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This study aimed to analyze different behavioral profiles in response to chronic social defeat using the sensorial contact model. We hypothesized that a passive profile, unlike an active one, would be associated with behavioral and physiological characteristics related to depression. Six-week-old OF1 male mice were subjected to defeat for 21 consecutive days. A combination of cluster and discriminant analyses of the behavior exhibited during confrontation on Day 21 established two behavioral profiles: active (n?=?22) and passive (n?=?34). Passive mice, with a high level of immobility and low non-social exploration, had higher plasma corticosterone concentrations than active mice after 21 days of defeat. Three days after the last defeat, passive mice had lower corticosterone levels than manipulated-control mice (n?=?11). Higher levels of interleukin-6 and tumor necrosis factor-α (TNF-α) in the spleen and lower hippocampal brain-derived neurotrophic factor levels were observed in passive mice in comparison with those in active mice and the manipulated controls. The only differences observed in active mice in relation to the manipulated control were higher plasma corticosterone (Day 21) and TNF-α levels. The results show that different behavioral profiles in response to chronic defeat are associated with different physiological profiles, and that the passive profile presents physiological characteristics previously associated with depression.  相似文献   
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In this paper we present the coreferential tagging of part of the EPEC Corpus of Basque. Although coreference is a pragmatic linguistic phenomenon highly dependent on the situational context, it shows some language-specific patterns that vary according to the features of each language. Due to the fact that Basque is not an Indo-European language, it differs considerably in grammar from the languages spoken in surrounding areas. We will explain these features and the decisions made in each case. After describing the criteria defined for coreferential tagging in Basque, the annotation process will be explained. Our annotation is based on a morphologically and syntactically annotated corpus that provides us with a manageable environment, in which the specific structures that are part of a reference chain can be more easily identified. A part of the corpus was tagged by two annotators who marked up the same text independently, and by another annotator that acted as judge, solving problems in case of disagreement. All this process has been automatized as a result of previous studies carried out in this field. The automatic detection of mentions (Soraluze et al., in: Proceedings of Konvens, 2012) has provided us with a better working environment, and given us the possibility to build a first significant corpus for a later computational treatment of automatic coreferential resolution.  相似文献   
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