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Record W3028920338 · doi:10.1039/d0tb00962h

Plasmonic photothermal microneedle arrays and single needles for minimally-invasive deep in-skin hyperthermia

2020· article· en· W3028920338 on OpenAlexfundno aff
Álvaro Cárcamo-Martínez, Brónach Mallon, Juan Domínguez‐Robles, Ana Sara Cordeiro, Maurizio Celentano, Eneko Larrañeta, Steven E. J. Bell, Ryan F. Donnelly

Bibliographic record

VenueJournal of Materials Chemistry B · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsEngineering and Physical Sciences Research CouncilQueen's University BelfastEuropean CommissionQueen's UniversityWellcome Trust
KeywordsPhotothermal therapyMaterials scienceNanorodPlasmonLaserHyperthermiaIrradiationPhotothermal effectBiomedical engineeringNanotechnologyOptoelectronicsOpticsMedicine

Abstract

fetched live from OpenAlex

We report, for the first time, crosslinked polymeric microneedle (MN) arrays and single needles (2 mm and 4.5 mm length) coated with gold nanorods (GnRs) to induce deep hyperthermia in a 3 mm-thickness skin model upon near infrared (NIR) laser irradiation. Using excised neonatal porcine skin as tissue model, it was seen that insertion capabilities of single prototypes were not affected by the coating, as around 80% of their length was inserted before and after coating. Insertion of MN arrays dropped from 74% to 55%, which could be attributed to a less sharp structure after the coating process. Nonetheless, GnRs-coated MN arrays achieved the highest increase in temperature in the skin model: over 15 °C after only 15 s of NIR laser irradiation (808 nm, 2 W cm-2). Surprisingly, removal of MN arrays after irradiation left no detectable polymer or plasmonic material behind, confirming the enhanced safety and minimally-invasive potential of this device for future biomedical applications of deep in skin hyperthermia.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.066
GPT teacher head0.340
Teacher spread0.274 · 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 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

Citations24
Published2020
Admission routes1
Has abstractyes

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