Liquid Transmission Electron Microscopy for Probing Collagen Biomineralization
Bibliographic record
Abstract
ABSTRACT Collagen biomineralization is foundational to hard tissue assembly. While studied extensively, collagen mineralization processes are not fully understood as the majority of theories are derived from electron microscopy (EM) in static, dehydrated, or frozen conditions, unlike the liquid phase environment where mineralization occurs dynamically. Herein, novel liquid transmission EM (TEM) strategies are presented, where collagen mineralization was explored in liquid conditions for the first time. Custom thin-film enclosures were employed to visualize the mineralization of reconstituted collagen fibrils in a calcium-phosphate and polyaspartic acid solution to promote intrafibrillar mineralization. TEM highlighted that at early time points, precursor mineral particles attached to collagen and progressed to crystalline mineral platelets aligned with fibrils at later time points. This aligns with observations from other techniques and validates this liquid TEM approach. This work provides a new liquid imaging approach for exploring collagen biomineralization, advancing toward understanding disease pathogenesis and remineralization strategies for hard tissues.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".