Nose-to-brain delivery of lithium via a sprayable in situ-forming hydrogel composed of chelating starch nanoparticles
Bibliographic record
Abstract
While bipolar disorder patients can benefit from lithium therapy, high levels of lithium in the serum can induce undesirable systemic side effects. Intranasal (IN) lithium delivery offers a potential solution to this challenge given its potential to facilitate improved lithium transport to brain when delivered to the olfactory mucosa. Herein, a sprayable, in situ forming nanoparticle network hydrogel (NNH) based on Schiff base interactions between chelator-functionalized oxidized starch nanoparticles (SNPs) and carboxymethyl chitosan (CMCh) is reported that can be deployed within the nasal cavity to release ultra-small penetrative SNPs over time. Chelating functional groups including citrate, ethylenediaminetetraacetic acid, and pentetic acid are shown to bind a variety of cations including lithium, magnesium, and calcium, with chelation directly linked to enhancements in the gel mechanics even for monovalent lithium. The hydrogels show high in vitro cytocompatibility with mouse striatal neuron and human primary nasal cell lines. Effective IN delivery of lithium to the brain is demonstrated for the first time, with both solution-based and hydrogel-loaded lithium showing in vivo efficacy in an amphetamine-induced pre-clinical rat bipolar manic phase model; specifically, IN-delivered NNHs can maintain successful attenuation of locomotor activity for up to 6 h while all other tested treatments (drug-only IN or conventional intraperitoneal delivery) failed to retain attenuation for more than two hours at the same lithium dose. As such, in situ-gelling and ion-chelating NNHs represent a new material that can effectively enable metal ion management in biomedical applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".