Random-Reaction-Seed Method for Automated Identification of Neurite Elongation and Branching

From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation

Digital reconstruction has been instrumental in deciphering how in vitro neuron architecture shapes information flow. Emerging approaches reconstruct neural systems as networks with the aim of understanding their organization through graph theory. Computational tools dedicated to this objective build models of nodes and edges based on key cellular features such as somata, axons, and dendrites. Fully automatic implementations of these tools are readily available, but they may also be purpose-built from specialized algorithms in the form of multi-step pipelines. Here we review software tools informing the construction of network models, spanning from noise reduction and segmentation to full network reconstruction. The scope and core specifications of each tool are explicitly defined to assist bench scientists in selecting the most suitable option for their microscopy dataset. Existing tools provide a foundation for complete network reconstruction, however more progress is needed in establishing morphological bases for directed/weighted connectivity and in software validation.

A CAR RNA FISH assay to study functional and spatial heterogeneity of chimeric antigen receptor T cells in tissue

Chimeric antigen receptor (CAR) T cells are engineered cells used in cancer therapy and are studied to treat infectious diseases. Trafficking and persistence of CAR T cells is an important requirement for efficacy to target cancer. Here, we describe a CAR RNA FISH histo-cytometry platform combined with a random reaction seed image analysis algorithm to quantitate spatial distribution and in vivo functional activity of a CAR T cell population at a single cell resolution for preclinical models. In situ, CAR T cell exhibited a heterogenous effector gene expression and this was related to the distance from tumor cells, allowing a quantitative assessment of the potential in vivo effectiveness. The platform offers the potential to study immune functions of genetically engineered cells in situ with their target cells in tissues with high statistical power and thus, can serve as an important tool for preclinical assessment of CAR T cell effectiveness.

The Rise of Molecules Able To Regenerate the Central Nervous System

Injury to the adult central nervous system (CNS) usually leads to permanent deficits of cognitive, sensory, and/or motor functions. The failure of axonal regeneration in the damaged CNS limits functional recovery. The lack of information concerning the biological mechanism of axonal regeneration and its complexity has delayed the process of drug discovery for many years compared to other drug classes. Starting in the early 2000s, the ability of many molecules to stimulate axonal regrowth was evaluated through automated screening techniques; many hits and some new mechanisms involved in axonal regeneration were identified. In this Perspective, we discuss the rise of the CNS regenerative drugs, the main biological techniques used to test these drug candidates, some of the most important screens performed so far, and the main challenges following the identification of a drug that is able to induce axonal regeneration in vivo.