Figure 1.

Characteristics of microbial aggregates derived from biofilms occurring on industrial surfaces and analyzed with the use of imaging flow cytometry (IFC) assisted by an advanced tool for processing and interpreting the cytometric results: a machine learning (ML) module of IDEAS software. The combination of IFC with the ML-based interpretation of flow cytometric data allowed for the precise discrimination of single microbial cells (singlets) from cellular complexes (aggregates), further characterized to identify small (composed of 2 to 3 microbial cells) and large aggregates (more than 3 cells).