A Versatile System for High-Throughput In Situ X-ray Screening and Data Collection of Soluble and Membrane-Protein Crystals
Bibliographic record
Abstract
Abstract In recent years, in situ data collection has been a major focus of progress in protein crystallography. Here, we introduce the Mylar in situ method using Mylar-based sandwich plates that are inexpensive, easy to make and handle, and show significantly less background scattering than other setups. A variety of cognate holders for patches of Mylar in situ sandwich films corresponding to one or more wells makes the method robust and versatile, allows for storage and shipping of entire wells, and enables automated crystal imaging, screening, and goniometer-based X-ray diffraction data-collection at room temperature and under cryogenic conditions for soluble and membrane-protein crystals grown in or transferred to these plates. We validated the Mylar in situ method using crystals of the water-soluble proteins hen egg-white lysozyme and sperm whale myoglobin as well as the 7-transmembrane protein bacteriorhodopsin from Haloquadratum walsbyi. In conjunction with current developments at synchrotrons, this approach promises high-resolution structural studies of membrane proteins to become faster and more routine.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".