Red light, Green light, Switch on, switch off: Problems in Cell Regulation
Bibliographic record
Abstract
Cell division is a tightly regulated process during embryonic development. If a gene switch is turned on outside of embryonic development, mitosis and cell differentiation are disrupted, which may cause unregulated cell division, potentially leading to cancer. An important step involves the glycosylation of cell surface glycans by sialic acid, which is critical for cell communication and differentiation during embryonic development. Changes in the glycosylation of the glycoconjugates by sialyltransferase (ST) are regulated at the tissue and temporal level. If temporal specificity is reset by the inappropriate switching on of the gene for ST production, the cell then expresses an inappropriate cell surface marker, correlated with increases in some cancers. The mechanism has yet to be determined. The Ashbury SMART Team (Students Modeling A Research Topic) modeled ST using 3D printing technology to highlight the important bonding features. There are four main amino acid sequence motifs classified by size and used to identify and clone STs. Although the sequence and structure for one enzyme is known, the structure of the others in this family remains a mystery. Although the production of this enzyme cannot be controlled at the genetic level, researchers hope to explore novel therapeutic inhibitors that could stop the functioning of the excess ST. Supported by a grant from NIH‐SEPA.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".