Audiological Findings in Patients with Vestibular Migraine and Migraine: History of Migraine May Be a Cause of Low-Tone Sudden Sensorineural Hearing Loss.

INTRODUCTION: The aim of this study was to investigate and compare the auditory findings in migraine, vestibular migraine (VM), and healthy controls. METHODS: Twenty-eight migraine patients (56 ears), 18 VM (36 ears), and 25 healthy controls (50 ears) were included. Audiometry, speech discrimination scores, distortion product optoacoustic emission (DPOAE), and auditory brainstem response were tested. RESULTS: The pure tone in the VM group showed higher thresholds at lower frequencies (250, 500, 1,000, 2,000 Hz) than the control group, with statistical differences observed (P250 Hz = 0.001, P500 Hz = 0.003, P1,000 Hz = 0.016, P2,000 Hz = 0.002). Compared with the healthy controls, the patients with VM had significantly lower amplitudes of DPOAE at 1 kHz (p < 0.001) and 2 kHz (p = 0.020), and the patients with migraine had lower amplitudes at 2 kHz (p = 0.042). Compared with the control group, the patients with migraine reported prolonged latency of wave V (p = 0.016) and IPL I-V (p = 0.003). The patients with VM had significant prolongation of IPL I-V (p = 0.024). CONCLUSION: Not only the peripheral, but also the central auditory system was involved in patients with migraine and VM. In particular, lower frequencies of the auditory system were more likely to be involved in VM. The history of migraine may be a cause of low-tone sudden sensorineural hearing loss.

Resveratrol ameliorates hypoxia/ischemia-induced brain injury in the neonatal rat via the miR-96/Bax axis.

OBJECTIVE: This study was aimed to investigate the mechanism of resveratrol on amelioration of hypoxia/ischemia (H/I)-induced brain injury. METHODS: The RT-PCR and western blot were used to detect the mRNA and protein expressions, respectively. The PC12 cell induced by OGD/R was as in vitro H/I brain injury model. The luciferase reporter assay was used to prove the relationship between Bax and miR-96, and the cell apoptosis was detected by MTT assay. The loss of MBP+ area in neonatal rats analyzed by immunohistochemistry was to evaluate the extent of brain injury. RESULTS: The miR-96 expression was decreased in the hippocampus and cerebral cortex of neonatal rats with H/I brain injury and the oxygenglucose deprivation/re-oxygenation (OGD/R)-induced PC12 cell, while Bax expression was opposite. And then the H/I rats and OGD/R-induced PC12 cell were treated with resveratrol (RSV); the results showed that the RSV could reverse the miR-96 and Bax expressions. Next, the luciferase reporter assay proved that Bax was a target of miR-96. We used the miR-96 inhibitor to suppress miR-96 expression in OGD/R-induced PC12 cell, and found that RSV regulated Bax expression and prevented OGD/R-induced PC12 cell apoptosis via miR-96. In addition, the immunohistochemistry was used to analyze the loss of MBP+ area in neonatal rats, and the result showed that the RSV significantly reduced the brain damage, increased miR-96 expression, and decreased Bax expression, while inhibition of miR-96 aggravated the brain damage and reversed the effect of RSV. CONCLUSION: Resveratrol ameliorates hypoxia/ischemia-induced brain injury in neonatal rat via the miR-96/ Bax axis.

[A Novel Channel Selection Method for Brain-computer Interface Based on Relief-SBS].

Regarding to the channel selection problem during the classification of electroencephalogram(EEG)signals,we proposed a novel method,Relief-SBS,in this paper.Firstly,the proposed method performed EEG channel selection by combining the principles of Relief and sequential backward selection(SBS)algorithms.And then correlation coefficient was used for classification of EEG signals.The selected channels that achieved optimal classification accuracy were considered as optimal channels.The data recorded from motor imagery task experiments were analyzed,and the results showed that the channels selected with our proposed method achieved excellent classification accuracy,and also outperformed other feature selection methods.In addition,the distribution of the optimal channels was proved to be consistent with the neurophysiological knowledge.This demonstrates the effectiveness of our method.It can be well concluded that our proposed method,Relief-SBS,provides a new way for channel selection.

A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

BACKGROUND: For sensorimotor rhythms based brain-computer interface (BCI) systems, classification of different motor imageries (MIs) remains a crucial problem. An important aspect is how many scalp electrodes (channels) should be used in order to reach optimal performance classifying motor imaginations. While the previous researches on channel selection mainly focus on MI tasks paradigms without feedback, the present work aims to investigate the optimal channel selection in MI tasks paradigms with real-time feedback (two-class control and four-class control paradigms). METHODS: In the present study, three datasets respectively recorded from MI tasks experiment, two-class control and four-class control experiments were analyzed offline. Multiple frequency-spatial synthesized features were comprehensively extracted from every channel, and a new enhanced method IterRelCen was proposed to perform channel selection. IterRelCen was constructed based on Relief algorithm, but was enhanced from two aspects: change of target sample selection strategy and adoption of the idea of iterative computation, and thus performed more robust in feature selection. Finally, a multiclass support vector machine was applied as the classifier. The least number of channels that yield the best classification accuracy were considered as the optimal channels. One-way ANOVA was employed to test the significance of performance improvement among using optimal channels, all the channels and three typical MI channels (C3, C4, Cz). RESULTS: The results show that the proposed method outperformed other channel selection methods by achieving average classification accuracies of 85.2, 94.1, and 83.2 % for the three datasets, respectively. Moreover, the channel selection results reveal that the average numbers of optimal channels were significantly different among the three MI paradigms. CONCLUSIONS: It is demonstrated that IterRelCen has a strong ability for feature selection. In addition, the results have shown that the numbers of optimal channels in the three different motor imagery BCI paradigms are distinct. From a MI task paradigm, to a two-class control paradigm, and to a four-class control paradigm, the number of required channels for optimizing the classification accuracy increased. These findings may provide useful information to optimize EEG based BCI systems, and further improve the performance of noninvasive BCI.

Zhike pingchuan granules improve bronchial asthma by regulating the IL-6/JAK2/STAT3 pathway.

The present study aimed to investigate the effects of zhike pingchuan granules (ZKPC) on bronchial asthma and the underlying mechanism. A bronchial asthma mouse model was established by aerosol inhalation of ovalbumin. The changes in lung pathomorphology were observed by hematoxylin and eosin staining. The levels of IL-1ß, TNF-α and IL-6 in bronchoalveolar lavage fluid (BALF) and serum were detected by corresponding ELISA kits. Levels of reactive oxygen species, malondialdehyde and superoxide dismutase in lung tissues were analyzed using corresponding kits. The expression of proteins related to apoptosis and the IL-6/janus kinase 2 (JAK2)/STAT3 pathway was detected by western blot analysis. The results showed that ZKPC significantly restored the dry/wet ratio and alleviated lung pathomorphology of bronchial asthmatic mice. In addition, ZKPC inhibits inflammation, oxidative stress levels and cell apoptosis in bronchial asthmatic mice and also suppressed the IL-6/JAK2/STAT3 pathway. Fedratinib (a JAK2 inhibitor) further strengthened the alleviative effects of ZKPC on bronchial asthma. In conclusion, ZKPC improved bronchial asthma by suppressing the IL-6/JAK2/STAT3 pathway.

EEG-based motor imagery classification accuracy improves with gradually increased channel number.

The question of how many channels should be sed for classification remains a key issue in the study of Brain-Computer Interface. Several studies have shown that a reduced number of channels can achieve the optimal classification accuracy in the offline analysis of motor imagery paradigm, which does not have real-time feedback as in the online control. However, for the cursor movement control paradigm, it remains unclear as to how many channels should be selected in order to achieve the optimal classification. In the present study, we gradually increased the number of channels, and adopted the time-frequency-spatial synthesized method for left and right motor imagery classification. We compared the effect of increasing channel number in two datasets, an imagery-based cursor movement control dataset and a motor imagery tasks dataset. Our results indicated that for the former dataset, the more channels we used, the higher the accuracy rate was achieved, which is in contrast to the finding in the latter dataset that optimal performance was obtained at a subset number of channels. When gradually increasing the number of channels from 2 to all in the analysis of cursor movement control dataset, the average training and testing accuracies from three subjects improved from 68.7% to 90.4% and 63.7% to 87.7%, respectively.