Vascular Dynamics Aid a Coupled Neurovascular Network Learn Sparse Independent Features: A Computational Model

Cerebral vascular dynamics are generally thought to be controlled by neural activity in a unidirectional fashion. However, both computational modeling and experimental evidence point to the feedback effects of vascular dynamics on neural activity. Vascular feedback in the form of glucose and oxygen controls neuronal ATP, either directly or via the agency of astrocytes, which in turn modulates neural firing. Recently, a detailed model of the neuron-astrocyte-vessel system has shown how vasomotion can modulate neural firing. Similarly, arguing from known cerebrovascular physiology, an approach known as “hemoneural hypothesis” postulates functional modulation of neural activity by vascular feedback. To instantiate this perspective, we present a computational model in which a network of “vascular units” supplies energy to a neural network. The complex dynamics of the vascular network, modeled by a network of oscillators, turns neurons ON and OFF randomly. The informational consequence of such dynamics is explored in the context of an auto-encoder network. In the proposed model, each vascular unit supplies energy to a subset of hidden neurons of an autoencoder network, which constitutes its “projective field.” Neurons that receive adequate energy in a given trial have reduced threshold, and thus are prone to fire. Dynamics of the vascular network are governed by changes in the reconstruction error of the auto-encoder network, interpreted as the neuronal demand. Vascular feedback causes random inactivation of a subset of hidden neurons in every trial. We observe that, under conditions of desynchronized vascular dynamics, the output reconstruction error is low and the feature vectors learnt are sparse and independent. Our earlier modeling study highlighted the link between desynchronized vascular dynamics and efficient energy delivery in skeletal muscle. We now show that desynchronized vascular dynamics leads to efficient training in an auto-encoder neural network

A NOVEL QSAR MODEL FOR EVALUATING AND PREDICTING THE INHIBITION ACTIVITY OF H1-RECEPTOR ANTAGONISTS: A SERIES OF THIENOPYRIMIDINE DERIVATIVES

ABSTRACT A Quantitative Structure Activity Relationship (QSAR) study has been established using combination of most influencing physiochemical parameters viz. thermodynamic, electronic, geometric & quantum mechanical descriptors, and H1-antihistaminic activity of a series of thienopyrimidines, the novel Histamine H1 receptor antagonists. Genetic function approximation (GFA) technique was used to identify the descriptors that have influence on biological activity. Dipole, AlogP 98, Jurs and LUMO descriptors were found to influence biological activity significantly. Lipophilicity of compounds was found to have a significant role in H1 Histaminic inhibition along with other thermodynamic, spatial and electronic descriptors. Positive contribution of Dipole, AlogP 98 descriptors suggests that molecules with lipophilic-electronic substituents are more likely to improve the potency. Developed models were found to be significant and predictive as evidenced from their internal and external cross-validation statistics.   Keywords: H1-receptor antagonists; thienopyrimidines; molecular descriptor; genetic function approximations; cross-validation; quantitative structure activity relationship Abbreviations: QSAR : Quantitative structure activity relationship GFA    : Genetic function approximation LOF    : Friedman’s lack of fit VIF     : Variance inflation factor Â

Cerebrovascular endothelial cells form transient Notch‐dependent cystic structures in zebrafish

We identify a novel endothelial membrane behaviour in transgenic zebrafish. Cerebral blood vessels extrude large transient spherical structures that persist for an average of 23 min before regressing into the parent vessel. We term these structures “kugeln”, after the German for sphere. Kugeln are only observed arising from the cerebral vessels and are present as late as 28 days post fertilization. Kugeln do not communicate with the vessel lumen and can form in the absence of blood flow. They contain little or no cytoplasm, but the majority are highly positive for nitric oxide reactivity. Kugeln do not interact with brain lymphatic endothelial cells (BLECs) and can form in their absence, nor do they perform a scavenging role or interact with macrophages. Inhibition of actin polymerization, Myosin II, or Notch signalling reduces kugel formation, while inhibition of VEGF or Wnt dysregulation (either inhibition or activation) increases kugel formation. Kugeln represent a novel Notch‐dependent NO‐containing endothelial organelle restricted to the cerebral vessels, of currently unknown function

Endothelial cells form transient Notch-dependent NO-containing cystic structures during zebrafish cerebrovascular development

Endothelial cell behaviour during blood vessel formation is highly complex and dynamic. Transgenic zebrafish have provided many new insights into these processes, due to their ability to provide detailed in vivo imaging. We here report a previously undescribed endothelial cell behaviour during zebrafish embryonic development. Endothelial cells of the cerebral vessels of 3-5d post fertilisation embryos extruded large membranous spherical structures. These were only found on the cerebral vessels, and did not detach from the parent vessel, instead regressing back into the endothelial cell. These structures did not communicate with the vessel lumen, exhibited periodic oscillations in size and shape, and were enriched with filamentous actin at their neck. Due to their unknown nature and spherical appearance we termed these structures kugeln (German for sphere). Pharmacological inhibition of vascular endothelial growth factor (VEGF) signalling significantly increased kugel number while Notch inhibition significantly reduced both kugel number and diameter. Kugeln contain little cytoplasm, but are highly positive for nitric oxide (NO) reactivity, suggesting they represent a novel NO containing organelle specific to the cerebral vessels

The effect of hyperglycemia on neurovascular coupling and cerebrovascular patterning in zebrafish

Neurovascular coupling (through which local cerebral blood flow changes in response to neural activation are mediated) is impaired in many diseases including diabetes. Current preclinical rodent models of neurovascular coupling rely on invasive surgery and instrumentation, but transgenic zebrafish coupled with advances in imaging techniques allow non-invasive quantification of cerebrovascular anatomy, neural activation, and cerebral vessel haemodynamics. We therefore established a novel non-invasive, non-anaesthetised zebrafish larval model of neurovascular coupling, in which visual stimulus evokes neuronal activation in the optic tectum that is associated with a specific increase in red blood cell speed in tectal blood vessels. We applied this model to the examination of the effect of glucose exposure on cerebrovascular patterning and neurovascular coupling. We found that chronic exposure of zebrafish to glucose impaired tectal blood vessel patterning and neurovascular coupling. The nitric oxide donor sodium nitroprusside rescued all these adverse effects of glucose exposure on cerebrovascular patterning and function. Our results establish the first non-mammalian model of neurovascular coupling, offering the potential to perform more rapid genetic modifications and high throughput screening than is currently possible using rodents. Furthermore, using this zebrafish model we reveal a potential strategy to ameliorate the effects of hyperglycemia on cerebrovascular function

Conference on Best Practices for Managing \u3cem\u3eDaubert\u3c/em\u3e Questions

This article is a transcript of the Philip D. Reed Lecture Series Conference on Best Practices for Managing Daubert Questions, held on October 25, 2019, at Vanderbilt Law School under the sponsorship of the Judicial Conference Advisory Committee on Evidence Rules. The transcript has been lightly edited and represents the panelists’ individual views only and in no way reflects those of their affiliated firms, organizations, law schools, or the judiciary

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

Psychometric Validation Of The Center For Epidemiological Studies Depression Scale In Head And Neck Cancer Patients

Objective The Center for Epidemiological Studies Depression Scale (CES-D) is a 20-item tool developed to screen for depression in the general population. To psychometrically evaluate and validate the CES-D scale for use in head and neck cancer (HNC) patients. Methods The CES-D was applied to 130 subjects at onset of radiation treatment and 3-months following treatment. Analysis was conducted via face and content validity using two expert raters, internal consistency was applied using Cronbach\u27s alpha, test retest reliability comparing baseline to 3-month application, concurrent validity was performed against the FACT-H&N and Pain Disability Index, construct validity was conducted via exploratory factor analysis. Results The sample was predominantly male receiving chemo radiation. Face validity was strong (α = 0.85). Significant difference was found in the mean score between depressed (CES-D cut point ≥ 16) vs. non-depressed (t = −15.84, p =.00) (95% CI = −17.18, −13.33). Internal consistency of the scale was high (α = 0.84). Test retest reliability (p \u3c.001) showed moderate-strong correlations (0.51), however was not sensitive to change in this sample across the study time period. Concurrent validity was strong (r = −0.77, 0.51). Factor analysis at baseline explained 54.92% of variance, with 3 distinct factors; depressed affect, somatic/retarded activity, and positive affect. In contrast to general populations, the factor ‘disturbed interpersonal skill’ was not retained. Conclusion Results confirm the reliability and validity of the CES-D as a measure of depression in HNC populations. Proposed cut off scores remain stable but scale responsiveness suggests caution when evaluating change over time in this population

Zebrafish vascular quantification : a tool for quantification of three-dimensional zebrafish cerebrovascular architecture by automated image analysis

Zebrafish transgenic lines and light sheet fluorescence microscopy allow in-depth insights into three-dimensional vascular development in vivo. However, quantification of the zebrafish cerebral vasculature in 3D remains highly challenging. Here, we describe and test an image analysis workflow for 3D quantification of the total or regional zebrafish brain vasculature, called zebrafish vasculature quantification (ZVQ). It provides the first landmark- or object-based vascular inter-sample registration of the zebrafish cerebral vasculature, producing population average maps allowing rapid assessment of intra- and inter-group vascular anatomy. ZVQ also extracts a range of quantitative vascular parameters from a user-specified region of interest, including volume, surface area, density, branching points, length, radius and complexity. Application of ZVQ to 13 experimental conditions, including embryonic development, pharmacological manipulations and morpholino-induced gene knockdown, shows that ZVQ is robust, allows extraction of biologically relevant information and quantification of vascular alteration, and can provide novel insights into vascular biology. To allow dissemination, the code for quantification, a graphical user interface and workflow documentation are provided. Together, ZVQ provides the first open-source quantitative approach to assess the 3D cerebrovascular architecture in zebrafish