The tunability, high power and flexible picoseconds-pulse time structure of terahertz (THz) radiation make the THz free-electron laser (FEL) a very attractive THz source of coherent radiation. This paper focuses on the development and perspectives of THz radiation sources based on the FEL. The principles of the low gain THz FEL oscillator, the SASE THz FEL amplifier and the supperradiant THz FEL are reviewed briefly, and the key technologies of THz FEL, such as injector, accelerator, undulator and optical cavity, are discussed, respectively. The current status of and future prospects for THz radiation sources based on the FEL are emphasized in this paper. Recent research and development have shown bright future in free-electron laser (FEL) THz radiation sources. The potential applications can be carried out in the field of imaging, material research, biology medicine, communication, diagnostics and many others.
Background: Due to its impairment in patients with schizophrenia, mismatch negativity (MMN) generation has been identified as a potential biomarker for identifying primary impairments in auditory sensory processing. This study aimed to investigate the dysfunctional differences in different MMN deviants and evoked theta power in patients with first-episode schizophrenia (FES) and chronic schizophrenia (CS).Methods: We measured frequency and duration MMN from 40 FES, 40 CS, and 40 healthy controls (HC). Evoked theta power was analyzed by event-related spectral perturbation (ERSP) approaches.Results: Deficits in duration MMN were observed in both FES (p = 0.048, Bonferroni-adjusted) and CS (p < 0.001, Bonferroni-adjusted). However, deficits in frequency MMN were restricted to the CS (p < 0.001, Bonferroni-adjusted). Evoked theta power deficits were observed in both patient groups when compared with the HC (p FES = 0.001, p CS < 0.001, Bonferroni-adjusted), yet no significant differences were found between FES and CS. Frequency MMN was correlated with the MATRICS consensus cognitive battery (MCCB) combined score (r = -0.327, p < 0.05) and MCCB verbal learning (r = -0.328, p < 0.05) in FES. Evoked theta power was correlated with MCCB working memory in both FES (r = 0.347, p < 0.05) and CS (r = 0.408, p < 0.01).Conclusion: These findings suggest that duration MMN and evoked theta power deficits may be more sensitive for detection of schizophrenia during its early stages. Moreover, frequency MMN and theta power could potentially linked to poor cognitive functioning in schizophrenic patients. The findings mentioned above indicated that the neural mechanisms of the three indexes may vary between people.
Mismatch negativity (MMN) has been consistently found deficit in schizophrenia, which was considered as a promising biomarker for assessing the impairments in preattentive auditory processing. However, the functional connectivity between brain regions based on MMN is not clear. This study provides an in-depth investigation in brain functional connectivity during MMN process among patients with firstepisode schizophrenia (FESZ), chronic schizophrenia (CSZ) and healthy control (HC). Electroencephalography (EEG) data of 128 channels is recorded during frequency and duration MMN in 40 FESZ, 40 CSZ patients and 40 matched HC subjects. We reconstruct the cortical endogenous electrical activity from EEG recordings using exact low-resolution electromagnetic tomography and build functional brain networks based on sourcelevel EEG data. Then, graph-theoretic features are extracted from the brain networks with the support vector machine (SVM) to classify FESZ, CSZ and HC groups, since the SVM has good generalization ability and robustness as a universally applicable nonlinear classifier. Furthermore, we introduce the graph neural network (GNN) model to directly learn for the network topology of brain network. Compared to HC, the damaged brain areas of CSZ are more extensive than FESZ, and the damaged area involved the auditory cortex. These results demonstrate the heterogeneity of the impacts of schizophrenia for different disease courses and the association between MMN and the auditory cortex. More importantly, the GNN classification results are significantly better than those of SVM, and hence the EEG-based GNN model of brain networks provides an effective method for discriminating among FESZ, CSZ and HC groups.
ObjectiveAlthough gastrointestinal (GI) symptoms are very common in patients with bipolar disorder (BD), Few studies have researched the pathomechanism behind these symptoms. In the present study, we aim at elucidate the pathomechanism of GI symptoms in BD through metabolomic analysis.MethodBD patients were recruited from Shanxi Bethune Hospital that divided into two groups, each group assessed with the 24-item Hamilton Depression Rating Scale (HAMD-24) according to the presence or absence of GI symptoms. Healthy controls were recruited from the medical examination center of the same hospital. Differential metabolites were identified and further analyzed using Metabo Analyst 3.0 to identify associated metabolic pathways.ResultsThere were significantly higher HAMD-24 scores in the GI symptoms group than that of non-GI symptoms group (p = 0.007). Based on metabolomic analysis results, we found that the common disturbances metabolic pathway of both two patients groups was ketone body metabolism, and the unique disturbances metabolic pathways of BD with GI symptoms were fatty acid biosynthesis and tyrosine metabolism, and these changes were independent of dietary habits.ConclusionBD patients with GI symptoms exhibited disturbances in fatty acid and tyrosine metabolism, perhaps suggesting that the GI symptoms in BD patients are related to disturbances of the gut microbiome. Both groups of patients jointly exhibit disturbances of ketone body metabolism, which may serve as a biomarker for the pathogenesis of BD patients.
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