A surface-enhanced Raman scattering-based approach for rapid and highly sensitive quantitative analysis of 3-carboxy-4-methyl-5-propyl-2-furanpropionate and indole-3-acetic acid in saline, human serum and uremic serum of patients with chronic kidney disease
Bibliographic record
Abstract
3-Carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF) and indole-3-acetic acid (IAA) are critical protein-bound uremic toxins that occur during chronic kidney disease (CKD). This study offers the first reported instance of surface-enhanced Raman scattering (SERS) coupled with an Au nanoparticle substrate for the simple quantification of CMPF and IAA in human serum samples. The detection limits of the CMPF and IAA analysis were estimated to be 0.04 nM (S/N = 3) and 0.05 μM (S/N = 3), respectively. The results demonstrate that the SERS technique is fast-acting and highly sensitive when it comes to the simultaneous and individual quantitative detection of CMPF and IAA in biological samples. We believe that this analytical tool could serve as a very useful method for practical applications during the analysis of CMPF and IAA in the serum and urine of patients at all stages of CKD and of healthy volunteers as well as in various reservoirs.
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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 | 0.001 | 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 | 0.000 | 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".