The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is limited. To extend research in this area, the researchers explored and analysed the academic articles published within the mentioned scope. Thus, in this paper a systematic review is carried out to map and draw the research scenery for EEG human emotion into a taxonomy. Systematically searched all articles about the, EEG human emotion based music in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 1999 to 2016. These databases feature academic studies that used EEG to measure brain signals, with a focus on the effects of music on human emotions. The screening and filtering of articles were performed in three iterations. In the first iteration, duplicate articles were excluded. In the second iteration, the articles were filtered according to their titles and abstracts, and articles outside of the scope of our domain were excluded. In the third iteration, the articles were filtered by reading the full text and excluding articles outside of the scope of our domain and which do not meet our criteria. Based on inclusion and exclusion criteria, 100 articles were selected and separated into five classes. The first class includes 39 articles (39%) consists of emotion, wherein various emotions are classified using artificial intelligence (AI). The second class includes 21 articles (21%) is composed of studies that use EEG techniques. This class is named 'brain condition'. The third class includes eight articles (8%) is related to feature extraction, which is a step before emotion classification. That this process makes use of classifiers should be noted. However, these articles are not listed under the first class because these eight articles focus on feature extraction rather than classifier accuracy. The fourth class includes 26 articles (26%) comprises studies that compare between or among two or more groups to identify and discover human emotion-based EEG. The final class includes six articles (6%) represents articles that study music as a stimulus and its impact on brain signals. Then, discussed the five main categories which are action types, age of the participants, and number size of the participants, duration of recording and listening to music and lastly countries or authors' nationality that published these previous studies. it afterward recognizes the main characteristics of this promising area of science in: motivation of using EEG process for measuring human brain signals, open challenges obstructing employment and recommendations to improve the utilization of EEG process.
Background: The tumor microenvironment and its stromal cells play an important role in cancer development and metastasis. Bone marrow-derived cells (BMDCs), a rich source of hematopoietic and mesenchymal stem cells, putatively contribute to this tumoral stroma. However their characteristics and roles within the tumor microenvironment are unclear. In the present study, BMDCs in the tumor microenvironment were traced using the green fluorescent protein (GFP) bone marrow transplantation model. Methods: C57BL/6 mice were irradiated and rescued by bone marrow transplantation from GFP-transgenic mice. Lewis lung cancer cells were inoculated into the mice to generate subcutaneous allograft tumors or lung metastases. Confocal microscopy, immunohistochemistry for GFP, α-SMA, CD11b, CD31, CD34 and CD105, and double-fluorescent immunohistochemistry for GFP-CD11b, GFP-CD105 and GFP-CD31 were performed. Results: Round and dendritic-shaped GFP-positive mononuclear cells constituted a significant stromal subpopulation in primary tumor peripheral area (PA) and metastatic tumor area (MA) microenvironment, thus implicating an invasive and metastatic role for these cells. CD11b co-expression in GFP-positive cells suggests that round/dendritic cell subpopulations are possibly BM-derived macrophages. Identification of GFP-positive mononuclear infiltrates co-expressing CD31 suggests that these cells might be BM-derived angioblasts, whereas their non-reactivity for CD34, CD105 and α-SMA implies an altered vascular phenotype distinct from endothelial cells. Significant upregulation of GFP-positive, CD31-positive and GFP/CD31 double-positive cell densities positively correlated with PA and MA (P<0.05). Conclusion: Taken together, in vivo evidence of traceable GFP-positive BMDCs in primary and metastatic tumor microenvironment suggests that recruited BMDCs might partake in cancer invasion and metastasis, possess multilineage potency and promote angiogenesis.
Noncoding repeat expansions cause various neuromuscular diseases, including myotonic dystrophies, fragile X tremor/ataxia syndrome, some spinocerebellar ataxias, amyotrophic lateral sclerosis and benign adult familial myoclonic epilepsies. Inspired by the striking similarities in the clinical and neuroimaging findings between neuronal intranuclear inclusion disease (NIID) and fragile X tremor/ataxia syndrome caused by noncoding CGG repeat expansions in FMR1, we directly searched for repeat expansion mutations and identified noncoding CGG repeat expansions in NBPF19 (NOTCH2NLC) as the causative mutations for NIID. Further prompted by the similarities in the clinical and neuroimaging findings with NIID, we identified similar noncoding CGG repeat expansions in two other diseases: oculopharyngeal myopathy with leukoencephalopathy and oculopharyngodistal myopathy, in LOC642361/NUTM2B-AS1 and LRP12, respectively. These findings expand our knowledge of the clinical spectra of diseases caused by expansions of the same repeat motif, and further highlight how directly searching for expanded repeats can help identify mutations underlying diseases.