the effects of endogenous retinoic acid (RA) on neuronal growth and guidance in the adult newt CNS after injury. Here, we now examine the expression of the retinoid X receptor RXRα (a potential heterodimeric transcriptional regulator with RARβ), in newt tail and spinal cord regeneration. We show that at 21 days post-amputation (dpa), RXRα is expressed at temporally distinct periods and in non-overlapping spatial domains compared to RARβ. Whereas RARβ protein levels increase, RXRα proteins level decrease by 21 dpa. A selective agonist for RXR, SR11237, prevents both this downregulation of RXRα and upregulation of RARβ and inhibits tail and caudal spinal cord regeneration. Moreover, treatment with a selective antagonist for RARβ, LE135, inhibits regeneration with the same morphological consequences as treatment with SR11237. Interestingly, LE135 treatment also inhibits the normal downregulation of RXRα in tail and spinal cord tissues at 21 dpa. These results reveal a previously unidentified, indirect regulatory feedback loop between these two receptor subtypes in regulating the regeneration of tail and spinal cord tissues in this regeneration-competent newt.
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.
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 | 0.001 |
| 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 it