High quality frozen extracts of <i>Xenopus laevis</i> eggs reveal size-dependent control of metaphase spindle micromechanics
Bibliographic record
Abstract
Abstract Cell-free extracts from unfertilized Xenopus laevis eggs offer the opportunity for a variety of biochemical assays for analyzing essential cell cycle events, such as metaphase spindle assembly. However, extracts’ utility is often hampered by their short storage-stability duration and high quality variation. Here, we report a simple two-step method for preparing frozen egg extracts that retain spindle assembly activity levels that are close to those of freshly prepared extracts. Extract degradation associated with the freeze-thaw process can be substantially reduced by using centrifugal filter-based dehydration and slow sample cooling. Large amounts of frozen extract stocks from single batch preparations allowed us to collect a large number of data in micromanipulation experiments that are intrinsically low-throughput and, hence, clarify correlations between metaphase spindle size and stiffness. We anticipate that our method provides an assay platform with minimized biological heterogeneity and makes egg extracts more accessible to researchers as distributable material. Summary The authors describe a method for preparing frozen extracts of Xenopus laevis eggs that retain spindle assembly activity levels that are close to those of freshly prepared extracts. This allowed for clarifying the correlation between spindle size and stiffness.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".