Improving preclinical to clinical translation in Alzheimer\u27s disease research.

Introduction: Preclinical testing in animal models is a critical component of the drug discovery and development process. While hundreds of interventions have demonstrated preclinical efficacy for ameliorating cognitive impairments in animal models, none have confirmed efficacy in Alzheimer\u27s disease (AD) clinical trials. Critically this lack of translation to the clinic points in part to issues with the animal models, the preclinical assays used, and lack of scientific rigor and reproducibility during execution. In an effort to improve this translation, the Preclinical Testing Core (PTC) of the Model Organism Development and Evaluation for Late-onset AD (MODEL-AD) consortium has established a rigorous screening strategy with go/no-go decision points that permits unbiased assessments of therapeutic agents. Methods: An initial screen evaluates drug stability, formulation, and pharmacokinetics (PK) to confirm appreciable brain exposure in the disease model at the pathologically relevant ages, followed by pharmacodynamics (PD) and predictive PK/PD modeling to inform the dose regimen for long-term studies. The secondary screen evaluates target engagement and disease modifying activity using non-invasive positron emission tomography/magnetic resonance imaging (PET/MRI). Provided the compound meets its go criteria for these endpoints, evaluation for efficacy on behavioral endpoints are conducted. Results: Validation of this pipeline using tool compounds revealed the importance of critical quality control (QC) steps that researchers need to be aware of when executing preclinical studies. These include confirmation of the active pharmaceutical ingredient and at the precise concentration expected; and an experimental design that is well powered and in line with the Animal Research Reporting of In vivo Experiments (ARRIVE) guidelines. Discussion: Taken together our experience executing a rigorous screening strategy with QC checkpoints provides insight to the challenges of conducting translational studies in animal models. The PTC pipeline is a National Institute on Aging (NIA)-supported resource accessible to the research community for investigators to nominate compounds for testing (https://stopadportal.synapse.org/), and these resources will ultimately enable better translational studies to be conducted

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

Dynamics of localization in a waveguide

This is a review of the dynamics of wave propagation through a disordered N-mode waveguide in the localized regime. The basic quantities considered are the Wigner-Smith and single-mode delay times, plus the time-dependent power spectrum of a reflected pulse. The long-time dynamics is dominated by resonant transmission over length scales much larger than the localization length. The corresponding distribution of the Wigner-Smith delay times is the Laguerre ensemble of random-matrix theory. In the power spectrum the resonances show up as a 1/t^2 tail after N^2 scattering times. In the distribution of single-mode delay times the resonances introduce a dynamic coherent backscattering effect, that provides a way to distinguish localization from absorption.Comment: 18 pages including 8 figures; minor correction

The Results of CHD7 Analysis in Clinically Well-Characterized Patients with Kallmann Syndrome

Item does not contain fulltextCONTEXT: Kallmann syndrome (KS) and CHARGE syndrome are rare heritable disorders in which anosmia and hypogonadotropic hypogonadism co-occur. KS is genetically heterogeneous, and there are at least eight genes involved in its pathogenesis, whereas CHARGE syndrome is caused by autosomal dominant mutations in only one gene, the CHD7 gene. Two independent studies showed that CHD7 mutations can also be found in a minority of KS patients. OBJECTIVE: We aimed to investigate whether CHD7 mutations can give rise to isolated KS or whether additional features of CHARGE syndrome always occur. DESIGN: We performed CHD7 analysis in a cohort of 36 clinically well-characterized Dutch patients with KS but without mutations in KAL1 and with known status for the KS genes with incomplete penetrance, FGFR1, PROK2, PROKR2, and FGF8. RESULTS: We identified three heterozygous CHD7 mutations. The CHD7-positive patients were carefully reexamined and were all found to have additional features of CHARGE syndrome. CONCLUSION: The yield of CHD7 analysis in patients with isolated KS seems very low but increases when additional CHARGE features are present. Therefore, we recommend performing CHD7 analysis in KS patients who have at least two additional CHARGE features or semicircular canal anomalies. Identifying a CHD7 mutation has important clinical implications for the surveillance and genetic counseling of patients

Interstellar Turbulence II: Implications and Effects

Interstellar turbulence has implications for the dispersal and mixing of the elements, cloud chemistry, cosmic ray scattering, and radio wave propagation through the ionized medium. This review discusses the observations and theory of these effects. Metallicity fluctuations are summarized, and the theory of turbulent transport of passive tracers is reviewed. Modeling methods, turbulent concentration of dust grains, and the turbulent washout of radial abundance gradients are discussed. Interstellar chemistry is affected by turbulent transport of various species between environments with different physical properties and by turbulent heating in shocks, vortical dissipation regions, and local regions of enhanced ambipolar diffusion. Cosmic rays are scattered and accelerated in turbulent magnetic waves and shocks, and they generate turbulence on the scale of their gyroradii. Radio wave scintillation is an important diagnostic for small scale turbulence in the ionized medium, giving information about the power spectrum and amplitude of fluctuations. The theory of diffraction and refraction is reviewed, as are the main observations and scintillation regions.Comment: 46 pages, 2 figures, submitted to Annual Reviews of Astronomy and Astrophysic

A high‐resolution spatial model to predict exposure to pharmaceuticals in European surface waters – ePiE

Environmental risk assessment of pharmaceuticals requires the determination of their environmental exposure concentrations. Existing exposure modelling approaches are often computationally demanding, require extensive data collection and processing efforts, have a limited spatial resolution, and have undergone limited evaluation against monitoring data. Here, we present ePiE (exposure to Pharmaceuticals in the Environment), a spatially explicit model calculating concentrations of active pharmaceutical ingredients (APIs) in surface waters across Europe at ~1 km resolution. ePiE strikes a balance between generating data on exposure at high spatial resolution while having limited computational and data requirements. Comparison of model predictions with measured concentrations of a diverse set of 35 APIs in the river Ouse (UK) and Rhine basins (North West Europe), showed around 95% were within an order of magnitude. Improved predictions were obtained for the river Ouse basin (95% within a factor of 6; 55% within a factor of 2), where reliable consumption data were available and the monitoring study design was coherent with the model outputs. Application of ePiE in a prioritisation exercise for the Ouse basin identified metformin, gabapentin, and acetaminophen as priority when based on predicted exposure concentrations. After incorporation of toxic potency, this changed to desvenlafaxine, loratadine and hydrocodone

Assessment of protein allergenicity on the basis of immune reactivity: animal models.

Because of the public concern surrounding the issue of the safety of genetically modified organisms, it is critical to have appropriate methodologies to aid investigators in identifying potential hazards associated with consumption of foods produced with these materials. A recent panel of experts convened by the Food and Agriculture Organization and World Health Organization suggested there is scientific evidence that using data from animal studies will contribute important information regarding the allergenicity of foods derived from biotechnology. This view has given further impetus to the development of suitable animal models for allergenicity assessment. This article is a review of what has been achieved and what still has to be accomplished regarding several different animal models. Progress made in the design and evaluation of models in the rat, the mouse, the dog and in swine is reviewed and discussed

A novel systems biology approach to evaluate mouse models of late-onset Alzheimer\u27s disease.

BACKGROUND: Late-onset Alzheimer\u27s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer\u27s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. RESULTS: This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of the 5xFAD mouse, a widely used amyloid pathology model, and three mouse models based on LOAD genetics carrying APOE4 and TREM2*R47H alleles demonstrated overlaps with distinct human AD modules that, in turn, were functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq showed strong correlation between gene expression changes independent of experimental platform. CONCLUSIONS: Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models