Sharp, N. R. | bioRxiv Science

bioRxiv2023

iPSC-Astrocyte morphology reflects patient clinical markers

Human iPSCs provide powerful cellular models of Alzheimers disease (AD) and offer many advantages over non-human models, including the potential to reflect variation in individual-specific pathophysiology and clinical symptoms Previous studies have demonstrated that iPSC-neurons from individuals with Alzheimers disease (AD) reflect clinical markers, including {beta}-amyloid (A{beta}) levels and synaptic vulnerability. However, despite neuronal loss being a key hallmark of AD pathology, many risk genes are predominantly expressed in glia, highlighting them as potential therapeutic targets. In this work iPSC-derived astrocytes were generated from a cohort of individuals with high versus low levels of the inflammatory marker YKL-40, in their cerebrospinal fluid (CSF). iPSC-derived astrocytes were treated with exogenous A{beta} oligomers and high content imaging demonstrated a correlation between astrocytes that underwent the greatest morphology change from patients with low levels of CSF-YKL-40 and more protective APOE genotypes. This finding was subsequently verified using similarity learning as an unbiased approach. This study shows that iPSC-derived astrocytes from AD patients reflect key aspects of the pathophysiological phenotype of those same patients, thereby offering a novel means of modelling AD, stratifying AD patients and conducting therapeutic screens. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/548687v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1df3486org.highwire.dtl.DTLVardef@f184d8org.highwire.dtl.DTLVardef@48a33dorg.highwire.dtl.DTLVardef@d53a90_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2021

Accounting for point count ambient noise increases population size estimates

Ambient noise is an integral component of natural environments, but it also creates challenges for avian monitoring programs. Ambient noise can mask bird vocalizations from observers during point counts, which may lead to systematic undercounting of birds in noisy environments. Here, we estimate detection probability and population size in models that either account for or omit the influence of ambient noise. We used data for four bird species, from 2228 point counts that were conducted during the 2019 Mountain Birdwatch field season. Community scientists assessed ambient noise using a simple scale. Despite relatively quiet conditions at sampling locations (x = 2.48), our information theoretical approach favored N-mixture models that incorporated ambient noise into the detection function for all four species. At the noisiest sampling locations, our models predicted detection probabilities that were as low as 10% for some species. Accounting for ambient noise resulted in a modest, mean increase of [≤]3.29% in the total population size for each species. Following our approach, other researchers can easily incorporate ambient noise assessments into their field protocols and analyses, with minimal costs or added complexity, to increase the comparability of studies conducted within different acoustic environments.

ecology↗