TFEB-mediated endolysosomal activity controls human hematopoietic stem cell fate
Bibliographic record
Abstract
It is critical to understand how human quiescent long-term hematopoietic stem cells (LT-HSCs) sense demand from daily and stress-mediated cues and then transition into bioenergetically active progeny to differentiate and meet these cellular needs. However, the demand-adapted regulatory circuits of these early steps of hematopoiesis are largely unknown. Here we show that lysosomes, sophisticated nutrient-sensing and signaling centers, are regulated dichotomously by transcription factor EB (TFEB) and MYC to balance catabolic and anabolic processes required for activating LT-HSCs and guiding their lineage fate. TFEB-mediated induction of the endolysosomal pathway causes membrane receptor degradation, limiting LT-HSC metabolic and mitogenic activation, promoting quiescence and self-renewal, and governing erythroid-myeloid commitment. In contrast, MYC engages biosynthetic processes while repressing lysosomal catabolism, driving LT-HSC activation. Our study identifies TFEB-mediated control of lysosomal activity as a central regulatory hub for proper and coordinated stem cell fate determination.
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".