Pyridoxamine-5-phosphate Enzyme-Linked Immune Mass Spectrometric Assay Substrate for Linear Absolute Quantification of Alkaline Phosphatase to the Yoctomole Range Applied to Prostate Specific Antigen
Bibliographic record
Abstract
There is a need to measure proteins that are present in concentrations below the detection limits of existing colorimetric approaches with enzyme-linked immunoabsorbent assays (ELISA). The powerful enzyme alkaline phosphatase conjugated to the highly specific bacterial protein streptavidin binds to biotinylated macromolecules like proteins, antibodies, or other ligands and receptors with a high affinity. The binding of the biotinylated detection antibody, with resulting amplification of the signal by the catalytic production of reporter molecules, is key to the sensitivity of ELISA. The specificity and amplification of the signal by the enzyme alkaline phosphatase in ELISA together with the sensitivity of liquid chromatography electrospray ionization and mass spectrometry (LC-ESI-MS) to detect femtomole to picomole amounts of reporter molecules results in an ultrasensitive enzyme-linked immune mass spectrometric assay (ELIMSA). The novel ELIMSA substrate pyridoxamine-5-phosphate (PA5P) is cleaved by the enzyme alkaline phosphatase to yield the basic and hydrophilic product pyridoxamine (PA) that elutes rapidly with symmetrical peaks and a flat baseline. Pyridoxamine (PA) and (13)C PA were both observed to show a linear relationship between log ion intensity and quantity from picomole to femtomole amounts by liquid chromatography-electrospray ionization and mass spectrometry. Four independent methods, (i) internal (13)C isotope PA dilution curves, (ii) internal (13)C isotope one-point calibration, (iii) external PA standard curve, and (iv) external (13)C PA standard curve, all agreed within 1 digit in the same order of magnitude on the linear quantification of PA. Hence, a mass spectrometer can be used to robustly detect 526 ymol of the alkaline phosphatase streptavidin probe and accurately quantify zeptomole amounts of PSA against log linear absolute standard by micro electrospray on a simple ion trap.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".