Protein Kinases and Caspases: Bidirectional Interactions in Apoptosis
Bibliographic record
Abstract
This chapter highlights the prevalence of protein kinase signaling in apoptotic pathways and emphasizes the emergence of global strategies to systematically investigate bidirectional crosstalk between protein kinase phosphorylation and caspase-mediated proteolysis in the propagation of irreversible apoptotic induction. Caspases are classified as cysteine proteases that catalyze irreversible cleavage of peptide bonds C-terminal to aspartic acid residues. The apoptotic role of protein kinases is of interest because posttranslational phosphorylation of both caspases and caspase substrates affects caspase functionality, and conversely, a variety of protein kinases are proteolytically digested by caspases to facilitate or prevent apoptosis. Throughout this chapter, examples have been provided highlighting the complex interactions between protein kinases and caspases that facilitate the progression of apoptosis. The emergence of novel strategies involving proteomics, computational approaches, and techniques designed to monitor the spatial and temporal induction of apoptotic pathways within intact cells offers comprehensive new insights regarding kinase-caspase interactions.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".