Disrupted Functional Connectivity of the Amygdala Predicts the Efficacy of Non-steroidal Anti-inflammatory Drugs in Migraineurs Without Aura.

Machine learning (ML) has been largely applied for predicting migraine classification. However, the prediction of efficacy of non-steroidal anti-inflammatory drugs (NSAIDs) in migraine is still in the early stages. This study aims to evaluate whether the combination of machine learning and amygdala-related functional features could help predict the efficacy of NSAIDs in patients with migraine without aura (MwoA). A total of 70 MwoA patients were enrolled for the study, including patients with an effective response to NSAIDs (M-eNSAIDs, n = 35) and MwoA patients with ineffective response to NSAIDs (M-ieNSAIDs, n = 35). Furthermore, 33 healthy controls (HCs) were matched for age, sex, and education level. The study participants were subjected to resting-state functional magnetic resonance imaging (fMRI) scanning. Disrupted functional connectivity (FC) patterns from amygdala-based FC analysis and clinical characteristics were considered features that could promote classification through multivariable logistic regression (MLR) and support vector machine (SVM) for predicting the efficacy of NSAIDs. Further, receiver operating characteristic (ROC) curves were drawn to evaluate the predictive ability of the models. The M-eNSAIDs group exhibited enhanced FC with ipsilateral calcarine sulcus (CAL), superior parietal gyrus (SPG), paracentral lobule (PCL), and contralateral superior frontal gyrus (SFG) in the left amygdala. However, the M-eNSAIDs group showed decreased FC with ipsilateral caudate nucleus (CAU), compared to the M-ieNSAIDs group. Moreover, the M-eNSAIDs group showed higher FC with left pre-central gyrus (PreCG) and post-central gyrus (PoCG) compared to HCs. In contrast, the M-ieNSAIDs group showed lower FC with the left anterior cingulate cortex (ACC) and right SFG. Furthermore, the MwoA patients showed increased FC with the left middle frontal gyrus (MFG) in the right amygdala compared to HCs. The disrupted left amygdala-related FC patterns exhibited significant correlations with migraine characteristics in the M-ieNSAIDs group. The MLR and SVM models discriminated clinical efficacy of NSAIDs with an area under the curve (AUC) of 0.891 and 0.896, sensitivity of 0.971 and 0.833, and specificity of 0.629 and 0.875, respectively. These findings suggest that the efficacy of NSAIDs in migraine could be predicted using ML algorithm. Furthermore, this study highlights the role of amygdala-related neural function in revealing underlying migraine-related neuroimaging mechanisms.

Comparative Study between ZOOMit and Conventional Intravoxel Incoherent Motion MRI for Assessing Parotid Gland Abnormalities in Patients with Early- or Mid-Stage Sjögren's Syndrome.

OBJECTIVE: To compare the reproducibility and performance of quantitative metrics between ZOOMit and conventional intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the diagnosis of early- and mid-stage Sjögren's syndrome (SS). MATERIALS AND METHODS: Twenty-two patients (mean age ± standard deviation, 52.0 ± 10.8 years; male:female, 2:20) with early- or mid-stage SS and 20 healthy controls (46.9 ± 14.6 years; male:female, 7:13) were prospectively enrolled in our study. ZOOMit IVIM and conventional IVIM MRI were performed simultaneously in all individuals using a 3T scanner. Quantitative IVIM parameters - including tissue diffusivity (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) - inter- and intra-observer reproducibility in measuring these parameters, and their ability to distinguish patients with SS from healthy individuals were assessed and compared between ZOOMit IVIM and conventional IVIM methods, appropriately. MR gland nodular grade (MRG) was also examined. RESULTS: Inter- and intra-observer reproducibility was better with ZOOMit imaging than with conventional IVIM imaging (ZOOMit vs. conventional, intraclass correlation coefficient of 0.897-0.941 vs. 0.667-0.782 for inter-observer reproducibility and 0.891-0.968 vs. 0.814-0.853 for intra-observer reproducibility). Significant differences in ZOOMit f, ZOOMit D*, conventional D*, and MRG between patients with SS and healthy individuals (all p < 0.05) were observed. ZOOMit D* outperformed conventional D* in diagnosing early- and mid-stage SS (area under receiver operating curve, 0.867 and 0.658, respectively; p = 0.002). The combination of ZOOMit D*, MRG, and ZOOMit f as a new diagnostic index for SS, increased diagnostic area under the curve to 0.961, which was higher than that of any single parameter (all p < 0.01). CONCLUSION: Considering its better reproducibility and performance, ZOOMit IVIM may be preferred over conventional IVIM MRI, and may subsequently improve the ability to diagnose early- and mid-stage SS.

Impaired effective functional connectivity of the sensorimotor network in interictal episodic migraineurs without aura.

BACKGROUND: Resting-state functional magnetic resonance imaging (Rs-fMRI) has confirmed sensorimotor network (SMN) dysfunction in migraine without aura (MwoA). However, the underlying mechanisms of SMN effective functional connectivity in MwoA remain unclear. We aimed to explore the association between clinical characteristics and effective functional connectivity in SMN, in interictal patients who have MwoA. METHODS: We used Rs-fMRI to acquire imaging data in 40 episodic patients with MwoA in the interictal phase and 34 healthy controls (HCs). Independent component analysis was used to profile the distribution of SMN and calculate the different SMN activity between the two groups. Subsequently, Granger causality analysis was used to analyze the effective functional connectivity between the SMN and other brain regions. RESULTS: Compared to the HCs, MwoA patients showed higher activity in the bilateral postcentral gyri (PoCG), but lower activity in the left midcingulate cortex (MCC). Moreover, MwoA patients showed decreased effective functional connectivity from the SMN to left middle temporal gyrus, right putamen, left insula and bilateral precuneus, but increased effective functional connectivity to the right paracentral lobule. There was also significant effective functional connectivity from the primary visual cortex, right cuneus and right putamen to the SMN. In the interictal period, there was positive correlation between the activity of the right PoCG and the frequency of headache. The disease duration was positively correlated with abnormal effective functional connectivity from the left PoCG to right precuneus. In addition, the headache impact scores were negatively correlated with abnormal effective functional connectivity from the left MCC to right paracentral lobule, as well as from the right precuneus to left PoCG. CONCLUSIONS: These differential, resting-state functional activities of the SMN in episodic MwoA may contribute to the understanding of migraine-related intra- and internetwork imbalances associated with nociceptive regulation and chronification.

Achieving high performance poly(vinylidene fluoride) dielectric composites via in situ polymerization of polypyrrole nanoparticles on hydroxylated BaTiO3 particles.

Polymer dielectric composites have widespread applications in many fields ranging from energy storage, microelectronic devices, and sensors to power driven systems, etc. and attract much attention of researchers. However, it is still challenging to prepare advanced polymer dielectric composites with a high dielectric constant (ε'), low dielectric loss (tan δ) and simultaneously high breakdown strength (E bd). In this work, conductive polypyrrole (PPy) nanoparticles were in situ synthesized in a reaction system containing the common barium titanate (BaTiO3, BT) or hydroxylated BaTiO3 (BTOH) particles, and then the PPy@BT and PPy@BTOH composite particles were incorporated into poly(vinylidene fluoride) (PVDF) to prepare the composites. The morphologies and microstructures of the PPy@BT and PPy@BTOH composite particles and the corresponding PVDF composites were comparatively investigated. The results showed that the PPy@BTOH composite particles had a 'mulberry'-like morphology with a rough surface and the self-assembled structure could be maintained in the PVDF composites, which was apparently different from the PVDF/PPy@BT composites, in which most of the PPy nanoparticles dissociatively dispersed in the PVDF matrix. Electrical conductivity measurements showed that at high particle content (≥20 wt%), the PPy@BTOH composite particles endowed the composites with lower electrical conductivity compared with the PPy@BT composite particles. Dielectric property measurements showed that the 'mulberry'-like PPy@BTOH composite particles endowed the PVDF composites with extremely high ε', ultralow tan δ and high E bd compared with the PVDF/PPy@BT composites with dissociatively dispersed PPy nanoparticles and BaTiO3 particles. The polarization and loss mechanisms of the composites were then proposed based on the morphologies and the microstructures of the composites. This work provides an alternative way to fabricate functional dielectric particles through trace functional groups inducing in situ polymerization of conductive polymers, and these particles can be used to fabricate advanced dielectric composites.