Bone formation on rough, but not polished, subcutaneously implanted Ti surfaces is preceded by macrophage accumulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Implanted rough surfaces have long been associated with the accumulation of macrophages and other cells of the monocytic lineage such as foreign body giant cells and osteoclasts. As cells of the moncytic lineage are part of the immune system, the response of this cell family to biomaterials has attracted wide concern. This study compared events at the interface of implant surface topographies with varied roughness in a rat subcutaneous model. Titanium-coated epoxy replicas of machined, etched, blasted, titanium-plasma-sprayed (TPS), sandblasted-and-etched (SLA), micromachined, and polished surfaces were implanted for up to 11 weeks, and processed for light or electron microscopy or immunohistochemistry for ED1, a marker for recruited macrophages. Initially, healing appeared similar among all surfaces, the frequency of mineralization followed the order of SLA, micromachined, TPS, machined, etched, blasted, and polished surfaces. On the SLA surface macrophages, as identified by both ultrastructural morphology and immunohistochemistry were the predominant cell type at 1 week and persisted until mineralization occurred as early as 2 weeks. On smoother surfaces collagenous matrix predominated at 2 weeks and subsequently increased with time. There, thus, appears to be two routes to bone-like tissue formation on Ti implants in this rat subcutaneous model; macrophage-mediated and macrophage-independent dense collagenous-matrix-associated.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it