Microfluidic production, stability and loading of synthetic giant unilamellar vesicles.

In advanced drug delivery, versatile liposomal formulations are commonly employed for safer and more accurate therapies. Here we report a method that allows a straightforward production of synthetic monodisperse (~ 100 µm) giant unilamellar vesicles (GUVs) using a microfluidic system. The stability analysis based on the microscopy imaging showed that at ambient conditions the produced GUVs had a half-life of 61 ± 2 h. However, it was observed that ~ 90% of the calcein dye that was loaded into GUVs was transported into a surrounding medium in 24 h, thus indicating that the GUVs may release these small dye molecules without distinguishable membrane disruption. We further demonstrated the feasibility of our method by loading GUVs with larger and very different cargo objects; small soluble fluorescent proteins and larger magnetic microparticles in a suspension. Compared to previously reported microfluidics-based production techniques, the obtained results indicate that our simplified method could be equally harnessed in creating GUVs with less cost, effort and time, which could further benefit studying closed membrane systems.

Nano1D: An accurate computer vision software for analysis and segmentation of low-dimensional nanostructures.

Nanoparticles in microscopy images are usually analyzed qualitatively or manually and there is a need for autonomous quantitative analysis of these objects. In this paper, we present a physics-based computational model for accurate segmentation and geometrical analysis of one-dimensional deformable overlapping objects from microscopy images. This model, named Nano1D, has four steps of preprocessing, segmentation, separating overlapped objects and geometrical measurements. The model is tested on SEM images of Ag and Au nanowire taken from different microscopes, and thermally fragmented Ag nanowires transformed into nanoparticles with different lengths, diameters, and population densities. It successfully segments and analyzes their geometrical characteristics including lengths and average diameter. The function of the algorithm is not undermined by the size, number, density, orientation and overlapping of objects in images. The main strength of the model is shown to be its ability to segment and analyze overlapping objects successfully with more than 99 % accuracy, while current machine learning and computational models suffer from inaccuracy and inability to segment overlapping objects. Benefiting from a graphical user interface, Nano1D can analyze 1D nanoparticles including nanowires, nanotubes, nanorods in addition to other 1D features of microstructures like microcracks, dislocations etc.

User-friendly analysis of droplet array images.

Water-in-oil droplets allow performing massive experimental parallelization and high-throughput studies, such as single-cell experiments. However, analyzing such vast arrays of droplets usually requires advanced expertise and sophisticated workflow tools, which limits accessibility for a wider user base in the fields of chemistry and biology. Thus, there is a need for more user-friendly tools for droplet analysis. In this article, we deliver a set of analytical pipelines for user-friendly analysis of typical scenarios in droplet experiments. We built pipelines that combine various open-source image-analysis software with a custom-developed data processing tool called "EasyFlow". Our pipelines are applicable to the typical experimental scenarios that users encounter when working with droplets: i) mono- and polydisperse droplets, ii) brightfield and fluorescent images, iii) droplet and object detection, iv) signal profile of droplets and objects (e.g., fluorescence).