Palladium–iridium nanocubes modified with a high-affinity DNA aptamer as paired viral diagnostic and therapeutic tools
Bibliographic record
Abstract
The COVID-19 pandemic emphasizes the need for the development of molecular tools that can be used as effective diagnostic and therapeutic agents. Herein we investigate the potential of aptamer-dressed nanomaterials both as diagnostics and therapeutics using SARS-CoV-2 as a model. The nanomaterials are based on the palladium-iridium (Pd–Ir) nanocubes modified with monomeric, dimeric or trimeric aptamers that exhibit varying affinities for the spike protein of SARS-CoV-2. These nanomaterials were first examined for diagnostic potential through the creation of a nanozyme-linked aptamer assay (NLAA) that takes advantage of the peroxidase-mimicking activity of Pd–Ir nanocubes. The trimeric aptamer-based NLAA demonstrated a limit of detection (LOD) of 9.3×10 3 cp/mL for pseudoviruses expressing the spike protein of SARS-CoV-2, 172- and 12.9-fold lower than that of the monomeric and dimeric aptamer-based NLAAs, respectively. Upon testing with 60 clinical saliva samples, the trimeric aptamer-based NLAA achieved a specificity of 100% and a sensitivity of 86.7%. The same nanomaterials were also examined for the ability to block viral entry to host cells. The trimeric aptamer-conjugated nanocubes exhibited a superior neutralizing ability, with an IC 50 value of 6.4 pM, 2.7-fold and 10.1-fold lower than that of the dimeric and monomeric aptamer nanocubes. Moreover, the trimeric aptamer-conjugated nanocubes exhibited excellent biostability and biocompatibility. Overall, our study provides a framework for combating future viral pandemics through the development of a paired biosensor and neutralizing agent made of the same aptamer-modified nanomaterial that recognizes an important viral surface protein like the spike protein of SARS-CoV-2. • Pd–Ir@trimeric aptamer outperforms its monomeric and dimeric aptamer counterparts. • Pd–Ir@trimeric aptamer demonstrated 100 % specificity and 86.7 % sensitivity for COVID-19 diagnosis using saliva. • Pd–Ir@trimeric aptamer achieved an IC 50 of 6.4 pM for SARS-CoV-2 neutralization by blocking spike protein.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".