A novel optical biosensor for in situ and small-scale monitoring of bacterial transport in saturated columns

Nonionic surfactant Tween 80-facilitated bacterial transport in porous media: A nonmonotonic concentration-dependent performance, mechanism, and machine learning prediction

The surfactant-enhanced bioremediation (SEBR) of organic-contaminated soil is a promising soil remediation technology, in which surfactants not only mobilize pollutants, but also alter the mobility of bacteria. However, the bacterial response and underlying mechanisms remain unclear. In this study, the effects and mechanisms of action of a selected nonionic surfactant (Tween 80) on Pseudomonas aeruginosa transport in soil and quartz sand were investigated. The results showed that bacterial migration in both quartz sand and soil was significantly enhanced with increasing Tween 80 concentration, and the greatest migration occurred at a critical micelle concentration (CMC) of 4 for quartz sand and 30 for soil, with increases of 185.2% and 27.3%, respectively. The experimental results and theoretical analysis indicated that Tween 80-facilitated bacterial migration could be mainly attributed to competition for soil/sand surface sorption sites between Tween 80 and bacteria. The prior sorption of Tween 80 onto sand/soil could diminish the available sorption sites for P. aeruginosa, resulting in significant decreases in deposition parameters (70.8% and 33.3% decrease in KD in sand and soil systems, respectively), thereby increasing bacterial transport. In the bacterial post-sorption scenario, the subsequent injection of Tween 80 washed out 69.8% of the bacteria retained in the quartz sand owing to the competition of Tween 80 with pre-sorbed bacteria, as compared with almost no bacteria being eluted by NaCl solution. Several machine learning models have been employed to predict Tween 80-faciliated bacterial transport. The results showed that back-propagation neural network (BPNN)-based machine learning could predict the transport of P. aeruginosa through quartz sand with Tween 80 in-sample (2 CMC) and out-of-sample (10 CMC) with errors of 0.79% and 3.77%, respectively. This study sheds light on the full understanding of SEBR from the viewpoint of degrader facilitation.

Quantitative, Temperature-Calibrated and Real-Time Glucose Biosensor Based on Symmetrical-Meandering-Type Resistor and Intertwined Capacitor Structure

Here, we propose a glucose biosensor with the advantages of quantification, excellent linearity, temperature-calibration function, and real-time detection based on a resistor and capacitor, in which the resistor works as a temperature sensor and the capacitor works as a biosensor. The resistor has a symmetrical meandering type structure that increases the contact area, leading to variations in resistance and effective temperature monitoring of a glucose solution. The capacitor is designed with an intertwined structure that fully contacts the glucose solution, so that capacitance is sensitively varied, and high sensitivity monitoring can be realized. Moreover, a polydimethylsiloxane microfluidic channel is applied to achieve a fixed shape, a fixed point, and quantitative measurements, which can eliminate influences caused by fluidity, shape, and thickness of the glucose sample. The glucose solution in a temperature range of 25-100 °C is measured with variations of 0.2716 Ω/°C and a linearity response of 0.9993, ensuring that the capacitor sensor can have reference temperature information before detecting the glucose concentration, achieving the purpose of temperature calibration. The proposed capacitor-based biosensor demonstrates sensitivities of 0.413 nF/mg·dL-1, 0.048 nF/mg·dL-1, and 0.011 pF/mg·dL-1; linearity responses of 0.96039, 0.91547, and 0.97835; and response times less than 1 second, respectively, at DC, 1 kHz, and 1 MHz for a glucose solution with a concentration range of 25-1000 mg/dL.