Neurotransmitter-Responsive Nanosensors for <i>T</i><sub>2</sub>-Weighted Magnetic Resonance Imaging
Bibliographic record
Abstract
Neurotransmitter-sensitive contrast agents for magnetic resonance imaging (MRI) have recently been used for mapping signaling dynamics in live animal brains, but paramagnetic sensors for T1-weighted MRI are usually effective only at micromolar concentrations that themselves perturb neurochemistry. Here we present an alternative molecular architecture for detecting neurotransmitters, using superparamagnetic iron oxide nanoparticles conjugated to tethered neurotransmitter analogs and engineered neurotransmitter binding proteins. Interactions between the nanoparticle conjugates result in clustering that is reversibly disrupted in the presence of neurotransmitter analytes, thus altering T2-weighted MRI signals. We demonstrate this principle using tethered dopamine and serotonin analogs, together with proteins selected for their ability to competitively bind either the analogs or the neurotransmitters themselves. Corresponding sensors for dopamine and serotonin exhibit target-selective relaxivity changes of up to 20%, while also operating below endogenous neurotransmitter concentrations. Semisynthetic magnetic particle sensors thus represent a promising path for minimally perturbative studies of neurochemical analytes.
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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 | 0.001 |
| 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".