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Record W2609208998 · doi:10.17975/sfj-2017-007

<i>In Vivo</i> Potential of Manganese Chelated Porphysomes as MRI Contrast Agents

2017· article· en· W2609208998 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSTEM Fellowship Journal · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIn vivoChelationConjugated systemLiposomePorphyrinChemistryMoietyManganeseBiophysicsNanoparticleFluorescenceCombinatorial chemistryNuclear magnetic resonanceMaterials scienceNanotechnologyBiochemistryStereochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Porphysome nanoparticles are composed of porphyrin-conjugated lipids. The attachment of the porphyrin moiety to each phospholipid confers novel properties to the liposome-like nanoparticle, allowing it to perform a variety of diagnostic and therapeutic applications. The metal chelating properties of porphyrin can be used to bind manganese (Mn), transforming the porphysome into a contrast agent for magnetic resonance imaging (MRI). Previous work has extensively characterized the properties of the Mn-porphysome. Herein, we build upon that work by demonstrating the bio-interactions of Mn-porphysomes in vitro to validate their study in vivo. Particle stability in serum was inferred from fluorescence quenching efficiency, and tolerability to cells was measured using an MTT assay. Mn-porphysomes remained &gt;80% quenched after 14H and showed no toxicity to cells at concentrations below 125 mM. These preliminary results suggest that the porphysome may be used to enhance MRI contrast in vivo.

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)0.001
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 score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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