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.

Myofibroblast stromal presence and distribution in squamous epithelial carcinomas, oral dysplasia and hyperkeratosis.

Purpose: Stromal elements play a key role in growth and development of different neoplasms. Myofibroblasts are the major components and occur in stromal tissue during carcinogenesis processes. The purpose of this study was to review the frequency and the distribution pattern of myofibroblasts(αSMA-positive) in the stroma of squamous epithelial carcinoma and to compare values with those for with oral dysplasia and hyperkeratosis.