Quantification of Immunostained Caspase-9 in Retinal Tissue
Bibliographic record
Abstract
The family of caspases is known to mediate many cellular pathways beyond cell death, including cell differentiation, axonal pathfinding, and proliferation. Since the identification of the family of cell death proteases, there has been a search for tools to identify and expand the function of specific family members in development, health, and disease states. However, many of the currently commercially available caspase tools that are widely used are not specific for the targeted caspase. In this report, we delineate the approach we have used to identify, validate, and target caspase-9 in the nervous system using a novel inhibitor and genetic approaches with immunohistochemical read-outs. Specifically, we used the retinal neuronal tissue as a model to identify and validate the presence and function of caspases. This approach enables the interrogation of cell-type specific apoptotic and non-apoptotic caspase-9 functions and can be applied to other complex tissues and caspases of interest. Understanding the functions of caspases can help to expand current knowledge in cell biology, and can also be advantageous to identify potential therapeutic targets due to their involvement in disease.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".