Development of a Low-Cost Lateral Flow Assay for Rapid Detection of Vibrio Cholerae
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cholera is an acute, often fatal diarrheal disease that primarily affects areas with poor sanitation and unclean water. Cholera is caused by toxigenic strains of Vibrio cholerae ( V. cholerae ), which cause the body to rapidly dehydrate upon colonizing the intestine. The WHO estimates that 2.9 million people contract cholera each year, resulting in approximately 95000 deaths [1]. Current methods for detection of V. cholerae are either inferential (detection of fecal coliforms or monitoring weather patterns) or diagnosed after an infection (stool tests) [2]. Even methods that have been developed for direct detection of V. cholerae fall short of detecting environmental concentrations of the bacterium (10-10 4 CFU/mL) [3]; a lateral flow assay (LFA) using gold nanoparticle-labelled antibodies for the simultaneous detection of O1 and O139 strains of V. cholerae achieved a limit of detection of 10 8 CFU/mL for O1 and 10 7 CFU/mL for O139 [4]. The current work aims to develop an LFA for the detection of V. cholerae at environmental conditions in drinking water under limited resource settings. By incorporating novel aptamers as antigen detecting agents, carbon nanoparticles as colorimetric indicators, and N-acetylglucosamine (GlcNAc)–a known chemoattractant for V. cholerae –in the sample pad, the limit of detection will be improved without the need for lengthy preprocessing steps or costly reagents. The antigen detection agent employed in the LFA is the aptamer V.ch27 which was identified by Mojarad and Gargaria [5]. This aptamer was shown to have a favourable secondary structure at 21°C and high binding affinity to the surface of V. cholerae bacteria. Aptamers are a synthetic alternative to conventionally used antibodies for this application. They exhibit specificities comparable to those of monoclonal antibodies, are cheaper to synthesize, and can be easily immobilized to surfaces via biotin-avidin complexing. Amorphous carbon nanoparticles (ACNPs) were chosen as the colorimetric indicator for the assay due to their strong black color and low cost [6]. For instance, carbon nanoparticles have shown a 100-fold decrease in the limit of detection for dengue fever antigen when compared to gold nanoparticles [7]. The ACNPs were synthesized by collecting the soot from burning candles followed by size selection by centrifugation, as previously described Zhang et al [8]. The chemotaxis of V. cholerae to GlcNAc is well documented in literature [9]. The sample pad of the LFA contains a GlcNAc solution which diffuses into the water sample. V. cholerae swim up the GlcNAc concentration gradient and accumulate in high concentrations at the sample pad. This in turn results in a high concentration of analyte entering the assay, and consequently, a greater signal intensity. Previous studies have shown that chemotaxis can be exploited to collect nearly all of the bacteria in a 100 mL water sample [10,11]. The fabricated LFA device will provide a rapid, accessible, and low-cost platform for V. cholerae detection in the water sources available to rural and low-income communities, without the need for technical training or well-established laboratory infrastructure. Successful implementation of the device will result in the overall reduction of global deaths due to cholera, as well as provide the framework for future preventative initiatives aimed towards cholera outbreak prediction and monitoring. References [1] “Cholera: The Forgotten Pandemic,” World Health Organization , 22-Oct-2018. [Online]. Available: https://www.who.int/cholera/the-forgotten-pandemic/en/ . [Accessed: 14-Nov-2020]. [2] https://link-springer-com.proxy.lib.uwaterloo.ca/chapter/10.1007%2F978-3-319-38884-7_15 [3] S. Schauer, et al., Applied and Environmental Microbiology , vol. 78, no. 20, pp. 7369–7375, Oct. 2012. [4] C. Y. Yu et al., Journal of Microbiological Methods , vol. 86, no. 3, pp. 277–282, Sep. 2011. [5] A. E. Mojarad and S. L. Mousavi Gargaria, Iranian Journal of Microbiology , vol. 12, no. 4, pp. 263–272, Aug. 2020. [6] E. M. Linares et al.,, J. Immunol. Methods , vol. 375, no. 1-2, pp. 264-270, Jan. 2012. [7] J. D. Bishop et al. Royal Soc. Chem. , vol. 19, pp. 2486-2499., Apr. 2019. [8] X. Zhang et al., J. Agric. Food. Chem , vol. 65, no. 35, pp. 8063-8071, Aug. 2017. [9] G. Reddi et al., Plos One , vol. 13, no. 7, Jul. 2018. [10] X. Ling and S. Roseman, PNAS , vol. 101, no. 2, pp. 627-631, Jan. 2004 [11] S. Dasgupta, N. S. K. Gunda, and S. K. Mitra, Environmental Science: Water Research & Technology , vol. 2, pp. 931-941, 2016.
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.
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 | 0.001 | 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