Explore the vast range of titles available.

Accurate estimates of the BOLD hemodynamic response function (HRF) are crucial for the interpretation and analysis of event-related functional MRI data. To date, however, there have been no comprehensive measurements of the HRF in white matter (WM) despite increasing evidence that BOLD signals in WM change after a stimulus. We performed an event-related cognitive task (Stroop color-word interference) to measure the HRF in selected human WM pathways. The task was chosen in order to produce robust, distributed centers of activity throughout the cortex. To measure the HRF in WM, fiber tracts were reconstructed between each pair of activated cortical areas. We observed clear task-specific HRFs with reduced magnitudes, delayed onsets and prolonged initial dips in WM tracts compared with activated grey matter, thus calling for significant changes to current standard models for accurately characterizing the HRFs in WM and for modifications of standard methods of analysis of functional imaging data. The hemodynamic response function (HRF) describes how changes in brain activity manifest as a transient signal (BOLD) that is detected by fMRI imaging. Here, the authors show that the HRF in white matter shows reduced magnitudes, delayed onsets, and prolonged initial dips compared to the grey matter HRF.

The topological characteristics of functional networks, derived from measurements of resting-state connectivity in gray matter (GM), are associated with individual cognitive abilities or specific dysfunctions. However, blood oxygen level-dependent (BOLD) signals in white matter (WM) are usually ignored or even regressed out as nuisance factors in the data analyses that underlie network models. Recent studies have demonstrated reliable detection of WM BOLD signals and imply these reflect associated neural activities. Here we evaluate quantitatively the contributions of individual WM voxels to the identification of functional networks, which we term their engagement (or conceptually, their importance). We quantify the engagement by measuring the reductions of connectivity, produced by ignoring the signal fluctuations within each WM voxel, with respect to both the entire network (global) or a single GM node (local). We observed highly reproducible spatial distributions of global engagement maps, as well as a trend toward increased relevance of deep WM voxels at delayed times. Local engagement maps exhibit homogeneous spatial distributions with respect to internal nodes that constitute a well-recognized sub-functional network, but inhomogeneous distributions with respect to other nodes. WM voxels show distinct distributions of engagement depending on their anatomical locations. These findings demonstrate the important role of WM in network modeling, thus supporting the need for changes of conventional views that WM signal variations represent only physiological noise. •Contributions of WM BOLD signals to brain functional networks are evaluated.•Spatial distributions of WM engagement maps are found to be highly reproducible.•A trend toward increased engagement of deep WM at delayed times is observed.•WM voxels exhibit region-dependent distributions of engagement.

Background Endothelial-to-Mesenchymal Transformation (EndMT) plays key roles in endothelial dysfunction during the pathological progression of atherosclerosis; however, its detailed mechanism remains unclear. Herein, we explored the biological function and mechanisms of upstream stimulating factor 1 (USF1) in EndMT during atherosclerosis. Methods The in vivo and in vitro atherosclerotic models were established in high fat diet-fed ApoE −/− mice and ox-LDL-exposed human umbilical vein endothelial cells (HUVECs). The plaque formation, collagen and lipid deposition, and morphological changes in the aortic tissues were evaluated by hematoxylin and eosin (HE), Masson, Oil red O and Verhoeff-Van Gieson (EVG) staining, respectively. EndMT was determined by expression levels of EndMT-related proteins. Target molecule expression was detected by RT-qPCR and Western blotting. The release of pro-inflammatory cytokines was measured by ELISA. Migration of HUVECs was detected by transwell and scratch assays. Molecular mechanism was investigated by dual-luciferase reporter assay, ChIP, and Co-IP assays. Results USF1 was up-regulated in atherosclerosis patients. USF1 knockdown inhibited EndMT by up-regulating CD31 and VE-Cadherin, while down-regulating α-SMA and vimentin, thereby repressing inflammation, and migration in ox-LDL-exposed HUVECs. In addition, USF1 transcriptionally activated ubiquitin-specific protease 14 (USP14), which promoted de-ubiquitination and up-regulation of NLR Family CARD Domain Containing 5 (NLRC5) and subsequent Smad2/3 pathway activation. The inhibitory effect of sh-USF1 or sh-USP14 on EndMT was partly reversed by USP14 or NLRC5 overexpression. Finally, USF1 knockdown delayed atherosclerosis progression via inhibiting EndMT in mice. Conclusion Our findings indicate the contribution of the USF1/USP14/NLRC5 axis to atherosclerosis development via promoting EndMT, which provide effective therapeutic targets.

•Auditory GABA levels and auditory network (AN)-DMN FC decreased in presbycusis.•Auditory GABA levels and AN-DMN FC mediated the cognitive-ear link in presbycusis.•Hearing loss may drive cognitive-ear link reorganization via decreased GABA levels. Recent studies suggest that the interaction between presbycusis and cognitive impairment may be partially explained by the cognitive-ear link. However, the underlying neurophysiological mechanisms remain largely unknown. In this study, we combined magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (fMRI) to investigate auditory gamma-aminobutyric acid (GABA) and glutamate (Glu) levels, intra- and inter-network functional connectivity, and their relationships with auditory and cognitive function in 51 presbycusis patients and 51 well-matched healthy controls. Our results confirmed reorganization of the cognitive-ear link in presbycusis, including decreased auditory GABA and Glu levels and aberrant functional connectivity involving auditory networks (AN) and cognitive-related networks, which were associated with reduced speech perception or cognitive impairment. Moreover, mediation analyses revealed that decreased auditory GABA levels and dysconnectivity between the AN and default mode network (DMN) mediated the association between hearing loss and impaired information processing speed in presbycusis. These findings highlight the importance of AN-DMN dysconnectivity in cognitive-ear link reorganization leading to cognitive impairment, and hearing loss may drive reorganization via decreased auditory GABA levels. Modulation of GABA neurotransmission may lead to new treatment strategies for cognitive impairment in presbycusis patients.

In response to a flickering visual stimulus, the BOLD response in primary visual cortex varies with the flickering frequency and is maximal when it is close to 8Hz. In previous studies we demonstrated that BOLD signals in specific white matter (WM) pathways covary with the alternations between stimulus conditions in a block design in similar manner to gray matter (GM) regions. Here we investigated whether WM tracts show varying responses to changes in flicker frequency and are modulated in the same manner as cortical areas. We used a Fourier analysis of BOLD signals to measure the signal amplitude and phase at the fundamental frequency of a block-design task in which flickering visual stimuli alternated with blank presentations, avoiding the assumption of any specific hemodynamic response function. The BOLD responses in WM pathways and the primary visual cortex were evaluated for flicker frequencies varying between 2 and 14Hz. The variations with frequency of BOLD signals in specific WM tracts followed closely those in primary visual cortex, suggesting that variations in cortical activation are directly coupled to corresponding BOLD signals in connected WM tracts. Statistically significant differences in the timings of BOLD responses were also measured between visual cortex and specific WM bundles. These results confirm that when cortical BOLD responses are modulated by selecting different task parameters, relevant WM tracts exhibit corresponding BOLD signals that are also affected.

In vivo functional changes in white matter during the progression of Alzheimer's disease (AD) have not been previously reported. Our objectives are to measure changes in white matter functional connectivity (FC) in an elderly population undergoing cognitive decline as AD develops, to establish their relationship to neuropsychological scores of cognitive abilities, and to assess the performance in prediction of AD using white matter FC measures as features. Analyses were conducted using resting state functional MRI and neuropsychological data from 383 ADNI participants, including 136 cognitive normal (CN) controls, 46 with significant memory concern, 83 with early mild cognitive impairment (MCI), 37 with MCI, 46 with late MCI, and 35 with AD dementia. FC metrics between segregated white matter tracts and discrete gray matter volumes or between white matter tracts were quantitatively analyzed and characterized, along with their relationships to 6 cognitive measures. Finally, supervised machine learning was implemented on white matter FCs to classify the participants and performance of the classification was evaluated. Significant decreases in FC measures were found in white matter with prominent, specific, regional deficits appearing in late MCI and AD dementia patients from CN. These changes significantly correlated with neuropsychological measurements of impairments in cognition and memory. The sensitivity and specificity of distinguishing AD dementia and CN using white matter FCs were 0.83 and 0.81 respectively. The white matter FC decreased in late MCI and AD dementia patients compared to CN participants, and this decrease was correlated with cognitive measures. White matter FC is valuable in the prediction of AD. All these findings suggest that white matter FC may be a promising avenue for understanding functional impairments in white matter tracts during AD progression.

Gamma-aminobutyric acid (GABA) is the primary inhibitory neurotransmitter in the brain. Although measurements of GABA levels in vivo in the human brain using edited proton magnetic resonance spectroscopy (1H-MRS) have been established for some time, it is has not been established how regional GABA levels vary with age in the normal human brain. In this study, 49 healthy men and 51 healthy women aged between 20 and 76years were recruited and J-difference edited spectra were recorded at 3T to determine the effect of age on GABA levels, and to investigate whether there are regional and gender differences in GABA in mesial frontal and parietal regions. Because the signal detected at 3.02ppm using these experimental parameters is also expected to contain contributions from both macromolecules (MM) and homocarnosine, in this study the signal is labeled GABA+ rather than GABA. Significant negative correlations were observed between age and GABA+ in both regions studied (GABA+/Cr: frontal region, r=−0.68, p<0.001, parietal region, r=−0.54, p<0.001; GABA+/NAA: frontal region, r=−0.58, p<0.001, parietal region, r=−0.49, p<0.001). The decrease in GABA+ with age in the frontal region was more rapid in women than men. Evidence of a measureable decline in GABA is important in considering the neurochemical basis of the cognitive decline that is associated with normal aging. •Levels of the brain GABA are shown to reduce with age throughout adulthood.•This decline is more rapid in the frontal region of female than male subjects.•Edited MR spectroscopy of GABA was applied in a large cohort of 100subjects.

Abstract Background: Limited data are available on the changes in the quality of care for ST elevation myocardial infarction (STEMI) during China's health system reform from 2009 to 2020. This study aimed to assess the changes in care processes and outcome for STEMI patients in Henan province of central China between 2011 and 2018. Methods: We compared the data from the Henan STEMI survey conducted in 2011-2012 (n = 1548, a cross-sectional study) and the Henan STEMI registry in 2016-2018 (n = 4748, a multicenter, prospective observational study). Changes in care processes and in-hospital mortality were determined. Process of care measures included reperfusion therapies, aspirin, P2Y12 antagonists, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and statins. Therapy use was analyzed among patients who were considered ideal candidates for treatment. Results: STEMI patients in 2016-2018 were younger (median age: 63.1 vs. 63.8 years) with a lower proportion of women (24.4% [1156/4748] vs. 28.2% [437/1548]) than in 2011-2012. The composite use rate for guideline-recommended treatments increased significantly from 2011 to 2018 (60.9% [5424/8901] vs. 82.7% [22,439/27,129], P <0.001). The proportion of patients treated by reperfusion within 12 h increased from 44.1% (546/1237) to 78.4% (2698/3440) (P <0.001) with a prolonged median onset-to-first medical contact time (from 144 min to 210 min, P <0.001). The use of antiplatelet agents, statins, and β-blockers increased significantly. The risk of in-hospital mortality significantly decreased over time (6.1% [95/1548] vs. 4.2% [198/4748], odds ratio [OR]: 0.67, 95% confidence interval [CI]: 0.50-0.88, P = 0.005) after adjustment. Conclusions: Gradual implementation of the guideline-recommended treatments in STEMI patients from 2011 to 2018 has been associated with decreased in-hospital mortality. However, gaps persist between clinical practice and guideline recommendation. Public awareness, reperfusion strategies, and construction of chest pain centers need to be further underscored in central China.

•Integrated functional and structural MRI maps white matter engagement.•White matter engagement correlates with other functional and structural properties.•Significant gender differences were found in white matter engagement.•Distribution of white matter engagement varies over time.•White matter engagement shows promise as a biomarker for neurological conditions. Current models of brain networks may potentially be improved by integrating our knowledge of structural connections, within and between circuits, with metrics of functional interactions between network nodes. The former may be obtained from diffusion MRI of white matter (WM), while the latter may be derived by measuring correlations between resting state BOLD signals from pairs of gray matter (GM) regions. From inspection of diffusion MRI data, it is clear that each WM voxel within a 3D image array may be traversed by multiple WM structural tracts, each of which connects a pair of GM nodes. We hypothesized that by appropriately weighting and then integrating the functional connectivity of each such connected pair, the overall engagement of any WM voxel in brain functions could be evaluated. This model introduces a structural constraint to earlier studies of WM engagement and addresses some limitations of previous efforts to relate structure and function. Using concepts derived from graph theory, we obtained spatial maps of WM engagement which highlight WM regions critical for efficient communications across the brain. The distributions of WM engagement are highly reproducible across subjects and depict a notable interdependence between the distribution of GM activities and the detailed organization of WM. Additionally, we provide evidence that the engagement varies over time and shows significant differences between genders. These findings suggest the potential of WM engagement as a measure of the integrity of normal brain functions and as a biomarker for neurological and cognitive disorders.

Functional magnetic resonance imaging studies have traditionally focused on gray matter, overlooking white matter despite growing evidence that functional blood oxygenation-level dependent effects also occur there. In particular, functional coupling across the gray-white matter boundary, an interface between local and global processing, remains poorly understood. This study introduces two metrics: gray-white matter functional connectivity, which captures temporal synchrony across the boundary, and gray-white blood oxygenation-level dependent power ratio, which reflects differences in signal amplitude. Gray-white matter functional connectivity aligns with patterns of myelination, long-range connectivity, and sensorimotor organization, suggesting efficient signal transmission. In contrast, the power ratio shows an inverse pattern, with higher values in higher-order regions, possibly reflecting increased metabolic demands in white matter. It also increases with age (8 to 21 years), suggesting developmental shifts in energetic demands. Together, these metrics highlight distinct yet complementary roles of signal fidelity and energy modulation at the gray-white matter boundary. This study introduces two new measures of brain function at the gray–white matter boundary, revealing distinct patterns of signal transmission and metabolic activity that deepen our understanding of brain organization and development.