Poly(ethylene glycol)-alendronate coated nanoparticles for magnetic resonance imaging of lymph nodes
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
Nanoparticulate systems can passively target regional lymphatic vessels and lymph nodes (LNs) after interstitial administration. Highly sensitive non-invasive imaging techniques, such as magnetic resonance imaging (MRI), can take advantage from particles' lymphotropic properties to provide a reliable tool to monitor lymphatic function and LN morphology with high spatial resolution. In this work, we developed and characterised a bioerodible nanosystem with MRI contrast properties, based on poly(ethylene glycol)-alendronate stabilised gadolinium calcium phosphate nanoparticles (NPs). After foot paw injection in mice, the particles exhibited a distinct pattern of gradual uptake into the local lymphatics and a localised deposition in the popliteal LN. Less variability in the onset of the signal, intensity and localisation was observed compared to the commercially available tracer gadobutrol, suggesting that these NPs could be useful to monitor physiological and dysfunctional lymphatic conditions. Moreover, dissolution of the particles indicated that they would be rapidly cleared from the body after imaging. Nevertheless, our findings call for an improvement of the system that includes reduction of gadolinium leakage from the NPs, and decrease in size of the latter to increase their selective uptake by the LN.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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