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Background: The post-processing technology of CTA offers significant advantages in evaluating left atrial enlargement (LAE) in patients with persistent atrial fibrillation (PAF). This study aims to identify parameters for rapidly and accurately diagnosing LAE in patients with PAF using CT cross-sections. Methods: Left atrial pulmonary venous (PV) CT was performed to 300 PAF patients with dual-source CT, and left atrial volume (LAV), left atrial anteroposterior diameter (LAD1), left atrial transverse diameter (LAD2), and left atrial area (LAA) were measured in the ventricular end systolic (ES) and middle diastolic (MD). LA index (LAI) = LA parameter/body surface area (BSA). Left atrial volume index (LAVIES) > 77.7 ml/m2 was used as the reference standard for the LAE diagnosis. Results: 227 patients were enrolled in the group, 101 (44.5%) of whom had LAE. LAVES and LAVMD (r = 0.983), LAVIES and LAVIMD (r = 0.984), LAAES and LAVIES (r = 0.817), LAAMD and LAVIES (r = 0.814) had strong positive correlations. The area under curve (AUC) showed that all measured parameters were suitable for diagnosing LAE, and the diagnostic efficacy was compared as follows: LAA/LAAI> LAD> the relative value index of LAD, LAD2> LAD1. LAA and LAAI demonstrated comparable diagnostic efficacy, with LAA being more readily available than LAAI. Conclusions: The axial LAA measured by CTA can be served as a parameter for the rapid and accurate diagnosis of LAE in patients with PAF. [ABSTRACT FROM AUTHOR]

Hypomyelinating leukodystrophy (HLD) is a rare genetic heterogeneous disease that can affect myelin development in the central nervous system. This study aims to analyze the clinical phenotype and genetic function of a family with HLD-7 caused by POLR3A mutation. The proband (IV6) in this family mainly showed progressive cognitive decline, dentin dysplasia, and hypogonadotropic hypogonadism. Her three old brothers (IV1, IV2, and IV4) also had different degrees of ataxia, dystonia, or dysarthria besides the aforementioned manifestations. Their brain magnetic resonance imaging showed bilateral periventricular white matter atrophy, brain atrophy, and corpus callosum atrophy and thinning. The proband and her two living brothers (IV2 and IV4) were detected to carry a homozygous mutation of the POLR3A (NM_007055.4) gene c. 2300G > T (p.Cys767Phe), and her consanguineous married parents (III1 and III2) were p.Cys767Phe heterozygous carriers. In the constructed POLR3A wild-type and p.Cys767Phe mutant cells, it was seen that overexpression of wild-type POLR3A protein significantly enhanced Pol III transcription of 5S rRNA and tRNA Leu-CAA. However, although the mutant POLR3A protein overexpression was increased compared to the wild-type protein overexpression, it did not show the expected further enhancement of Pol III function. On the contrary, Pol III transcription function was frustrated (POLR3A, BC200, and tRNA Leu-CAA expression decreased), and MBP and 18S rRNA expressions were decreased. This study indicates that the POLR3A p.Cys767Phe variant caused increased expression of mutated POLR3A protein and abnormal expression of Pol III transcripts, and the mutant POLR3A protein function was abnormal. [ABSTRACT FROM AUTHOR]

Background: Primary ciliary dyskinesia (PCD) is an autosomal recessive hereditary disease characterized by recurrent respiratory infections. In clinical manifestations, DNAH5 (NM_001361.3) is one of the recessive pathogenic genes. Primary familial brain calcification (PFBC) is a neurodegenerative disease characterized by bilateral calcification in the basal ganglia and other brain regions. PFBC can be inherited in an autosomal dominant or recessive manner. A family with PCD caused by a DNAH5 compound heterozygous variant and PFBC caused by a MYORG homozygous variant was analyzed. Methods: In this study, we recruited three generations of Han families with primary ciliary dyskinesia combined with primary familial brain calcification. Their clinical phenotype data were collected, next-generation sequencing was performed to screen suspected pathogenic mutations in the proband and segregation analysis of families was carried out by Sanger sequencing. The mutant and wild-type plasmids were constructed and transfected into HEK293T cells instantaneously, and splicing patterns were detected by Minigene splicing assay. The structure and function of mutations were analyzed by bioinformatics analysis. Results: The clinical phenotypes of the proband (II10) and his sister (II8) were bronchiectasis, recurrent pulmonary infection, multiple symmetric calcifications of bilateral globus pallidus and cerebellar dentate nucleus, paranasal sinusitis in the whole group, and electron microscopy of bronchial mucosa showed that the ciliary axoneme was defective. There was also total visceral inversion in II10 but not in II8. A novel splice variant C.13,338 + 5G > C and a frameshift variant C.4314delT (p. Asn1438lysfs *10) were found in the DNAH5 gene in proband (II10) and II8. c.347_348dupCTGGCCTTCCGC homozygous insertion variation was found in the MYORG of the proband. The two pathogenic genes were co-segregated in the family. Minigene showed that DNAH5 c.13,338 + 5G > C has two abnormal splicing modes: One is that part of the intron bases where the mutation site located is translated, resulting in early translation termination of DNAH5; The other is the mutation resulting in the deletion of exon76. Conclusions: The newly identified DNAH5 splicing mutation c.13,338 + 5G > C is involved in the pathogenesis of PCD in the family, and forms a compound heterozygote with the pathogenic variant DNAH5 c.4314delT lead to the pathogenesis of PCD. [ABSTRACT FROM AUTHOR]

In the era of big data, with the continuous popularization of social media, various text data are growing in the network and in life. It is of great significance to analyze and manage text data using text classification technology. Text classification is a basic research field in the field of artificial intelligence natural language processing. Under the given criteria, it classifies text according to content. The application scenarios of text classification are very extensive, such as sentiment analysis, topic classification, relationship classification, etc. Deep learning is a method of representation learning based on data in machine learning, and it shows good classification effect in text data processing. Chinese text and English text have differences in form, sound, and image. Focusing on the uniqueness of Chinese text classification, this paper analyzes and expounds the deep learning methods used for Chinese text classification, and finally sorts out commonly used datasets for Chinese text classification. [ABSTRACT FROM AUTHOR]