Integrated microfluidic immunoassays for point-of-care diagnostic measurement of human serum cystatin C in chronic kidney disease
Bibliographic record
Abstract
Cystatin C (CYS-C) is considered superior to creatinine as a serum biomarker of estimated glomerular filtration rate (eGFR) for chronic kidney disease (CKD) assessment. It is minimally influenced by non-filtration-specific factors such as muscle mass, age and gender. However, currently CYS-C testing is limited to specialized diagnostic labs and no point-of-care (PoC) tools are clinically available. To address this gap, we leveraged the enabling power of microfluidic devices for PoC tests of CYS-C. Among the microfluidic devices, PDMS-based wet chips and paper-based dry chips have been widely used for disease biomarker measurements with their respective advantages and limitations. Therefore, in this study, we developed a PDMS-based microfluidic immunoturbidity chip allowing side-scattering optical measurement and a paper-based microfluidic lateral flow immunoassay chip plus a novel electric field-assisted antibody loading protocol for quantitative CYS-C tests. We demonstrated that both chips meet the clinical requirements of the serum CYS-C detection range and limit. Importantly, each type of microfluidic chip is integrated with a custom-developed portable reader as PoC test prototypes. In validation studies using serum samples from CKD patients, both chip tests showed a similar agreement level with the traditional well plate-based immunoturbidity assay test results. As an integrated PoC test system, the microfluidic CYS-C paper chip test showed higher accuracy in determining the eGFR range based on several clinically relevant grouping criteria compared to the turbidity chip test. Collectively, these integrated microfluidic assays offer practical solutions for decentralized PoC diagnostic tests of CKD with competitive advantages over existing methods. • Developed two types of microfluidic devices for point-of-care testing of serum cystatin C. • Developed two portable readers, one for each type of microfluidic device. • The developed microfluidic systems were effectively applied to test clinical samples.
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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 | 0.001 | 0.001 |
| 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".