J Int Med Res
September 2024
Wernicke encephalopathy (WE) is an acute life-threatening neurological condition caused by thiamine (vitamin B1) deficiency. Patients with WE often present with a triad of symptoms consisting of ophthalmoplegia, gait ataxia, and mental confusion. If WE is not treated in a timely manner, it can lead to serious complications such as confusion, coma, or death.
View Article and Find Full Text PDFBackground: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a rare autoimmune disorder. The symptoms of anti-NMDAR encephalitis include behavioral problems, speech problems, psychosis, seizures, and memory deficits, among others. However, laryngospasm is rare.
View Article and Find Full Text PDFAutoantibodies targeting aquaporin 4 (AQP4) water channels are a sensitive and specific biomarker for neuromyelitis optica spectrum disorder (NMOSD). Presence of AQP4 antibodies distinguishes NMOSD from multiple sclerosis. We present our experience with an anti-AQP4 antibody-positive patient diagnosed with NMOSD who complained of intractable nausea and vomiting, not restricted to optic neuritis or acute myelitis during the first attack.
View Article and Find Full Text PDFMud crab reovirus (MCRV) is the causative agent of a severe disease in cultured mud crab (Scylla paramamosain), which has caused huge economic losses in China. MCRV is a double-stranded RNA virus with 12 genomic segments. In this paper, SDS-PAGE, mass spectrometry and Western blot analyses revealed that the VP12 protein encoded by S12 gene is a structural protein of MCRV.
View Article and Find Full Text PDFMud crab reovirus (MCRV) is the causative agent of a serious disease with high mortality in cultured mud crab (Scylla serrata). This study sequenced and analyzed 12 genome segments of MCRV. The 12 genome segments had a total length of 24.
View Article and Find Full Text PDFGuang Pu Xue Yu Guang Pu Fen Xi
May 2011
Due to the high data dimensionality of a hyperspectral image, dimensionality reduction algorithm has attracted much attention in hyperspectral image analysis. Band selection algorithm, which selects appropriate bands from the original set of spectral bands, can preserve original information from the data and is useful for image classification and recognition. In the present paper, a novel band selection algorithm based on orthogonal projection divergence (OPD) is proposed, it aims to discriminate the interesting objects from background and noise information, maximize the spectral similarity between different spectral vectors by projecting the original data to feature space.
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