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Exosome Packaging of the Targeted Antioxidant CAT‐SKL to Protect the Sensory Cells in the Inner Ear

2019· article· en· W3174005929 on OpenAlexafffund
Sureka Selvakumaran, Sarah H. Hayes, Qingfan Liu, Tiffany Ni, Paul A. Walton, Brian L. Allman

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsWestern University
FundersCanadian Institutes of Health ResearchW. Garfield Weston Foundation
KeywordsOtotoxicityOxidative stressCochleaViability assayAntioxidantMicrovesiclesPharmacologyCatalaseReactive oxygen speciesCisplatinCell biologyMedicineCellChemistryBiologyBiochemistryInternal medicineChemotherapyAudiologymicroRNA

Abstract

fetched live from OpenAlex

Hearing loss is a chronic health condition that affects millions of people worldwide. In addition to age‐related hearing loss, excessive exposure to loud noise or ototoxic chemotherapy drugs (e.g., cisplatin) can also lead to hearing impairment via oxidative stress in the sensory cells in the inner ear (cochlea). In such cases, the endogenous antioxidant enzymes (e.g., catalase) in the cochlea that normally mitigate the accumulation of reactive oxygen species become overwhelmed, resulting in permanent cell damage. To combat this oxidative stress, our research program is working to find effective strategies to deliver therapeutic doses of exogenous catalase to the cochlea. In the present study, we aimed (1) to evaluate whether our recombinant derivative of catalase, CAT‐SKL (which is designed to target the peroxisomes of cells) could protect against cisplatin‐induced cell death in vitro , and (2) to package CAT‐SKL into exosomes, and determine the safety, distribution and efficacy of this targeted antioxidant in vivo . In our first experiments, we assessed the safety and protective effects of CAT‐SKL using cochlear‐derived cells (HEI‐OC1) and WST‐1 cell viability assays. As predicted based on our previous studies in other tissues (e.g., brain, retina), CAT‐SKL was not harmful to HEI‐OC1 cells, and actually improved cell viability at higher concentrations. Importantly, CAT‐SKL offered significant protection against cisplatin‐induced ototoxicity, even when the doses of cisplatin exceeded levels known to cause damage. Motivated by this in vitro otoprotection, we then endeavored to package CAT‐SKL into exosomes, as this would provide a strategy to deliver the novel pharmaceutical in vivo . We packaged CAT‐SKL into macrophage‐derived exosomes (exoCAT‐SKL) via sonication, and purified the loaded exosomes using size exclusion chromatography. Successful loading of exoCAT‐SKL was confirmed using Western blotting and H202 decomposition assays. Next, adult mice were delivered intranasal administrations of a biotinylated version of CAT‐SKL packaged in exosomes, and their brains were then harvested and processed for streptavidin immunohistological staining. We observed extensive labelling of exoCAT‐SKL in the brains of these mice; evidence that intranasal administration not only effectively introduced our therapeutic into systemic circulation, but it was able to surpass tissue specific barriers that usually hinder uptake of therapeutics. Our ongoing experiments are investigating the bioavailability of repetitive intranasal dosing of exoCAT‐SKL in adult mice by harvesting their organs, and performing histopathological assessments. Once we have established the bioavailability of exoCAT‐SKL in the cochlea following intranasal delivery, we will be poised to investigate its efficacy at attenuating cisplatin‐induced ototoxicity in vivo . Based on our findings, we suggest that CAT‐SKL is a promising therapeutic for protection of cochlear cells from cisplatin‐induced ototoxicity, and that packaging CAT‐SKL into exosomes may offer an effective way to deliver therapeutic doses of this targeted antioxidant to cells undergoing oxidative stress. Support or Funding Information BrainsCAN, CIHR, The W. Garfield Weston Foundation This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.251
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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