Examining Neural Connectivity in Schizophrenia Using Task-Based EEG: A Graph Theory Approach.

Schizophrenia (SZ) is a complex disorder characterized by a range of symptoms and behaviors that have significant consequences for individuals, families, and society in general. Electroencephalography (EEG) is a valuable tool for understanding the neural dynamics and functional abnormalities associated with schizophrenia. Research studies utilizing EEG have identified specific patterns of brain activity in individuals diagnosed with schizophrenia that may reflect disturbances in neural synchronization and information processing in cortical circuits. Considering the temporal dynamics of functional connectivity provides a more comprehensive understanding of brain networks' organization and how they change during different cognitive states. This temporal perspective would enhance our understanding of the underlying mechanisms of schizophrenia. In the present study, we will use measures based on graph theory to obtain dynamic and static indicators in order to evaluate differences in the functional connectivity of individuals diagnosed with SZ and healthy controls using an ecologically valid task. At the static level, patients showed alterations in their ability to segregate information, particularly in the default mode network (DMN). As for dynamic measures, patients showed reduced values in most metrics (segregation, integration, centrality, and resilience), reflecting a reduced number of dynamic states of brain networks. Our results show the utility of combining static and dynamic indicators of functional connectivity from EEG sensors.

Extracellular HMGA1 Promotes Tumor Invasion and Metastasis in Triple-Negative Breast Cancer.

PURPOSE: The study of the cancer secretome suggests that a fraction of the intracellular proteome could play unanticipated roles in the extracellular space during tumorigenesis. A project aimed at investigating the invasive secretome led us to study the alternative extracellular function of the nuclear protein high mobility group A1 (HMGA1) in breast cancer invasion and metastasis. EXPERIMENTAL DESIGN: Antibodies against HMGA1 were tested in signaling, adhesion, migration, invasion, and metastasis assays using breast cancer cell lines and xenograft models. Fluorescence microscopy was used to determine the subcellular localization of HMGA1 in cell lines, xenograft, and patient-derived xenograft models. A cohort of triple-negative breast cancer (TNBC) patients was used to study the correlation between subcellular localization of HMGA1 and the incidence of metastasis. RESULTS: Our data show that treatment of invasive cells with HMGA1-blocking antibodies in the extracellular space impairs their migration and invasion abilities. We also prove that extracellular HMGA1 (eHMGA1) becomes a ligand for the Advanced glycosylation end product-specific receptor (RAGE), inducing pERK signaling and increasing migration and invasion. Using the cytoplasmic localization of HMGA1 as a surrogate marker of secretion, we showed that eHMGA1 correlates with the incidence of metastasis in a cohort of TNBC patients. Furthermore, we show that HMGA1 is enriched in the cytoplasm of tumor cells at the invasive front of primary tumors and in metastatic lesions in xenograft models. CONCLUSIONS: Our results strongly suggest that eHMGA1 could become a novel drug target in metastatic TNBC and a biomarker predicting the onset of distant metastasis.