Combined Raman Microscopy and Transmission Electron Microscopy shows the co-existence of whitlockite crystals and carbonated hydroxyapatite-mineralized collagen fibrils in human calcified aortic valves
Bibliographic record
Abstract
Abstract Aortic valve stenosis (AS), the leading valvular disease in aging populations, is driven by complex extracellular matrix (ECM) modifications and progressive calcification. Despite its clinical significance, the molecular mechanisms underlying AS remain poorly understood, limiting therapeutic options to invasive valve replacement. This study employs Raman microscopy, a label-free imaging technique, and its integration with transmission electron microscopy (TEM) to elucidate the biochemical and ultrastructural changes in stenotic aortic valves. High-resolution spectroscopic imaging revealed distinct extracellular matrix modification across different regions, involving elastin degradation, cholesterol deposition, and mineral formation, comprising not only hydroxyapatite (cHAp) but also whitlockite. Elastin-rich domains associated with cHAp deposition exhibited cross-link degradation, while collagen matrices supported mineralized phases with varying mineral-to-matrix ratios that, in heavily mineralized regions, went far above those of mature human bone. For the first time we demonstrated whitlockite as a mineral deposit in calcified aortic valves, in areas with different degrees of calcification. This implies that this Mg containing mineral, which has been considered a precursor to cHAp in pathological calcification, forms independently, challenging prevailing models of calcification. The combination of Raman and TEM showed how bone-like cHAp mineralized collagen matrix in later stages engulfs the initial non-physiological whitlockite deposits. This correlative multimodal approach advances our understanding of AS by capturing spatially resolved chemical and structural dynamics at the nanoscale. The findings highlight Raman microscopy’s potential for probing calcification mechanisms across diverse tissue types and suggest its role in identifying novel therapeutic targets. This study underscores the value of integrative imaging methodologies in unraveling complex pathological processes and advancing patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".