ABSTRACT
Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia. We combined a multiscale method and weighted permutation entropy to characterize MEG signals from 19 schizophrenia patients and 16 healthy controls. When the scale was larger than 42, the MEG signals of schizophrenia patients were significantly more complex than those of healthy controls (p<0.004). The difference in complexity between patients with schizophrenia and the controls was strongest in the frontal and occipital areas (p<0.001), and there was almost no difference in the central area. In addition, the results showed that the dynamic range of MEG complexity is wider in healthy individuals than in people with schizophrenia. Overall, the multiscale weighted permutation entropy method reliably quantified the complexity of MEG from schizophrenia patients, contributing to the development of potential magnetoencephalographic biomarkers for schizophrenia.
ABSTRACT
PURPOSE: To explore the clinical distribution characteristics and antimicrobial susceptibilities of carbapenem-resistant Escherichia coli (CR-ECO) in Hebei Province, China, from 2017 to 2019, and provide data on the treatment of this bacterial infection and the prevention of its spread. MATERIALS AND METHODS: A total of 1439 CR-ECO strains were collected from 2017 to 2019 in Hebei Province, China. Drug sensitivity tests were performed using the minimum inhibitory concentration (MIC) method, and the data were analyzed statistically using WHONET5.6 software. RESULTS: A total of 54,377 strains of Escherichia coli were isolated in Hebei Province from 2017 to 2019, of which 1439 strains were CR-ECO (2.65%). The highest proportion (33.78%) of strains was isolated from urine, and the detection rate showed a slow downward trend over the past 3 years. CR-ECO was mainly detected in densely populated and economically developed areas. Of all the patients, 54.2% were from the medical ward; the ratio of male to female patients with CR-ECO infections was 1.35:1; elderly patients and adults accounted for 59.6% and 30.8%, respectively, whereas minors and newborns accounted for 4.9% and 4.7%, respectively. For CR-ECO, the drug resistance rates to ß-lactams were all higher than 80% and there was an annual increasing trend, while the drug resistance rates to quinolones remained nearly unchanged. The rate of resistance to aminoglycosides was relatively low, especially to amikacin (approximately 22%). The MIC50 of other antibacterial drugs, except amikacin, was equal to or higher than the break point of drug resistance. CONCLUSION: From 2017 to 2019, the isolation rate of CR-ECO in Hebei Province, China, remained stable; however, the drug resistance rate showed an upward trend, primarily in cases of urinary tract infections in older men; the resistance rate to amikacin was the lowest.
ABSTRACT
Distinct cortical activity during face recognition was reported by a number of studies. Classical coherence analysis reflects the synchronization between two random processes in certain frequency under the assumption that the signals are stationary. In EEG study, the coherence analysis is mainly used to analyze the coupling and drive-response relation about the brain activities in different regions. Classical coherence analysis can extract the rhythmic consistency of the EEG activities in different regains. However, classical coherence can not extract the transient synchrony characteristics of brain activities. In order to track the spatial-temporal characteristics of EEG activities during cognitive conception, the time-varying coherence analysis is proposed. The EEG of 10 participants was recorded during recognition of familiar and unfamiliar faces, experiment results show that there is obvious difference about the model of information communication between temporal region and other brain regions in alpha rhythm during cognitive processing.
