Use of Personal Glucose Meters for the Detection of E. Coli in Water
Notice bibliographique
Résumé
Contamination of potable water with pathogenic bacteria such as Escherichia coli ( E.coli ) is a major concern in the developing countries. Often water is consumed without any prior treatment leading to several water borne ailments such as diarrhea. According to United States Environmental Protection Agency (USEPA), the total concentration of E.coli in potable water should be restricted to 0 Colony Forming Units (CFU) per 100 ml of water for potable water and 126 CFU /100 ml for recreational water. The conventional methods of pathogen detection generally involve transporting the contaminated water samples to centralized laboratories where detection and quantification techniques are based on instant culturing of bacteria, enzymatic reactions, and molecular (immunological or genetic) methods of detection. These processes often take 24 – 48 hours to produce results and are often expensive due to the additional requirements of resources and qualified personnel. Such a system for water monitoring is not suitable for low-resource settings. Rapid, easy to use and inexpensive detection systems need to be developed in order to empower individual households to regularly monitor their bacteriological water quality. One of the best examples of such rapid and simple detection systems is the Personal Glucose meter (PGM), which is used by patients with diabetes to regularly monitor their blood glucose levels. This system is based on an electrochemical reaction where in the glucose present in the sample is made to react with an enzyme electrode containing glucose oxidase and the resulting change in the current is measured, which in turn can be correlated to the concentration of the glucose. We have developed a simple method for the detection of E.coli and total coliform using PGMs by monitoring the consumption of glucose as a carbon source by E.coli during their growth cycle. Contaminated water samples with bacterial concentrations in the range of 2-2x10 8 CFU/mL were supplied with glucose solutions with known concentrations and Lauryl Tryptose (LT) broth as the growth medium in order to induce the consumption of glucose by E.coli . The drop in glucose concentrations in these samples was measured every hour with a PGM. It was observed that samples with very high concentrations of E.coli (2x10 6 - 2x10 8 CFU/mL) showed a drop in the glucose concentrations within an hour and samples with extremely low E.coli concentrations (2 CFU/mL) showed a drop in glucose concentrations within a maximum of 8 hours. This method can provide qualitative as well as quantitative results to determine the level of contamination in potable water. The time required to produce results with this method is much lower than the conventional colony counting method and the cost involved is quite less compared to the equipment required for ELISA plate readers. The current PGMs available in the market are portable and can produce reliable quantitative results. These systems are quite robust, simple and can be used by any untrained person. PGMs have also been recently integrated with smart phones thereby resulting in a further increase in their base of users. The E.coli detection kit presented here is simple, easy to use, reliable, cost effective and does not involve any toxic reagents or end products. This method doesn’t warrant any special training and can be used by any unskilled person on site at the source of water.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».