Lipoblastoma is a rare tumor of infancy. It originates from the white fetal fat in soft tissue. The most common location of this rare tumor is extremity and to best of our knowledge less than 10 cases of intrathoracic and mediastinal lipoblastoma has been reported in the English literature. Herein we present our experience with a 15-month-old boy infant who presented with severe dyspnea. Imaging studies showed a mass in the thoracic cavity and mediastinum which was diagnosed as lipoblastoma after pathologic examination of the resected mass. Lipoblastoma has been considered as a tumor of soft tissue, but it should also be considered as a rare cause of intrathoracic masses of young children.

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In a normal development, structure and functions of the infant's brain change efficiently to enable one's communication with the external world. However, it is still a mystery that how dominant connections of the brain network called "backbone" change in the infancy period. In this study developmental changes in the backbone of functional brain network are investigated. Therefore, resting state EEG of 15 infants (7 girls, full-term) with no family health problem were recorded at the ages of 6 and 18 months. Subsequently, the brain functional network was estimated from the cleaned EEG using Weighted Phase Lag Index (WPLI) algorithm. The WPLI network was then explored using the graph theory by Minimum Spanning Tree. Parameters of the MST including diameter, betweenness, leaf number, eccentricity, and hierarchy were calculated. Subsequently, a pairwise t-test was performed based on the MST parameters to compare backbone of the brain network between both age groups. Based on the Power Spectral Analysis, four frequency bands including delta, lower alpha, lower beta, and gamma bands were selected, each of them investigated separately. The results showed an increase of eccentricity and diameter, and a reduction in leaf numbers, betweenness and hierarchy (lower complexity) in the functional networks of the frequencies with enhanced power (eg. gamma). In addition, opposite results were observed in the networks related to the frequencies with declined power (eg. delta). Our findings indicate that backbone of the brain functional network changes in a frequency specific manner, and a reverse order follows the changes in oscillatory pattern.