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Record W4403553586 · doi:10.1002/nano.202400107

Near‐Infrared Nanoparticle‐Mediated Photothermal Cancer Therapy: A Comprehensive Review of Advances in Monitoring and Controlling Thermal Effects for Effective Cancer Treatment

2024· review· en· W4403553586 on OpenAlex
Fatma Oudjedi, Andrew G. Kirk

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNano Select · 2024
Typereview
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhotothermal therapyCancerCancer therapyCancer treatmentNanotechnologyNanoparticleMaterials scienceMedicineInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Photothermal therapy (PTT) has emerged as a promising alternative to conventional cancer treatments such as radiation therapy, chemotherapy, and surgery. PTT uses light‐absorbing nanomaterials to induce localized hyperthermia and selectively eliminate cancer cells, thus offering advantages over traditional interventions. This literature review focuses on nanoparticles for PTT, their heating properties, and their functions in theragnostic applications for photothermal cancer treatment. It highlights the fundamental principles, recent spectroscopic developments for diagnosis and treatment monitoring, clinical advancements in near‐infrared (NIR) nanoparticle‐mediated PTT, and emerging numerical methods for preclinical planning of PTT.

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
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)0.0000.000

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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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