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Record W3156207566 · doi:10.1007/s12274-021-3483-z

Nucleobase, nucleoside, nucleotide, and oligonucleotide coordinated metal ions for sensing and biomedicine applications

2021· article· en· W3156207566 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

VenueNano Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNucleobaseNanomaterialsBiomoleculeNanotechnologyNucleotideOligonucleotideCombinatorial chemistryBiosensorMetal ions in aqueous solutionDNANucleosideMaterials scienceChemistryMetalOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Metal ions play critical roles in chemical, biological, and environmental processes. Various biomolecules have the ability to coordinate with metal ions and form various materials. Nucleobases, nucleosides, and nucleotides, as the essential components of DNA, have emerged as a useful building block for the construction of functional nanomaterials. In recent years, DNA oligonucleotides have also been used for this purpose. We herein review the strategies for the synthesis of soft nanomaterials through the assembly of nucleotides (or DNA) and metal ions to yield various nanoparticles, fibers, and hydrogels. Such coordination methods are simple to operate and can be carried out under ambient conditions. The luminescent, catalytic, and molecular recognition properties of these coordination materials are described with representative recent examples. Their applications ranging from biosensing, enzyme encapsulation, catalysis, templated shell growth to cancer therapy are highlighted. Finally, challenges of this field and future perspectives are discussed.

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 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 score0.131
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.367
Teacher spread0.334 · 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