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Record W4411339137 · doi:10.26685/urncst.794

pH-Dependent Release and Folate Receptor Alpha (FRα) Targeting To Allow Exclusive Targeting of Lipid-Nanoparticles (LNP)

2025· article· en· W4411339137 on OpenAlexaffabout
Meghan A. Cymbron, Densika Ravindiralingam, Thomas Liang

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2025
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsFolate receptorChemistrySolid lipid nanoparticleNanoparticleNanotechnologyCancer researchMedicineMaterials scienceInternal medicineCancer

Abstract

fetched live from OpenAlex

Introduction: Colorectal cancer rates continue to rise in Canada, placing an increasing economic burden on the healthcare system and profoundly impacting patients’ quality of life. Here, we propose a novel method for delivering anti-colorectal cancer treatment that uses a Eudragit-coated folate-LNP conjugation to allow pH-sensitive release and specificity for cancerous colon cells. Methods: GFP-tagged IL-10 mRNA will serve as a biomarker to evaluate folate receptor alpha (FR binding, transfection, and release of therapeutic contents by the novel LNP formulation in LS174 human cells, measured by flow cytometry. To confirm exclusive delivery, tissue samples from the small and large intestines of ApcMin/+ mice treated with the formulation will be analyzed using ELISA following oral gavage. MTT assay of healthy, non-cancerous CCD 841 CoN will confirm consistent cell viability across non-targeted colonic tissue. Expected Results: The folate-LNP formulation is expected to bind FR on the LS174 cells efficiently and release the encapsulated IL-10 mRNA after endosomal escape, evidenced by significantly higher fluorescence in treated cells than the negative controls. In the mouse model, the Eudragit coating is anticipated to dissolve exclusively in the colonic tissue of the mouse models, with minimal dissolution in the small intestine, allowing targeted binding to cancerous colonic enterocytes. Discussion: Our proposed folate-LNP formulation is designed to achieve targeted delivery to colonic tissue by leveraging pH-sensitive release and FR upregulation in colorectal cancer cells. Efficient binding and successful translation of IL-10 mRNA in the LS174 cells will demonstrate the formulation’s specificity and therapeutic potential. Exclusive localization to cancerous colonic tissue in the mouse model will confirm the ability to bypass non-target tissues. Conclusion: This approach represents the first known proposal for a Eudragit-coated folate-LNP molecule targeting the colon. If successful, this approach could offer a more effective, targeted treatment for colorectal cancer, minimizing systemic side effects and improving patient outcomes. Future research and clinical validation are required to confirm the safety and efficacy of this approach, as well as to determine the patients who will benefit most.

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 score0.003

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 integrity0.0010.000
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 head0.364
Teacher spread0.336 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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