ThermoCyte: an inexpensive open-source temperature control system for in vitro live cell imaging

3D-printed stage-top (Fig. 1, B) was designed using Autodesk TinkerCad, and is made available as STL files. ThermoCyte code (Fig. 1, C) was written in the Arduino IDE. All code is included unedited as .ino files. Temperature values from ThermoCyte (Fig. 3, Fig. 9, C) were collected by logging raw temperature readings detected by Arduino thermocouples using 'putty', a free SSH and Telnet client. Logs are made available as comma-separated values file (.csv). Circularity values (Fig. 5, E) were calculated using ImageJ 'shape descriptors' function. Circularity values are included as a comma-separated values (.csv) Pixel intensity traces relating to calcium transients (Fig. 6, Fig. 8) were extracted from raw images. Photobleaching was corrected using napari bleach correct in Napari image viewer, specifically the 'histogram matching' function (python 3). Motion artefact was corrected using moco plugin in FIJI. Cells were segmented as objects using cellpose 2.0 (Python 3). Mean grey intensity values for each cell were extracted using FIJI, and these values for each cell (over time) are provided unedited as a comma-separated values (.csv). Calcium Peak analysis (Fig. 7 A-D, Fig 8 C, D) was generated from raw pixel intensity data, provided in (5) above. This was carried out using custom Python code, supplied here as .py files (python 3). Statistical analysis of calcium peak data (Fig. 7 A-D, Fig 8 C, D) was carried out using custom python code, supplied here as .py files (python 3).