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Record W4306249794 · doi:10.21203/rs.3.rs-2143931/v1

Lipid Nanoparticle Mediated Delivery of Docetaxel Prodrug for Exploiting Full Potential of Gold Radiosensitizers in the Treatment of Pancreatic Cancer.

2022· preprint· en· W4306249794 on OpenAlexafffund
Abdulaziz Alhussan, Nolan Jackson, Sarah Eaton, Nancy Dos Santos, Ingrid Barta, Josh Zaifman, Sam Chen, Yuen Yi C. Tam, Sunil Krishnan, Devika B. Chithrani

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaBritish Columbia Knowledge Development FundNational Institutes of HealthUniversity of Victoria
KeywordsDocetaxelIn vivoProdrugPancreatic cancerIn vitroChemistryPharmacologyColloidal goldToxicityCancerDrug deliveryCancer researchMedicineInternal medicineNanoparticleBiochemistryNanotechnologyBiologyMaterials science

Abstract

fetched live from OpenAlex

Abstract Background Pancreatic cancer is one of the leading causes of cancer deaths worldwide. Current chemoradiation therapy suffers from normal tissue toxicity. To overcome this problem, we are proposing incorporating nanoparticles as radiosensitizers and as drug delivery vehicles into current chemoradiation regimes. Gold nanoparticles (GNPs) and Docetaxel (DTX) have shown very promising synergetic radiosensitization effects despite DTX toxicity to normal tissues. Here, we explored the effect of DTX prodrug encapsulated in lipid nanoparticles (LNP DTX−P ) on GNP uptake in pancreatic cancer models in vitro and in vivo . Methods For the in vitro experiment, pancreatic cancer cell line, MIA PaCa-2, were cultured and dosed with 7.5 µg/mL of GNPs (of ~ 11 nm in diameter functionalized with PEG and RGD peptide) and with 45 nM of free DTX or equivalent dose of LNP DTX−P . For the in vivo experiment, MIA PaCa-2 were implanted subcutaneously in NRG mice and the mice were dosed with 2 mg/kg of GNPs and 6 mg/kg of DTX or equivalent dose of LNP DTX−P . GNPs content in mice and in cells were measured using Inductively Coupled Plasma–Mass Spectrometry (ICP–MS). Results The results show that LNP DTX−P treated tumour samples have no less than 191% increase in GNPs uptake compared to control samples in both in vitro and in vivo . The results also show that LNP DTX−P treated tumour samples have retained over 160% of GNPs compared to control samples in both in vitro and in vivo . No significant difference was found in GNP uptake or retention between free DTX and LNP DTX−P in tumour treated samples in vivo . Conclusions The results are very promising as LNP DTX−P have superior targeting of tumour tissues compared to free DTX due to their nano size and their ability to be functionalized. Because of their minimal toxicity to normal tissues, both GNPs and LNP DTX−P can be ideal radiosensitization candidates in radiotherapy and would produce very promising synergistic therapeutic outcome. Current radiotherapy treatments can hugely benefit from the effects of these two radiosensitizers boosting the radiation dose to the tumour while reducing the normal tissue dose. This in return will improve patient outcome and quality of life.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.344
Teacher spread0.289 · 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 teacher head, 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

Citations7
Published2022
Admission routes2
Has abstractyes

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