Multimodal and Multiscale Characterization of the <scp>Bone‐Bacteria</scp> Interface in a Case of <scp>Medication‐Related</scp> Osteonecrosis of the Jaw
Bibliographic record
Abstract
ABSTRACT Medication‐related osteonecrosis of the jaw (MRONJ) is a known side effect of bisphosphonates (BPs). Although bacterial infection is usually present, the etiology of MRONJ remains unknown. Here we apply a multimodal and multiscale (micro‐to‐nano) characterization approach to investigate the interface between necrotic bone and bacteria in MRONJ. A non‐necrotic bone sample was used as control. Both necrotic and non‐necrotic bone samples were collected from the jaw of a female individual affected by MRONJ after using BPs for 23 years. For the first time, resin cast etching was used to expose bacteria at the necrotic site. The bone–bacteria interface was also resolved at the nanoscale by scanning transmission electron microscopy (STEM). Nanosized particulates, likely corresponding to degraded bone mineral, were often noted in close proximity to or enclosed by the bacteria. STEM also revealed that the bone–bacteria interface is composed of a hypermineralized front fading into a highly disordered region, with decreasing content of calcium and phosphorus, as assessed by electron energy loss spectroscopy (EELS). This, combined with the variation in calcium, phosphorus, and carbon across the necrotic bone–bacteria interface evaluated by scanning electron microscopy (SEM)‐energy dispersive X‐ray spectroscopy (EDX) and the lower mineral‐to‐matrix ratio measured by micro‐Raman spectroscopy in necrotic bone, indicates the absence of a mineralization front in MRONJ. It appears that the bone–bacteria interface originates not only from uncontrolled mineralization but also from the direct action of bacteria degrading the bone matrix. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".