2021 Frank Stinchfield Award: A novel cemented hip hemiarthroplasty infection model with real-time in vivo imaging in rats
Bibliographic record
Abstract
Aims The aims of this study were to develop an in vivo model of periprosthetic joint infection (PJI) in cemented hip hemiarthroplasty, and to monitor infection and biofilm formation in real-time. Methods Sprague-Dawley rats underwent cemented hip hemiarthroplasty via the posterior approach with pre- and postoperative gait assessments. Infection with Staphylococcus aureus Xen36 was monitored with in vivo photoluminescent imaging in real-time. Pre- and postoperative gait analyses were performed and compared. Postmortem micro (m) CT was used to assess implant integration; field emission scanning electron microscopy (FE-SEM) was used to assess biofilm formation on prosthetic surfaces. Results All animals tolerated surgery well, with preservation of gait mechanics and weightbearing in control individuals. Postoperative in vivo imaging demonstrated predictable evolution of infection with logarithmic signal decay coinciding with abscess formation. Postmortem mCT qualitative volumetric analysis showed high contact area and both cement-bone and cement-implant interdigitation. FE-SEM revealed biofilm formation on the prosthetic head. Conclusion This study demonstrates the utility of a new, high-fidelity model of in vivo PJI using cemented hip hemiarthroplasty in rats. Inoculation with bioluminescent bacteria allows for non-invasive, real-time monitoring of infection. Cite this article: Bone Joint J 2021;103-B(7 Supple B):9–16.
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 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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".