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Record W4416417196 · doi:10.1002/smll.202513138

Upconverting Nanoparticle‐Loaded Microneedles for Near‐Infrared Responsive Delivery of Gonadotropins to Increase Success of In Vitro Fertilization

2025· article· en· W4416417196 on OpenAlexaff
Vivienne Tam, Rusvir Trana, Alfonso Nieto‐Argüello, Ore‐Oluwa Olasubulumi, Samuel Babity, Artiom Skripka, Fiorenzo Vetrone, Davide Brambilla, Marta Cerruti

Bibliographic record

VenueSmall · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsInstitut National de la Recherche ScientifiqueMcGill University
Fundersnot available
KeywordsHypodermic needleIn vitroIn vitro fertilisationHuman fertilizationBolus (digestion)Drug delivery

Abstract

fetched live from OpenAlex

Abstract In vitro fertilization (IVF) requires repeated bolus injections of gonadotropins at precise times, making it a painful and stressful experience for women. Polymeric microneedles (MNs) present a painless alternative to hypodermic needles, but controlling the release of drugs through MNs remains a challenge. Here, we report the development of a hydrogel MN patch integrated with upconverting nanoparticles coated with light‐breakable mesoporous silica (UCNP@LBMS) that releases the IVF gonadotropin, leuprolide, in response to near‐infrared (NIR) light, while retaining the UCNPs within the MN patch. In rats, a 5 min NIR pulse of 2 W cm −2 results in a significant increase in leuprolide release in both skin and plasma, with MN length playing an important role in drug bioavailability. Beyond IVF, UCNP‐integrated MN patches offer a painless, automated alternative in any application that requires daily, repeated, time‐sensitive hypodermic needle injections, such as diabetes or multiple sclerosis.

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 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 score0.016
Threshold uncertainty score0.759

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)0.0000.000

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 head0.065
GPT teacher head0.395
Teacher spread0.330 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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