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Abstract Background Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity. Methods The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6–25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity. Results Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = − 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity. Limitations This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable. Conclusions Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Gene size and fold change expression breakdown for CNS cell type-specific DE genes. Significant DE genes with CNS cell type-specific designations were broken down into 4 categories—(1) decreased expression, gene size 100 kb (light orange); (3) increased expression, gene size 100 kb (red). Within each category, DE genes are organized by their respective CNS cell type-specific distribution. The exact Log2 fold change and gene size (kb) values are listed for each DE gene. File format: Microsoft Excel spreadsheet. (XLS 66 kb)

Abstract Background Atherosclerosis, a major source of cardiovascular disease, is asymptomatic for decades until the activation of thrombosis and the rupture of enlarged plaques, resulting in acute coronary syndromes and sudden cardiac arrest. Magnetic resonance imaging (MRI) is a noninvasive nuclear imaging technique to assess the degree of atherosclerotic plaque with high spatial resolution and excellent soft tissue contrast. However, MRI lacks sensitivity for preventive medicine, which limits the ability to observe the onset of vulnerable plaques. In this study, we engineered hybrid metal oxide-peptide amphiphile micelles (HMO-Ms) that combine an inorganic, magnetic iron oxide or manganese oxide inner core with organic, fibrin-targeting peptide amphiphiles, consisting of the sequence CREKA, for potential MRI imaging of thrombosis on atherosclerotic plaques. Results Hybrid metal oxide-peptide amphiphile micelles, consisting of an iron oxide (Fe-Ms) or manganese oxide (Mn-Ms) core with CREKA peptides, were self-assembled into 20–30 nm spherical nanoparticles, as confirmed by dynamic light scattering and transmission electron microscopy. These hybrid nanoparticles were found to be biocompatible with human aortic endothelial cells in vitro, and HMO-Ms bound to human clots three to five times more efficiently than its non-targeted counterparts. Relaxivity studies showed ultra-high r2 value of 457 mM−1 s−1 and r1 value of 0.48 mM−1 s−1 for Fe-Ms and Mn-Ms, respectively. In vitro, MR imaging studies demonstrated the targeting capability of CREKA-functionalized hybrid nanoparticles with twofold enhancement of MR signals. Conclusion This novel hybrid class of MR agents has potential as a non-invasive imaging method that specifically detects thrombosis during the pathogenesis of atherosclerosis.

Fold change (FC ≤ 1.5) list and GO enrichment analysis of probes affected by IHNV status.

This repository contains information about submitted solutions and resulting analysis metrics of the 2019 Quantitative Susceptibility Mapping Reconstruction Challenge. The original susceptibility maps submitted for participation in the challenge are available here and here. The package contains seven Comma-Separated Values (CSV) files and two PDF files: master_stage1_anonymized.csv: Results of stage 1 of the challenge at the time of presentation at the workshop (fully-blinded); master_stage2_snr1_anonymized.csv: Results of stage 2 of the challenge using the high noise dataset at the time of presentation at the workshop (fully-blinded); master_stage2_snr2_anonymized.csv: Results of stage 2 of the challenge using the low noise dataset at the time of presentation at the workshop (fully-blinded); submission_form_stage1.pdf: PDF export of the online form used in stage 1; submission_form_stage2.pdf: PDF export of the online form used in stage 2. For the manuscript, we analyzed these CSV files with scripts reported here. Each csv file contains metrics for all submitted solutions along with detailed information about the algorithm used, provided by the participant at the time of submission. The very first record in each file is a header containing a list of field names: normalized rmse: Whole-brain root-mean-squared error relative to ground truth; rmse_detrend_tissue: Root-mean-squared error relative to ground truth (after detrending) in grey and white matter mask; rmse_detrend_blood: Root-mean-squared error relative to ground truth (after detrending) using a one-pixel dilated vein mask; rmse_detrend_DGM: Root-mean-squared error relative to ground truth (after detrending) in a deep gray matter mask (substantia nigra & subthalamic nucleus, red nucleus, dentate nucleus, putamen, globus pallidus and caudate); DeviationFromLinearSlope: Absolute difference between the slope of the average value of the six deep gray matter regions vs. the prescribed mean value and 1.0; CalcStreak: Estimation of the impact of the streaking artifact in a region of interest surrounding the calcification through the standard deviation of the difference map between reconstruction and the ground truth; DeviationFromCalcMoment: Absolute deviation from the volumetric susceptibility moment of the reconstructed calcification, compared to the ground truth (computed at in the high-resolution model); Submission Identifier: Self-chosen unique identifier of the submission; Submission Identifier of the corresponding Stage 1 submission: This is the Submission Identifier of the solution submitted to Stage 2 that was calculated with a similar algorithm in Stage 1; Changes with respect to Stage 1 submission: Self-reported information about modifications made to the algorithm for Stage 2; Number of submissions in Stage 2: The number of solutions that were submitted to Stage 2 with a similar algorithm; Sim1/Sim2: Filename of the submitted solutions for Stage 1; File name of the zip-file you are going to upload: Filename of the file uploaded to Stage 2; Full name of the algorithm: Self-reported full name of the algorithm used; Preferred Acronym: Self-reported acronym of the algorithm used; Algorithm-type: Self-reported type of algorithm used; Does your algorithm incorporate information derived from magnitude images?: Self-reported Yes/No; Regularization terms: Self-reported types of regularization terms involved; Did your algorithm use the provided frequency map or the four individual echo phase images?: Self-reported information about involved magnitude information; Publication-ready description of the reconstruction technique: Self-reported description of the algorithm; Publications that describe the algorithm: Self-reported literature reference; Algorithm publicly available?: Self-reported public availability of the algorithm; If your algorithm is not yet publicly available, would you be willing to make it available at the end of the challenge?: Self-reported willingness to share the algorithm code with the public; Specific information about this solution: Self-reported detailed information about the solution; Herewith, I permit the QSM Challenge committee to publish my uploaded files (calculated maps) after the completion of the challenge: Self reported agreement with publication of submitted solution; Ground truth was not explicitly or implicitly incorporated into your algorithm or solution: Self-reported confirmation that the ground truth was not incorporated in the solution.

Individual variability in delay of gratification (DG) is associated with a number of important outcomes in both non-human and human primates. Using diffusion tensor imaging (DTI), this study describes the relationship between probabilistic estimates of white matter tracts projecting from the caudate to the prefrontal cortex (PFC) and DG abilities in a sample of 49 captive chimpanzees (Pan troglodytes). After accounting for time between collection of DTI scans and DG measurement, age and sex, higher white matter connectivity between the caudate and right dorsal PFC was found to be significantly associated with the acquisition (i.e. training phase) but not the maintenance of DG abilities. No other associations were found to be significant. The integrity of white matter connectivity between regions of the striatum and the PFC appear to be associated with inhibitory control in chimpanzees, with perturbations on this circuit potentially leading to a variety of maladaptive outcomes. Additionally, results have potential translational implications for understanding the pathophysiology of a number of psychiatric and clinical outcomes in humans. Latzman_et_al_DTI_DG

Abstract Background Primary open angle glaucoma is a heterogeneous group of optic neuropathies that results in optic nerve degeneration and a loss of retinal ganglion cells (RGCs) ultimately causing blindness if allowed to progress. Elevation of intraocular pressure (IOP) is the most attributable risk factor for developing glaucoma and lowering of IOP is currently the only available therapy. However, despite lowering IOP, neurodegenerative effects persist in some patients. Hence, it would be beneficial to develop approaches to promote neuroprotection of RGCs in addition to IOP lowering therapies. The endothelin system is a key target for intervention against glaucomatous neurodegeneration. The endothelin family of peptides and receptors, particularly endothelin-1 (ET-1) and endothelin B (ETB) receptor, has been shown to have neurodegenerative roles in glaucoma. The purpose of this study was to examine changes in endothelin A (ETA) receptor protein expression in the retinas of adult male Brown Norway rats following IOP elevation by the Morrison’s model of ocular hypertension and the impact of ETA receptor overexpression on RGC viability in vitro. Results IOP elevation was carried out in one eye of Brown Norway rats by injection of hypertonic saline through episcleral veins. After 2 weeks of IOP elevation, immunohistochemical analysis of retinal sections from rat eyes showed an increasing trend in immunostaining for ETA receptors in multiple retinal layers including the inner plexiform layer, ganglion cell layer and outer plexiform layer. Following 4 weeks of IOP elevation, a significant increase in immunostaining for ETA receptor expression was found in the retina, primarily in the inner plexiform layer and ganglion cells. A modest increase in staining for ETA receptors was also found in the outer plexiform layer in the retina of rats with IOP elevation. Cell culture studies showed that overexpression of ETA receptors in 661W cells as well as primary RGCs decreases cell viability, compared to empty vector transfected cells. Adeno-associated virus mediated overexpression of the ETA receptor produced an increase in the ETB receptor in primary RGCs. Conclusions Elevated IOP results in an appreciable change in ETA receptor expression in the retina. Overexpression of the ETA receptor results in an overall decrease in cell viability, accompanied by an increase in ETB receptor levels, suggesting the involvement of both ETA and ETB receptors in mediating cell death. These findings raise possibilities for the development of ETA/ETB dual receptor antagonists as neuroprotective treatments for glaucomatous neuropathy.

Additional file 10: Table S9. CpG DMRs identified among neuronal samples isolated from the two hippocampus tissue groups.