ObjectiveNeuroimaging evidence suggested that the thalamic nuclei may play different roles in the progress of idiopathic generalized epilepsy (IGE). This study aimed to demonstrate the alterations in morphometry and functional connectivity in the thalamic nuclei in IGE.MethodsFifty-two patients with IGE characterized by generalized tonic-clonic seizures and 67 healthy controls were involved in the study. The three-dimensional high-resolution T1-weighted MRI data were acquired for voxel-based morphometry (VBM) analysis, and resting-state blood-oxygenation level functional MRI data were acquired for functional connectivity analysis. The thalamic nuclei of bilateral medial dorsal nucleus (MDN) and pulvinar, as detected with decreased gray matter volumes in patients with IGE through VBM analysis, were selected as seed regions for functional connectivity analysis.ResultsDifferent alteration patterns were found in functional connectivity of the thalamic nuclei with decreased gray matter volumes in IGE. Seeding at the MDN, decreased connectivity in the bilateral orbital frontal cortex, caudate nucleus, putamen and amygdala were found in the patients (P<0.05 with correction). However, seeding at the pulvinar, no significant alteration of functional connectivity was found in the patients (P<0.05 with correction).ConclusionsSome specific impairment of thalamic nuclei in IGE was identified using morphological and functional connectivity MRI approaches. These findings may strongly support the different involvement of the thalamocortical networks in IGE.

BackgroundCarotid atherosclerotic plaque rupture is an important source of ischemic stroke. However, the prevalence of high‐risk plaque (HRP) defined as plaques with luminal surface disruption, a lipid‐rich necrotic core occupying >40% of the wall, or intraplaque hemorrhage in Chinese population remains unclear. This study uses carotid magnetic resonance imaging (CMRI) to investigate HRP prevalence in carotid arteries of Chinese patients with cerebrovascular symptoms.Methods and ResultsPatients with cerebral ischemic symptoms in the anterior circulation within 2 weeks and carotid plaque determined by ultrasound were recruited and underwent CMRI. The HRP features were identified and compared between symptomatic and asymptomatic arteries. Receiver‐operating‐characteristic analysis was used to calculate area‐under‐the‐curve (AUC) of stenosis and maximum wall thickness for discriminating presence of HRP. In 1047 recruited subjects, HRP detected by CMRI was nearly 1.5 times more prevalent than severe stenosis (≥50%) in this cohort (28% versus 19%, P<0.0001). Approximately two thirds of HRPs were found in arteries with <50% stenosis. The prevalence of HRP in symptomatic carotid arteries was significantly higher than that of the contralateral asymptomatic carotid arteries (23.0% versus 16.4%, P=0.001). Maximum wall thickness was found to be a stronger discriminator than stenosis for HRP (AUC: 0.93 versus 0.81, P<0.0001).ConclusionsThere are significantly more high‐risk carotid plaques than carotid arteries with ≥50% stenosis in symptomatic Chinese patients. A substantial number of HRPs were found in arteries with lower grade stenosis and maximum wall thickness was a stronger indicator for HRP than luminal stenosis.Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT02017756.

Mounting evidence has shown that periodontitis is associated with diabetes. However, a causal relationship remains to be determined. Recent studies reported that periodontitis may be associated with gut microbiota, which plays an important role in the development of diabetes. Therefore, we hypothesized that gut microbiota might mediate the link between periodontitis and diabetes. Periodontitis was induced by ligatures. Glycemic homeostasis was evaluated through fasting blood glucose (FBG), serum glycosylated hemoglobin (HbA1c), and intraperitoneal glucose tolerance test. Micro–computed tomography and hematoxylin and eosin staining were used to evaluate periodontal destruction. The gut microbiota was analyzed using 16S ribosomal RNA gene sequencing and bioinformatics. Serum endotoxin, interleukin (IL) 6, tumor necrosis factor α (TNF-α), and IL-1β were measured to evaluate the systemic inflammation burden. We found that the levels of FBG, HbA1c, and glucose intolerance were higher in the periodontitis (PD) group than in the control (Con) group ( P < 0.05). When periodontitis was eliminated, the FBG significantly decreased ( P < 0.05). Several butyrate-producing bacteria were decreased in the gut microbiota of the PD group, including Lachnospiraceae_NK4A136_group, Eubacterium_fissicatena_group, Eubacterium_coprostanoligenes_group, and Ruminococcaceae_UCG-014 ( P < 0.05), which were negatively correlated with serum HbA1c ( P < 0.05). Subsequently, the gut microbiota was depleted using antibiotics or transplanted through cohousing. Compared with the PD group, the levels of HbA1c and glucose intolerance were decreased in the gut microbiota-depleted mice with periodontitis (PD + Abx) ( P < 0.05), as well as the serum levels of endotoxin and IL-6 ( P < 0.05). The serum levels of IL-6, TNF-α, and IL-1β in the PD + Abx group were higher than those of the Con group ( P < 0.05). Antibiotics exerted a limited impact on the periodontal microbiota. When the PD mice were cohoused with healthy ones, the elevated FBG and HbA1c significantly recovered ( P < 0.05), as well as the aforementioned butyrate producers ( P < 0.05). Thus, within the limitations of this study, our data indicated that the gut microbiota may mediate the influence of periodontitis on prediabetes.

Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) have overlapping symptoms, and accurate differential diagnosis is important for targeted intervention and treatment. Previous studies suggest that the deep learning (DL) techniques have the potential to solve the differential diagnosis problem of FTD, AD and normal controls (NCs), but its performance is still unclear. In addition, existing DL-assisted diagnostic studies still rely on hypothesis-based expert-level preprocessing. On the one hand, it imposes high requirements on clinicians and data themselves; On the other hand, it hinders the backtracking of classification results to the original image data, resulting in the classification results cannot be interpreted intuitively. In the current study, a large cohort of 3D T1-weighted structural magnetic resonance imaging (MRI) volumes (n = 4,099) was collected from two publicly available databases, i.e., the ADNI and the NIFD. We trained a DL-based network directly based on raw T1 images to classify FTD, AD and corresponding NCs. And we evaluated the convergence speed, differential diagnosis ability, robustness and generalizability under nine scenarios. The proposed network yielded an accuracy of 91.83% based on the most common T1-weighted sequence [magnetization-prepared rapid acquisition with gradient echo (MPRAGE)]. The knowledge learned by the DL network through multiple classification tasks can also be used to solve subproblems, and the knowledge is generalizable and not limited to a specified dataset. Furthermore, we applied a gradient visualization algorithm based on guided backpropagation to calculate the contribution graph, which tells us intuitively why the DL-based networks make each decision. The regions making valuable contributions to FTD were more widespread in the right frontal white matter regions, while the left temporal, bilateral inferior frontal and parahippocampal regions were contributors to the classification of AD. Our results demonstrated that DL-based networks have the ability to solve the enigma of differential diagnosis of diseases without any hypothesis-based preprocessing. Moreover, they may mine the potential patterns that may be different from human clinicians, which may provide new insight into the understanding of FTD and AD.

The purpose of this study is to investigate the characteristics of intracranial vessel wall enhancement and its relationship with ischemic infarction in patients with Moyamoya vasculopathy (MMV). Forty-seven patients with MMV confirmed by angiography were enrolled in this study. The vessel wall enhancement of the distal internal carotid artery, anterior cerebral artery and middle cerebral artery was classified into eccentric and concentric patterns, as well as divided into three grades: grade 0, grade 1 and grade 2. The relationship between ischemic infarction and vessel wall enhancement was also determined. Fifty-six enhanced lesions were found in patients with (n = 25) and without acute infarction (n = 22). The incidence of lesions with grade 2 enhancement in patients with acute infarction was greater than that in those without acute infarction (p = 0.011). In addition, grade 2 enhancement of the intracranial vessel wall was significantly associated with acute ischemic infarction (Odds ratio, 26.7; 95% confidence interval: 2.8–258.2; p = 0.005). Higher-grade enhancement of the intracranial vessel wall is independently associated with acute ischemic infarction in patients with MMV. The characteristics of intracranial vessel wall enhancement may serve as a marker of its stability and provide important insight into ischemic stroke risk factors.

We report a highly asymmetric magnetoresistance (MR) bias dependence, with the inverse MR peaking at a negative bias and a sign reversal occurring at a positive bias in prototypical La 0.7 Sr 0.3 MnO 3 (LSMO)/Alq 3 /Co organic spin valve (OSV) with a tunnel barrier between LSMO and Alq 3 . This behavior is in strong contrast with the commonly found inverse MR in entire bias range for LSMO/Alq 3 /Co OSVs. The MR bias voltage dependence is independent on the type of the tunnel barrier, either SrTiO 3 or Al 2 O 3 . Together with first-principle calculations, we demonstrate that the strongly hybridized Co d-states with Alq 3 molecules at the interface are responsible for the efficient d-states spin injection and the observed MR bias dependence is originated from the energy dependent density of states of Co d-states. These findings open up new possibilities to engineer interfacial bonding between ferromagnetic materials and a wide variety of molecule selections for the desired spin transport properties.

Background To determine the usefulness of the size of carotid artery intraplaque hemorrhage (IPH) in discriminating the risk of acute ischemic stroke using cardiovascular magnetic resonance (CMR) vessel wall imaging. Methods Symptomatic patients with carotid atherosclerotic plaque who participated in a cross-sectional, multicenter study of CARE-II (NCT02017756) were included. All patients underwent carotid and brain CMR imaging. Carotid plaque burden and the size of plaque compositions including calcification, lipid-rich necrotic core (LRNC), and IPH were measured. Presence of acute cerebral infarct (ACI) in ipsilateral hemisphere of carotid plaque was determined. The relationship between carotid plaque features and presence of ipsilateral ACI was then analyzed. Results Of 687 recruited patients (62.7 ± 10.1 years; 69.4% males) with carotid plaque, 28.5% had ACI in ipsilateral hemispheres. Logistic regression revealed that carotid plaque burden was significantly associated with the presence of ACI before and after adjusted for clinical confounding factors. The volume of LRNC, %LRNC volume, volume of IPH, and %IPH volume were significantly associated with ACI before (volume of LRNC: OR = 1.297, p = 0.005; %LRNC volume: OR = 1.119, p = 0.018; volume of IPH: OR = 2.514, p = 0.003; %IPH volume: OR = 2.202, p = 0.003) and after (volume of LRNC: OR = 1.312, p = 0.006; %LRNC volume: OR = 1.90, p = 0.034; volume of IPH: OR = 2.907, p = 0.007; % IPH volume: OR = 2.374, p = 0.004) adjusted for clinical confounding factors. The association between volume of IPH and ACI remained statistically significant after further adjusted for plaque volume (OR = 2.813, p = 0.016) or both plaque volume and volume of LRNC (OR = 4.044, p = 0.024). Conclusions In symptomatic patients with carotid atherosclerotic plaques, the size of IPH is independently associated with ipsilateral ACI, suggesting the size of IPH might be a useful indicator for the risk of ACI. Trial registration Clinical Trial Registration-URL: http://www.clinicaltrials.gov . Unique Identifier: NCT02017756.

The structural covariance network (SCN) has provided a perspective on the largescale brain organization impairment in the Alzheimer's Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1-weighted structural magnetic resonance images of the subjects.Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/ posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.