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Record W4385254342 · doi:10.3390/vaccines11081278

Plant Virus Nanoparticles Combat Cancer

2023· review· en· W4385254342 on OpenAlexaff
Mehdi Shahgolzari, Srividhya Venkataraman, Anne Osano, Paul A. Akpa, Kathleen Hefferon

Bibliographic record

VenueVaccines · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTumor microenvironmentCancer therapyCancerCancer cellNanotechnologyImmune systemBiocompatibilityCancer treatmentCancer researchTumor cellsMedicineChemistryMaterials scienceImmunology

Abstract

fetched live from OpenAlex

Plant virus nanoparticles (PVNPs) have garnered considerable interest as a promising nanotechnology approach to combat cancer. Owing to their biocompatibility, stability, and adjustable surface functionality, PVNPs hold tremendous potential for both therapeutic and imaging applications. The versatility of PVNPs is evident from their ability to be tailored to transport a range of therapeutic agents, including chemotherapy drugs, siRNA, and immunomodulators, thereby facilitating targeted delivery to the tumor microenvironment (TME). Furthermore, PVNPs may be customized with targeting ligands to selectively bind to cancer cell receptors, reducing off-target effects. Additionally, PVNPs possess immunogenic properties and can be engineered to exhibit tumor-associated antigens, thereby stimulating anti-tumor immune responses. In conclusion, the potential of PVNPs as a versatile platform for fighting cancer is immense, and further research is required to fully explore their potential and translate them into clinical applications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.202
GPT teacher head0.369
Teacher spread0.167 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2023
Admission routes1
Has abstractyes

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