Haves and have nots must find a better way: The case for open scientific hardware

Low-cost (<€5), open-source, potential alternative to commercial spectrophotometers

Spectrophotometry is a fundamental technique in many areas of science, with many applications and uses. The cost of spectrophotometers has acted as a barrier on the teaching and use of the technique. Here, we provide open-source plans to a 3D-printed cuvette holder with an interchangeable narrow–spectral bandwidth light-emitting diode (LED) block that can be used in conjunction with a smartphone’s ambient light sensor (ALS) to perform spectrophotometry. A Lego version with an interchangeable LED block is also presented. Results from the smartphone spectrophotometer in comparison with commercially available spectrophotometers demonstrated functionality, and the model may have many applications, especially in indirect spectrophotometry, such as in the protein assay shown here. The plans for the 3D-printed model are freely available on GitHub, as are editable files to allow customisation by users. We would encourage users to share adaptations with the scientific community.

The cost of spectrophotometers has acted as a barrier to the teaching and use of spectrophotometry; this Community Page article provides 3D printed plans for a cuvette holder with an interchangeable LED block that can be used with a smartphone’s Ambient Light Sensor (ALS) to perform spectrophotometry for less than €5.

A 3D-printed hand-powered centrifuge for molecular biology

The centrifuge is an essential tool for many aspects of research and medical diagnostics. However, conventional centrifuges are often inaccessible outside of standard laboratory settings, such as remote field sites, because they require a constant external power source and can be prohibitively costly in resource-limited settings and Science, technology, engineering, and mathematics (STEM)-focused programs. Here we present the 3D-Fuge, a 3D-printed hand-powered centrifuge, as a novel alternative to standard benchtop centrifuges. Based on the design principles of a paper-based centrifuge, this 3D-printed instrument increases the volume capacity to 2 mL and can reach hand-powered centrifugation speeds up to 6,000 rpm. The 3D-Fuge devices presented here are capable of centrifugation of a wide variety of different solutions such as spinning down samples for biomarker applications and performing nucleotide extractions as part of a portable molecular lab setup. We introduce the design and proof-of-principle trials that demonstrate the utility of low-cost 3D-printed centrifuges for use in remote field biology and educational settings.

This Community Page article describes a low-cost 3D-printed centrifuge to enable sequencing in remote field conditions and lowering the barrier to synthetic biology research in high schools to broaden participation in hands-on STEM.

Stytra: An open-source, integrated system for stimulation, tracking and closed-loop behavioral experiments

We present Stytra, a flexible, open-source software package, written in Python and designed to cover all the general requirements involved in larval zebrafish behavioral experiments. It provides timed stimulus presentation, interfacing with external devices and simultaneous real-time tracking of behavioral parameters such as position, orientation, tail and eye motion in both freely-swimming and head-restrained preparations. Stytra logs all recorded quantities, metadata, and code version in standardized formats to allow full provenance tracking, from data acquisition through analysis to publication. The package is modular and expandable for different experimental protocols and setups. Current releases can be found at https://github.com/portugueslab/stytra. We also provide complete documentation with examples for extending the package to new stimuli and hardware, as well as a schema and parts list for behavioral setups. We showcase Stytra by reproducing previously published behavioral protocols in both head-restrained and freely-swimming larvae. We also demonstrate the use of the software in the context of a calcium imaging experiment, where it interfaces with other acquisition devices. Our aims are to enable more laboratories to easily implement behavioral experiments, as well as to provide a platform for sharing stimulus protocols that permits easy reproduction of experiments and straightforward validation. Finally, we demonstrate how Stytra can serve as a platform to design behavioral experiments involving tracking or visual stimulation with other animals and provide an example integration with the DeepLabCut neural network-based tracking method.

pyPhotometry: Open source Python based hardware and software for fiber photometry data acquisition

Fiber photometry is the process of recording bulk neural activity by measuring fluorescence changes in activity sensitive indicators such as GCaMP through an optical fiber. We present a system of open source hardware and software for fiber photometry data acquisition consisting of a compact, low cost, data acquisition board built around the Micropython microcontroller, and a cross platform graphical user interface (GUI) for controlling acquisition and visualising signals. The system can acquire two analog and two digital signals, and control two external LEDs via built in LED drivers. Time-division multiplexed illumination allows independent readout of fluorescence evoked by different excitation wavelengths from a single photoreceiver signal. Validation experiments indicate this approach offers better signal to noise for a given average excitation light intensity than sinusoidally-modulated illumination. pyPhotometry is substantially cheaper than commercial hardware filling the same role, and we anticipate, as an open source and comparatively simple tool, it will be easily adaptable and therefore of broad interest to a wide range of users.

Building and hacking open source hardware

The first edition of the Aspects of Neuroscience Brainhack took place at the Department of Physics at University of Warsaw, Poland between November 17th and 19th 2017. This hackathon was one of the satellite events of the Aspects of Neuroscience conference, it was organized by the Brainhack organization to promote interaction between researchers, encouraging open (neuro)science and collaborations on projects related to the study of the nervous system. The event had a total of nine projects on many different topics including functional connectivity research, white matter tractography, classification of brain-ageing biomarkers through machine learning, presentation of a portable one channel EEG registration device and a do it yourself 3D-printed neurobiology lab. The latter is highlighted in this paper.