Label-free multiplex electrochemical immunosensor for early diagnosis of lysosomal storage disorders
Bibliographic record
Abstract
Pompe, Gaucher and Krabbe disease are lysosomal storage disorders (LSDs) which are a group of genetic diseases that causes the accumulation of lipids in tissues and cells. Pompe, Gaucher and Krabbe are characterized by the deficiency of acid α-glucosidase (GAA), β-Glucocerebrosidase (GBA) and galactocerebrosidase (GALC), and treatable if detected in their early stages. Here, we present the fabrication of an electrochemical immunosensor for the multiplexed quantification and simultaneous detection of GAA, GBA and GALC. The sensor was developed by electrodepositing gold nanoparticles (AuNPs) on an array of carbon electrodes, followed by the immobilization of GAA, GBA and GALC specific antibodies via functionalization with cysteamine and glutaraldehyde. The multiplexed immunosensor was able to successfully detect GAA, GBA and GALC at the femtomolar level with respective low detection limits of 0.12 pg/ml, 0.31 pg/ml and 0.18 pg/ml. The immunosensor showed good selectivity, sensitivity and good recovery when spiked in human serum, which confirms its possible applicability in point-of-care testing for the early diagnosis of LSDs.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".