2,086 research outputs found
Ser-634 and Ser-636 of Kaposi’s Sarcoma-Associated Herpesvirus RTA are Involved in Transactivation and are Potential Cdk9 Phosphorylation Sites
The replication and transcription activator (RTA) of Kaposi’s sarcoma-associated herpesvirus (KSHV), K-RTA, is a lytic switch protein that moderates the reactivation process of KSHV latency. By mass spectrometric analysis of affinity purified K-RTA, we showed that Thr-513 or Thr-514 was the primary in vivo phosphorylation site. Thr-513 and Thr-514 are proximal to the nuclear localization signal (527KKRK530) and were previously hypothesized to be target sites of Ser/Thr kinase hKFC. However, substitutions of Thr with Ala at 513 and 514 had no effect on K-RTA subcellular localization or transactivation activity. By contrast, replacement of Ser with Ala at Ser-634 and Ser-636 located in a Ser/Pro-rich region of K-RTA, designated as S634A/S636A, produced a polypeptide with ∼10 kDa shorter in molecular weight and reduced transactivation in a luciferase reporter assay relative to the wild type. In contrast to prediction, the decrease in molecular weight was not due to lack of phosphorylation because the overall Ser and Thr phosphorylation state in K-RTA and S634A/S636A were similar, excluding that Ser-634 or Ser-636 motif served as docking sites for consecutive phosphorylation. Interestingly, S634A/S636A lost ∼30% immuno-reactivity to MPM2, an antibody specific to pSer/pThr-Pro motif, indicating that 634SPSP637 motif was in vivo phosphorylated. By in vitro kinase assay, we showed that K-RTA is a substrate of CDK9, a Pro-directed Ser/Thr kinase central to transcriptional regulation. Importantly, the capability of K-RTA in associating with endogenous CDK9 was reduced in S634A/S636A, which suggested that Ser-634 and Ser-636 may be involved in CDK9 recruitment. In agreement, S634A/S636A mutant exhibited ∼25% reduction in KSHV lytic cycle reactivation relative to that by the wild type K-RTA. Taken together, our data propose that Ser-634 and Ser-636 of K-RTA are phosphorylated by host transcriptional kinase CDK9 and such a process contributes to a full transcriptional potency of K-RTA
Image operator learning coupled with CNN classification and its application to staff line removal
Many image transformations can be modeled by image operators that are
characterized by pixel-wise local functions defined on a finite support window.
In image operator learning, these functions are estimated from training data
using machine learning techniques. Input size is usually a critical issue when
using learning algorithms, and it limits the size of practicable windows. We
propose the use of convolutional neural networks (CNNs) to overcome this
limitation. The problem of removing staff-lines in music score images is chosen
to evaluate the effects of window and convolutional mask sizes on the learned
image operator performance. Results show that the CNN based solution
outperforms previous ones obtained using conventional learning algorithms or
heuristic algorithms, indicating the potential of CNNs as base classifiers in
image operator learning. The implementations will be made available on the
TRIOSlib project site.Comment: To appear in ICDAR 201
A Longitudinal Historical Population Database in Asia. The Taiwanese Historical Household Registers Database (1906–1945)
For the past 35 years, the Taiwan Historical Household Registers Database (THHRD) has been significant for historical demographic research on Asia. In recent years, researchers have continued adding new demographic information to the database. This allows for the expansion of research on the topic of historical households in the region. However, there are still many issues to address in the field of Asian historical demography. This paper provides a brief introduction on the uses of THHRD for future research
Vitamin D status in non-supplemented postmenopausal Taiwanese women with osteoporosis and fragility fracture
Novel Common Genetic Susceptibility Loci for Colorectal Cancer
BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screenin
3D bioactive composite scaffolds for bone tissue engineering
Bone is the second most commonly transplanted tissue worldwide, with over four million operations using bone grafts or bone substitute materials annually to treat bone defects. However, significant limitations affect current treatment options and clinical demand for bone grafts continues to rise due to conditions such as trauma, cancer, infection and arthritis. Developing bioactive three-dimensional (3D) scaffolds to support bone regeneration has therefore become a key area of focus within bone tissue engineering (BTE). A variety of materials and manufacturing methods including 3D printing have been used to create novel alternatives to traditional bone grafts. However, individual groups of materials including polymers, ceramics and hydrogels have been unable to fully replicate the properties of bone when used alone. Favourable material properties can be combined and bioactivity improved when groups of materials are used together in composite 3D scaffolds. This review will therefore consider the ideal properties of bioactive composite 3D scaffolds and examine recent use of polymers, hydrogels, metals, ceramics and bio-glasses in BTE. Scaffold fabrication methodology, mechanical performance, biocompatibility, bioactivity, and potential clinical translations will be discussed
Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries
In the version of this article initially published, the author affiliations incorrectly listed “Candiolo Cancer Institute FPO-IRCCS, Candiolo (TO), Italy” as “Candiolo Cancer Institute, Candiolo, Italy.” The change has been made to the HTML and PDF versions of the article
The trans-ancestral genomic architecture of glycemic traits
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk
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