Human pluripotent stem cells (hPSCs) have promising therapeutic applications due to their infinite capacity for self-renewal and pluripotency. Genomic stability is imperative for the clinical use of hPSCs; however, copy number variation (CNV), especially recurrent CNV at 20q11.21, may contribute genomic instability of hPSCs. Furthermore, the effects of CNVs in hPSCs at the whole-transcriptome scale are poorly understood. This study aimed to examine the functional in vivo and in vitro effects of frequently detected CNVs at 20q11.21 during early-stage differentiation of hPSCs. Comprehensive transcriptome profiling of abnormal hPSCs revealed that the differential gene expression patterns had a negative effect on differentiation potential. Transcriptional heterogeneity identified by single-cell RNA sequencing (scRNA-seq) of embryoid bodies from two different isogenic lines of hPSCs revealed alterations in differentiated cell distributions compared with that of normal cells. RNA-seq analysis of 22 teratomas identified several differentially expressed lineage-specific markers in hPSCs with CNVs, consistent with the histological results of the altered ecto/meso/endodermal ratio due to CNVs. Our results suggest that CNV amplification contributes to cell proliferation, apoptosis, and cell fate specification. This work shows the functional consequences of recurrent genetic abnormalities and thereby provides evidence to support the development of cell-based applications.

Osteoporosis is a condition characterized by decreased bone mineral density (BMD) and reduced bone strength, leading to an increased risk of fractures. Here, to identify novel risk variants for susceptibility to osteoporosis-related traits, an exome-wide association study is performed with 6,485 exonic single nucleotide polymorphisms (SNPs) in 2,666 women of two Korean study cohorts. The rs2781 SNP in UBAP2 gene is suggestively associated with osteoporosis and BMD with p-values of 6.1 × 10⁻⁷ (odds ratio = 1.72) and 1.1 × 10⁻⁷ in the case-control and quantitative analyzes, respectively. Knockdown of Ubap2 in mouse cells decreases osteoblastogenesis and increases osteoclastogenesis, and knockdown of ubap2 in zebrafish reveals abnormal bone formation. Ubap2 expression is associated with E-cadherin (Cdh1) and Fra1 (Fosl1) expression in the osteclastogenesis-induced monocytes. UBAP2 mRNA levels are significantly reduced in bone marrow, but increased in peripheral blood, from women with osteoporosis compared to controls. UBAP2 protein level is correlated with the blood plasma level of the representative osteoporosis biomarker osteocalcin. These results suggest that UBAP2 has a critical role in bone homeostasis through the regulation of bone remodeling.

Multiple endocrine neoplasia type 1 (MEN1) syndrome is an autosomal dominant hereditary disorder characterized by the presence of endocrine tumors affecting the parathyroid, pancreas, and pituitary. A heterozygous germline inactivating mutation in the MEN1 gene (first hit) may be followed by somatic loss of the remaining normal copy or somatic mutations in the MEN1 gene (second hit). Whole-exome sequencing has been successfully used to elucidate the mutations associated with the different types of tumors. We performed whole-exome sequencing (WES) on three parathyroid tumors, one pancreatic insulinoma, and a blood sample taken from the same patient with MEN1 to study tumor heterogeneity in MEN1 originating from different tumors. We identified a novel frame-shift deletion (c.1382_1383delAG, p.E461GfsX69) in the MEN1 gene using WES, which was confirmed by Sanger sequencing. WES and the SNP array revealed somatic LOH on chromosome 11 in parathyroid tumors (left upper, left lower, and right upper parathyroid). However, we did not detect a somatic MEN1 gene mutation or LOH in the pancreatic insulinoma. WES revealed two somatic functional variants outside the MEN1 gene in the pancreatic insulinoma. This study revealed heterogeneity among tumors in the same patient with MEN1, suggesting that different tumor-specific tumorigenic mechanisms may contribute to the pathogenesis of MEN1 tumors. The present study supports the clinical applicability of the WES strategy to research on multiple tumor samples and blood.

Primary hepatic angiosarcoma (PHA) is a rare and aggressive liver malignancy of endothelial cell origin and is associated with poor outcome. Pre-operative confirmation of the diagnosis is challenging, as clinical and radiological findings are generally non-specific. Very rarely, spontaneous haemoperitoneum may occur due to the spontaneous rupture of previously undiagnosed PHA. We describe a case of a 28-year-old male with haemoperitoneum due to the rupture of previously undiagnosed PHA. After failing to respond to the non-operative measures, the patient underwent emergency partial liver resection and recovered without any post-operative complications. Histopathological examination of the specimen confirmed the diagnosis of PHA. Two months after the operation, the patient represented with advanced metastatic disease and disseminated intravascular coagulation (DIC). The patient died one month after discharge. A patient with PHA presents a diagnostic challenge due to its rare incidence and non-specific clinical findings. Spontaneous intra-abdominal haemorrhage can occur due to PHA rupture and carries a dismal prognosis. In addition to emergency haemorrhage control, complete surgical resection with clear margins is the definitive treatment to date, however, most cases of PHA are unresectable at diagnosis and recurrence is common even after complete resection. PHA is associated with very poor outcomes, due to its rapid progression, early recurrence, and metastatic nature. The median survival is approximately 5 months. Haemoperitoneum secondary to rupture of previously undiagnosed PHA is uncommon and is a poor prognostic indicator. Complete surgical resection of the disease is challenging and there is no established treatment.

We study a basic information ranking problem in networks where each node holds an individual preference over a set of items and the goal for each node is to identify a sorted list of items with the largest aggregate preference. We would like to achieve this with a fully decentralized algorithm that uses a limited per-node memory and limited pair-wise communications. We show how this problem can be reduced to a plurality selection problem where the goal for each node is to identify an item with the largest aggregate ranking score, and show that solving the reduced problem solves the original ranking problem with high probability. Then we introduce a simple and natural plurality selection algorithm for the selection over m >; 1 items that uses only log₂(m) + 1 bits of per-node memory and per pair-wise communication. We prove correctness of the algorithm with high probability as the number of nodes grows large for the case when each node communicates with any other node, and establish tight convergence time bounds. The information ranking problem studied in this paper is a basic ranking problem that arises in various applications such as sorting elements in distributed computing systems, parallel databases, and may as well serve as a model of decentralized inference and opinion formation in distributed environments.