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Record W4285170576 · doi:10.7150/thno.72949

Aptamers used for molecular imaging and theranostics - recent developments

2022· review· en· W4285170576 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.

Bibliographic record

VenueTheranostics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersH. Lundbeck A/SLundbeckfonden
KeywordsAptamerMolecular imagingNanotechnologyComputational biologyMedical physicsMedicineBiologyMaterials scienceMolecular biologyBiotechnology

Abstract

fetched live from OpenAlex

Aptamers are single stranded oligonucleotides that fold into three dimensional structures and are able to recognize a variety of molecular targets. Due to the similarity to antibodies with regards to specificity and affinity and their chemical versatility, aptamers are increasingly used to create targeted probes for in vivo molecular imaging and therapy. Hence, aptamer-based probes have been utilized in practically all major imaging modalities such as nuclear imaging, magnetic resonance imaging, x-ray computed tomography, echography and fluorescence imaging, as well as newer modalities such as surface enhanced Raman spectroscopy. Aside from targeting, aptamers have been used for the creation of sensors that allow the localized detection of cellular markers such as ATP in vivo. This review focuses on in vivo studies of aptamer-based probes for imaging and theranostics since the comprehensive overview by Bouvier-Mller and Ducong in 2018.

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 score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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