Physical forces modulate cell differentiation and proliferation processes
Bibliographic record
Abstract
Currently, the predominant hypothesis explains cellular differentiation and behaviour as an essentially genetically driven intracellular process, suggesting a gene-centrism paradigm. However, although many living species genetic has now been described, there is still a large gap between the genetic information interpretation and cell behaviour prediction. Indeed, the physical mechanisms underlying the cell differentiation and proliferation, which are now known or suspected to guide such as the flow of energy through cells and tissues, have been often overlooked. We thus here propose a complementary conceptual framework towards the development of an energy-oriented classification of cell properties, that is, a mitochondria-centrism hypothesis based on physical forces-driven principles. A literature review on the physical-biological interactions in a number of various biological processes is analysed from the point of view of the fluid and solid mechanics, electricity and thermodynamics. There is consistent evidence that physical forces control cell proliferation and differentiation. We propose that physical forces interfere with the cell metabolism mostly at the level of the mitochondria, which in turn control gene expression. The present perspective points towards a paradigm shift complement in biology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".