Synthesis and Application of Metal Oxide/Graphene Oxide Nanocomposite Probe for Biosensing Methionine in Uremic Blood and Urine Samples
Bibliographic record
Abstract
Methionine (Met, Figure 1) is an essential amino acid in higher mammals as well as a substrate for most amino acids like taurine and cysteine. Met is responsible for cellular growth and development in humans since it contributes to the synthesis of most proteins as well as detoxify and regulate cellular aging. Changes in blood level Met may not be detrimental to human health, however, its contribution to regulating cysteine and homocysteine may contribute to some metabolic disorders in end-stage renal disease (ESRD) patients with no heart-related ailments. In the present study, a novel research approach toward synthesis of pencil probe composed of AgO/CuO/graphene oxide nanocomposites is presented. This probe was then utilized in biosensing Met in uremic blood and urine samples at the nano-level of detection. Prior to Met sensing, the synthesized probe was characterized using X-ray Photoelectron Spectroscopy, Raman spectroscopy and scanning electron microscopy techniques. Accompanying electrode reactions were monitored by means of cyclic voltammetry and electrochemical impedance spectroscopic techniques. The Ag-induced catalytic activity between pH 6-10 was observed following Met oxidation at the surface of the probe in the presence of hydroxide ions. Detection of Met was ascribed to the unique electroactive Ag and Cu sites of the probe. Its efficiency toward Met biosensing within both uremic blood and urine samples in the presence of potential sample-bound interferences was also investigated. With the emergence of complications involving some cardiovascular diseases associated with residual methionine in very few ESRD patients undergoing dialysis, this work presents a molecular nanao-level Met sensing as a disease biomarker. The lowest limit of detection for Met in this study was 45, 50 and 60 nM in the serum, plasma and urine, respectively. Keywords: Biosensing; Disease biomarker; Methionine; Uremic blood; Pencil sensing probe Figure 1. Molecular structure of methionine (Met) analyte. Figure 1
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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) | 0.000 | 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".