Discrimination of single base mismatched oligonucleotides related to the <i>rpoB</i> gene of <i>Mycobacterium tuberculosis</i> using a surface plasmon resonance biosensor
Bibliographic record
Abstract
Single base mismatched oligonucleotides related to the rpoB gene of Mycobacterium tuberculosis, the mutations of which cause drug resistance of the infectious agent, were detected and discriminated using a surface plasmon resonance biosensor system. Thiol-modified oligonucleotides of the selected sequence (the probe) and 1-mercapto-6-hexanol were immobilized on a gold sensor surface. Hybridization between immobilized probe P2 and perfectly matched target T2 as well as a single base mismatched target TN was investigated in buffer solutions of various stringencies. Discrimination of perfectly matched and single base mismatched targets is achieved due to a difference in the level of their hybridization with the immobilized probe depending on stringency of the buffer solution. In 0.5×SSC buffer solution (7.5 mM sodium citrate, pH 7, containing 75 mM NaCl), sensor response at T2 injection into the measuring sensor cell was 16 times that at TN injection. The experimental results on surface hybridization between the studied oligonucleotides demonstrated a good correlation with theoretical calculations of thermodynamic parameters of these interactions in the solution. The described approach could be proposed as a basis for creating a biosensor for real-time label-free diagnostics of drug-resistant tuberculosis.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".