An MRI contrast agent based on a zwitterionic metal-chelating polymer for hepatorenal angiography and tumor imaging
Bibliographic record
Abstract
MRI contrast agents such as paramagnetic Gd(iii)-chelates, can improve the ability of MRI in differentiating diseased and healthy tissues, and have been widely used in clinical diagnosis. However, the enhancement effect of small molecular MRI contrast agents is unsatisfied due to their relative high rotation rates. Furthermore, the small molecular contrast agents also suffer from the short blood half-life and nonspecific extracellular diffusion in tissues, which also restricts their applications. To address these issues, we developed a macromolecular MRI contrast agent based on a zwitterionic metal-chelating polymer. Poly(acrylic acid) (PAA) was chosen as the main chain, and diethylenetriamine pentaacetic acid (DTPA) as the metal-chelating group was coupled through the carboxyl groups of PAA using diethylenetriamine (DET) as a linker. The macromolecular MRI contrast agent constructed by chelating with Gd3+ (Gd-PAA) exhibited a much higher longitudinal relaxation rate (r1) than the clinical contrast agent Gd-DTPA. Importantly, due to the stealth ability of the zwitterionic structure, Gd-PAA can reside in the blood long enough without any microvascular leakage in the extracellular space of normal tissues, which allows it to be used for precise blood MR imaging, such as hepatorenal angiography, but also for tumor imaging because of the enhanced permeability and retention (EPR) effecta. Besides, the result of long-term toxicity tests highlights the safety feature of the current contrast agent. Hence, the current contrast agent overcomes the defect of traditional small molecular Gd(iii)-based T1-weighted contrast agents and shows great prospects for future clinical applications.
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 | 0.000 | 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 | 0.000 | 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 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".