Nano-encapsulated curcumin in a chinchilla ear model
Bibliographic record
Abstract
Cisplatin is an extensively used chemotherapeutic agent in the treatment of a broad spectrum of tumors. Ototoxicity is currently the most frequent dose limiting side-effect of cisplatinum chemotherapy. Ototoxicity has been shown to be the result of two mechanisms: oxidation, and more recently: inflammation. Various agents have been studied to prevent cisplatin ototoxicity. None has been proven effective in clinical trials to this date. Curcumin, a spice derived from a plant called Curcuma longa, possesses antioxidant activity and inhibits mediators of inflammation. However, curcumin low solubility in water and its low bioavailability limit its use. These issues can be solved using a novel technique called nano-encapsulation. In this research project, we wanted to find out whether curcumin could be nano-encapsulated, and, if so, whether the nano-encapsulated curcumin applied transtympanically is ototoxic, and whether it could be detected in the cochlear fluid and the blood. To answer these questions, a polymer of N-isopropylacrylamide (NIPAM), N-vinyl-2-pyrrolidone (VP), Poly(ethyleneglycol) monoacrylate (PEG-A) was formed. Curcumin was then mounted in this polymer. Different measurements were performed to characterize the created molecule such as the fourier transform infrared (FTIR) spectroscopy, the ultraviolet visible (UV-Vis) spectroscopy, and the atomic force microscopy (AFM). Results showed that curcumin was indeed nano-encapsulated. To test the safety of the nano-encapsulated curcumin, it was applied transtympanically to the ears of 5 chinchillas. The hearing was recorded using the auditory brainstem response (ABR) and the distortion product otoacoustic emission (DPOAE). Results of this pilot study showed that the nano-encapsulated curcumin is not ototoxic. To detect the presence of the nano-encapsulated curcumin in the cochlear fluid and the blood, it was applied transtympanically to chinchillas. The cochlear fluids and the blood samples were withdrawn
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".