Through-grid wicking enables high-speed cryoEM specimen preparation
Bibliographic record
Abstract
Blotting times for conventional cryoEM specimen preparation complicate time-resolved studies and lead to some specimens adopting preferred orientations or denaturing at the air-water interface. Here, it is shown that solution sprayed onto one side of a holey cryoEM grid can be wicked through the grid by a glass-fiber filter held against the opposite side, often called the `back', of the grid, producing a film suitable for vitrification. This process can be completed in tens of milliseconds. Ultrasonic specimen application and through-grid wicking were combined in a high-speed specimen-preparation device that was named `Back-it-up' or BIU. The high liquid-absorption capacity of the glass fiber compared with self-wicking grids makes the method relatively insensitive to the amount of sample applied. Consequently, through-grid wicking produces large areas of ice that are suitable for cryoEM for both soluble and detergent-solubilized protein complexes. The speed of the device increases the number of views for a specimen that suffers from preferred orientations.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".