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Record W2564010196 · doi:10.1016/j.omtn.2016.12.002

Aptamers for CD Antigens: From Cell Profiling to Activity Modulation

2016· review· en· W2564010196 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Therapy — Nucleic Acids · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAptamerNucleic acidFlow cytometryBiologyCellAntigenMolecular biologyChemistryComputational biologyBiochemistryImmunology

Abstract

fetched live from OpenAlex

Nucleic acid-based aptamers are considered to be a promising alternative to antibodies because of their strong and specific binding to diverse targets, fast and inexpensive chemical synthesis, and easy labeling with a fluorescent dye or therapeutic agent. Cluster of differentiation (CD) proteins are among the most popular antigens for aptamers on the cell surface. These anti-CD aptamers could be used in cell biology and biomedicine, from simple cell phenotyping by flow cytometry or fluorescent microscopy to diagnosis and treatment of HIV/AIDS to cancer and immune therapies. The unique feature of aptamers is that they can act simultaneously as an agonist and antagonist of CD receptors depending on a degree of aptamer oligomerization. Aptamers can also deliver small interfering RNA to silence vital genes in CD-positive cells. In this review, we summarize nucleic acid sequences of anti-CD aptamers and their use, which have been validated in multiple studies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0000.000

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 head0.025
GPT teacher head0.322
Teacher spread0.297 · 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