Cell-type expression and activation by light of neuropsins in the developing and mature Xenopus retina
Bibliographic record
Abstract
Photosensitive opsins detect light and perform image- or nonimage-forming tasks. Opsins such as the “classical” visual opsins and melanopsin are well studied. However, the retinal expression and functions of a novel family of neuropsins are poorly understood. We explored the developmental time-course and cell-type specificity of neuropsin (opn5, 6a, 6b, and 8) expression in Xenopus laevis by in situ hybridization and immunohistochemistry. We compared the Xenopus results with publicly available single cell RNA sequencing (scRNA-seq) data from zebrafish, chicken, and mouse. Additionally, we analyzed light-activation of neuropsin-expressing cells through induction of c-fos mRNA. opn5 and opn8 expression begins at stage 37/38 when the retinal circuits begin to be activated. Once retinal circuits connect to the brain, opn5 mRNA is distributed across multiple retinal cell types, including bipolar (~70%–75%), amacrine (~10%), and retinal ganglion (~20%) cells, with opn8 present in amacrine (~70%) and retinal ganglion (~30%) cells. opn6a and opn6b mRNAs emerge in newborn-photoreceptors (stage 35), and are colocalized in rods and cones by stage 37/38. Interestingly, in the mature larval retina (stage 43/44), opn6a and opn6b mRNAs become preferentially localized to rods and cones, respectively, while newborn photoreceptors bordering the proliferative ciliary marginal zone express both genes. In zebrafish, opn6a and opn6b are also expressed in photoreceptors, while Müller glia and amacrine cells express opn8c. Most neuropsin-expressing retinal ganglion cells display c-fos expression in response to light, as do over half of the neuropsin-expressing interneurons. This study gave a better understanding of retinal neuropsin-expressing cells, their developmental onset, and light activation.
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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) | 0.002 | 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".