Connecting the speckles: Splicing kinases and their role in tumorigenesis and treatment response
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
Alternative pre-mRNA splicing in higher eukaryotes enhances transcriptome complexity and proteome diversity. Its regulation is mediated by a complex RNA-protein network that is essential for the maintenance of cellular and tissue homeostasis. Disruptions to this regulatory network underlie a host of human diseases and contribute to cancer development and progression. The splicing kinases are an important family of pre-mRNA splicing regulators, , which includes the CDC-like kinases (CLKs), the SRSF protein kinases (SRPKs) and pre-mRNA splicing 4 kinase (PRP4K/PRPF4B). These splicing kinases regulate pre-mRNA splicing via phosphorylation of spliceosomal components and serine-arginine (SR) proteins, affecting both their nuclear localization within nuclear speckle domains as well as their nucleo-cytoplasmic shuttling. Here we summarize the emerging evidence that splicing kinases are dysregulated in cancer and play important roles in both tumorigenesis as well as therapeutic response to radiation and chemotherapy.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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