Hybrid multimodal contrast agent for multiscale <i>in vivo</i> investigation of neuroinflammation
Bibliographic record
Abstract
Neuroinflammation is a process common to several brain pathologies. Despites its medical relevance, it still remains poorly understood; there is therefore a need to develop new in vivo preclinical imaging strategies to monitor inflammatory processes longitudinally. We here present the development of a hybrid imaging nanoprobe named NP3, that was specifically designed to get internalized by phagocytic cells and imaged in vivo with MRI and bi-photon microscopy. NP3 is composed of a 16 nm core of gadolinium fluoride (GdF3), coated with bisphosphonate polyethylene glycol (PEG) and functionalized with a Lemke-type fluorophore. It has a hydrodynamic diameter of 28 ± 8 nm and a zeta potential of -42 ± 6 mV. The MR relaxivity ratio at 7 T is r1/r2 = 20; therefore, NP3 is well suited as a T2/T2* contrast agent. In vitro cytotoxicity assessments performed on four human cell lines revealed no toxic effects of NP3. In addition, NP3 is internalized by macrophages in vitro without inducing inflammation or cytotoxicity. In vivo, uptake of NP3 has been observed in the spleen and the liver. NP3 has a prolonged vascular remanence, which is an advantage for macrophage uptake in vivo. The proof-of-concept that NP3 may be used as a contrast agent targeting phagocytic cells is provided in an animal model of ischemic stroke in transgenic CX3CR1-GFP/+ mice using three complementary imaging modalities: MRI, intravital two-photon microscopy and phase contrast imaging with synchrotron X-rays. In summary, NP3 is a promising preclinical tool for the multiscale and multimodal investigation of neuroinflammation.
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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 | 0.000 | 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 | 0.001 | 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 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".