The roles of S6K1 and S6K2 in the growth and size homeostasis of mammalian cells
Bibliographic record
Abstract
Cell size is a fundamental aspect of organismal form that remains poorly understood in multicellular organisms.The maintenance of cell size homeostasis is crucial in mammals, in which different cell types must maintain a particular cell size.The mechanisms regulating cell size have become increasingly clear in yeast, where the available nutrients in the immediate environment directly regulates cell size by regulating the synthesis of the cyclin Cln3.These processes are unclear in mammals, where cell size does not directly correspond to the available nutrients and must be differentially regulated in different tissues.Basic questions such as whether cell size checkpoints exist in mammalian cells remain controversial.Investigating the ability of different factors to maintain the homogeneity of cell size within a population in addition to its effect on average size could provide useful insights into this question.It is well known that the mTOR pathway regulates cellular growth and proliferation.While it regulates proliferation through the downstream 4E-BPs, it regulates growth through the S6 kinases, S6K1 and S6K2.Therefore, investigating the role of the S6Ks in maintaining cell size homogeneity could reveal how mTOR regulates growth and clarify how cell size is regulated more generally.While it is generally claimed that both S6Ks promote growth, it is unknown whether S6K1 and S6K2 play unique roles in cell size regulation or whether both are necessary for growth.Nonetheless, a major limitation of our knowledge of cell size regulation in multicellular organisms is the lack of a robust method to measure cell size and variation in size.In order to identify size checkpoints, it is necessary to develop a method in which both the size and cell cycle position can be measured at the level of single cells.I have contrasted different methods in cell size 1
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".