Infantile haemangiomas are the most common tumours in infants. Large facial haemangiomas are associated with posterior fossa malformations, haemangiomas, arteriel malformations, cardiac defects and eye anomalies (PHACE) syndrome in 20-31%. The diagnosis requires a large facial haemangiom and the minimum of one extracutaneous manifestation. Infants with large facial haemangiomas are in risk of PHACE syndrome and need to be referred to paediatric expertise. This case represents an infant with a large facial haemangioma, who was diagnosed with a coarctatio aortae and hence the PHACE syndrome.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Investigating the quality of European silver eels by quantifying contaminants and parasite infestation in a French Mediterranean lagoon complex.
Environ Sci Pollut Res Int
January 2025
Tour du Valat, Research Institute for the Conservation of Mediterranean Wetlands, Le Sambuc, Arles, France.
Coastal lagoons are diverse habitats with significant ecological gradients, which provide crucial ecosystem services but face threats from human activities such as invasive species and pollution. Among the species inhabiting the lagoons, the critically endangered European eel (Anguilla anguilla) is an emblematic species strongly impacted by contamination and parasitism. Several indicators were developed to assess the quality of eel at a large geographic scale.
View Article and Find Full Text PDFClimate Change-Induced Decline in Succulent in Namibia's Arid Regions.
Plants (Basel)
January 2025
Department of Plant and Soil Sciences, University of Pretoria, Hatfield, Pretoria P.O. Box X20, South Africa.
The global rise in temperatures due to climate change has made it difficult even for specialised desert-adapted plant species to survive on sandy desert soils. Two of Namibia's iconic desert-adapted plant species, and the quiver tree , have recently been shown to be under threat because of climate change. In the current study, three ecologically important Namibian milk bushes were evaluated for their climate change response.
View Article and Find Full Text PDFZero-Trust Access Control Mechanism Based on Blockchain and Inner-Product Encryption in the Internet of Things in a 6G Environment.
Sensors (Basel)
January 2025
State Grid Zaozhuang Power Supply Company, Zaozhuang 277899, China.
Within the framework of 6G networks, the rapid proliferation of Internet of Things (IoT) devices, coupled with their decentralized and heterogeneous characteristics, presents substantial security challenges. Conventional centralized systems face significant challenges in effectively managing the diverse range of IoT devices, and they are inadequate in addressing the requirements for reduced latency and the efficient processing and analysis of large-scale data. To tackle these challenges, this paper introduces a zero-trust access control framework that integrates blockchain technology with inner-product encryption.
View Article and Find Full Text PDFRWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT.
Sensors (Basel)
January 2025
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. Traditional centralized IoT architectures often face issues such as single points of failure and insufficient reliability, while blockchain, with its decentralized and tamper-resistant properties, offers a promising solution. However, existing blockchain consensus mechanisms struggle to meet the high throughput, low latency, and scalability demands of IoT applications.
View Article and Find Full Text PDFResearch on a Novel Unsupervised-Learning-Based Pipeline Leak Detection Method Based on Temporal Kolmogorov-Arnold Network with Autoencoder Integration.
Sensors (Basel)
January 2025
College of Energy and Power Engineering, Xihua University, Chengdu 610039, China.
Artificial intelligence (AI) technologies have been widely applied to the automated detection of pipeline leaks. However, traditional AI methods still face significant challenges in effectively detecting the complete leak process. Furthermore, the deployment cost of such models has increased substantially due to the use of GPU-trained neural networks in recent years.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!