A Novel Intranasal Spray Device for the Administration of Nanoparticles to Rodents
Bibliographic record
Abstract
Experimental intranasal (IN) delivery of nanoparticle (NP) drug carriers is typically performed using a pipette with or without anesthesia, a technique that may be a poor simulation of practical IN administration of drug-loaded NPs in humans. Existing IN spray devices suffer from drawbacks in terms of variability in dose-control and spray duration as well as the application of nonuniform pressure fields when a NP-formulated drug is aerosolized. Furthermore, existing spray devices require large volumes that may not be available or may be prohibitively expensive to prepare. In response, we have developed a novel pneumatically driven IN spray device for the administration of NPs, which is capable of administering extremely small quantities (50–100 μl) of NP suspension in a fine spray that disperses the NPs uniformly onto the tissue. This device was validated using haloperidol-loaded Solanum tuberosum lectin (STL)-functionalized, poly(ethylene glycol)–block-poly(d,l-lactic-co-glycolic acid) (PEG–PLGA) NPs targeted for delivery to the brain for schizophrenia treatment. A pneumatic pressure of 100 kPa was found to be optimal to produce a spray that effectively aerosolizes NP suspensions and delivers them evenly to the olfactory epithelium. IN administration of STL-functionalized NPs using the IN spray device increased brain tissue haloperidol concentrations by a factor of 1.2–1.5× compared to STL-functionalized NPs administered IN with a pipette. Such improved delivery enables the use of lower drug doses and thus offers both fewer local side-effects and lower costs without compromising therapeutic efficacy.
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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 | 0.003 | 0.001 |
| 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 | 0.001 | 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".