Fatality owing to pulmonary hemorrhage following pamidronate disodium administration in a neonate with osteogenesis imperfecta type 2: A case report.

We report the case of a patient with osteogenesis imperfecta (OI) who developed pulmonary hemorrhage 4 d after pamidronate disodium (PA) administration, despite a relatively stable respiratory status. Bisphosphonates are introduced to reduce osteoclast activity and are now widely used in patients with OI. Bisphosphonates are typically well-tolerated in children, and the standard of care involves cyclic intravenous administration of PA. However, in practice, there is limited experience with the use of PA for severe OI during the neonatal period, and its safety remains uncertain. This report aimed to describe the respiratory events potentially associated with PA in a neonatal patient with OI type 2, suggesting that serious life-threatening complications of pulmonary hemorrhage may occur after PA administration. Further studies are required to assess the relationship between pulmonary hemorrhage and PA administration, aiming to enhance prophylaxis measures.

Three Consecutive Cases of Familial Hemophagocytic Lymphohistiocytosis, Including a Case Due to Maternal Uniparental Disomy.

We have experienced 3 consecutive cases of familial hemophagocytic lymphohistiocytosis (FHL). All affected infants had mutations in exon 3 of the perforin gene. The first had a homozygous mutation, c.1168C>T (p.R390*), caused by maternal uniparental isodisomy. The second and third had compound heterozygous mutations: c.781G>A (p.E261K) and c.1491T>A (p.C497*); c.1724G>T (p.C242G) and p.R390*, respectively. FHL is very rare in Northern Japan but should be suspected if infants exhibit prolonged fever. This is the first report of a relationship of p.R390* with FHL caused by uniparental isodisomy, and the second reported case of FHL type 2 with this form of inheritance.

Delay-Tolerance-Based Mobile Data Offloading Using Deep Reinforcement Learning.

The demand for mobile data communication has been increasing owing to the diversification of its purposes and the increase in the number of mobile devices accessing mobile networks. Users are experiencing a degradation in communication quality due to mobile network congestion. Therefore, improving the bandwidth utilization efficiency of cellular infrastructure is crucial. We previously proposed a mobile data offloading protocol (MDOP) for improving the bandwidth utilization efficiency. Although this method balances a load of evolved node B by taking into consideration the content delay tolerance, accurately balancing the load is challenging. In this paper, we apply deep reinforcement learning to MDOP to solve the temporal locality of a traffic. Moreover, we examine and evaluate the concrete processing while considering a delay tolerance. A comparison of the proposed method and bandwidth utilization efficiency of MDOP showed that the proposed method reduced the network traffic in excess of the control target value by 35% as compared with the MDOP. Furthermore, the proposed method improved the data transmission ratio by the delay tolerance range. Consequently, the proposed method improved the bandwidth utilization efficiency by learning how to provide the bandwidth to the user equipment when MDOP cannot be used to appropriately balance a load.