Semi-Automated Quantitative Evaluation of Neuron Developmental Morphology In Vitro Using the Change-Point Test.

Neuron morphology gives rise to distinct axons and dendrites and plays an essential role in neuronal functionality and circuit dynamics. In rat hippocampal neurons, morphological development occurs over roughly one week in vitro. This development has been qualitatively described as occurring in 5 stages. Still, there is a need to quantify cell growth to monitor cell culture health, understand cell responses to sensory cues, and compare experimental results and computational growth model predictions. To address this need, embryonic rat hippocampal neurons were observed in vitro over six days, and their processes were quantified using both standard morphometrics (degree, number of neurites, total length, and tortuosity) and new metrics (distance between change points, relative turning angle, and the number of change points) based on the Change-Point Test to track changes in path trajectories. Of the standard morphometrics, the total length of neurites per cell and the number of endpoints were significantly different between 0.5, 1.5, and 4 days in vitro, which are typically associated with Stages 2-4. Using the Change-Point Test, the number of change points and the average distance between change points per cell were also significantly different between those key time points. This work highlights key quantitative characteristics, both among common and novel morphometrics, that can describe neuron development in vitro and provides a foundation for analyzing directional changes in neurite growth for future studies.

Evaluating anthropometric scaling of a generic adult model to represent pediatric shoulder strength.

The structure of the developing musculoskeletal system during childhood and adolescence influences tissue loading and function. Anatomical features important for musculoskeletal loading such as muscle volume and limb proportion vary with age but limited available anatomical data for the developing limb makes predicting loads challenging. Our aim was to evaluate whether anthropometric scaling of an existing adult musculoskeletal upper limb model is sufficient to accurately represent pediatric strength. An adult upper limb model was scaled using two scale factors based on length features and max isometric force (MIF). Length features (e.g. limb and muscle length) were scaled based on linear regression for available literature reports of forearm length vs. height (N = 366 Pediatric, N = 107 Adults), while MIF was scaled based on relating body mass vs. total shoulder muscle volume (N = 6). Children-specific models were developed for 6 pediatric individuals whose height, body mass, and shoulder moment-generating capacity (a common measure of strength) were previously reported. These models were used to predict isometric shoulder moments for flexion/extension, internal/external rotation, and ad/abduction and compared with physical measurements previously reported. The predicted isometric shoulder moments were significantly correlated to measured moments for these same individuals (p < 0.04, r2 > 0.7). However, predicted moments tended to underestimate measured values; shoulder external rotation was most accurately predicted (slope: 1.1234) while shoulder adduction was most underestimated (slope: 0.4624). This work provides an initial basis for pediatric scaling but illustrates the important need for additional direct measures of muscle size and limb strength and function in a pediatric population.

Modeling neuron growth using isogeometric collocation based phase field method.

We present a new computational framework of neuron growth based on the phase field method and develop an open-source software package called "NeuronGrowth_IGAcollocation". Neurons consist of a cell body, dendrites, and axons. Axons and dendrites are long processes extending from the cell body and enabling information transfer to and from other neurons. There is high variation in neuron morphology based on their location and function, thus increasing the complexity in mathematical modeling of neuron growth. In this paper, we propose a novel phase field model with isogeometric collocation to simulate different stages of neuron growth by considering the effect of tubulin. The stages modeled include lamellipodia formation, initial neurite outgrowth, axon differentiation, and dendrite formation considering the effect of intracellular transport of tubulin on neurite outgrowth. Through comparison with experimental observations, we can demonstrate qualitatively and quantitatively similar reproduction of neuron morphologies at different stages of growth and allow extension towards the formation of neurite networks.