Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models

The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture, which we call DeepVess, yielded a segmentation accuracy that was better than both the current state-of-the-art and a trained human annotator, while also being orders of magnitude faster. To explore the effects of aging and Alzheimer's disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer's disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments ($>75\mu m$) in aged animals as compared to young, in both wild type and Alzheimer's disease mouse models.Comment: 34 pages, 9 figure

Study on mechanical properties of coal before and after flooding considering bedding direction

The weak bedding plane and the water-softening coal will lead to the decrease in mechanical properties, which has an important influence on the stability of underground reservoirs and the prevention and control of water inrush accidents in coal mine. To study the comprehensive influence of bedding and soaking on the mechanical properties of coal, the uniaxial compression deformation and failure characteristics of coal under different soaking conditions were analyzed through a non-destructive soaking test and uniaxial compression test and based on the Digital image correlation method (DIC). The mechanical property parameters and surface strain field information of axial parallel and vertical bedded coal samples in the natural state, natural water absorption and forced water absorption were obtained. The results shown that the water absorption characteristics of coal shown obvious stratification differences, and the mechanical properties were affected by the combined effects of stratification and soaking. The specific results were as follows, ① Capillary action led to stronger water adsorption in axial parallel-bedded coal than in axial vertical-bedded coal, and the natural limiting water absorption rate of axial parallel-bedded coal was 2.2 times higher than that of axial vertical-bedded coal. ② The uniaxial compressive strength and elastic modulus of coal were mainly affected by bedding and supplemented by soaking. The failure mode was related to the direction of bedding. The failure mode of axial vertical coal was shear failure, while that of axial parallel coal was split failure. ③ The coal failure was a process of transformation from uniform to non-uniform deformation. After water soaking, the coal appeared strain concentration area earlier, its compaction stage was prolonged, and the elastic deformation stage was shortened. The research results were helpful to further understand the water soaking characteristics, mechanical properties, and rupture evolution of axial parallel and vertical bedded coals, and can be used as a reference for the protection and stability analysis of reserved coal pillars in underground reservoirs

Differential loss of spinal interneurons in a mouse model of ALS

Amyotrophic lateral sclerosis (ALS) leads to a loss of specific motor neuron populations in the spinal cord and cortex. Emerging evidence suggests that interneurons may also be affected, but a detailed characterization of interneuron loss and its potential impacts on motor neuron loss and disease progression is lacking. To examine this issue, the fate of V1 inhibitory neurons during ALS was assessed in the ventral spinal cord using the SODG93A mouse model. The V1 population makes up ∼30% of all ventral inhibitory neurons, ∼50% of direct inhibitory synaptic contacts onto motor neuron cell bodies, and is thought to play a key role in modulating motor output, in part through recurrent and reciprocal inhibitory circuits. We find that approximately half of V1 inhibitory neurons are lost in SODG93A mice at late disease stages, but that this loss is delayed relative to the loss of motor neurons and V2a excitatory neurons. We further identify V1 subpopulations based on transcription factor expression that are differentially susceptible to degeneration in SODG93A mice. At an early disease stage, we show that V1 synaptic contacts with motor neuron cell bodies increase, suggesting an upregulation of inhibition before V1 neurons are lost in substantial numbers. These data support a model in which progressive changes in V1 synaptic contacts early in disease, and in select V1 subpopulations at later stages, represent a compensatory upregulation and then deleterious breakdown of specific interneuron circuits within the spinal cord

Data from: Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models

The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture, which we call DeepVess, yielded a segmentation accuracy that was better than both the current state-of-the-art and a trained human annotator, while also being orders of magnitude faster. To explore the effects of aging and Alzheimer's disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer's disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments (>75μm) in aged animals as compared to young, in both wild type and Alzheimer's disease mouse models. These data support these findings.This work was supported by the European Research Council grant 615102 (NN), the National Institutes of Health grant AG049952 (CS), the National Institutes of Health grants R01LM012719 and R01AG053949 (MS), and the National Science Foundation Cornell NeuroNex Hub grant (1707312, MS and CS)

Effect of Cytochrome b5 Content on the Activity of Polymorphic CYP1A2, 2B6, and 2E1 in Human Liver Microsomes.

Human cytochrome b5 (Cyt b5) plays important roles in cytochrome P450 (CYP)-mediated drug metabolism. However, the expression level of Cyt b5 in normal human liver remains largely unknown. The effect of Cyt b5 on overall CYP activity in human liver microsomes (HLM) has rarely been reported and the relationship between Cyt b5 and the activity of polymorphic CYP has not been systematically investigated. In this study, we found that the median value of Cyt b5 protein was 270.01 pmol/mg from 123 HLM samples, and 12- and 19-fold individual variation was observed in Cyt b5 mRNA and protein levels, respectively. Gender and smoking clearly influenced Cyt b5 content. In addition, we found that Cyt b5 protein levels significantly correlated with the overall activity of CYP1A2, 2B6, and 2E1 in HLM. However, when the CYP activities were sorted by single nucleotide polymorphisms (SNP), the effect of Cyt b5 protein on the kinetic parameters varied greatly. There were significant correlations between Cyt b5 content and Vmax and CLint of CYP1A2 wild-types (3860GG, 2159GG, and 5347CC) as well as homozygous mutants (163AA and 3113GG). In contrast to Vmax and CLint, the Km of CYP2B6 516GG and 785AA genotypes was inversely associated with Cyt b5 content. Correlations between Cyt b5 content and Vmax and CLint of CYP2E1 -1293GG, -1293GC, 7632TT, 7632TA, -333TT, and -352AA genotypes were also observed. In conclusion, Cyt b5 expression levels varied considerably in the Chinese cohort from this study. Cyt b5 had significant impact on the overall activity of CYP1A2, 2B6, and 2E1 in HLM and the effects of Cyt b5 protein on polymorphic CYP1A2, 2B6, and 2E1 activity were SNP-dependent. These findings suggest that Cyt b5 plays an important role in CYP-mediated activities in HLM and may possibly be a contributing factor for the individual variation observed in CYP enzyme activities

Auxin-induced signaling protein nanoclustering contributes to cell polarity formation.

Cell polarity is fundamental to the development of both eukaryotes and prokaryotes, yet the mechanisms behind its formation are not well understood. Here we found that, phytohormone auxin-induced, sterol-dependent nanoclustering of cell surface transmembrane receptor kinase 1 (TMK1) is critical for the formation of polarized domains at the plasma membrane (PM) during the morphogenesis of cotyledon pavement cells (PC) in Arabidopsis. Auxin-induced TMK1 nanoclustering stabilizes flotillin1-associated ordered nanodomains, which in turn promote the nanoclustering of ROP6 GTPase that acts downstream of TMK1 to regulate cortical microtubule organization. In turn, cortical microtubules further stabilize TMK1- and flotillin1-containing nanoclusters at the PM. Hence, we propose a new paradigm for polarity formation: A diffusive signal triggers cell polarization by promoting cell surface receptor-mediated nanoclustering of signaling components and cytoskeleton-mediated positive feedback that reinforces these nanodomains into polarized domains

Auxin-induced signaling protein nanoclustering contributes to cell polarity formation.

Cell polarity is fundamental to the development of both eukaryotes and prokaryotes, yet the mechanisms behind its formation are not well understood. Here we found that, phytohormone auxin-induced, sterol-dependent nanoclustering of cell surface transmembrane receptor kinase 1 (TMK1) is critical for the formation of polarized domains at the plasma membrane (PM) during the morphogenesis of cotyledon pavement cells (PC) in Arabidopsis. Auxin-induced TMK1 nanoclustering stabilizes flotillin1-associated ordered nanodomains, which in turn promote the nanoclustering of ROP6 GTPase that acts downstream of TMK1 to regulate cortical microtubule organization. In turn, cortical microtubules further stabilize TMK1- and flotillin1-containing nanoclusters at the PM. Hence, we propose a new paradigm for polarity formation: A diffusive signal triggers cell polarization by promoting cell surface receptor-mediated nanoclustering of signaling components and cytoskeleton-mediated positive feedback that reinforces these nanodomains into polarized domains