Tap: A Novel Cellular Protein That Interacts with Tip of Herpesvirus Saimiri and Induces Lymphocyte Aggregation

AbstractTip of herpesvirus saimiri associates with Lck and down-regulates Lck-mediated activation. We identified a novel cellular Tip-associated protein (Tap) by a yeast two-hybrid screen. Tap associated with Tip following transient expression in COS-1 cells and stable expression in human Jurkat-T cells. Expression of Tip and Tap in Jurkat-T cells induced dramatic cell aggregation. Aggregation was likely caused by the up-regulated surface expression of adhesion molecules including integrin α, L-selectin, ICAM-3, and H-CAM. Furthermore, NF-κB transcriptional factor of aggregated cells had approximately 40-fold higher activity than that of parental cells. Thus, Tap is likely to be an important cellular mediator of Tip function in T cell transformation by herpesvirus saimiri

A Case of Infected Left Atrial Myxoma With Concomitant Mitral Valve Endocarditis

Myxoma is the most common primary tumor in the heart. Cardiac myxomas can present in various manners including embolization and fever, sometimes simulating endocarditis. However, they are rarely infected. We report here a case of an infected left atrial myxoma that seeded a normal mitral valve and atypically presented with multiple embolic events in the lower extremities along with multiple splenic and a cerebellar infarction

Effects of an internal medicine floor interdisciplinary team on hospital and clinical outcomes of seniors with acute medical illness

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100310/1/ggi12035.pd

Molecular cloning of the Ecotin gene in Escherichia coli

AbstractThe nucleotide sequence of a 876 bp region in E. coli chromosome that encodes Ecotin was determined. The proposed coding sequence for Ecotin is 486 nucleotides long, which would encode a protein consisting of 162 amino acids with a calculated molecular weight of 18 192 Da. The deduced primary sequence of Ecotin includes a 20-residue signal sequence, cleavage of which would give rise to a mature protein with a molecular weight of 16 099 Da. Ecotin does not contain any consensus reactive site sequences of known serine protease inhibitor families, suggesting that Ecotin is a novel inhibitor

A new mosaic der(18)t(1;18)(q32.1;q21.3) with developmental delay and facial dysmorphism

We report the case of a 22-month-old boy with a new mosaic partial unbalanced translocation of 1q and 18q. The patient was referred to our Pediatric Department for developmental delay. He showed mild facial dysmorphism, physical growth retardation, a hearing disability, and had a history of patent ductus arteriosus. White matter abnormality on brain magnetic resonance images was also noted. His initial routine chromosomal analysis revealed a normal 46,XY karyotype. In a microarray-based comparative genomic hybridization (aCGH) analysis, subtle copy number changes in 1q32.1–q44 (copy gain) and 18q21.33–18q23 (copy loss) suggested an unbalanced translocation of t(1;18). Repeated chromosomal analysis revealed a low-level mosaic translocation karyotype of 46,XY,der(18)t(1;18)(q32.1;q21.3)[12]/46,XY[152]. Because his parents had normal karyotypes, his translocation was considered to be de novo. The abnormalities observed in aCGH were confirmed by metaphase fluorescent in situ hybridization. We report this patient as a new karyotype presenting developmental delay, facial dysmorphism, cerebral dysmyelination, and other abnormalities

VEGF-A regulated by progesterone governs uterine angiogenesis and vascular remodelling during pregnancy

Peer reviewe

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimers disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The time orientation and 3-word recall score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.The publication costs, design of the study, data management and writing the manuscript for this article were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538), Korea Ministry of Health & Welfare, and from the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Korean Government (MSIP; No. 2014M3C7A1064752)