Sensitivity, specificity, and diagnostic yield of the superficial peroneal nerve (SPN)/peroneus brevis muscle (PBM) biopsy in 43 patients with clinically suspected vasculitic neuropathy was studied. Biopsies were classified as "definite", "suspicious" or "possible" in accordance with established criteria. Vasculitis was detected in 27 patients (21 with non-systemic vasculitis, and six with systemic vasculitis). In patients with "definite" vasculitis (n=13), the sensitivity of SPN/PBM biopsy was 76.4% with 100% specificity. By including patients suspicious for vasculitis (n=10), sensitivity increased to 85.1% but the specificity dropped to 87.5%. The overall diagnostic yield of SPN biopsy in those patients with definite vasculitis was 76.9% (10/13), and 53.8% (7/13) for muscle biopsy. The addition of muscle biopsy increased the diagnostic yield by 23%. Asymmetric nerve fiber loss, Wallerian degeneration and presence of hemosiderin were statistically significant markers of probable vasculitis. Muscle tissue was more likely to show hemosiderin (85.7%) than a nerve biopsy (71%). A combined SPN/PBM biopsy offers excellent diagnostic yield in the diagnosis of vasculitic neuropathy.
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http://dx.doi.org/10.1016/j.jocn.2011.11.034 | DOI Listing |
Theranostics
January 2025
State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Extracellular vesicles (EVs) are carriers of a diverse array of bioactive molecules, making them valuable clinical tools for liquid biopsy in disease diagnosis and prognosis evaluation. These molecules play critical roles in various physiological and pathological conditions, and effective separation of EVs is essential to achieve these objectives. Due to the high heterogeneity of EVs, particularly with regard to their cargo molecules, merely isolating the general EV population is inadequate for liquid biopsy and biological function studies.
View Article and Find Full Text PDFEJNMMI Res
January 2025
Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon, Korea.
Background: This study aimed to establish the optimal cutoff values for visual amyloid positivity using standardized uptake value ratios (SUVRs) in [F]flutemetamol (FMM) positron emission tomography (PET) imaging. Given the variability in amyloid assessment, our goal was to determine cutoff values that enhance diagnostic accuracy and assist clinicians in reliably identifying amyloid positivity.
Results: The identified cutoff values for visual amyloid positivity were > 1.
Mol Biol Rep
January 2025
Department of Agronomy and Plant Breeding Sciences, Agricultural College of Aburaihan, University of Tehran, Pakdasht, Iran.
Background: Tomato yellow leaf curl virus (TYLCV), tomato mosaic virus (ToMV), and Fusarium wilt are three of tomatoes' most important viral and fungal diseases.
Methods And Results: In this study, the application of molecular markers associated with tomato yellow leaf curl virus resistance gene (Ty1), tomato mosaic virus resistance gene (Tm2), and Fusarium wilt resistance gene (I-1) (linked marker) were evaluated. In order to optimize and use SNP markers (by HRM diagnostic method) and SCAR markers, segregating populations of tomatoes were produced by self-pollination of commercial hybrid cultivars.
Clin Transl Med
January 2025
BOE Technology Group Co., Ltd, Beijing, China.
Background: Multi-omics features of cell-free DNA (cfDNA) can effectively improve the performance of non-invasive early diagnosis and prognosis of cancer. However, multimodal characterization of cfDNA remains technically challenging.
Methods: We developed a comprehensive multi-omics solution (COMOS) to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA.
J Magn Reson Imaging
February 2025
BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, New York, USA.
Background: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.
Purpose: To report initial results on automatic classification of liver MRE image quality using various deep learning (DL) architectures.
Study Type: Retrospective, single center, IRB-approved human study.
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