@article{clark_huayta_morton_meyer_san-miguel_2024, title={Morphological hallmarks of dopaminergic neurodegeneration are associated with altered neuron function in Caenorhabditis elegans}, volume={100}, ISSN={["1872-9711"]}, DOI={10.1016/j.neuro.2023.12.005}, abstractNote={Caenorhabditis elegans (C. elegans) is an excellent model system to study neurodegenerative diseases, such as Parkinson's disease, as it enables analysis of both neuron morphology and function in live animals. Multiple structural changes in neurons, such as cephalic dendrite morphological abnormalities, have been considered hallmarks of neurodegeneration in this model, but their relevance to changes in neuron function are not entirely clear. We sought to test whether hallmark morphological changes associated with chemically induced dopaminergic neuron degeneration, such as dendrite blebbing, breakage, and loss, are indicative of neuronal malfunction and result in changes in behavior. We adapted an established dopaminergic neuronal function assay by measuring paralysis in the presence of exogenous dopamine, which revealed clear differences between cat-2 dopamine deficient mutants, wildtype worms, and dat-1 dopamine abundant mutants. Next, we integrated an automated image processing algorithm and a microfluidic device to segregate worm populations by their cephalic dendrite morphologies. We show that nematodes with dopaminergic dendrite degeneration markers, such as blebbing or breakage, paralyze at higher rates in a dopamine solution, providing evidence that dopaminergic neurodegeneration morphologies are correlated with functional neuronal outputs.}, journal={NEUROTOXICOLOGY}, author={Clark, Andrew S. and Huayta, Javier and Morton, Katherine S. and Meyer, Joel N. and San-Miguel, Adriana}, year={2024}, month={Jan}, pages={100–106} }
 @article{clark_kalmanson_morton_hartman_meyer_san-miguel_2023, title={An unbiased, automated platform for scoring dopaminergic neurodegeneration in C. elegans}, volume={18}, ISSN={["1932-6203"]}, url={https://doi.org/10.1371/journal.pone.0281797}, DOI={10.1371/journal.pone.0281797}, abstractNote={Caenorhabditis elegans(C.elegans) has served as a simple model organism to study dopaminergic neurodegeneration, as it enables quantitative analysis of cellular and sub-cellular morphologies in live animals. These isogenic nematodes have a rapid life cycle and transparent body, making high-throughput imaging and evaluation of fluorescently tagged neurons possible. However, the current state-of-the-art method for quantifying dopaminergic degeneration requires researchers to manually examine images and score dendrites into groups of varying levels of neurodegeneration severity, which is time consuming, subject to bias, and limited in data sensitivity. We aim to overcome the pitfalls of manual neuron scoring by developing an automated, unbiased image processing algorithm to quantify dopaminergic neurodegeneration inC.elegans. The algorithm can be used on images acquired with different microscopy setups and only requires two inputs: a maximum projection image of the four cephalic neurons in theC.eleganshead and the pixel size of the user’s camera. We validate the platform by detecting and quantifying neurodegeneration in nematodes exposed to rotenone, cold shock, and 6-hydroxydopamine using 63x epifluorescence, 63x confocal, and 40x epifluorescence microscopy, respectively. Analysis of tubby mutant worms with altered fat storage showed that, contrary to our hypothesis, increased adiposity did not sensitize to stressor-induced neurodegeneration. We further verify the accuracy of the algorithm by comparing code-generated, categorical degeneration results with manually scored dendrites of the same experiments. The platform, which detects 20 different metrics of neurodegeneration, can provide comparative insight into how each exposure affects dopaminergic neurodegeneration patterns.}, number={7}, journal={PLOS ONE}, author={Clark, Andrew S. and Kalmanson, Zachary and Morton, Katherine and Hartman, Jessica and Meyer, Joel and San-Miguel, Adriana}, editor={Lajoie, PatrickEditor}, year={2023}, month={Jul} }
 @article{clark_san-miguel_2021, title={A bioinspired, passive microfluidic lobe filtration system}, volume={21}, ISSN={["1473-0189"]}, url={http://dx.doi.org/10.1039/d1lc00449b}, DOI={10.1039/d1lc00449b}, abstractNote={Lobe filtration is a bioinspired, non-clogging microparticle filtration mechanism capable of high throughput processing. Simulations of complex velocity profiles provide a robust explanation for this microparticle filtration mechanism.}, number={19}, journal={LAB ON A CHIP}, publisher={Royal Society of Chemistry (RSC)}, author={Clark, Andrew S. and San-Miguel, Adriana}, year={2021}, month={Aug} }