Nucleobase, nucleoside, nucleotide, and oligonucleotide coordinated metal ions for sensing and biomedicine applications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".