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Fig. 3 | BMC Biology

Fig. 3

From: Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock

Fig. 3

Deep learning allows quantitative analysis of aging-induced morphological changes in PVD. a Qualitative inspection of PVD at 3 time points of their life span shows an increase in number of beads throughout the dendrites. Protrusion formation was identified in both anterior and posterior parts of the PVD neuron. Yellow arrows point to neuronal beads. bd Average number of beads, average of mean bead size, and average inter-bead distance of both anterior and posterior regions of PVD throughout aging. Lines are the 25th percentile, mean, and 75th percentile. Whisker is the standard deviation. Statistical analysis was performed with one-way ANOVA followed by Tukey’s (c) or Steel-Dwass (b, d) tests for multiple comparison with equal or unequal variance assumptions, respectively, and significance level determined using Bonferroni correction (α = 0.016) for multiple feature comparisons. *P < 0.016, **P < 0.001, and ***P < 0.0001. e, f Average number of beads, and average inter-bead distance of anterior vs. posterior regions of PVD throughout the aging process. Error bar is SEM. Pairwise statistical analysis was performed with t test and Bonferroni correction. *P < 0.008 and ***P < 0.0001

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