Study of Dendrite Differentiation Using Drosophila Dendritic Arborization Neurons.

Neurons receive, process, and integrate inputs. These operations are organized by dendrite arbor morphology, and the dendritic arborization (da) neurons of the Drosophila peripheral sensory nervous system are an excellent experimental model for examining the differentiation processes that build and shape the dendrite arbor. Studies in da neurons are enabled by a wealth of fly genetic tools that allow targeted neuron manipulation and labeling of the neuron's cytoskeletal or organellar components. Moreover, as da neuron dendrite arbors cover the body wall, they are highly accessible for live imaging analysis of arbor patterning. Here, we outline the structure and function of different da neuron types and give examples of how they are used to elucidate central mechanisms of dendritic arbor formation.

Use of DeTerm for Automated Drosophila Dendrite Arbor Terminal Counts.

Neurons have a complex dendritic architecture that governs information flow through a circuit. Manual quantification of dendritic arbor morphometrics is time-consuming and can be inaccurate. Automated quantification systems such as DeTerm help to overcome these limitations. DeTerm is a software tool that automatically recognizes dendrite branch terminals with high precision. It uses an artificial neural network to label the terminals, count them, and provide each terminal's positional data. DeTerm can recognize the dendritic terminals of Drosophila dendritic arborization (da) neurons, and it can also examine other types of neurons, including mouse Purkinje cells. It is freely available and works on Mac, Windows, and Linux. Here, we describe the use of DeTerm.

Filleting and Immunostaining of Larvae to Visualize Drosophila Dendritic Arborization Neuron Dendrite Arbors.

Nervous system formation involves the specification of neuron identity, followed by precise circuit construction; this includes controlling the pattern and connectivity of the dendrite arbor. Drosophila dendritic arborization (da) neurons are a powerful experimental model for studying dendrite arbor differentiation mechanisms. da neuron dendrite arbors elaborate in two dimensions in the body wall, making it easy to visualize them with high resolution. Immunostaining is a conventional method to examine arbor pattern and the subcellular distribution of proteins. In addition, images acquired from immunostaining protocols can amplify weaker signals from fluorescent transgenic proteins and be used to quantify protein expression levels. This protocol describes a broadly applicable dissection, fixation, and immunostaining approach in Drosophila larvae.

Mounting of Embryos, Larvae, and Pupae for Live Drosophila Dendritic Arborization Neuron Imaging.

Live imaging approaches are essential for monitoring how neurons go through a coordinated series of differentiation steps in their native mechanical and chemical environment. These imaging approaches also allow the study of dynamic subcellular processes such as cytoskeleton remodeling and the movement of organelles. Drosophila dendritic arborization (da) neurons are a powerful experimental system for studying the dendrite arbor in live animals. da neurons are located on the internal surface of the body wall and, therefore, are easily accessible for imaging. Moreover, many genetic tools target da neurons to disrupt genes or proteins of interest and allow the investigator to visualize fluorescent markers and endogenously tagged proteins in the neurons. This protocol introduces methods for preparing and mounting intact Drosophila embryos, larvae, and pupae, allowing live imaging of dynamic cellular processes in da neurons.

Culture of Larval and Pupal Drosophila Dendritic Arborization Neurons.

Drosophila dendritic arborization (da) neurons are a powerful model for studying neuronal differentiation and sensory functions. A general experimental strength of this model is the examination of the neurons in situ in the body wall. However, for some analyses, restricted access to the neurons in situ causes difficulty; da neuron cultures circumvent this. Here, we outline isolation and culture techniques for larval and pupal da neurons. Investigators can use these cultures to perform high-resolution imaging, quantitative immunohistochemistry, and electrophysiology.

Mosaic Analysis with a Repressible Cell Marker (MARCM) Clone Generation in Drosophila Dendritic Arborization Neurons.

Mosaic analysis with a repressible cell marker (MARCM) is used in Drosophila research to create labeled homozygous mutant clones of cells in an otherwise heterozygous fly. It allows the study of the effect of embryonically lethal genes and the determination of cell autonomy for a mutant phenotype. When used in dendritic arborization (da) neurons with a fluorescent protein targeted to the plasma membrane, MARCM allows the identification of homozygous mutant neurons and clear imaging of the dendrite arbor in both live and fixed preparations. Previous protocols that outlined experimental procedures to create MARCM clones in da neurons used a heat shock promoter to drive Flippase (FLP) expression; such an approach requires laborious embryo collection and heat shock steps, and it creates clones in other tissues besides the da neurons. The updated protocol described here outlines the use of FLP expression driven by a sensory organ precursor promoter (SOP-FLP); it requires no embryo collection or manipulation steps and creates clones exclusively in the peripheral sensory neuron lineage.

Association of dietary flavan-3-ol intakes with plasma phenyl-γ-valerolactones: analysis from the TUDA cohort of healthy older adults.

BACKGROUND: Dietary polyphenols, including flavan-3-ols (F3O), are associated with better health outcomes. The relationship of plasma phenyl-γ-valerolactones (PVLs), the products of colonic bacterial metabolism of F3O, with dietary intakes is unclear. OBJECTIVES: To investigate whether plasma PVLs are associated with self-reported intakes of total F3O and procyanidins+(epi)catechins. DESIGN: We measured 9 PVLs by uHPLC-MS-MS in plasma from adults (>60y) in the Trinity-Ulster-Department of Agriculture (TUDA study (2008 to 2012; n=5186) and a follow-up subset (2014 to 2018) with corresponding dietary data (n=557). Dietary (poly)phenols collected by FFQ were analyzed using Phenol-Explorer. RESULTS: Mean (95% confidence interval [CI]) intakes were estimated as 2283 (2213, 2352) mg/d for total (poly)phenols, 674 (648, 701) for total F3O, and 152 (146, 158) for procyanidins+(epi)catechins. Two PVL metabolites were detected in plasma from the majority of participants, 5-(hydroxyphenyl)-γ-VL-sulfate (PVL1) and 5-(4'-hydroxyphenyl)-γ-VL-3'-glucuronide (PVL2). The 7 other PVLs were detectable only in 1-32% of samples. Self-reported intakes (mg/d) of F3O (r = 0.113, P = 0.017) and procyanidin+(epi)catechin (r = 0.122, P = 0.010) showed statistically significant correlations with the sum of PVL1 and PVL 2 (PVL1+2). With increasing intake quartiles (Q1-Q4), mean (95% CI) PVL1+2 increased; from 28.3 (20.8, 35.9) nmol/L in Q1 to 45.2 (37.2, 53.2) nmol/L in Q4; P = 0.025, for dietary F3O, and from 27.4 (19.1, 35.8) nmol/L in Q1 to 46.5 (38.2, 54.9) nmol/L in Q4; P = 0.020, for procyanidins+(epi)catechins. CONCLUSIONS: Of 9 PVL metabolites investigated, 2 were detected in most samples and were weakly associated with intakes of total F3O and procyanidins+(epi)catechins. Future controlled feeding studies are required to validate plasma PVLs as biomarkers of these dietary polyphenols.

STING-Triggered CNS Inflammation in Human Neurodegenerative Diseases.

BACKGROUND: Some neurodegenerative diseases have an element of neuroinflammation that is triggered by viral nucleic acids, resulting in the generation of type I interferons. In the cGAS-STING pathway, microbial and host-derived DNA bind and activate the DNA sensor cGAS, and the resulting cyclic dinucleotide, 2'3-cGAMP, binds to a critical adaptor protein, stimulator of interferon genes (STING), which leads to activation of downstream pathway components. However, there is limited work demonstrating the activation of the cGAS-STING pathway in human neurodegenerative diseases. METHODS: Post-mortem CNS tissue from donors with multiple sclerosis (n = 4), Alzheimer's disease (n = 6), Parkinson's disease (n = 3), amyotrophic lateral sclerosis (n = 3) and non-neurodegenerative controls (n = 11) were screened by immunohistochemistry for STING and relevant protein aggregates (e.g., amyloid-ß, α-synuclein, TDP-43). Human brain endothelial cells were cultured and stimulated with the STING agonist palmitic acid (1-400 µM) and assessed for mitochondrial stress (release of mitochondrial DNA into cytosol, increased oxygen consumption), downstream regulator factors, TBK-1/pIRF3 and inflammatory biomarker interferon-ß release and changes in ICAM-1 integrin expression. RESULTS: In neurodegenerative brain diseases, elevated STING protein was observed mainly in brain endothelial cells and neurons, compared to non-neurodegenerative control tissues where STING protein staining was weaker. Interestingly, a higher STING presence was associated with toxic protein aggregates (e.g., in neurons). Similarly high STING protein levels were observed within acute demyelinating lesions in multiple sclerosis subjects. To understand non-microbial/metabolic stress activation of the cGAS-STING pathway, brain endothelial cells were treated with palmitic acid. This evoked mitochondrial respiratory stress up to a ~2.5-fold increase in cellular oxygen consumption. Palmitic acid induced a statistically significant increase in cytosolic DNA leakage from endothelial cell mitochondria (Mander's coefficient; p < 0.05) and a significant increase in TBK-1, phosphorylated transcription factor IFN regulatory factor 3, cGAS and cell surface ICAM. In addition, a dose response in the secretion of interferon-ß was observed, but it failed to reach statistical significance. CONCLUSIONS: The histological evidence shows that the common cGAS-STING pathway appears to be activated in endothelial and neural cells in all four neurodegenerative diseases examined. Together with the in vitro data, this suggests that the STING pathway might be activated via perturbation of mitochondrial stress and DNA leakage, resulting in downstream neuroinflammation; hence, this pathway may be a target for future STING therapeutics.

Spatio-temporal monitoring of health facility-level malaria trends in Zambia and adaptive scaling for operational intervention.

Background: The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies. Methods: This study developed intelligent data analytics incorporating Bayesian trend and spatio-temporal Integrated Laplace Approximation models to analyse high-burden over 32 million reported malaria cases from 1743 health facilities in Zambia between 2009 and 2015. Results: The results show that at least 5.4 million people live in catchment areas with increasing trends of malaria, covering over 47% of all health facilities, while 5.7 million people live in areas with a declining trend (95% CI), covering 27% of health facilities. A two-scale spatio-temporal trend comparison identified significant differences between health facilities and higher-level districts, and the pattern observed in the southeastern region of Zambia provides the first evidence of the impact of recently implemented localised interventions. Conclusions: The results support our recommendation for an adaptive scaling approach when implementing national malaria monitoring, control and elimination strategies and a particular need for stratified subnational approaches targeting high-burden regions with increasing disease trends. Strong clusters along borders with highly endemic countries in the north and south of Zambia underscore the need for coordinated cross-border malaria initiatives and strategies.

CUX2 deficiency causes facilitation of excitatory synaptic transmission onto hippocampus and increased seizure susceptibility to kainate.

CUX2 gene encodes a transcription factor that controls neuronal proliferation, dendrite branching and synapse formation, locating at the epilepsy-associated chromosomal region 12q24 that we previously identified by a genome-wide association study (GWAS) in Japanese population. A CUX2 recurrent de novo variant p.E590K has been described in patients with rare epileptic encephalopathies and the gene is a candidate for the locus, however the mutation may not be enough to generate the genome-wide significance in the GWAS and whether CUX2 variants appear in other types of epilepsies and physiopathological mechanisms are remained to be investigated. Here in this study, we conducted targeted sequencings of CUX2, a paralog CUX1 and its short isoform CASP harboring a unique C-terminus on 271 Japanese patients with a variety of epilepsies, and found that multiple CUX2 missense variants, other than the p.E590K, and some CASP variants including a deletion, predominantly appeared in patients with temporal lobe epilepsy (TLE). The CUX2 variants showed abnormal localization in human cell culture analysis. While wild-type CUX2 enhances dendritic arborization in fly neurons, the effect was compromised by some of the variants. Cux2- and Casp-specific knockout mice both showed high susceptibility to kainate, increased excitatory cell number in the entorhinal cortex, and significant enhancement in glutamatergic synaptic transmission to the hippocampus. CASP and CUX2 proteins physiologically bound to each other and co-expressed in excitatory neurons in brain regions including the entorhinal cortex. These results suggest that CUX2 and CASP variants contribute to the TLE pathology through a facilitation of excitatory synaptic transmission from entorhinal cortex to hippocampus.

A Risk-Based IoT Decision-Making Framework Based on Literature Review with Human Activity Recognition Case Studies.

The Internet of Things (IoT) is a key and growing technology for many critical real-life applications, where it can be used to improve decision making. The existence of several sources of uncertainty in the IoT infrastructure, however, can lead decision makers into taking inappropriate actions. The present work focuses on proposing a risk-based IoT decision-making framework in order to effectively manage uncertainties in addition to integrating domain knowledge in the decision-making process. A structured literature review of the risks and sources of uncertainty in IoT decision-making systems is the basis for the development of the framework and Human Activity Recognition (HAR) case studies. More specifically, as one of the main targeted challenges, the potential sources of uncertainties in an IoT framework, at different levels of abstraction, are firstly reviewed and then summarized. The modules included in the framework are detailed, with the main focus given to a novel risk-based analytics module, where an ensemble-based data analytic approach, called Calibrated Random Forest (CRF), is proposed to extract useful information while quantifying and managing the uncertainty associated with predictions, by using confidence scores. Its output is subsequently integrated with domain knowledge-based action rules to perform decision making in a cost-sensitive and rational manner. The proposed CRF method is firstly evaluated and demonstrated on a HAR scenario in a Smart Home environment in case study I and is further evaluated and illustrated with a remote health monitoring scenario for a diabetes use case in case study II. The experimental results indicate that using the framework's raw sensor data can be converted into meaningful actions despite several sources of uncertainty. The comparison of the proposed framework to existing approaches highlights the key metrics that make decision making more rational and transparent.

WNT3A-loaded exosomes enable cartilage repair.

Cartilage defects repair poorly. Recent genetic studies suggest that WNT3a may contribute to cartilage regeneration, however the dense, avascular cartilage extracellular matrix limits its penetration and signalling to chondrocytes. Extracellular vesicles actively penetrate intact cartilage. This study investigates the effect of delivering WNT3a into large cartilage defects in vivo using exosomes as a delivery vehicle. Exosomes were purified by ultracentrifugation from conditioned medium of either L-cells overexpressing WNT3a or control un-transduced L-cells, and characterized by electron microscopy, nanoparticle tracking analysis and marker profiling. WNT3a loaded on exosomes was quantified by western blotting and functionally characterized in vitro using the SUPER8TOPFlash reporter assay and other established readouts including proliferation and proteoglycan content. In vivo pathway activation was assessed using TCF/Lef:H2B-GFP reporter mice. Wnt3a loaded exosomes were injected into the knees of mice, in which large osteochondral defects were surgically generated. The degree of repair was histologically scored after 8 weeks. WNT3a was successfully loaded on exosomes and resulted in activation of WNT signalling in vitro. In vivo, recombinant WNT3a failed to activate WNT signalling in cartilage, whereas a single administration of WNT3a loaded exosomes activated canonical WNT signalling for at least one week, and eight weeks later, improved the repair of osteochondral defects. WNT3a assembled on exosomes, is efficiently delivered into cartilage and contributes to the healing of osteochondral defects.

Transcription factor encoding of neuron subtype: Strategies that specify arbor pattern.

Dendrite and axon arbors form scaffolds that connect a neuron to its partners; they are patterned to support the specific connectivity and computational requirements of each neuron subtype. Transcription factor networks control the specification of neuron subtypes, and the consequent diversification of their stereotyped arbor patterns during differentiation. We outline how the differentiation trajectories of stereotyped arbors are shaped by hierarchical deployment of precursor cell and postmitotic transcription factors. These transcription factors exert modular control over the dendrite and axon features of a single neuron, create spatial and functional compartmentalization of an arbor, instruct implementation of developmental patterning rules, and exert operational control over the cell biological processes that construct an arbor.

Effects of maternal folic acid supplementation during the second and third trimesters of pregnancy on neurocognitive development in the child: an 11-year follow-up from a randomised controlled trial.

BACKGROUND: Maternal folic acid (FA) supplementation before and in early pregnancy prevents neural tube defects (NTD), but it is uncertain whether continuing FA after the first trimester has benefits on offspring health. We aimed to evaluate the effect of FA supplementation throughout pregnancy on cognitive performance and brain function in the child. METHODS: Follow-up investigation of 11-year-old children, residing in Northern Ireland, whose mothers had participated in a randomised trial of Folic Acid Supplementation in the Second and Third Trimesters (FASSTT) in pregnancy and received 400 µg/day FA or placebo from the 14th gestational week. Cognitive performance (Full Scale Intelligence Quotient, Verbal Comprehension, Working Memory, Perceptual Reasoning, and Processing Speed) was assessed using the Wechsler Intelligence Scale for Children. Neuronal function was assessed using magnetoencephalographic (MEG) brain imaging. RESULTS: Of 119 mother-child pairs in the FASSTT trial, 68 children were assessed for neurocognitive performance at 11-year follow-up (Dec 2017 to Nov 2018). Children of mothers randomised to FA compared with placebo scored significantly higher in two Processing Speed tests, i.e. symbol search (mean difference 2.9 points, 95% CI 0.3 to 5.5, p = 0.03) and cancellation (11.3 points, 2.5 to 20.1, p = 0.04), whereas the positive effect on Verbal Comprehension was significant in girls only (6.5 points, 1.2 to 11.8, p = 0.03). MEG assessment of neuronal responses to a language task showed increased power at the Beta (13-30 Hz, p = 0.01) and High Gamma (49-70 Hz, p = 0.04) bands in children from FA-supplemented mothers, suggesting more efficient semantic processing of language. CONCLUSIONS: Continued FA supplementation in pregnancy beyond the early period currently recommended to prevent NTD can benefit neurocognitive development of the child. MEG provides a non-invasive tool in paediatric research to objectively assess functional brain activity in response to nutrition and other interventions. TRIAL REGISTRATION: ISRCTN ISRCTN19917787 . Registered on 15 May 2013.

Climate change and the dynamics of age-related malaria incidence in Southern Africa.

In the last decade, many malaria-endemic countries, like Zambia, have achieved significant reductions in malaria incidence among children <5 years old but face ongoing challenges in achieving similar progress against malaria in older age groups. In parts of Zambia, changing climatic and environmental factors are among those suspectedly behind high malaria incidence. Changes and variations in these factors potentially interfere with intervention program effectiveness and alter the distribution and incidence patterns of malaria differentially between young children and the rest of the population. We used parametric and non-parametric statistics to model the effects of climatic and socio-demographic variables on age-specific malaria incidence vis-à-vis control interventions. Linear regressions, mixed models, and Mann-Kendall tests were implemented to explore trends, changes in trends, and regress malaria incidence against environmental and intervention variables. Our study shows that while climate parameters affect the whole population, their impacts are felt most by people aged ≥5 years. Climate variables influenced malaria substantially more than mosquito nets and indoor residual spraying interventions. We establish that climate parameters negatively impact malaria control efforts by exacerbating the transmission conditions via more conducive temperature and rainfall environments, which are augmented by cultural and socioeconomic exposure mechanisms. We argue that an intensified communications and education intervention strategy for behavioural change specifically targeted at ≥5 aged population where incidence rates are increasing, is urgently required and call for further malaria stratification among the ≥5 age groups in the routine collection, analysis and reporting of malaria mortality and incidence data.

Modelling of malaria risk, rates, and trends: A spatiotemporal approach for identifying and targeting sub-national areas of high and low burden.

While mortality from malaria continues to decline globally, incidence rates in many countries are rising. Within countries, spatial and temporal patterns of malaria vary across communities due to many different physical and social environmental factors. To identify those areas most suitable for malaria elimination or targeted control interventions, we used Bayesian models to estimate the spatiotemporal variation of malaria risk, rates, and trends to determine areas of high or low malaria burden compared to their geographical neighbours. We present a methodology using Bayesian hierarchical models with a Markov Chain Monte Carlo (MCMC) based inference to fit a generalised linear mixed model with a conditional autoregressive structure. We modelled clusters of similar spatiotemporal trends in malaria risk, using trend functions with constrained shapes and visualised high and low burden districts using a multi-criterion index derived by combining spatiotemporal risk, rates and trends of districts in Zambia. Our results indicate that over 3 million people in Zambia live in high-burden districts with either high mortality burden or high incidence burden coupled with an increasing trend over 16 years (2000 to 2015) for all age, under-five and over-five cohorts. Approximately 1.6 million people live in high-incidence burden areas alone. Using our method, we have developed a platform that can enable malaria programs in countries like Zambia to target those high-burden areas with intensive control measures while at the same time pursue malaria elimination efforts in all other areas. Our method enhances conventional approaches and measures to identify those districts which had higher rates and increasing trends and risk. This study provides a method and a means that can help policy makers evaluate intervention impact over time and adopt appropriate geographically targeted strategies that address the issues of both high-burden areas, through intensive control approaches, and low-burden areas, via specific elimination programs.

Near-term climate change impacts on sub-national malaria transmission.

The role of climate change on global malaria is often highlighted in World Health Organisation reports. We modelled a Zambian socio-environmental dataset from 2000 to 2016, against malaria trends and investigated the relationship of near-term environmental change with malaria incidence using Bayesian spatio-temporal, and negative binomial mixed regression models. We introduced the diurnal temperature range (DTR) as an alternative environmental measure to the widely used mean temperature. We found substantial sub-national near-term variations and significant associations with malaria incidence-trends. Significant spatio-temporal shifts in DTR/environmental predictors influenced malaria incidence-rates, even in areas with declining trends. We highlight the impact of seasonally sensitive DTR, especially in the first two quarters of the year and demonstrate how substantial investment in intervention programmes is negatively impacted by near-term climate change, most notably since 2010. We argue for targeted seasonally-sensitive malaria chemoprevention programmes.

Pop-guide: Population modeling guidance, use, interpretation, and development for ecological risk assessment.

The assimilation of population models into ecological risk assessment (ERA) has been hindered by their range of complexity, uncertainty, resource investment, and data availability. Likewise, ensuring that the models address risk assessment objectives has been challenging. Recent research efforts have begun to tackle these challenges by creating an integrated modeling framework and decision guide to aid the development of population models with respect to ERA objectives and data availability. In the framework, the trade-offs associated with the generality, realism, and precision of an assessment are used to guide the development of a population model commensurate with the protection goal. The decision guide provides risk assessors with a stepwise process to assist them in developing a conceptual model that is appropriate for the assessment objective and available data. We have merged the decision guide and modeling framework into a comprehensive approach, Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE), for the development of population models for ERA that is applicable across regulatory statutes and assessment objectives. In Phase 1 of Pop-GUIDE, assessors are guided through the trade-offs of ERA generality, realism, and precision, which are translated into model objectives. In Phase 2, available data are assimilated and characterized as general, realistic, and/or precise. Phase 3 provides a series of dichotomous questions to guide development of a conceptual model that matches the complexity and uncertainty appropriate for the assessment that is in concordance with the available data. This phase guides model developers and users to ensure consistency and transparency of the modeling process. We introduce Pop-GUIDE as the most comprehensive guidance for population model development provided to date and demonstrate its use through case studies using fish as an example taxon and the US Federal Insecticide Fungicide and Rodenticide Act and Endangered Species Act as example regulatory statutes. Integr Environ Assess Manag 2021;17:767-784. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent-Based Population Models for Ecological Risk Assessment.

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC.

Distinct Microtubule Organizing Center Mechanisms Combine to Generate Neuron Polarity and Arbor Complexity.

Dendrite and axon arbor wiring patterns determine the connectivity and computational characteristics of a neuron. The identities of these dendrite and axon arbors are created by differential polarization of their microtubule arrays, and their complexity and pattern are generated by the extension and organization of these arrays. We describe how several molecularly distinct microtubule organizing center (MTOC) mechanisms function during neuron differentiation to generate and arrange dendrite and axon microtubules. The temporal and spatial organization of these MTOCs generates, patterns, and diversifies arbor wiring.