Portable CIP-based microfluidic platform for optical bacteriadetection
Bibliographic record
Abstract
The increasing need, along with the advancements in microfluidics technology, has sparked the transition from conventional pathogen detection methods to faster, miniaturized, and cost-effective point-of-care (POC) and point-of-use (POU) technologies for use in remote and user settings.Microfluidic technology, commonly known as "Lab-on-a-Chip" (LOC), is a versatile, multipurpose instrument that amplifies scientific findings in its microchannels.On the other hand, as a steady and trustworthy indication in the bacteria detection system, Cell Imprinted Polymers (CIPs), synthesizes highly selective sorbents that are customized to our target bacteria.The integration of microfluidics and imprinted polymers has become a promising technique in biosensing applications in the recent years.We have previously developed a facile approach to coat bacterium-specific CIPs on florescent magnetic microparticles (MMPs) as a biosensing interface.CIP-coated MMPs (CIP-MMPs) were captured in a microfluidic device using external magnet and internal magnetic iron-PDMS microstructures, then fluorescent attenuation microscopy was used for proof-of-principle E. coli detection, achieving a limit of detection (LOD) of 10 2 CFU/mL.In this work, we introduce a portable optical platform that employs our MIP-based microfluidic biosensor to detect bacteria cells in water.The platform consists of portable optical and mechanical components that are assembled onto a 3D-printed housing.The system is powered by a portable laptop that also serve as the controller for the micropump and the display for the microscope.The micropump precisely controls the flow to the microfluidic chip while a fluorescent image of the detection area is displayed in realtime.To investigate the effect of bacteria concentration on capturing efficiency, E. coli OP50 solutions of different concentrations of 0, 10 3 , 10 5 and 10 7 CFU/mL were prepared in LB and run through the device.The CIP-MMPs at 0 concentration of bacteria were exhibiting a slight decrease in their fluorescent intensity over time, indicating a possible 10-15% decrease due to photobleaching.The fluorescent intensity reduction in 10 3 CFU/mL bacteria concentration was not significantly different compared to 0 concentration.The significant reduction in florescent intensity was observed in 10 5 and 10 7 CFU/mL concentrations of bacteria (48% and 65% respectively).This result confirmed the limit of detection (LOD) of ~10 5 CFU/mL for our designed sensing platform.Using this setting, we were able to develop a portable and low-cost platform technology for detection of bacteria at low LOD and wide concentration range which can be considered as an applicable water quality monitoring tool.
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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 | 0.000 |
| 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 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".