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Record W2024482300 · doi:10.1166/jnn.2011.4167

Single-Domain Antibody Bioconjugated Near-IR Quantum Dots for Targeted Cellular Imaging of Pancreatic Cancer

2011· article· en· W2024482300 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

VenueJournal of Nanoscience and Nanotechnology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsSingle-domain antibodyQuantum dotMaterials sciencePancreatic cancerMolecular imagingEpithelial cell adhesion moleculeCancer researchNanotechnologyCarcinoembryonic antigenAntibodyCancerBiophysicsMedicineIn vivoImmunologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Successful targeted imaging of BxPC3 human pancreatic cancer cells is feasible with near-IR CdTeSe/CdS quantum dots (QDs) functionalized with single-domain antibody (sdAb) 2A3. For specific targeting, sdAbs are superior to conventional antibodies, especially in terms of stability, aggregation, and production cost. The bright CdTeSe/CdS QDs were synthesized to emit in the diagnostic window of 650-900 nm with a narrow emission band. 2A3 was derived from llama and is small in size of 13 kDa, but with fully-functional recognition to the target carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6), a possible biomarker as a therapeutic target of pancreatic cancer. For compelling imaging, optical may be the most sensible among the various imaging modalities, regarding the sensitivity and cost. This first report on sdAb-conjugated near-IR QDs with high signal to background sensitivity for targeted cellular imaging brings insights into the development of optical molecular imaging for early stage cancer diagnosis.

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 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 score0.039
Threshold uncertainty score0.382

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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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