Localized reconstruction in Scipion expedites the analysis of symmetry mismatches in cryo-EM data
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Bibliographic record
Abstract
Technological advances in transmission electron microscopes and detectors have turned cryogenic electron microscopy (cryo-EM) into an essential tool for structural biology. A commonly used cryo-EM data analysis method, single particle analysis, averages hundreds of thousands of low-dose images of individual macromolecular complexes to determine a density map of the complex. The presence of symmetry in the complex is beneficial since each projection image can be assigned to multiple views of the complex. However, data processing that applies symmetry can average out asymmetric features and consequently data analysis methods are required to resolve asymmetric structural features. Scipion is a cryo-EM image processing framework that integrates functions from different image processing packages as plugins. To extend its functionality for handling symmetry mismatches, we present here a Scipion plugin termed LocalRec implementing the localized reconstruction method. When tested on an adenovirus data set, the plugin enables resolving the symmetry-mismatched trimeric fibre bound to the five-fold vertices of the capsid. Furthermore, it improves the structure determination of the icosahedral capsid by dealing with the defocus gradient across the particle. LocalRec is expected to be widely applicable in a range of cryo-EM investigations of flexible and symmetry mismatched complexes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it