Aptamer-Based Electrochemical Microfluidic Biosensor for the Detection of <i>Cryptosporidium parvum</i>
Why this work is in the frame
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Bibliographic record
Abstract
Cryptosporidium parvum is a high-risk and opportunistic waterborne parasitic pathogen with highly infectious oocysts that can survive harsh environmental conditions for long periods. Current state-of-the-art methods are limited to lengthy imaging and antibody-based detection techniques that are slow, labor-intensive, and demand trained personnel. Therefore, the development of new sensing platforms for rapid and accurate identification at the point-of-care (POC) is essential to improve public health. Herein, we propose a novel electrochemical microfluidic aptasensor based on hierarchical 3D gold nano-/microislands (NMIs), functionalized with aptamers specific to C. parvum . We used aptamers as robust synthetic biorecognition elements with a remarkable ability to bind and discriminate among molecules to develop a highly selective biosensor. Also, the 3D gold NMIs feature a large active surface area that provides high sensitivity and a low limit of detection (LOD), especially when they are combined with aptamers,. The performance of the NMI aptasensor was assessed by testing the biosensor’s ability to detect different concentrations of C. parvum oocysts spiked in different sample matrices, i.e., buffer, tap water, and stool, within 40 min detection time. The electrochemical measurements showed an acceptable LOD of 5 oocysts mL –1 in buffer medium, as well as 10 oocysts mL –1 in stool and tap water media, over a wide linear range of 10–100,000 oocysts mL –1 . Moreover, the NMI aptasensor recognized C. parvum oocysts with high selectivity while exhibiting no significant cross-reactivity to other related coccidian parasites. The specific feasibility of the aptasensor was further demonstrated by the detection of the target C. parvum in patient stool samples. Our assay showed coherent results with microscopy and real-time quantitative polymerase chain reaction, achieving high sensitivity and specificity with a significant signal difference ( p < 0.001). Therefore, the proposed microfluidic electrochemical biosensor platform could be a stepping stone for the development of rapid and accurate detection of parasites at the POC.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it