Dissecting whole-brain conduction delays through MRI microstructural measures

Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences

A case of persistent human pegivirus infection in two separate pregnancies of a woman

Human pegivirus (HPgV) is best known for persistent, presumably non-pathogenic, infection and a propensity to co-infect with human immunodeficiency virus or hepatitis C virus. However, unique attributes, such as the increased risk of malignancy or immune modulation, have been recently recognized for HPgV. We have identified a unique case of a woman with high levels HPgV infection in two pregnancies, which occurred 4 years apart and without evidence of human immunodeficiency virus or hepatitis C virus infection. The second pregnancy was complicated by congenital heart disease. A high level of HPgV infection was detected in the maternal blood from different trimesters by RT-PCR and identified as HPgV type 1 genotype 2 in both pregnancies. In the second pregnancy, the decidua and intervillous tissue of the placenta were positive for HPgV by PCR but not the chorion or cord blood (from both pregnancies), suggesting no vertical transmission despite high levels of viremia. The HPgV genome sequence was remarkably conserved over the 4 years. Using VirScan, sera antibodies for HPgV were detected in the first trimester of both pregnancies. We observed the same anti-HPgV antibodies against the non-structural NS5 protein in both pregnancies, suggesting a similar non-E2 protein humoral immune response over time. To the best of our knowledge, this is the first report of persistent HPgV infection involving placental tissues with no clear indication of vertical transmission. Our results reveal a more elaborate viral-host interaction than previously reported, expand our knowledge about tropism, and opens avenues for exploring the replication sites of this virus

A comprehensive diffusion MRI dataset acquired on the MGH Connectome scanner in a biomimetic brain phantom

We provide a comprehensive diffusion MRI dataset acquired with a novel biomimetic phantom mimicking human white matter. The fiber substrates in the diffusion phantom were constructed from hollow textile axons (“taxons”) with an inner diameter of 11.8±1.2 µm and outer diameter of 33.5±2.3 µm. Data were acquired on the 3 T CONNECTOM MRI scanner with multiple diffusion times and multiple q-values per diffusion time, which is a dedicated acquisition for validation of microstructural imaging methods, such as compartment size and volume fraction mapping. Minimal preprocessing was performed to correct for susceptibility and eddy current distortions. Data were deposited in the XNAT Central database (project ID: dMRI_Phant_MGH)

The quality of energy- and macronutrient-balanced diets regulates host susceptibility to influenza in mice

Modulation of individual macronutrients or caloric density is known to regulate host resistance to infection in mice. However, the impact of diet composition, independent of macronutrient and energy content, on infection susceptibility is unclear. We show that two laboratory rodent diets, widely used as standard animal feeds and experimental controls, display distinct abilities in supporting mice during influenza infection. Mice placed on the highly processed AIN93G showed increased mortality to infection compared with those on a grain-based chow diet, suggesting a detrimental role for highly processed food in host defense. We further demonstrate that the heightened susceptibility of AIN93G-fed mice was associated with the failure in homeostasis restoration mediated by the cytokine interferon (IFN)-γ. Our findings show that diet composition calibrates host survival threshold by regulating adaptive homeostasis and highlights a pivotal role for extrinsic signals in host phenotype and outcome of host-pathogen interaction

Estimating axial diffusivity in the NODDI model

To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model ( d ∥ = 1.7 μ m 2 /ms ). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ∼ 2 − 2.5 μ m 2 /ms , in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data

Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization

The estimation of the apparent axon diameter (AAD) via diffusion MRI is affected by the incoherent alignment of single axons around its axon bundle direction, also known as orientational dispersion. The simultaneous estimation of AAD and dispersion is challenging and requires the optimization of many parameters at the same time. We propose to reduce the complexity of the estimation with an multi-stage approach, inspired to alternate convex search, that separates the estimation problem into simpler ones, thus avoiding the estimation of all the relevant model parameters at once. The method is composed of three optimization stages that are iterated, where we separately estimate the volume fractions, diffusivities, dispersion, and mean AAD, using a Cylinder and Zeppelin model. First, we use multi-shell data to estimate the undispersed axon micro-environment’s signal fractions and diffusivities using the spherical mean technique; then, to account for dispersion, we use the obtained micro-environment parameters to estimate a Watson axon orientation distribution; finally, we use data acquired perpendicularly to the axon bundle direction to estimate the mean AAD and updated signal fractions, while fixing the previously estimated diffusivity and dispersion parameters. We use the estimated mean AAD to initiate the following iteration. We show that our approach converges to good estimates while being more efficient than optimizing all model parameters at once. We apply our method to ex-vivo spinal cord data, showing that including dispersion effects results in mean apparent axon diameter estimates that are closer to their measured histological values

Life-threatening influenza pneumonitis in a child with inherited IRF9 deficiency

Life-threatening pulmonary influenza can be caused by inborn errors of type I and III IFN immunity. We report a 5-yr-old child with severe pulmonary influenza at 2 yr. She is homozygous for a loss-of-function IRF9 allele. Her cells activate gamma-activated factor (GAF) STAT1 homodimers but not IFN-stimulated gene factor 3 (ISGF3) trimers (STAT1/STAT2/IRF9) in response to IFN-α2b. The transcriptome induced by IFN-α2b in the patient's cells is much narrower than that of control cells; however, induction of a subset of IFN-stimulated gene transcripts remains detectable. In vitro, the patient's cells do not control three respiratory viruses, influenza A virus (IAV), parainfluenza virus (PIV), and respiratory syncytial virus (RSV). These phenotypes are rescued by wild-type IRF9, whereas silencing IRF9 expression in control cells increases viral replication. However, the child has controlled various common viruses in vivo, including respiratory viruses other than IAV. Our findings show that human IRF9- and ISGF3-dependent type I and III IFN responsive pathways are essential for controlling IAV

Disrupting Circadian Homeostasis of Sympathetic Signaling Promotes Tumor Development in Mice

and why disruption of circadian rhythm may lead to tumorigenesis. oncogenic potential, leading to tumor development in the same organ systems in wild-type and circadian gene-mutant mice. is a clock-controlled physiological function. The central circadian clock paces extracellular mitogenic signals that drive peripheral clock-controlled expression of key cell cycle and tumor suppressor genes to generate a circadian rhythm in cell proliferation. Frequent disruption of circadian rhythm is an important tumor promoting factor

Advanced brain MRI may help understand the link between migraine and multiple sclerosis

Abstract Background There is a clinical association between migraine and multiple sclerosis. Main body Migraine and MS patients share similar demographics, with the highest incidence among young, female and otherwise healthy patients. The same hormonal constellations/changes trigger disease exacerbation in both entities. Migraine prevalence is increased in MS patients, which is further enhanced by disease-modifying treatment. Clinical data show that onset of migraine typically starts years before the clinical diagnosis of MS, suggesting that there is either a unidirectional relationship with migraine predisposing to MS, and/or a “shared factor” underlying both conditions. Brain imaging studies show white matter lesions in both MS and migraine patients. Neuroinflammatory mechanisms likely play a key role, at least as a shared downstream pathway. In this review article, we provide an overview of the literature about 1) the clinical association between migraine and MS as well as 2) brain MRI studies that help us better understand the mechanistic relationship between both diseases with implications on their underlying pathophysiology. Conclusion Studies suggest a migraine history predisposes patients to develop MS. Advanced brain MR imaging may shed light on shared and distinct features, while helping us better understand mechanisms underlying both disease entities