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

Sodium nitroprusside prevents the detrimental effects of glucose on the neurovascular unit and behaviour in zebrafish

Diabetes is associated with dysfunction of the neurovascular unit, although the mechanisms of this are incompletely understood, and currently no treatment exists to prevent these negative effects. We previously found that the NO donor sodium nitroprusside (SNP) prevents the detrimental effect of glucose on neurovascular coupling in zebrafish. We therefore sought to establish the wider effects of glucose exposure on both the neurovascular unit and on behaviour in zebrafish and the ability of SNP to prevent these. We incubated 4 days post fertilisation (dpf) zebrafish embryos in 20mM glucose or mannitol for five days until 9dpf, with or without 0.1mM SNP co-treatment for 24h (8-9dpf), and quantified vascular nitric oxide reactivity, vascular mural cell number, expression of a klf2a reporter, glial fibrillary acidic protein (GFAP) and TRPV4, as well as spontaneous neuronal activation at 9dpf, all in the optic tectum. We also assessed the effect on light/dark preference and locomotory characteristics during free-swimming studies. We find that glucose exposure significantly reduced nitric oxide reactivity, klf2a reporter expression, vascular mural cell number and TRPV4 expression, while significantly increasing spontaneous neuronal activation and GFAP expression (all in the optic tectum). Furthermore, when we examined larval behaviour we found glucose exposure significantly altered light/dark preference and high and low speed locomotion while in light. Co-treatment with SNP reversed all these molecular and behavioural effects of glucose exposure. Our findings comprehensively describe the negative effects of glucose exposure on the vascular anatomy, molecular phenotype, and function of the optic tectum and on whole organism behaviour. We also show that SNP or other NO donors may represent a therapeutic strategy to ameliorate the complications of diabetes on the neurovascular unit

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

Aromatic Stacking Facilitated Self-Assembly of Ultrashort Ionic Complementary Peptide Sequence: β-Sheet Nanofibers with Remarkable Gelation and Interfacial Properties

Understanding peptide self-assembly mechanisms and stability of the formed assemblies is crucial for development of functional nanomaterials. Herein, we have adopted rational design approach to demonstrate how minimal structural modification to a non-assembling ultra-short ionic self-complementary tetrapeptide FEFK (Phe4) remarkably enhanced stability of self-assembly into β-sheet nanofibres and induced hydrogelation. This was achieved by replacing flexible phenylalanine residue (F) by the rigid phenylglycine (Phg) resulting in constrained analogue PhgEPhgK (Phg4), which positioned aromatic rings in an orientation favourable for aromatic stacking. Phg4 self-assembly into stable β-sheet ladders was facilitated by π-staking of aromatic sidechains alongside hydrogen bonding between backbone amides along the nanofibre axis. The contribution of these non-covalent interactions in stabilising self-assembly was predicted by in silico modelling using molecular dynamics simulations and semi-empirical quantum mechanics calculations. In aqueous medium, Phg4 β-sheet nanofibres entangled at a critical gelation concentration > 20 mg/mL forming a network of nanofibrous hydrogel. Phg4 also demonstrated unique surface activity in presence of immiscible oils and was superior to commercial emulsifiers in stabilising oil-in-water emulsions. This was attributed to interfacial adsorption of amphiphilic nanofibrilles forming nanofibrillised microspheres. To our knowledge, Phg4 is the shortest ionic self-complementary peptide rationally designed to self-assemble into stable β-sheet nanofibres capable of gelation and emulsification. Our results suggest that Ultra-short Ionic-complementary Constrained Peptides or UICPs have significant potential for the development of cost-effective, sustainable and multifunctional soft bionanomaterials

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

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong