Validation of a new multiplex assay against individual immunoassays for the quantification of reproductive, stress, and energetic metabolism biomarkers in urine specimens
Bibliographic record
Abstract
UNLABELLED: Measuring multiple hormones simultaneously in a single assay saves sample volume, labor, time, reagents, money, and consumables. Thus, multiplex arrays represent a faster, more economically and ecologically sound alternative to singleton assays. OBJECTIVES: To validate a new, commercially available multiplex female array produced by Quansys Biosciences against individual immunoassays for the quantification of six hormones in urine samples from women in different reproductive stages. METHODS: Urine samples were analyzed using the new Quansys multiplex female hormone array and compared with well-established individual immunoassays for adiponectin, free cortisol, c-peptide, estrone-3-glucuronide (E₁G), follicle stimulating hormone beta-subunit (FSH-beta), and human chorionic gonadotropin beta-subunit (hCG-beta). Correlations between assays were assessed using Pearson correlation, linear regression and Bland-Altman analysis. The temporal profiles of free cortisol, E1G, FSH-beta, and hCG-beta were also compared. RESULTS: The multiplex array was highly correlated with the individual immunoassays for five of the tested hormones (Pearson's correlation coefficient ≥ 0.75), and yielded temporal patterns of hormone profiles consistent with the individual immunoassays for free cortisol, E₁G, FSH-beta, and hCG-beta. CONCLUSIONS: The Quansys multiplex female hormone array is a valid alternative method to individual immunoassays for the quantification of stress, reproductive and energetic hormones and metabolites in human urine samples and can be used to examine the dynamic interactions between these hormones.
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 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 | 0.001 |
| 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 | 0.001 |
| 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".