<i>In Vivo</i> Magnetic Resonance Imaging and Relaxometry Study of a Porous Hydrogel Implanted in the Trapezius Muscle of Rabbits
Bibliographic record
Abstract
In vivo magnetic resonance imaging (MRI) and relaxometry were performed to assess noninvasively the tissue reaction and the biological integration of hydrogels made of poly[N-(2-hydroxypropyl) methacrylamide] (PHPMA) after implantation in the trapezius muscle of rabbits. The benefits of incorporating RGD peptide sequences in the polymer backbone were also investigated. The histological status of each implant was probed by the trend of their transversal relaxation times, T(2), while their biocompatibility was evaluated by analyzing the host tissue response through the evolution of the relaxation times of the adjacent muscle tissue. MR results showed the good acceptability of both hydrogels by the host tissue. The transversal relaxation curves of each implant exhibited two distinct phases as a function of implantation time: (1) a monoexponential phase, dominated by the influx of fluids inside the implants; and (2) a biexponential phase related to the infiltration of cells and the granulation tissue formation within the porous structure of each polymer. These MR findings were correlated with the results of conventional histological analyses. The present study demonstrates the effectiveness of MR methods in noninvasively monitoring the biocompatibility and histological status of implanted porous biomaterials.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".