Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools.

The overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) signal patterns could be used to predict changes in commonly monitored water quality parameters by using artificial intelligence/machine learning tools. To test this hypothesis, the study first examines a proof of concept by correlating between MPS's signals and high algae concentrations in an algal cultivation pond. Then, the study expanded upon these findings and examined if multiple water quality parameters could be predicted in real surface waters, like irrigation canals.

Measurement of free chlorine levels in water using potentiometric responses of biofilms and applications for monitoring and managing the quality of potable water.

Residual free chlorine is not monitored continuously at scale in drinking water distribution systems because existing real-time sensor technologies require frequent maintenance, cleaning, and calibration, which makes these products too costly to be used throughout a distribution system. As a result, current measurement approaches require manual sampling, which is not feasible for the consistent monitoring of free chlorine because chlorine concentrations vary significantly throughout pipeline distribution and over time and space. This research presents an alternative and cost-effective method of predicting free chlorine levels in drinking water using graphite electrodes coated with naturally grown microbial biofilms.

Microbial potentiometric sensor array measurements in unsaturated soils.

The overarching goal of this study is to demonstrate a novel technology for monitoring changes in electrical potential of unsaturated soils using biofilm-populated electrodes. The novelty of the study stems from the fact that it demonstrates a method for measuring open-circuit potentials (OCP) in environments without the presence of an electrolyte solution. This study also reveals that using a biofilm-populated electrode as a reference in stable environments could successfully be employed to assess and monitor the electrochemical potential generated by plants and microorganisms.

Structural characterization of interactions between the double-stranded RNA-binding zinc finger protein JAZ and nucleic acids.

The interactions of the human double-stranded RNA-binding zinc finger protein JAZ with RNA or DNA were investigated using electrophoretic mobility-shift assays, isothermal calorimetry, and nuclear magnetic resonance spectroscopy. Consistent with previous reports, JAZ has very low affinity for duplex DNA or single-stranded RNA, but it binds preferentially to double-stranded RNA (dsRNA) with no detectable sequence specificity. The affinity of JAZ for dsRNA is unaffected by local structural features such as loops, overhangs, and bulges, provided a sufficient length of reasonably well-structured A-form RNA (about 18 bp for a single zinc finger) is present.