Effects of digestion protocols on the isolation and characterization of metal-metal wear particles. II. Analysis of ion release and particle composition
Bibliographic record
Abstract
The isolation of metal wear particles from hip simulator lubricants is important for understanding wear mechanisms and the tissue response to particulate material. Part I of this study demonstrated that isolation protocols involving digestion reagents can chemically attack metal-metal wear particles, reducing their size and changing their shape. In part II of this study, Co and Cr ion concentrations in solution after each digestion protocol were measured by flame atomic absorption spectrometry, and wear particle composition was determined by X-ray analysis spectra. The exposure of wear particles in water to alkaline solutions caused an increasing release of Cr ions in solution with alkaline concentration and time, and a corresponding decrease in particle Cr peak intensity on X-ray spectra. As a result, particles exposed to 12N KOH for 48 h displayed Co peaks and no Cr. In contrast, enzymatic protocols caused a release of Co ions in solution and a corresponding decrease in particle Co peak intensity on X-ray spectra, especially with sodium phosphate as a buffer. However, when isolating particles from 95% serum, there was an initial protective effect of serum proteins, presumably because of their binding to Co and Cr. As a result, the extent of Cr ion release from metal wear particles in 95% serum after alkaline treatments was diminished, although still present, whereas both enzymatic protocols resulted in a negligible release of Co and Cr ions into solution. Particle composition analysis after enzymatic treatments revealed the presence of chromium oxide particles and CoCrMo particles with variable Co/Cr ratios. After alkaline treatments, the chromium oxide particles increasingly disappeared with time and alkaline concentration, demonstrating a change in particle composition after these treatments. This study demonstrated that digestion reagents can induce chemical changes that affect particle composition. Of all the protocols tested, the enzymatic protocols were the least damaging to the particles and appeared to be the best compromise for isolation and characterization of metal particles, especially in 95% serum. Special care on the choice of buffers should be taken when isolating particles from a lower concentration of serum.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".