Microfluidic Based Biosensor for Detection of Cardiac Markers
Bibliographic record
Abstract
Myocardial Infarction (MI) occurs when the blood flow to the heart is blocked. It is major threat to human kind. Current laboratory and ELISA tests are expensive, time consuming, and are not very sensitive. Biosensors can play an important role in the diagnosis of MI without relying on hospital visits. Therefore, researchers are focusing to develop rapid, hand-held, inexpensive biosensors for detecting cardiac markers. In the present study, one of the cardiac markers (Troponin T) is detected using microfluidic based biosensor. Troponin T (cTnT) releases in to the blood serum within 4–6 h after minor heart attack and remains elevated for up to 2 weeks, which will help in diagnosing the heart condition. In this work, a microfluidic channel with an array of gold strips is considered for detecting and quantifying the Troponin T in an aqueous solution. Troponin T primary (capture) antibody is immobilized on gold strip using self assembled monolayer (SAM) consisting of a homogeneous mixture of oligo (ethylene glycol) (OEG)-terminated alkanethiolate and mercaptohexadecanoic acid (MHDA). Then, an aqueous solution containing Troponin T antigen is injected into the microchannel to facilitate antibody-antigen reaction to take place in less time. Later, FITC tagged Troponin T secondary (detection) antibody is dispensed in to the channel for quantification of Troponin T antigen. Using confocal fluorescent reader, the variation of fluorescent intensity across the microchannel is measured and quantified the concentration of Troponin T antigen with calibrated samples. Contact angle measurement system, Fourier Transform Infrared Spectroscopy and Ellipsometer are used to characterize the surface properties at each stage of biomolecule immobilization.
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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".