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Record W3038775292 · doi:10.20517/cdr.2020.20

Exploring near-infrared absorbing nanocarriers to overcome cancer drug resistance

2020· review· en· W3038775292 on OpenAlexaff
Siwei Chu, Ursula Stochaj

Bibliographic record

VenueCancer Drug Resistance · 2020
Typereview
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsMcGill University
Fundersnot available
KeywordsNanocarriersNanomedicineNanotechnologyCancer therapyCancerMultiple drug resistanceBroad spectrumDrugDrug resistanceDrug deliveryMedicineMaterials sciencePharmacologyNanoparticleChemistryBiologyCombinatorial chemistryInternal medicine

Abstract

fetched live from OpenAlex

One of the major obstacles of successful cancer therapy is cancer drug resistance. The unique tools and applications developed by nanomedicine provide new approaches to surmount this common limitation of current treatment regimens. Nanocarriers that absorb light in the near-infrared spectrum are particularly suitable for this purpose. These nanocarriers can produce heat, release drugs or stimulate the production of physiologically relevant compounds when illuminated with near-infrared light. The current review summarizes the causes contributing to cancer multidrug resistance. The major types of nanocarriers that have been developed in recent years to overcome these hurdles are described. We focus on nanoparticles that are responsive to near-infrared light and suitable to surmount cancer multidrug resistance. Our review concludes with the bottlenecks that currently restrict the use of nanocarriers in the clinic and an outlook on future directions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.721
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.067
GPT teacher head0.288
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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