Personal Food Computer: A new device for controlled-environment agriculture

Due to their interdisciplinary nature, devices for controlled-environment agriculture have the possibility to turn into ideal tools not only to conduct research on plant phenology but also to create curricula in a wide range of disciplines. Controlled-environment devices are increasing their functionalities as well as improving their accessibility. Traditionally, building one of these devices from scratch implies knowledge in fields such as mechanical engineering, digital electronics, programming, and energy management. However, the requirements of an effective controlled environment device for personal use brings new constraints and challenges. This paper presents the OpenAg Personal Food Computer (PFC); a low cost desktop size platform, which not only targets plant phenology researchers but also hobbyists, makers, and teachers from elementary to high-school levels (K-12). The PFC is completely open-source and it is intended to become a tool that can be used for collective data sharing and plant growth analysis. Thanks to its modular design, the PFC can be used in a large spectrum of activities.Comment: 9 pages, 11 figures, Accepted at the 2017 Future Technologies Conference (FTC

Simulated ablation for detection of cells impacting paracrine signalling in histology analysis

Intra-tumour phenotypic heterogeneity limits accuracy of clinical diagnostics and hampers the efficiency of anti-cancer therapies. Dealing with this cellular heterogeneity requires adequate understanding of its sources, which is extremely difficult, as phenotypes of tumour cells integrate hardwired (epi)mutational differences with the dynamic responses to microenvironmental cues. The later comes in form of both direct physical interactions, as well as inputs from gradients of secreted signalling molecules. Furthermore, tumour cells can not only receive microenvironmental cues, but also produce them. Despite high biological and clinical importance of understanding spatial aspects of paracrine signaling, adequate research tools are largely lacking. Here, a partial differential equation (PDE)–based mathematical model is developed that mimics the process of cell ablation. This model suggests how each cell might contribute to the microenvironment by either absorbing or secreting diffusible factors, and quantifies the extent to which observed intensities can be explained via diffusion-mediated signalling. The model allows for the separation of phenotypic responses to signalling gradients within tumour microenvironments from the combined influence of responses mediated by direct physical contact and hardwired (epi)genetic differences. The method is applied to a multi-channel immunofluorescence in situ hybridisation (iFISH)–stained breast cancer histological specimen, and correlations are investigated between: HER2 gene amplification, HER2 protein expression and cell interaction with the diffusible microenvironment. This approach allows partial deconvolution of the complex inputs that shape phenotypic heterogeneity of tumour cells and identifies cells that significantly impact gradients of signalling molecules