LAMA: automated image analysis for the developmental phenotyping of mouse embryos.

Advanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines.

Magnetic resonance imaging reveals specific anatomical changes in the brain of Agat- and Gamt-mice attributed to creatine depletion and guanidinoacetate alteration.

Arginine:glycine amidinotransferase- and guanidinoacetate methyltransferase deficiency are severe neurodevelopmental disorders. It is not known whether mouse models of disease express a neuroanatomical phenotype. High-resolution magnetic resonance imaging (MRI) with advanced image analysis was performed in perfused, fixed mouse brains encapsulated with the skull from male, 10-12 week old Agat -exc and B6J.Cg-Gamt tm1Isb mice (n = 48; n = 8 per genotype, strain). T2-weighted MRI scans were nonlinearly aligned to a 3D atlas of the mouse brain with 62 structures identified. Local differences in brain shape related to genotype were assessed by analysis of deformation fields. Creatine (Cr) and guanidinoacetate (GAA) were measured with high-performance liquid chromatography (HPLC) in brain homogenates (n = 24; n = 4 per genotype, strain) after whole-body perfusion. Cr was decreased in the brain of Agat- and Gamt mutant mice. GAA was decreased in Agat-/- and increased in Gamt-/- . Body weight and brain volume were lower in Agat-/- than in Gamt-/- . The analysis of entire brain structures revealed corpus callosum, internal capsule, fimbria and hypothalamus being different between the genotypes in both strains. Eighteen and fourteen significant peaks (local areas of difference in relative size) were found in Agat- and Gamt mutants, respectively. Comparing Agat-/- with Gamt-/- , we found changes in three brain regions, lateral septum, amygdala, and medulla. Intra-strain differences in four brain structures can be associated with Cr deficiency, while the inter-strain differences in three brain structures of the mutant mice may relate to GAA. Correlating these neuroanatomical findings with gene expression data implies the role of Cr metabolism in the developing brain and the importance of early intervention in patients with Cr deficiency syndromes.

Mouse models of 17q21.31 microdeletion and microduplication syndromes highlight the importance of Kansl1 for cognition.

Koolen-de Vries syndrome (KdVS) is a multi-system disorder characterized by intellectual disability, friendly behavior, and congenital malformations. The syndrome is caused either by microdeletions in the 17q21.31 chromosomal region or by variants in the KANSL1 gene. The reciprocal 17q21.31 microduplication syndrome is associated with psychomotor delay, and reduced social interaction. To investigate the pathophysiology of 17q21.31 microdeletion and microduplication syndromes, we generated three mouse models: 1) the deletion (Del/+); or 2) the reciprocal duplication (Dup/+) of the 17q21.31 syntenic region; and 3) a heterozygous Kansl1 (Kans1+/-) model. We found altered weight, general activity, social behaviors, object recognition, and fear conditioning memory associated with craniofacial and brain structural changes observed in both Del/+ and Dup/+ animals. By investigating hippocampus function, we showed synaptic transmission defects in Del/+ and Dup/+ mice. Mutant mice with a heterozygous loss-of-function mutation in Kansl1 displayed similar behavioral and anatomical phenotypes compared to Del/+ mice with the exception of sociability phenotypes. Genes controlling chromatin organization, synaptic transmission and neurogenesis were upregulated in the hippocampus of Del/+ and Kansl1+/- animals. Our results demonstrate the implication of KANSL1 in the manifestation of KdVS phenotypes and extend substantially our knowledge about biological processes affected by these mutations. Clear differences in social behavior and gene expression profiles between Del/+ and Kansl1+/- mice suggested potential roles of other genes affected by the 17q21.31 deletion. Together, these novel mouse models provide new genetic tools valuable for the development of therapeutic approaches.

Progressive neuroanatomical changes caused by Grin1 loss-of-function mutation.

NMDA receptor dysfunction is central to the encephalopathies caused by missense mutations in the NMDA receptor subunit genes. Missense variants of GRIN1, GRIN2A, and GRIN2B cause similar syndromes with varying severity of intellectual impairment, autism, epilepsy, and motor dysfunction. To gain insight into possible biomarkers of NMDAR hypofunction, we asked whether a loss-of-function variant in the Grin1 gene would cause structural changes in the brain that could be detected by MRI. We also studied the developmental trajectory of these changes to determine whether structural changes coincided with reported cognitive impairments in the mice. We performed magnetic resonance imaging in male Grin1-/- knockdown mice (GluN1KD) that were three, six, or twelve weeks old. Deformation-based morphometry was used to assess neuroanatomical differences. Volumetric reductions were detected in substantia nigra and striatum of GluN1KD mice at all ages. Changes in limbic structures were only evident at six weeks of age. Reductions in white matter volumes were first evident at three weeks, and additional deficits were detected at six and twelve weeks. FluoroJade immunofluorescence revealed degenerating neurons in twelve-week old GluN1KD mice. We conclude that Grin1 loss-of-function mutations cause volume reductions in dopaminergic structures early in development, while changes to limbic and white matter structures are delayed and are more pronounced in post-adolescent ages. The evidence of degenerating neurons in the mature brain indicates an ongoing process of cell loss as a consequence of NMDAR hypofunction.

The effect of automated landmark identification on morphometric analyses.

Morphometric analysis of anatomical landmarks allows researchers to identify specific morphological differences between natural populations or experimental groups, but manually identifying landmarks is time-consuming. We compare manually and automatically generated adult mouse skull landmarks and subsequent morphometric analyses to elucidate how switching from manual to automated landmarking will impact morphometric analysis results for large mouse (Mus musculus) samples (n = 1205) that represent a wide range of 'normal' phenotypic variation (62 genotypes). Other studies have suggested that the use of automated landmarking methods is feasible, but this study is the first to compare the utility of current automated approaches to manual landmarking for a large dataset that allows the quantification of intra- and inter-strain variation. With this unique sample, we investigated how switching to a non-linear image registration-based automated landmarking method impacts estimated differences in genotype mean shape and shape variance-covariance structure. In addition, we tested whether an initial registration of specimen images to genotype-specific averages improves automatic landmark identification accuracy. Our results indicated that automated landmark placement was significantly different than manual landmark placement but that estimated skull shape covariation was correlated across methods. The addition of a preliminary genotype-specific registration step as part of a two-level procedure did not substantially improve on the accuracy of one-level automatic landmark placement. The landmarks with the lowest automatic landmark accuracy are found in locations with poor image registration alignment. The most serious outliers within morphometric analysis of automated landmarks displayed instances of stochastic image registration error that are likely representative of errors common when applying image registration methods to micro-computed tomography datasets that were initially collected with manual landmarking in mind. Additional efforts during specimen preparation and image acquisition can help reduce the number of registration errors and improve registration results. A reduction in skull shape variance estimates were noted for automated landmarking methods compared with manual landmarking. This partially reflects an underestimation of more extreme genotype shapes and loss of biological signal, but largely represents the fact that automated methods do not suffer from intra-observer landmarking error. For appropriate samples and research questions, our image registration-based automated landmarking method can eliminate the time required for manual landmarking and have a similar power to identify shape differences between inbred mouse genotypes.

P63 expression plays a role in developmental rate, embryo size, and local morphogenesis.

BACKGROUND: The p63 gene is integral to the development of many body parts including limb, palate, teeth, and urogenital tract. Loss of p63 expression may alter developmental rate, which is crucial to normal morphogenesis. To validate a novel, unbiased embryo phenotyping software tool, we tested whether delayed development contributes to the pathological phenotype of a p63 mouse mutant (p63-/- ). We quantified dysmorphology in p63-/- embryos and tested for universal growth delay relative to wild-type (WT) embryos. Fixed embryos (n = 6; p63-/- ) aged day (E) 15.5 were micro-CT scanned and quantitatively analyzed using a digital WT atlas that defined volumetric differences between p63-/- and WT embryos. RESULTS: p63-/- embryos showed a growth delay of approximately 22 hr (0.9 days). Among the E15.5 mutants, overall size was closest to WT E14.6 mice but shape was closest to WT E14.0. The atlas clearly identified in p63-/- embryos malformations of epithelial derivatives including limbs, tail, urogenital structures, brain, face, and tooth. CONCLUSIONS: The software atlas technique described the p63-/- phenotype as a combination of developmental delay (i.e., heterochrony) and malformation (i.e., pathological shape; failed organogenesis). This study identifies for the first time global and local roles for p63 in prenatal growth and development. Developmental Dynamics 247:779-787, 2018. © 2018 Wiley Periodicals, Inc.

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.

4D atlas of the mouse embryo for precise morphological staging.

After more than a century of research, the mouse remains the gold-standard model system, for it recapitulates human development and disease and is quickly and highly tractable to genetic manipulations. Fundamental to the power and success of using a mouse model is the ability to stage embryonic mouse development accurately. Past staging systems were limited by the technologies of the day, such that only surface features, visible with a light microscope, could be recognized and used to define stages. With the advent of high-throughput 3D imaging tools that capture embryo morphology in microscopic detail, we now present the first 4D atlas staging system for mouse embryonic development using optical projection tomography and image registration methods. By tracking 3D trajectories of every anatomical point in the mouse embryo from E11.5 to E14.0, we established the first 4D atlas compiled from ex vivo 3D mouse embryo reference images. The resulting 4D atlas comprises 51 interpolated 3D images in this gestational range, resulting in a temporal resolution of 72 min. From this 4D atlas, any mouse embryo image can be subsequently compared and staged at the global, voxel and/or structural level. Assigning an embryonic stage to each point in anatomy allows for unprecedented quantitative analysis of developmental asynchrony among different anatomical structures in the same mouse embryo. This comprehensive developmental data set offers developmental biologists a new, powerful staging system that can identify and compare differences in developmental timing in wild-type embryos and shows promise for localizing deviations in mutant development.

Variability of brain anatomy for three common mouse strains.

The way in which brain structures express different morphologies is not fully understood. Here we investigate variability in brain anatomy using ex vivo MRI of three common laboratory mouse strains: in two inbred strains (C57BL/6 and 129S6) and one outbred strain (CD-1). We use Generalised Procrustes Analysis (GPA) to estimate modes of anatomical variability. We find three distinct bilateral modes of anatomical surface variability associated with the motor cortex, the anterior somatosensory, the retrosplenial and the entorhinal cortex. The modes of variability that are associated with the motor cortex and anterior somatosensory cortex are predominantly due to genetic, i.e. strain differences. Next, we specifically test if a particular strain is more variable. We find that only the mode associated with motor cortex size has a slightly larger variance in the outbred CD-1 mice compared to the two inbred strains. This suggests that the hypothesis that outbred strains are more variable in general is not true for brain anatomy and the use of outbred CD-1 mice does probably not come at the price of increased variability. Further, we show that the first two principal components distinguish between the three strains with 91% accuracy. This indicates that neuroanatomical strain differences are captured by considerably fewer dimensions than necessary for atlas-based or voxel-wise testing. Statistical comparisons based on shape models could thus be a powerful complement to traditional atlas and voxel-based methods at detecting gene-related brain differences in mice. Finally, we find that the principal components of individual brain structures are correlated, suggesting a tightly coupled network of interdependent developmental trajectories. These results raise the question to what degree neuroanatomical variability is directly genetically determined or the result of experience and epigenetic mechanisms.

Proximal cerebral arteries develop myogenic responsiveness in heart failure via tumor necrosis factor-α-dependent activation of sphingosine-1-phosphate signaling.

BACKGROUND: Heart failure is associated with neurological deficits, including cognitive dysfunction. However, the molecular mechanisms underlying reduced cerebral blood flow in the early stages of heart failure, particularly when blood pressure is minimally affected, are not known. METHODS AND RESULTS: Using a myocardial infarction model in mice, we demonstrate a tumor necrosis factor-α (TNFα)-dependent enhancement of posterior cerebral artery tone that reduces cerebral blood flow before any overt changes in brain structure and function. TNFα expression is increased in mouse posterior cerebral artery smooth muscle cells at 6 weeks after myocardial infarction. Coordinately, isolated posterior cerebral arteries display augmented myogenic tone, which can be fully reversed in vitro by the competitive TNFα antagonist etanercept. TNFα mediates its effect via a sphingosine-1-phosphate (S1P)-dependent mechanism, requiring sphingosine kinase 1 and the S1P(2) receptor. In vivo, sphingosine kinase 1 deletion prevents and etanercept (2-week treatment initiated 6 weeks after myocardial infarction) reverses the reduction of cerebral blood flow, without improving cardiac function. CONCLUSIONS: Cerebral artery vasoconstriction and decreased cerebral blood flow occur early in an animal model of heart failure; these perturbations are reversed by interrupting TNFα/S1P signaling. This signaling pathway may represent a potential therapeutic target to improve cognitive function in heart failure.

Mapping registration sensitivity in MR mouse brain images.

Nonlinear registration algorithms provide a way to estimate structural (brain) differences based on magnetic resonance images. Their ability to align images of different individuals and across modalities has been well-researched, but the bounds of their sensitivity with respect to the recovery of salient morphological differences between groups are unclear. Here we develop a novel approach to simulate deformations on MR brain images to evaluate the ability of two registration algorithms to extract structural differences corresponding to biologically plausible atrophy and expansion. We show that at a neuroanatomical level registration accuracy is influenced by the size and compactness of structures, but do so differently depending on how much change is simulated. The size of structures has a small influence on the recovered accuracy. There is a trend for larger structures to be recovered more accurately, which becomes only significant as the amount of simulated change is large. More compact structures can be recovered more accurately regardless of the amount of simulated change. Both tested algorithms underestimate the full extent of the simulated atrophy and expansion. Finally we show that when multiple comparisons are corrected for at a voxelwise level, a very low rate of false positives is obtained. More interesting is that true positive rates average around 40%, indicating that the simulated changes are not fully recovered. Simulation experiments were run using two fundamentally different registration algorithms and we identified the same results, suggesting that our findings are generalizable across different classes of nonlinear registration algorithms.

Performing label-fusion-based segmentation using multiple automatically generated templates.

Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively).

Effects of a ketogenic diet during pregnancy on embryonic growth in the mouse.

BACKGROUND: The increasing use of the ketogenic diet (KD), particularly by women of child-bearing age, raises a question about its suitability during gestation. To date, no studies have thoroughly investigated the direct implications of a gestational ketogenic diet on embryonic development. METHODS: To fill this knowledge gap we imaged CD-1 mouse embryos whose mothers were fed either a Standard Diet (SD) or a KD 30 days prior to, as well as during gestation. Images were collected at embryonic days (E) 13.5 using Optical Projection Tomography (OPT) and at E17.5 using Magnetic Resonance Imaging (MRI). RESULTS: An anatomical comparison of the SD and KD embryos revealed that at E13.5 the average KD embryo was volumetrically larger, possessed a relatively larger heart but smaller brain, and had a smaller pharynx, cervical spinal cord, hypothalamus, midbrain, and pons, compared with the average SD embryo. At E17.5 the KD embryo was found to be volumetrically smaller with a relatively smaller heart and thymus, but with enlarged cervical spine, thalamus, midbrain and pons. CONCLUSION: A ketogenic diet during gestation results in alterations in embryonic organ growth. Such alterations may be associated with organ dysfunction and potentially behavioral changes in postnatal life.

Suppressor of fused controls mid-hindbrain patterning and cerebellar morphogenesis via GLI3 repressor.

Sonic Hedgehog and its GLI transcriptional effectors control foliation complexity during cerebellar morphogenesis by promoting granule cell precursor proliferation. Here, we reveal a novel contribution of Sonic Hedgehog-GLI signaling to cerebellar patterning and cell differentiation by generating mice with targeted deletion of Suppressor of Fused (SuFu), a regulator of Sonic Hedgehog signaling, in the mid-hindbrain. Postnatal SuFu-deficient mice exhibit impaired motor coordination and severe cerebellar mispatterning. SuFu conditional knock-out embryos display abnormal mid-hindbrain morphology associated with misexpression of Fgf8, and delayed differentiation and abnormal migration of major cerebellar cell types. Sonic Hedgehog is ectopically expressed in the external granule layer and Hedgehog signaling is upregulated. While expression of full-length GLI transcriptional activators downstream of Hedgehogs is markedly reduced, a processed form of GLI3, a transcriptional repressor, is essentially lost. Genetic expression of a Gli3 allele encoding GLI3 repressor in SuFu-deficient mice largely rescues abnormal cerebellar patterning and cell differentiation observed in mice with SuFu deficiency alone. Together, our data demonstrate that SuFu controls cerebellar patterning and cell differentiation in a GLI3 repressor-dependent manner.

Cerebellar abnormalities in purine nucleoside phosphorylase deficient mice.

Inherited defects in purine nucleoside phosphorylase (PNP) cause severe T cell immunodeficiency and progressive neurological dysfunction, yet little is known about the effects of PNP deficiency on the brain. PNP-KO mice display metabolic and immune anomalies similar to those observed in patients. Our objectives were to characterize brain abnormalities in PNP-KO mice and determine whether restoring PNP activity prevents these abnormalities. We analyzed structural brain defects in PNP-KO mice by magnetic resonance imaging, while assessing motor deficits using the accelerating rotarod and stationary balance beam tests. We detected morphological abnormalities and apoptosis in the cerebellum of PNP-KO mice by hematoxylin and eosin, electron microscopy, TUNEL and activated caspase 3 staining. We treated PNP-KO mice with PNP fused to the HIV-TAT protein transduction domain (TAT-PNP) from birth or from 4 weeks of age. Magnetic resonance imaging revealed a smaller than normal cerebellum in PNP-KO mice. PNP-KO mice displayed motor abnormalities including rapid fall from the rotating rod and frequent slips from the balance beam. The cerebellum of PNP-KO mice contained reduced purkinje cells (PC), which were irregular in shape and had degenerated dendrites. PC from the cerebellum of PNP-KO mice, expanded ex vivo, demonstrated increased apoptosis, which could be corrected by supplementing cultures with TAT-PNP. TAT-PNP injections restored PNP activity in the cerebellum of PNP-KO mice. TAT-PNP from birth, but not treatment initiated at 4 weeks of age, prevented the cerebellar PC damage and motor deficits. We conclude that PNP deficiency cause cerebellar abnormalities, including PC damage and progressive motor deficits. TAT-PNP treatment from birth can prevent the neurological abnormalities in PNP-KO mice.

Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation.

Purpose: Ensembles of convolutional neural networks (CNNs) often outperform a single CNN in medical image segmentation tasks, but inference is computationally more expensive and makes ensembles unattractive for some applications. We compared the performance of differently constructed ensembles with the performance of CNNs derived from these ensembles using knowledge distillation, a technique for reducing the footprint of large models such as ensembles. Approach: We investigated two different types of ensembles, namely, diverse ensembles of networks with three different architectures and two different loss-functions, and uniform ensembles of networks with the same architecture but initialized with different random seeds. For each ensemble, additionally, a single student network was trained to mimic the class probabilities predicted by the teacher model, the ensemble. We evaluated the performance of each network, the ensembles, and the corresponding distilled networks across three different publicly available datasets. These included chest computed tomography scans with four annotated organs of interest, brain magnetic resonance imaging (MRI) with six annotated brain structures, and cardiac cine-MRI with three annotated heart structures. Results: Both uniform and diverse ensembles obtained better results than any of the individual networks in the ensemble. Furthermore, applying knowledge distillation resulted in a single network that was smaller and faster without compromising performance compared with the ensemble it learned from. The distilled networks significantly outperformed the same network trained with reference segmentation instead of knowledge distillation. Conclusion: Knowledge distillation can compress segmentation ensembles of uniform or diverse composition into a single CNN while maintaining the performance of the ensemble.

A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines.

In recent years, the replicability of neuroimaging findings has become an important concern to the research community. Neuroimaging pipelines consist of myriad numerical procedures, which can have a cumulative effect on the accuracy of findings. To address this problem, we propose a method for simulating artificial lesions in the brain in order to estimate the sensitivity and specificity of lesion detection, using different automated corticometry pipelines. We have applied this method to different versions of two widely used neuroimaging pipelines (CIVET and FreeSurfer), in terms of coefficients of variation; sensitivity and specificity of detecting lesions in 4 different regions of interest in the cortex, while introducing variations to the lesion size, the blurring kernel used prior to statistical analyses, and different thickness metrics (in CIVET). These variations are tested in a between-subject design (in two random groups, with and without lesions, using T1-weigted MRIs of 152 individuals from the International Consortium of Brain Mapping (ICBM) dataset) and in a within-subject pre-/post-lesion design [using 21 T1-Weighted MRIs of a single adult individual, scanned in the Infant Brain Imaging Study (IBIS)]. The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.

Regionally reduced brain volume, altered serotonin neurochemistry, and abnormal behavior in mice null for the circadian rhythm output gene Magel2.

Magel2 belongs to the MAGE/necdin family of proteins, which have roles in cell cycle, differentiation, and apoptosis. The Magel2 gene is expressed in various brain regions, most notably the hypothalamus. Mice with a targeted deletion of Magel2 display hypoactivity, blunted circadian rhythm, decreased fertility, and increased adiposity. The human ortholog, MAGEL2, is one of a set of paternally expressed, imprinted genes inactivated in most cases of Prader-Willi syndrome, a complex neurodevelopmental disorder. To explore the role of Magel2, brain morphology, brain neurochemistry, and behavior were measured in Magel2-null mice. Brain volume was reduced in specific regions, particularly in the parieto-temporal lobe of the cerebral cortex, the amygdala, the hippocampus, and the nucleus accumbens, as measured by quantitative magnetic resonance imaging. Abnormal neurochemistry was detected in brain samples from adult mice, consisting of decreased serotonin and 5-hydroxyindoleacetic acid in the cortex and the hypothalamus, and decreased dopamine in the hypothalamus. Magel2-null mice displayed relatively normal motor and learning abilities, but exhibited abnormal behavior in novel environments. This study lends support to the important role of the circadian rhythm output gene Magel2 in brain structure and behavior.

MRI to Assess Neurological Function.

This article describes a detailed set of protocols for mouse brain imaging using MRI. We focus primarily on measuring changes in neuroanatomy, and provide both instructions for mouse preparation and details on image acquisition, image processing, and statistics. Practical details as well as theoretical considerations are provided. © 2018 by John Wiley & Sons, Inc.

Neurobiological Mechanisms of Chemotherapy-induced Cognitive Impairment in a Transgenic Model of Breast Cancer.

Animal studies have reinforced clinical reports of cognitive impairment in cancer survivors following chemotherapy but, until now, all pre-clinical research in this area has been conducted on normal rodents. The present study investigated the effects of chemotherapy on cognition and underlying biological mechanisms in the FVB/N-Tg (MMTV-neu) 202 Mul/J mouse, a well-characterized transgenic model of breast cancer that has similarities to the tumorigenesis which occurs in humans. Tumor-bearing and control mice received three weekly injections of a combination of methotrexate + 5-fluorouracil, or an equal volume of saline. Different aspects of learning and memory were measured before and after treatment. The effects of tumor and chemotherapy on neurogenesis, neuro-inflammatory cytokine activity, and brain volume, as they relate to corresponding cognitive changes, were also measured. The toxic effects of chemotherapy extended to the cancerous model in which substantial cognitive impairment was also associated with the disease. Cognitive deficits were greatest in tumorigenic mice that received the anti-cancer drugs. Both tumor growth and chemotherapy caused significant changes in brain volume, including the hippocampus and frontal lobes, two structures that are directly implicated in cognitive tasks that were shown to be vulnerable. The level of hippocampal neurogenesis in adulthood was suppressed in chemotherapy-treated mice and associated with loss of hippocampus-controlled cognitive function. Dysregulation of cytokine activity was found in tumorigenic mice and associated with impaired cognitive performance. The results show that chemotherapy and tumor development independently contribute to cognitive deficits through different biological mechanisms.