University of Madeira

About: University of Madeira is a education organization based out in Funchal, Portugal. It is known for research contribution in the topics: Population & Dendrimer. The organization has 1014 authors who have published 2759 publications receiving 59457 citations.

Zwitterionic Gadolinium(III)-Complexed Dendrimer-Entrapped Gold Nanoparticles for Enhanced Computed Tomography/Magnetic Resonance Imaging of Lung Cancer Metastasis

Abstract: Design of dual mode or multimode contrast agents or nanoplatforms with antifouling properties is crucial for improved cancer diagnosis since the antifouling materials are able to escape the clearan...

Characterization of phenolic compounds in Helichrysum melaleucum by high-performance liquid chromatography with on-line ultraviolet and mass spectrometry detection

Abstract: Helicrysum melaleucum is a medicinal plant traditionally used in the islands of the Macaronesia region for the treatment of respiratory diseases. In this work, the phenolic compounds of Helicrysum melaleucum plants collected in different geographical locations of Madeira Island and their morphological parts (total aerial parts, leaves, flowers and stems) were extracted and analyzed separately by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC-DAD/ESI-MS(n)). A total of 68 compounds were characterized based mainly on their UV and mass spectra. These included derivatives of O-glycosylated flavonoids (flavonol and flavones type), quinic acid, caffeic acid, lignans and polyphenols. The flowers were found to be the morphological part with higher variety of phenolic compounds. The large differences in the phenolic composition of plants collected from different geographical locations allowed the identification of a few components, such as pinoresinol and methoxylated flavone derivatives, likely to be useful as geographical markers. Also, these results promote further comparison of the bioactivities of the different samples analyzed. This paper marks the first report on the chemical analysis of Helichrysum melaleucum species.

Machine Learning for Brain Stroke: A Review

Abstract: Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. An application of ML and Deep Learning in health care is growing however, some research areas do not catch enough attention for scientific investigation though there is real need of research. Therefore, the aim of this work is to classify state-of-arts on ML techniques for brain stroke into 4 categories based on their functionalities or similarity, and then review studies of each category systematically. A total of 39 studies were identified from the results of ScienceDirect web scientific database on ML for brain stroke from the year 2007 to 2019. Support Vector Machine (SVM) is obtained as optimal models in 10 studies for stroke problems. Besides, maximum studies are found in stroke diagnosis although number for stroke treatment is least thus, it identifies a research gap for further investigation. Similarly, CT images are a frequently used dataset in stroke. Finally SVM and Random Forests are efficient techniques used under each category. The present study showcases the contribution of various ML approaches applied to brain stroke.