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https://www.selleckchem.com/products/Rapamycin.html the deep learning-based label-label transition model provides distinctive contextual clues to enhance BioNER over the static transition model. We demonstrate that the proposed framework enables the dynamic transition model to adaptively explore the contextual relations between adjacent labels in a fine-grained way. We expect that our study can be a stepping stone for further prosperity of biomedical literature mining.BACKGROUND Arrhythmogenic cardiomyopathy (AC) is one of the leading causes for sudden cardiac death (SCD). Recent studies have identified mutations in cardiac desmosomes as key players in the pathogenesis of AC. However, the specific etiology in individual families remains largely unknown. METHODS A 4-generation family presenting with syncope, lethal ventricular arrhythmia and SCD was recruited. Targeted next generation sequencing (NGS) was performed and validated by Sanger sequencing. Plasmids containing the mutation and wild type (WT) were constructed. Real-time PCR, western-blot and immunofluorescence were performed to detect the functional change due to the mutation. RESULTS The proband, a 56-year-old female, presented with recurrent palpitations and syncope. An ICD was implanted due to her family history of SCD/ aborted SCD. NGS revealed a novel heterozygous frame-shift variant (c.832delG) in Desmoplakin (DSP) among 5 family members. The variant led to frame-shift and premature termination, producing a truncated protein. Cardiac magnetic resonance (CMR) of the family members carrying the same variant shown myocardium thinning and fatty infiltration in the right ventricular, positive bi-ventricular late gadolinium enhancement and severe RV dysfunction, fulfilling the diagnostic criteria of AC. HEK293T cells transfected with mutant plasmids expressed truncated DSP mRNA and protein, upregulation of nuclear junction plakoglobin (JUP) and downregulation of β-catenin, when compared with WT. CONCLUSION W

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