PyScratch: An ease of use tool for analysis of scratch assays.

BACKGROUND AND OBJECTIVE: Image acquisition has greatly benefited from the automation of microscopes and has been followed by an increasing amount and complexity of data acquired. Here, we present the PyScratch, a new tool for processing spatial and temporal information from scratch assays. PyScratch is an open-source software implemented in Python that analyses the migration area in an automated fashion. METHODS: The software was developed in Python. Wound healing assays were used to validate its performance. The images were acquired using Cytation 5™ during 60 h. Data were analyzed using One-Way ANOVA. RESULTS: PyScratch performed a robust analysis of confluent cells, showing that high plating density affects cell migration. Additionally, PyScratch was approximately six times faster than a semi-automated analysis. CONCLUSIONS: PyScratch offers a user-friendly interface allowing researches with little or no programming skills to perform quantitative analysis of in vitro scratch assays.

3D Printed e-Tongue.

Nowadays, one of the biggest issues addressed to electronic sensor fabrication is the build-up of efficient electrodes as an alternative way to the expensive, complex and multistage processes required by traditional techniques. Printed electronics arises as an interesting alternative to fulfill this task due to the simplicity and speed to stamp electrodes on various surfaces. Within this context, the Fused Deposition Modeling 3D printing is an emerging, cost-effective and alternative technology to fabricate complex structures that potentiates several fields with more creative ideas and new materials for a rapid prototyping of devices. We show here the fabrication of interdigitated electrodes using a standard home-made CoreXY 3D printer using transparent and graphene-based PLA filaments. Macro 3D printed electrodes were easily assembled within 6 min with outstanding reproducibility. The electrodes were also functionalized with different nanostructured thin films via dip-coating Layer-by-Layer technique to develop a 3D printed e-tongue setup. As a proof of concept, the printed e-tongue was applied to soil analysis. A control soil sample was enriched with several macro-nutrients to the plants (N, P, K, S, Mg, and Ca) and the discrimination was done by electrical impedance spectroscopy of water solution of the soil samples. The data was analyzed by Principal Component Analysis and the 3D printed sensor distinguished clearly all enriched samples despite the complexity of the soil chemical composition. The 3D printed e-tongue successfully used in soil analysis encourages further investments in developing new sensory tools for precision agriculture and other fields exploiting the simplicity and flexibility offered by the 3D printing techniques.