3D In Vitro Neuron on a Chip for Probing Calcium Mechanostimulation

The evolution of tissue on a chip systems holds promise for mimicking the response of biological functionality of physiological systems. One important direction for tissue on a chip approaches are neuron‐based systems that could mimic neurological responses and lessen the need for in vivo experimentation. For neural research, more attention has been devoted recently to understanding mechanics due to issues in areas such as traumatic brain injury (TBI) and pain, among others. To begin to address these areas, a 3D Nerve Integrated Tissue on a Chip (NITC) approach combined with a Mechanical Excitation Testbed (MET) System is developed to impose external mechanical stimulation toward more realistic physiological environments. PC12 cells differentiated with nerve growth factor, which were cultured in a controlled 3D scaffolds, are used. The cells are labeled in a 3D NITC system with Fluo‐4‐AM to examine their calcium response under mechanical stimulation synchronized with image capture. Understanding the neural responses to mechanical stimulation beyond 2D systems is very important for neurological studies and future personalized strategies. This work will have implications in a diversity of areas including tissue‐on‐a‐chip systems, biomaterials, and neuromechanics.Developing more physiologically relevant 3D neuron integrated systems with external mechanics with synchronized image capture enables understanding of cellular responses that are important for advancing future neural studies and personalized strategies. This work examines calcium response with respect to voice coil actuator controlled force profiles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163437/3/adbi202000080-sup-0001-SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163437/2/adbi202000080_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163437/1/adbi202000080.pd

Characterization of neural mechanotransduction response in human traumatic brain injury organoid model

Abstract The ability to model physiological systems through 3D neural in-vitro systems may enable new treatments for various diseases while lowering the need for challenging animal and human testing. Creating such an environment, and even more impactful, one that mimics human brain tissue under mechanical stimulation, would be extremely useful to study a range of human-specific biological processes and conditions related to brain trauma. One approach is to use human cerebral organoids (hCOs) in-vitro models. hCOs recreate key cytoarchitectural features of the human brain, distinguishing themselves from more traditional 2D cultures and organ-on-a-chip models, as well as in-vivo animal models. Here, we propose a novel approach to emulate mild and moderate traumatic brain injury (TBI) using hCOs that undergo strain rates indicative of TBI. We subjected the hCOs to mild (2 s $$^{-1}$$ - 1 ) and moderate (14 s $$^{-1}$$ - 1 ) loading conditions, examined the mechanotransduction response, and investigated downstream genomic effects and regulatory pathways. The revealed pathways of note were cell death and metabolic and biosynthetic pathways implicating genes such as CARD9, ENO1, and FOXP3, respectively. Additionally, we show a steeper ascent in calcium signaling as we imposed higher loading conditions on the organoids. The elucidation of neural response to mechanical stimulation in reliable human cerebral organoid models gives insights into a better understanding of TBI in humans

Range-wide indicators of African great ape density distribution

Species distributions are influenced by processes occurring at multiple spatial scales. It is therefore insufficient to model species distribution at a single geographic scale, as this does not provide the necessary understanding of determining factors. Instead, multiple approaches are needed, each differing in spatial extent, grain, and research objective. Here, we present the first attempt to model continent-wide great ape density distribution. We used site-level estimates of African great ape abundance to (1) identify socioeconomic and environmental factors that drive densities at the continental scale, and (2) predict range-wide great ape density. We collated great ape abundance estimates from 156 sites and defined 134 pseudo-absence sites to represent additional absence locations. The latter were based on locations of unsuitable environmental conditions for great apes, and on existing literature. We compiled seven socioeconomic and environmental covariate layers and fitted a generalized linear model to investigate their influence on great ape abundance. We used an Akaike-weighted average of full and subset models to predict the range-wide density distribution of African great apes for the year 2015. Great ape densities were lowest where there were high Human Footprint and Gross Domestic Product values; the highest predicted densities were in Central Africa, and the lowest in West Africa. Only 10.7% of the total predicted population was found in the International Union for Conservation of Nature Category I and II protected areas. For 16 out of 20 countries, our estimated abundances were largely in line with those from previous studies. For four countries, Central African Republic, Democratic Republic of the Congo, Liberia, and South Sudan, the estimated populations were excessively high. We propose further improvements to the model to overcome survey and predictor data limitations, which would enable a temporally dynamic approach for monitoring great apes across their range based on key indicators