Cluster Recognition by Delaunay Triangulation of Synaptic Proteins in 3D

What's the cost-effective pattern for rural wastewater treatment?

Inadequate sanitation infrastructure is a global problem that is particularly impacting rural areas. And decentralized wastewater management system is considered as the feasible solution for rural sewage treatment (RuST). However, determining the cost-effective (CE) pattern for decentralized RuST is methodologically challenging because of scarce decision-support tools. In this research, a RuST optimization model (RuST-OM) was developed to gain an insight into the CE pattern of RuST based on the greedy algorithm. This model involves tradeoffs in the economy-of-scale and technology of wastewater treatment system versus the cost and energy consumption of the sewage collection system. The investment associated with the CE pattern for RuST is closely linked to the environmental demand, RuST coverage, topographic complexity, and degree of household dispersion. The cost of the CE pattern falls between the onsite-B and community-based pattern, and this range represents the optimized interval for RuST planning. Nature-based technology is a sustainable alternative for RuST in areas characterized by low or moderate environmental demand. To ensure applicability of the RuST-OM in other countries/regions, built-in datasets (e.g., technology and pipeline design parameters) are designed based on rural area features that can be modified as necessary. This research highlights the utility of the CE pattern for RuST planning, and can serve as a reference for RuST planning around the world.

The Decade of Super-Resolution Microscopy of the Presynapse

The presynaptic compartment of the chemical synapse is a small, yet extremely complex structure. Considering its size, most methods of optical microscopy are not able to resolve its nanoarchitecture and dynamics. Thus, its ultrastructure could only be studied by electron microscopy. In the last decade, new methods of optical superresolution microscopy have emerged allowing the study of cellular structures and processes at the nanometer scale. While this is a welcome addition to the experimental arsenal, it has necessitated careful analysis and interpretation to ensure the data obtained remains artifact-free. In this article we review the application of nanoscopic techniques to the study of the synapse and the progress made over the last decade with a particular focus on the presynapse. We find to our surprise that progress has been limited, calling for imaging techniques and probes that allow dense labeling, multiplexing, longer imaging times, higher temporal resolution, while at least maintaining the spatial resolution achieved thus far.

Quantitative Analysis of Nuclear Lamins Imaged by Super-Resolution Light Microscopy

The nuclear lamina consists of a dense fibrous meshwork of nuclear lamins, Type V intermediate filaments, and is ~14 nm thick according to recent cryo-electron tomography studies. Recent advances in light microscopy have extended the resolution to a scale allowing for the fine structure of the lamina to be imaged in the context of the whole nucleus. We review quantitative approaches to analyze the imaging data of the nuclear lamina as acquired by structured illumination microscopy (SIM) and single molecule localization microscopy (SMLM), as well as the requisite cell preparation techniques. In particular, we discuss the application of steerable filters and graph-based methods to segment the structure of the four mammalian lamin isoforms (A, C, B1, and B2) and extract quantitative information.