Tract Profiles Research Articles

Fiber tract profiles of community dwelling older adults with LATE‐NC and associations with postmortem TDP‐43

AbstractBackgroundTAR DNA‐binding protein 43 (TDP‐43), has been shown to be involved in various neurodegenerative disorders involving axonal damage including ALS, FTLD, and LATE. Studying the relationships between postmortem TDP‐43 and antemortem white matter (WM) structural integrity can allow for a better understanding of underlying neural mechanisms of the disease. Measures of white matter integrity assume fiber bundles to maintain similar characteristics along the length of the tract, however, advanced computational research has identified that white matter integrity varies in stereotyped patterns along the tract.MethodsIn‐vivo diffusion‐weighted images were gathered on a 1.5T scanner from subjects from the Religious Orders Study and the Rush Memory and Aging Project. Tractography was conducted for each subject using Mrtrix3 and Automated Fiber Quantification (AFQ) was used to calculate fractional anisotropy (FA) along fiber tracts for 20 major fiber bundles. A semi‐quantitative rating of TDP‐43 severity was assessed in 5 brain regions. We utilized regression models to relate postmortem disease and antemortem FA at 100 nodes along each fiber tract while controlling for coexisting Alzheimer’s disease pathology and demographics.ResultsThe 63 subjects were 91.2 (SD = 6.2) [range: 71.7‐103.6] years old at death. Thirty‐eight percent had TDP‐43 pathology and 36% had cognitive changes before death. Overall, fiber tract profiles revealed variation of FA along each fiber bundle. Results measuring the relationship to disease revealed a significant negative relationship (FWE corrected‐p<0.05) between postmortem TDP‐43 and FA at unique portions of the left hippocampal cingulum.ConclusionFindings support current literature indicating white matter integrity does not follow a uniform pattern along fiber tracts in older adults. Pathology relationships reveal unique portions of tracts which have unique relationships to TDP‐43. Understanding the relationship between disease and these vulnerable regions will be critical in elucidating the effect of TDP‐43 on white matter integrity leading to cognitive decline.

Structural Development of Speech Networks in Young Children at Risk for Speech Disorder.

Characterizing the structural development of the neural speech network in early childhood is important for understanding speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old at risk for early speech disorder were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using multi-compartment restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus ( pars opercularis ), right pre-supplementary/ supplementary motor area (pre-SMA/SMA), and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automatic fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT. These findings suggest that individual differences in speech performance are reflected in structural gray and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.

Tractometry of the Human Connectome Project: resources and insights.

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry-"Tractoscope" (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

Functional repeated measures analysis of variance and its application

This paper is inspired by medical studies in which the same patients with multiple sclerosis are examined at several successive visits (doctor’s appointments) and described by fractional anisotropy tract profiles, which can be represented as f unctions. Since the observations for each patient are dependent random processes, they follow a repeated measures design for functional data. To compare the results for different visits, we thus consider functional repeated measures analysis of variance. For this purpose, a pointwise test statistic is constructed by adapting the classical test statistic for one-way repeated measures analysis of variance to the functional data framework. By integrating and taking the supremum of the pointwise test statistic, we create two global test statistics. In addition to verifying the general null hypothesis of the equality of mean functions corresponding to different objects, we also propose a simple method for post hoc analysis. We illustrate the finite sample properties of permutation and bootstrap testing procedures in an extensive simulation study. Finally, we analyze a real data example in detail. All methods are implemented in the R package rmfanova, available on CRAN.

Association between segmental alterations of white matter bundles and cognitive performance in first-episode, treatment-naïve young adults with major depressive disorder

BackgroundCumulative evidence has consistently shown that white matter (WM) disruption is associated with cognitive decline in geriatric depression. However, limited research has been conducted on the correlation between these lesions and cognitive performance in untreated young adults with major depressive disorder (MDD), particularly with the specific segmental alterations of the fibers. MethodDiffusion tensor images were performed on 60 first-episode, treatment-naïve young adult patients with MDD and 54 matched healthy controls (HCs). Automated fiber quantification was applied to calculate the tract profiles of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) to evaluate the WM microstructural organization. Correlation analysis was performed to find the associations between the diffusion properties and cognitive performance. ResultsCompared with HCs, patients with MDD exhibited predominantly different diffusion properties in bilateral uncinate fasciculus (UF), corticospinal tracts (CSTs), left superior longitudinal fasciculus and anterior thalamic radiation. The FA of the temporal cortex portion of right UF was positively correlated with working memory. The MD of the temporal component of left UF was negatively correlated with working memory and positively correlated with symptom severity. Additionally, a positive correlation between the MD of left CST and the psychomotor speed, negative correlation between the MD of left CST and the executive functions and complex attentional processes were observed. ConclusionsOur study validated the alterations in spatial localization of WM microstructure and its correlations with cognitive performance in first-episode, treatment-naïve young adults with MDD. This study added to the knowledge of the neuropathological basis of MDD.

Subtle microstructural alterations in white matter tracts involved in socio-emotional processing after very preterm birth

Children born very preterm (VPT, < 32 weeks of gestation) have an increased risk of developing socio-emotional difficulties. Possible neural substrates for these socio-emotional difficulties are alterations in the structural connectivity of the social brain due to premature birth. The objective of the current study was to study microstructural white matter integrity in VPT versus full-term (FT) born school-aged children along twelve white matter tracts involved in socio-emotional processing. Diffusion MRI scans were obtained from a sample of 35 VPT and 38 FT 8-to-12-year-old children. Tractography was performed using TractSeg, a state-of-the-art neural network-based approach, which offers investigation of detailed tract profiles of fractional anisotropy (FA). Group differences in FA along the tracts were investigated using both a traditional and complementary functional data analysis approach. Exploratory correlations were performed between the Social Responsiveness Scale (SRS-2), a parent-report questionnaire assessing difficulties in social functioning, and FA along the tract. Both analyses showed significant reductions in FA for the VPT group along the middle portion of the right SLF I and an anterior portion of the left SLF II. These group differences possibly indicate altered white matter maturation due to premature birth and may contribute to altered functional connectivity in the Theory of Mind network which has been documented in earlier work with VPT samples. Apart from reduced social motivation in the VPT group, there were no significant group differences in reported social functioning, as assessed by SRS-2. We found that in the VPT group higher FA values in segments of the left SLF I and right SLF II were associated with better social functioning. Surprisingly, the opposite was found for segments in the right IFO, where higher FA values were associated with worse reported social functioning. Since no significant correlations were found for the FT group, this relationship may be specific for VPT children. The current study overcomes methodological limitations of previous studies by more accurately segmenting white matter tracts using constrained spherical deconvolution based tractography, by applying complementary tractometry analysis approaches to estimate changes in FA more accurately, and by investigating the FA profile along the three components of the SLF.

Abnormal white matter along fibers by automated fiber quantification in patients undergoing hemodialysis.

Abnormal white matter has been reported in patients with end-stage renal disease (ESRD). However, few studies have investigated the relationship between specific damage segments and cognition in ESRD. This study aimed to delineate white matter alterations in ESRD and its relationship with cognition. A total of 36 patients undergoing hemodialysis and 25 healthy controls underwent diffusion tensor imaging (DTI) and a series of neuropsychiatric tests. Automated fiber quantification was used to extract distinct DTI indices, and the relationship between the specific segment of the white matter and clinical properties was investigated. Furthermore, a support vector machine was applied to differentiate patients with ESRD from healthy controls. Fractional anisotropy values decreased in multiple fiber bundles, including bilateral thalamic radiata, cingulum cingulate, inferior fronto-occipital fasciculus (IFOF), uncinate, Callosum_Forceps_Major/Callosum_Forceps_Minor (CFMaj/CFMin), and left uncinate from the tract level in patients with ESRD. Specific damaged segments were detected in 8 fiber bundles, including bilateral thalamic radiation, cingulum cingulate, IFOF, CFMin, and left corticospinal tract. Few alterations in these fiber bundles were correlated with cognition impairment and hemoglobin levels. The tract profiles of the left thalamic radiata and left cingulum cingulate could be used to differentiate hemodialysis patients from healthy controls, with an accuracy of 76.9% and 67.6%, respectively. This study revealed white matter damage in hemodialysis patients. This damage occurred in specific segments of the tract, especially in the left thalamic radiata and left cingulum cingulate, which might become a new biomarker for patients with ESRD and cognition impairment.

Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research

Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles 2 (RTP2), a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. RTP2 reads structural MRI data and processes them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice.

Examining The Effects Of Mild Traumatic Brain Injury On Brainstem Integrity

Concussion-related brainstem injuries have received little attention in research, yet concussion-related symptoms, e.g. headache and postural instability, share a common neurological origin within the brainstem. As advanced neuroimaging techniques evolve, so do opportunities to better examine the underlying damage in the brainstem and its related white matter (WM) circuitry following an mTBI. PURPOSE: To examine the brainstem integrity in mTBI patients using advanced neuroimaging techniques. METHODS: T1-weighted and diffiusion-weighted MRI scans were performed on 13 mTBI participants within 14 days of their injuries and 3 individuals without history of brain injury. Diffusion images were acquired using a multishell high-definition fiber tracking sequence. The data were reconstructed using generalized q-sampling imaging, then a deterministic fiber tracking algorithm was applied to generate WM tract profiles indicating the quantitative anisotropy (QA) for the bilateral frontal, parietal, and occipital corticopontine tracts (CPT), the corticospinal tracts (CST), the corticoreticular tracts (CRT), and the middle cerebellar peduncle (MCP). Volumes of the midbrain, pons, medulla oblongata, and superior cerebellar peduncle were determined using Freesurfer v6. A two-sample t-test was used to determine between-group differences in the segmented brainstem structures. One-dimensional statistical parametric mapping was performed to compare WM tracts, and Hedge’s g was calculated to determine between-group effect size.RESULTS: QA values for the first 5% (caudal end) of the left CPT-F was significantly lower in the mTBI group (p = .021). Large effect sizes were found when comparing mTBI to control groups for overall tract QA for the right CPT-O and CPT-F, left and right CPT-P, CST, CRT, and MCP (g > 0.8), with the largest effect for the left CPT-F tract (g = 1.64). There were no significant differences between groups in the segmented brainstem volumes. CONCLUSION: Lower QA values in the caudal portion of the CPT-F indicate that WM near the brainstem may be susceptible to mTBI-related change despite a lack of effect on brainstem volume. Further research should investigate the brainstem after mTBI. Supported by NIH Grant R21 12973518

An urban diet differentially alters the gut microbiome and metabolomic profiles compared with a seed diet in mourning doves.

Urbanization influences food quality and availability for many avian species, with increased access to human refuse and food subsidies in built environments. In relation to such nutritional intakes and their presumed impact on microbes harbored in the intestinal tract and metabolic profiles of host physiological systems, our overall knowledge of the role of gut microbiome (GM) and metabolomic expression in the avian host lags far behind our understanding of mammals. Therefore, the objective of this investigation was to examine the potential differential effect of an urban modeled versus control (i.e., bird seed) diet on the GM, the metabolic profiles of plasma, liver, adipose, kidney, and muscle tissues, and circulating endotoxin and inflammatory factors in urban-caught mourning doves (Zenaida macroura). We hypothesized that the urban diet would differently impact the profiles of the GM and tissue metabolomes and increase plasma lipopolysaccharide (LPS) and proinflammatory factors compared with animals fed a seed diet. After a 4-wk-diet period, contents of the large intestine were sequenced to profile the microbiome, metabolomic analyses were performed on plasma and tissue homogenates, and circulating LPS and inflammatory markers were assessed. The composition of the GM was significantly dissimilar between diets, with greater abundance of Erysipelatoclostridiaceae, Sanguibacteraceae, Oribacterium, and Sanguibacter and decreased circulating LPS in the urban-fed birds. These differences were largely not reflected in the surveyed metabolomes and plasma inflammatory markers. This research supports the notion that the microbial composition in urban doves is impacted by diet, though may only weakly associate with host physiology.

Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract

Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 ± 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.

Tract profiles of the cerebellar peduncles in children who stutter.

Cerebellar-cortical loops comprise critical neural circuitry that supports self-initiated movements and motor adjustments in response to perceived errors, functions that are affected in stuttering. It is unknown whether structural aspects of cerebellar circuitry are affected in stuttering, particularly in children close to symptom onset. Here we examined white matter diffusivity characteristics of the three cerebellar peduncles (CPs) based on diffusion MRI (dMRI) data collected from 41 children who stutter (CWS) and 42 controls in the 3-11years range. We hypothesized that CWS would exhibit decreased fractional anisotropy (FA) in the right CPs given the contralateral connectivity of the cerebellar-cortical loops and past reports of structural differences in left cortical areas in stuttering speakers. Automatic Fiber Quantification (AFQ) was used to track and segment cerebellar white matter pathways and to extract diffusivity measures. We found significant group differences for FA in the right inferior CP (ICP) only: controls showed significantly higher FA in the right ventral ICP compared to CWS, controlling for age, sex, and verbal IQ. Furthermore, FA of right ICP was negatively correlated with stuttering frequency in CWS. These results suggest an early developmental difference in the right ICP for CWS compared to age-matched peers, which may indicate an alteration in error processing, a function previously linked to the ICP. Lower FA here may impact error monitoring and sensory input processing to guide motor corrections. Further longitudinal investigations in children may provide additional insights into how CP development links to stuttering persistence and recovery.

Tractography of supplementary motor area projections in progressive speech apraxia and aphasia

Progressive apraxia of speech (AOS) is a motor speech disorder affecting the ability to produce phonetically or prosodically normal speech. Progressive AOS can present in isolation or co-occur with agrammatic aphasia and is associated with degeneration of the supplementary motor area. We aimed to assess breakdowns in structural connectivity from the supplementary motor area in patients with any combination of progressive AOS and/or agrammatic aphasia to determine which supplementary motor area tracts are specifically related to these clinical symptoms. Eighty-four patients with progressive AOS or progressive agrammatic aphasia were recruited by the Neurodegenerative Research Group and underwent neurological, speech/language, and neuropsychological testing, as well as 3 T diffusion magnetic resonance imaging. Of the 84 patients, 36 had apraxia of speech in isolation (primary progressive apraxia of speech, PPAOS), 40 had apraxia of speech and agrammatic aphasia (AOS-PAA), and eight had agrammatic aphasia in isolation (progressive agrammatic aphasia, PAA). Tractography was performed to identify 5 distinct tracts connecting to the supplementary motor area. Fractional anisotropy and mean diffusivity were assessed at 10 positions along the length of the tracts to construct tract profiles, and median profiles were calculated for each tract. In a case-control comparison, decreased fractional anisotropy and increased mean diffusivity were observed along the supplementary motor area commissural fibers in all three groups compared to controls. PPAOS also had abnormal diffusion in tracts from the supplementary motor area to the putamen, prefrontal cortex, Broca’s area (frontal aslant tract) and motor cortex, with greatest abnormalities observed closest to the supplementary motor area. The AOS-PAA group showed abnormalities in the same set of tracts, but with greater involvement of the supplementary motor area to prefrontal tract compared to PPAOS. PAA showed abnormalities in the left prefrontal and frontal aslant tracts compared to both other groups, with PAA showing greatest abnormalities furthest from the supplementary motor area. Severity of AOS correlated with tract metrics in the supplementary motor area commissural and motor cortex tracts. Severity of aphasia correlated with the frontal aslant and prefrontal tracts. These findings provide insight into how AOS and agrammatism are differentially related to disrupted diffusivity, with progressive AOS associated with abnormalities close to the supplementary motor area, and the frontal aslant and prefrontal tracts being particularly associated with agrammatic aphasia.

The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study

This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes.

Psychoradiological abnormalities in treatment-naive noncomorbid patients with posttraumatic stress disorder.

BackgroundNeuroimaging studies in posttraumatic stress disorder (PTSD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these are localized to specific regions of fiber tracts, and what diagnostic value they might have. This study set out to explore the spatial profile of WM abnormalities along defined fiber tracts in PTSD.MethodsDiffusion tensor images were obtained from 77 treatment‐naive noncomorbid patients with PTSD and 76 demographically matched trauma‐exposed non‐PTSD (TENP) controls. Using automated fiber quantification, tract profiles of fractional anisotropy, axial diffusivity, mean diffusivity, and radial diffusivity were calculated to evaluate WM microstructural organization. Results were analyzed by pointwise comparisons, by correlation with symptom severity, and for diagnosis‐by‐sex interactions. Support vector machine analyses assessed the ability of tract profiles to discriminate PTSD from TENP.ResultsCompared to TENP, PTSD showed lower fractional anisotropy accompanied by higher radial diffusivity and mean diffusivity in the left uncinate fasciculus, and lower fractional anisotropy accompanied by higher radial diffusivity in the right anterior thalamic radiation. Tract profile alterations were correlated with symptom severity, suggesting a pathophysiological relevance. There were no significant differences in diagnosis‐by‐sex interaction. Tract profiles allowed individual classification of PTSD versus TENP with significant accuracy, of potential diagnostic utility.ConclusionsThese findings add to the knowledge of the neuropathological basis of PTSD. WM alterations based on a tract‐profile quantification approach are a potential biomarker for PTSD.

Toward Developing Robust Myotonic Dystrophy Brain Biomarkers using White Matter Tract Profiles Sub-Band Energy and A Framework of Ensemble Predictive Learning.

The myotonic dystrophies (DM1 and DM2) are dominantly inherited disorders that cause pathological changes throughout the body and the brain. DM patients have difficulties with memory, attention, executive functioning, social cognition, and visuospatial function. Quantifying and understanding diffusion measures along main brain white matter fiber tracts offer a unique opportunity to reveal new insights into DM development and characterization. In this work, a novel supervised system is proposed, which is based on Tract Profiles sub-band energy information. The proposed system utilizes a Bayesian stacked random forest to diagnose, characterize, and predict DM clinical outcomes. The evaluation data consists of fractional anisotropies calculated for twelve major white matter tracts of 96 healthy controls and 62 DM patients. The proposed system discriminates DM vs. control with 86% accuracy, which is significantly higher than previous works. Additionally, it discovered DM brain biomarkers that are accurate and robust and will be helpful in planning clinical trials and monitoring clinical performance.

Alterations in white matter integrity and asymmetry in patients with benign childhood epilepsy with centrotemporal spikes and childhood absence epilepsy: An automated fiber quantification tractography study

PurposeTo investigate whether patients with benign childhood epilepsy with centrotemporal spikes (BECTS) and childhood absence epilepsy (CAE) show distinct patterns of white matter (WM) alterations and structural asymmetry compared with healthy controls and the relationship between WM alterations and epilepsy-related clinical variables. MethodsWe used automated fiber quantification to create tract profiles of fractional anisotropy (FA) and mean diffusivity (MD) in twenty-six patients with BECTS, twenty-nine patients with CAE, and twenty-four healthy controls. Group differences in FA and MD were quantified at 100 equidistant nodes along the fiber tract and these alterations and epilepsy-related clinical variables were correlated. A lateralization index (LI) representing the structural asymmetry of the fiber tract was computed and compared between both patient groups and controls. ResultsCompared with healthy controls, the BECTS group showed widespread FA reduction in 43.75% (7/16) and MD elevation in 50% (8/16) of identified fiber tracts, and the CAE group showed regional FA reduction in 31.25% (5/16) and MD elevation in 25% (4/16) of identified fiber tracts. In the BECTS group, FA and MD in the right anterior thalamic radiation positively and negatively correlated with the number of antiepileptic drugs, respectively, and MD in the right arcuate fasciculus (AF) positively correlated with seizure frequency. In the CAE group, the LI values were significantly lower in the inferior fronto-occipital fasciculus and the AF. ConclusionThe two childhood epilepsy syndromes display different patterns of WM alterations and structural asymmetry, suggesting that neuroanatomical differences may underlie the different profiles of BECTS and CAE.

Oral-Gut Microbiome Axis in Gastrointestinal Disease and Cancer.

Simple SummaryMicrobiota dysbiosis is correlated with numerous diseases in the human body. To date, the research on the microbiome-associated diseases been focused on an organ-specific microbiome. However, the interorgan microbial network is emerging as an important regulator in physiological functions and pathological processes. The oral cavity and gut are the two largest microbial ecosystems. Recent studies have demonstrated that the oral-to-gut and gut-to-oral microbial transmission can regulate pathogenesis, indicating the presence of the oral–gut microbiome axis. Here, we will review the role of the oral–gut microbiome axis in gastrointestinal disease and cancer, which may provide insight for precise diagnosis/prognosis and effective treatment.It is well-known that microbiota dysbiosis is closely associated with numerous diseases in the human body. The oral cavity and gut are the two largest microbial habitats, playing a major role in microbiome-associated diseases. Even though the oral cavity and gut are continuous regions connected through the gastrointestinal tract, the oral and gut microbiome profiles are well-segregated due to the oral–gut barrier. However, the oral microbiota can translocate to the intestinal mucosa in conditions of the oral–gut barrier dysfunction. Inversely, the gut-to-oral microbial transmission occurs as well in inter- and intrapersonal manners. Recently, it has been reported that oral and gut microbiomes interdependently regulate physiological functions and pathological processes. Oral-to-gut and gut-to-oral microbial transmissions can shape and/or reshape the microbial ecosystem in both habitats, eventually modulating pathogenesis of disease. However, the oral–gut microbial interaction in pathogenesis has been underappreciated to date. Here, we will highlight the oral–gut microbiome crosstalk and its implications in the pathogenesis of the gastrointestinal disease and cancer. Better understanding the role of the oral–gut microbiome axis in pathogenesis will be advantageous for precise diagnosis/prognosis and effective treatment.

Oral–Gut Microbiome Axis in Gastrointestinal Disease and Cancer

It is well-known that microbiota dysbiosis is closely associated with numerous diseases in the human body. The oral cavity and gut are the two largest microbial habitats, playing a major role in microbiome-associated diseases. Even though the oral cavity and gut are continuous regions connected through the gastrointestinal tract, the oral and gut microbiome profiles are well-segregated due to the oral–gut barrier. However, the oral microbiota can translocate to the intestinal mucosa in conditions of the oral–gut barrier dysfunction. Inversely, the gut-to-oral microbial transmission occurs as well in inter- and intrapersonal manners. Recently, it has been reported that oral and gut microbiomes interdependently regulate physiological functions and pathological processes. Oral-to-gut and gut-to-oral microbial transmissions can shape and/or reshape the microbial ecosystem in both habitats, eventually modulating pathogenesis of disease. However, the oral–gut microbial interaction in pathogenesis has been underappreciated to date. Here, we will highlight the oral–gut microbiome crosstalk and its implications in the pathogenesis of the gastrointestinal disease and cancer. Better understanding the role of the oral–gut microbiome axis in pathogenesis will be advantageous for precise diagnosis/prognosis and effective treatment.

Aeroacoustic differences between the Japanese fricatives [ɕ] and [ç

To elucidate the linguistic similarity between the alveolo-palatal sibilant [ɕ] and palatal non-sibilant [ç] in Japanese, the aeroacoustic differences between the two consonants were explored via experimentation with participants and analysis using simplified vocal tract models. The real-time magnetic resonance imaging (rtMRI) observations of articulatory movements demonstrated that some speakers use a nearly identical place of articulation for /si/ [ɕi] and /hi/ [çi]. Simplified vocal tract models were then constructed based on the data captured by static MRI, and the model-generated synthetic sounds were compared with speaker data producing [ɕ] and [ç]. Speaker data demonstrated that the amplitude of the broadband noise of [ç] was weaker than that of [ɕ]; the characteristic peak amplitude at approximately 4 kHz was greater in [ç] than in [ɕ], although the mid-sagittal vocal tract profiles were nearly identical for three of ten subjects in the rtMRI observation. These acoustic differences were reproduced by the proposed models, with differences in the width of the coronal plane constriction and the flow rate. The results suggest the need to include constriction width and flow rate as parameters for articulatory phonetic descriptions of speech sounds.