Multiphase condensates from a kinetically arrested phase transition
Bibliographic record
Abstract
The formation of biomolecular condensates through liquid-liquid phase separation from proteins and nucleic acids is emerging as a spatial organisational principle used by living cells. Many such biomolecular condensates are not, however, homogeneous fluids, but contain an internal structure consisting of distinct sub-compartments with different compositions. In many instances, such compartments inside the condensate are depleted in the biopolymers that make up the condensate. Here, we describe that this multiphase structure arises from a kinetically arrested phase transition. The combination of a change in composition coupled with a slow response to this change can lead to the spontaneous formation of multiple emulsions consisting of several inner cores within a polymer-rich middle phase. In the case of liquid-like biomolecular condensates, the slow diffusion of biopolymers causes nucleation of biopolymer-poor liquid inside of the condensate to achieve the new equilibrium composition. This framework shows that multiphase condensates can be a result of kinetic trapping, rather than thermodynamic stability, and provides and avenue to understand and control the internal structure of condensates in vitro and in vivo .
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".