Extensions to the Visual Predictive Check to facilitate model performance evaluation

The Visual Predictive Check (VPC) is a valuable and supportive instrument for evaluating model performance. However in its most commonly applied form, the method largely depends on a subjective comparison of the distribution of the simulated data with the observed data, without explicitly quantifying and relating the information in both. In recent adaptations to the VPC this drawback is taken into consideration by presenting the observed and predicted data as percentiles. In addition, in some of these adaptations the uncertainty in the predictions is represented visually. However, it is not assessed whether the expected random distribution of the observations around the predicted median trend is realised in relation to the number of observations. Moreover the influence of and the information residing in missing data at each time point is not taken into consideration. Therefore, in this investigation the VPC is extended with two methods to support a less subjective and thereby more adequate evaluation of model performance: (i) the Quantified Visual Predictive Check (QVPC) and (ii) the Bootstrap Visual Predictive Check (BVPC). The QVPC presents the distribution of the observations as a percentage, thus regardless the density of the data, above and below the predicted median at each time point, while also visualising the percentage of unavailable data. The BVPC weighs the predicted median against the 5th, 50th and 95th percentiles resulting from a bootstrap of the observed data median at each time point, while accounting for the number and the theoretical position of unavailable data. The proposed extensions to the VPC are illustrated by a pharmacokinetic simulation example and applied to a pharmacodynamic disease progression example

High-Affinity Inhibitors of Human NAD+-Dependent 15-Hydroxyprostaglandin Dehydrogenase: Mechanisms of Inhibition and Structure-Activity Relationships

BACKGROUND: 15-Hydroxyprostaglandin dehydrogenase (15-PGDH, EC 1.1.1.141) is the key enzyme for the inactivation of prostaglandins, regulating processes such as inflammation or proliferation. The anabolic pathways of prostaglandins, especially with respect to regulation of the cyclooxygenase (COX) enzymes have been studied in detail; however, little is known about downstream events including functional interaction of prostaglandin-processing and -metabolizing enzymes. High-affinity probes for 15-PGDH will, therefore, represent important tools for further studies. PRINCIPAL FINDINGS: To identify novel high-affinity inhibitors of 15-PGDH we performed a quantitative high-throughput screen (qHTS) by testing >160 thousand compounds in a concentration-response format and identified compounds that act as noncompetitive inhibitors as well as a competitive inhibitor, with nanomolar affinity. Both types of inhibitors caused strong thermal stabilization of the enzyme, with cofactor dependencies correlating with their mechanism of action. We solved the structure of human 15-PGDH and explored the binding modes of the inhibitors to the enzyme in silico. We found binding modes that are consistent with the observed mechanisms of action. CONCLUSIONS: Low cross-reactivity in screens of over 320 targets, including three other human dehydrogenases/reductases, suggest selectivity of the present inhibitors for 15-PGDH. The high potencies and different mechanisms of action of these chemotypes make them a useful set of complementary chemical probes for functional studies of prostaglandin-signaling pathways. ENHANCED VERSION: This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S2

Notch and Wnt Signaling Mediated Rod Photoreceptor Regeneration by Müller Cells in Adult Mammalian Retina

Background: Evidence emerging from a variety of approaches used in different species suggests that Müller cell function may extend beyond its role of maintaining retinal homeostasis to that of progenitors in the adult retina. Enriched Müller cells in vitro or those that re-enter cell cycle in response to neurotoxin-damage to retina in vivo display multipotential and self-renewing capacities, the cardinal features of stem cells. Methodology/Principal Findings: We demonstrate that Notch and Wnt signaling activate Müller cells through their canonical pathways and that a rare subset of activated Müller cells differentiates along rod photoreceptor lineage in the outer nuclear layer. The differentiation of activated Müller cells along photoreceptor lineage is confirmed by multiple approaches that included Hoechst dye efflux analysis, genetic analysis using retina from Nrl-GFP mice, and lineage tracing using GS-GFP lentivirus in wild type and rd mice in vitro and S334ter rats in vivo. Examination of S334ter rats for head-neck tracking of visual stimuli, a behavioral measure of light perception, demonstrates a significant improvement in light perception in animals treated to activate Müller cells. The number of activated Müller cells with rod photoreceptor phenotype in treated animals correlates with the improvement in their light perception. Conclusion/Significance: In summary, our results provide a proof of principle for non-neurotoxin-mediated activation o

Quantitative High-Throughput Screen Identifies Inhibitors of the Schistosoma mansoni Redox Cascade

Schistosomiasis is a tropical disease associated with high morbidity and mortality, currently affecting over 200 million people worldwide. Praziquantel is the only drug used to treat the disease, and with its increased use the probability of developing drug resistance has grown significantly. The Schistosoma parasites can survive for up to decades in the human host due in part to a unique set of antioxidant enzymes that continuously degrade the reactive oxygen species produced by the host's innate immune response. Two principal components of this defense system have been recently identified in S. mansoni as thioredoxin/glutathione reductase (TGR) and peroxiredoxin (Prx) and as such these enzymes present attractive new targets for anti-schistosomiasis drug development. Inhibition of TGR/Prx activity was screened in a dual-enzyme format with reducing equivalents being transferred from NADPH to glutathione via a TGR-catalyzed reaction and then to hydrogen peroxide via a Prx-catalyzed step. A fully automated quantitative high-throughput (qHTS) experiment was performed against a collection of 71,028 compounds tested as 7- to 15-point concentration series at 5 µL reaction volume in 1536-well plate format. In order to generate a robust data set and to minimize the effect of compound autofluorescence, apparent reaction rates derived from a kinetic read were utilized instead of end-point measurements. Actives identified from the screen, along with previously untested analogues, were subjected to confirmatory experiments using the screening assay and subsequently against the individual targets in secondary assays. Several novel active series were identified which inhibited TGR at a range of potencies, with IC50s ranging from micromolar to the assay response limit (∼25 nM). This is, to our knowledge, the first report of a large-scale HTS to identify lead compounds for a helminthic disease, and provides a paradigm that can be used to jump-start development of novel therapeutics for other neglected tropical diseases

Dynamic Modeling of Cell Migration and Spreading Behaviors on Fibronectin Coated Planar Substrates and Micropatterned Geometries

An integrative cell migration model incorporating focal adhesion (FA) dynamics, cytoskeleton and nucleus remodeling, actin motor activity, and lamellipodia protrusion is developed for predicting cell spreading and migration behaviors. This work is motivated by two experimental works: (1) cell migration on 2-D substrates under various fibronectin concentrations and (2) cell spreading on 2-D micropatterned geometries. These works suggest (1) cell migration speed takes a maximum at a particular ligand density (~1140 molecules/µm2) and (2) that strong traction forces at the corners of the patterns may exist due to combined effects exerted by actin stress fibers (SFs). The integrative model of this paper successfully reproduced these experimental results and indicates the mechanism of cell migration and spreading. In this paper, the mechanical structure of the cell is modeled as having two elastic membranes: an outer cell membrane and an inner nuclear membrane. The two elastic membranes are connected by SFs, which are extended from focal adhesions on the cortical surface to the nuclear membrane. In addition, the model also includes ventral SFs bridging two focal adhesions on the cell surface. The cell deforms and gains traction as transmembrane integrins distributed over the outer cell membrane bond to ligands on the ECM surface, activate SFs, and form focal adhesions. The relationship between the cell migration speed and fibronectin concentration agrees with existing experimental data for Chinese hamster ovary (CHO) cell migrations on fibronectin coated surfaces. In addition, the integrated model is validated by showing persistent high stress concentrations at sharp geometrically patterned edges. This model will be used as a predictive model to assist in design and data processing of upcoming microfluidic cell migration assays

CD133+ adult human retinal cells remain undifferentiated in Leukaemia Inhibitory Factor (LIF)

<p>Abstract</p> <p>Background</p> <p>CD133 is a cell surface marker of haematopoietic stem and progenitor cells. Leukaemia inhibitory factor (LIF), sustains proliferation and not differentiation of embryonic stem cells. We used CD133 to purify adult human retinal cells and aimed to determine what effect LIF had on these cultures and whether they still had the ability to generate neurospheres.</p> <p>Methods</p> <p>Retinal cell suspensions were derived from adult human post-mortem tissue with ethical approval. With magnetic automated cell sorting (MACS) CD133⁺retinal cells were enriched from post mortem adult human retina. CD133⁺retinal cell phenotype was analysed by flow cytometry and cultured cells were observed for proliferative capacity, neuropshere generation and differentiation with or without LIF supplementation.</p> <p>Results</p> <p>We demonstrated purification (to 95%) of CD133⁺cells from adult human postmortem retina. Proliferating cells were identified through BrdU incorporation and expression of the proliferation markers Ki67 and Cyclin D1. CD133⁺retinal cells differentiated whilst forming neurospheres containing appropriate lineage markers including glia, neurons and photoreceptors. LIF maintained CD133⁺retinal cells in a proliferative and relatively undifferentiated state (Ki67, Cyclin D1 expression) without significant neurosphere generation. Differentiation whilst forming neurospheres was re-established on LIF withdrawal.</p> <p>Conclusion</p> <p>These data support the evidence that CD133 expression characterises a population of cells within the resident adult human retina which have progenitor cell properties and that their turnover and differentiation is influenced by LIF. This may explain differences in retinal responses observed following disease or injury.</p

Neuron-glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006

Neuron-Glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the "Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds., Springer-Verlag New York, 2020 (2nd edition

A Neuron-Glial Perspective for Computational Neuroscience

International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells