Induced neuroblastoma cell differentiation, associated with transient HES‐1 activity and reduced HASH1 expression, is inhibited by Notch1
Bibliographic record
Abstract
Neuroblastoma is a childhood tumor that originates from the sympathetic nervous system.The tumor cells have embryonic features, presumably as a consequence of an impaired capacity to respond to signals and transcriptional control mechanisms operating during normal differentiation.Two basic helix-loop-helix transcription factors, human achaete-scute homologue-1 (HASH-1) and hairy/enhancer of split homologue-1 (HES-1), are crucial for proper development of some neuronal cells.Here, their potential roles during sympathetic differentiation of human neuroblastoma cells have been investigated.In all tested protocols for induction of differentiation of SH-SY5Y and SK-N-BE(2) neuroblastoma cells, HASH-1 expression was rapidly decreased with a concomitant, often transient, increase in HES-1 expression.In gel mobility shift assays, using extracts from neuroblastoma cells, HES-1 bound to an oligonucleotide corresponding to a sequence in the HASH-1 promoter including the so-called N-box, suggesting that the transiently increased HES-1 activity in differentiating neuroblastoma cells is involved in down-regulation of HASH-1.Constitutive expression of the intracellular domain of Notch1, which activates the HES-1 promoter in SH-SY5Y cells, inhibited spontaneous and induced morphological differentiation of these neuroblastoma cells.Our data show that functional sympathetic neuronal differentiation of neuroblastoma cells is associated with transient activation of HES-1 and down-regulation of HASH-1 expression.
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 | 0.000 | 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) | 0.001 | 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 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".