Activation of AMP-activated Protein Kinase Is Essential for Lysophosphatidic Acid-induced Cell Migration in Ovarian Cancer Cells

Lysophosphatidic acid (LPA) is a bioactive phospholipid that affects various biological functions, such as cell proliferation, migration, and survival, through LPA receptors. Among them, the motility of cancer cells is an especially important activity for invasion and metastasis. Recently, AMP-activated protein kinase (AMPK), an energy-sensing kinase, was shown to regulate cell migration. However, the specific role of AMPK in cancer cell migration is unknown. The present study investigated whether LPA could induce AMPK activation and whether this process was associated with cell migration in ovarian cancer cells. We found that LPA led to a striking increase in AMPK phosphorylation in pathways involving the phospholipase C-beta 3 (PLC-beta 3) and calcium/calmodulin-dependent protein kinase kinase beta (CaMKK beta) in SKOV3 ovarian cancer cells. siRNA-mediated knockdown of AMPK beta 1, PLC-beta 3, or (CaMKK beta) impaired the stimulatory effects of LPA on cell migration. Furthermore, we found that knockdown of AMPK beta 1 abrogated LPA-induced activation of the small GTPase RhoA and ezrin/radixin/moesin proteins regulating membrane dynamics as membrane-cytoskeleton linkers. In ovarian cancer xenograft models, knockdown of AMPK significantly decreased peritoneal dissemination and lung metastasis. Taken together, our results suggest that activation of AMPK by LPA induces cell migration through the signaling pathway to cytoskeletal dynamics and increases tumor metastasis in ovarian cancer.close161

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

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

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

Analyses of pig genomes provide insight into porcine demography and evolution

For 10,000 years pigs and humans have shared a close and complex relationship. From domestication to modern breeding practices, humans have shaped the genomes of domestic pigs. Here we present the assembly and analysis of the genome sequence of a female domestic Duroc pig (Sus scrofa) and a comparison with the genomes of wild and domestic pigs from Europe and Asia. Wild pigs emerged in South East Asia and subsequently spread across Eurasia. Our results reveal a deep phylogenetic split between European and Asian wild boars ∼1 million years ago, and a selective sweep analysis indicates selection on genes involved in RNA processing and regulation. Genes associated with immune response and olfaction exhibit fast evolution. Pigs have the largest repertoire of functional olfactory receptor genes, reflecting the importance of smell in this scavenging animal. The pig genome sequence provides an important resource for further improvements of this important livestock species, and our identification of many putative disease-causing variants extends the potential of the pig as a biomedical model

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. 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

有限 可換群 G에 대한 End(G)와 Aut(G)의 位數

이 論文에서 有限可換群 G의 準同型寫像 전체의 環 End(G)와 그 單元群 U(End(G)) 즉 Aut(G)의 位數를 결정하는 다음 定理를 증명하였다

Robust estimators for target tracking

Several non-adaptive robust estimator design methods are discussed in this thesis. Constant estimator gains that guarantee the acceptable performance of the estimator in the presence of target model uncertainties are computed. Two approaches are considered for designing robust estimators: a theoretical approach and a trajectory-based approach. In the theoretical approach, cost functions are related to the estimation error variance obtainable from the Lyapunov equation under the assumption of Gaussian white noise system input. Several methods for designing estimators robust to parameter variations in the plant model are presented. A mechanism for trading off small estimator error variance and low sensitivity to unknown parameter variations is developed using the estimator gains computed from an iterative algorithm. A robust estimator design method that considers both real parameter variations and the unknown inputs is also presented. Trading off the robustness to real parameter variations and the robustness to unknown inputs is possible using a design parameter. In the trajectory-based approach, the cost functions are related to the estimation error with target trajectories generated by a realistic (deterministic) pilot input. An estimator is designed to have acceptable performance in tracking several different target trajectories with a capability to trade off the mean and maximum estimation error. These robust estimator design methods are applied to the aircraft tracking problem. A tracker with a mathematical model capable of using both position data and orientation data is designed to be robust to the uncertainties of the aircraft being tracked. This tracker\u27s performance is compared with the performance of the conventional $\alpha - \beta$ tracker that uses only position data

整數環 위의 周期群 基底의 群環에 同型인 群環

이 論文에서 有限群 G에 대한 整數環 위의 群環 Z〔G〕에 대하여, Berman, Glauberman, Whitcomb, Jackson, Passman 등에 의하여 밝혀진 內容을 周期群 G에 대한 群環 Z〔G〕에 一般化하여 다음과 같은 結果가 성립함을 밝혔다. 周期群 G,H에 대하여, Z〔G〕≅ Z〔H〕이면 다음이 성립한다. 1. Z(G)≅Z(H). 단, Z(G), Z(H)는 각각 群 G,H의 中心이다. 2. G/G≅H/H. 단, G',H'은 각각 G,H의 交換子部分群이다. 3. {l}=Z₀(G)⊆Z₁(G)⊆…⊆Zn(G)⊆…, {I} =Z₀(H)⊆Z₁(H)⊆…⊆Zn(H)⊆… 을 각각 G, H의 upper central series라 하면, 모든 n에 대하여 Z〔G/Zn(G)〕≅Z〔HjZη(H)〕이고 Zn-1(G)/Zn(G)≅Zn-1(H)/Zn(H). 4. trG, trH를 각각 Z〔G〕, Z〔H〕의 trace map이라 하면, 임의의 同型寫像 ϴ: Z〔G〕→Z〔H〕에 대하여 trHϴ=trG. 5. ϴ: Z〔G〕→Z〔H〕를 同型寫像이라 할 때, 임의의 α∊C(Z〔G〕)에 대하여 ϴ(α*)=ϴ(α)* 단, C(Z〔G〕)는 Z〔G〕의 中心이고 α=∑axx라 할 때 a*=∑axx-1이다. 6. L₁,L₂를 각각 G, H의 有限正規部分群 전체로 이루어진 束(lattice)이라 할 때, 각 N∊L₁에 대하여 ⨍(N)=η(N)인 束同型寫像 ⨍:L₁→L₂와 環同型寫像 η:Z〔G〕→Z〔H〕가 존재하고 Z〔G/N〕≅ Z〔H/η(N)〕이다. 7. G를 임의의 群, H를 G의 周期部分群이라 할 때, 群 H/H'은 덧셈군 ω(Z〔H〕)Z〔G〕/ω(Z〔H〕)ω(Z〔G〕)과 同型이다. 단, ω(Z〔G〕), ω(Z〔H〕)은 각각 Z〔G〕, Z〔H〕의 augmentation ideal이다

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In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.clos