Mechanical impact on neural stem cell lineage decisions in human brain organoids
Bibliographic record
Abstract
Abstract During neurodevelopment neural stem cells give rise to a spatially patterned tissue in which a regionally differentially regulated balance between proliferation and differentiation produces the fine-tuned number of neurons and macroglia necessary for a functional central nervous system. The cells driving these highly intricated developmental processes of patterning, growth and differentiation are constantly exposed to a mechanical environment that is however variable between different brain regions and along differentiation trajectories. Here we demonstrate that both, acute mechanical manipulations as well as a persistent change in the mechanical environment provided to human brain organoids, instruct neural stem cell lineage decisions. Furthermore, we dissect the underlying changes in the molecular program of organoid-resident cells by bulk- and single cell RNA-sequencing and reveal that mechanical manipulations impact on molecular programs governing early patterning events as well as cell-type specifically alter cellular metabolism. Thus, our results unravel a regulatory network linking mechanics and neural stem cell lineage decisions.
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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".