Bibliographic record
Abstract
Distinct morphological subtypes of colorectal cancer (CRC) confer a bleak clinical outlook. In a recent issue of The Journal of Pathology, Onuma et al investigated morphological evolution of a highly fatal CRC subtype known as micropapillary cancer (MPC). This study enhances understanding of MPC biology including essential regulatory signals, cellular and multicellular phenotypes, as well as cancer behaviour. Iterative modelling in three-dimensional (3D) patient-derived CRC tissue-originated spheroids (CTOSs) revealed spatiotemporal oscillations of Rho-ROCK hyperactivity underlying reversal of membrane polarity and suppression of lumen formation during development of multicellular MPC morphology. Corroborative studies in CTOSs, xenografts, and archival human CRCs confirm human disease relevance. Although cancer morphology has previously been considered irreversible, targeted inhibition of Rho-ROCK activity restored membrane polarity, lumenized multicellular assembly, and suppressed MPC morphology in 3D CTOS cultures and xenografts. Collectively, the study identifies molecular, biophysical, and multicellular mechanisms implicated in morphological evolution of micropapillary CRC. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".