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Record W4210459027 · doi:10.1039/d1ob02468j

A dual therapeutic system based on corrole-siRNA conjugates

2022· article· en· W4210459027 on OpenAlexafffund
Ifrodet Giorgees, Fan Wu, Zhen Shen, Jean‐Paul Desaulniers

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPorphyrin and Phthalocyanine Chemistry
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsCorroleGene knockdownSmall interfering RNAGene silencingChemistryPhotosensitizerRNA interferencePhotodynamic therapyBiophysicsCell biologyTransfectionGeneBiochemistryPhotochemistryRNABiology

Abstract

fetched live from OpenAlex

s of 387.8, 77.8, 60.0, and 49.4 pM in the absence of red light, and 101.0, 57.2, 55.3, and 23.8 pM in the presence of red light. Furthermore, PDT showed approximately a 50% decrease in cell viability for red-light irradiated cells treated with corrole-siRNAs, demonstrating the effective role of corrole to act as a photosensitizer while still maintaining robust siRNA activity. In conclusion, corrole-siRNAs show a promising path for developing novel siRNA combination therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes2
Has abstractyes

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