Expression of PKC in the developing zebrafish,Danio rerio
Bibliographic record
Abstract
Protein kinase C (PKC) is a family of enzymes involved in a wide range of biological functions. We investigated the expression of PKC-positive cells in zebrafish embryos and larvae within the first week of development to determine the developmental profile of PKC-containing cells. Our other goal was to determine if PKC alpha was associated with Rohon-Beard neurons during the first 5 days of development, when they are reported to undergo apoptosis. First, we confirmed the specificity of the antibodies by Western blotting zebrafish brain homogenates with anti-PKC and anti-PKC alpha, and detected single protein bands of approximately 78-82 kDa in size. Immunohistochemistry showed that several types of neurons were labeled, including neurons in the trigeminal ganglia, the dorsal spinal cord, and the dorsal root ganglia. Double-labeling with anti-PKC alpha and both anti-Islet-1 and zn12 confirmed the identity of the PKC-positive cells in the brain as trigeminal neurons, and in the spinal cord as Rohon-Beard cells. Some Rohon-Beard cells were labeled with anti-PKC alpha up to 7 days post fertilization (dpf). We performed TUNEL labeling and found no correlation between TUNEL-labeled and PKC alpha-labeled Rohon-Beard cells, suggesting that PKC alpha is not involved in Rohon-Beard apoptosis. Only approximately 40% of the approximately 130 Rohon-Beard cells at 24 h postfertilization (hpf) were positively labeled for PKC. Mauthner cells were labeled by anti-PKC, but not anti-PKC alpha, suggesting that the major form of PKC within these cells was not PKC alpha.
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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 | 0.001 | 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".