Gadolinium Effects on Liposome Fluidity and Size Depend on the Headgroup and Side Chain Structure of Key Mammalian Brain Lipids
Bibliographic record
Abstract
The lanthanide metal gadolinium has been used in the healthcare industry as a paramagnetic contrast agent for years. Gadolinium deposition in brain tissue and kidneys has been reported following gadolinium-based contrast agent administration to patients undergoing MRI. This study demonstrates the detrimental effects of gadolinium exposure at the level of the cell membrane. Biophysical analysis using fluorescence spectroscopy and dynamic light scattering illustrates differential interactions of gadolinium ions with key classes of brain membrane lipids, including phosphatidylcholines and sphingomyelins, as well as brain polar extracts and biomimetic brain model membranes. Electrostatic attraction to negatively charged lipids like phosphatidylserine facilitates metal complexation but zwitterionic phosphatidylcholine and sphingomyelin interaction was also significant, leading to membrane rigidification and increases in liposome size. Effects were stronger for fully saturated over monounsaturated acyl chains. The metal targets key lipid classes of brain membranes and these biophysical changes could be very detrimental in biological membranes, suggesting that the potential negative impact of gadolinium contrast agents will require more scientific attention.
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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 | 0.000 | 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".