Hypermethylation of the TGF-β target, ABCA1 is associated with poor prognosis in ovarian cancer patients

Background The dysregulation of transforming growth factor-β (TGF-β) signaling plays a crucial role in ovarian carcinogenesis and in maintaining cancer stem cell properties. Classified as a member of the ATP-binding cassette (ABC) family, ABCA1 was previously identified by methylated DNA immunoprecipitation microarray (mDIP-Chip) to be methylated in ovarian cancer cell lines, A2780 and CP70. By microarray, it was also found to be upregulated in immortalized ovarian surface epithelial (IOSE) cells following TGF-β treatment. Thus, we hypothesized that ABCA1 may be involved in ovarian cancer and its initiation. Results We first compared the expression level of ABCA1 in IOSE cells and a panel of ovarian cancer cell lines and found that ABCA1 was expressed in HeyC2, SKOV3, MCP3, and MCP2 ovarian cancer cell lines but downregulated in A2780 and CP70 ovarian cancer cell lines. The reduced expression of ABCA1 in A2780 and CP70 cells was associated with promoter hypermethylation, as demonstrated by bisulfite pyro-sequencing. We also found that knockdown of ABCA1 increased the cholesterol level and promoted cell growth in vitro and in vivo. Further analysis of ABCA1 methylation in 76 ovarian cancer patient samples demonstrated that patients with higher ABCA1 methylation are associated with high stage (P = 0.0131) and grade (P = 0.0137). Kaplan-Meier analysis also found that patients with higher levels of methylation of ABCA1 have shorter overall survival (P = 0.019). Furthermore, tissue microarray using 55 ovarian cancer patient samples revealed that patients with a lower level of ABCA1 expression are associated with shorter progress-free survival (P = 0.038). Conclusions ABCA1 may be a tumor suppressor and is hypermethylated in a subset of ovarian cancer patients. Hypermethylation of ABCA1 is associated with poor prognosis in these patients

INSPIRESat-1: An Ionosphere and Solar X-ray Observing MicroSat

The International Satellite Program in Research and Education’s (INSPIRE) first satellite is an Ionosphere and Solar X-ray observing microsat slated for launch in November of 2019 onboard an ISRO Polar Satellite Launch Vehicle. The microsat has a mission specific structure fitting on a PSLV ring deployer. There are two payloads aboard with two different science objectives. The Compact Ionosphere Probe (CIP) will take in-situ measurements of ion density, composition, temperature, velocity, and electron temperature. The CIP is a smaller version of the Advanced Ionosphere Probe (AIP, both developed in Taiwan) currently operating onboard the FORMOSat-5. This instrument is capable of sampling the ionosphere at 1 and 8 Hz. The second payload is the Dual Aperture X-ray Solar spectrometer (DAXSS). DAXSS is a modified Amptek X123 that will observe Solar X-rays, specifically soft X-rays. Hot plasma in the sun’s corona is best measured in the soft X-rays. Many emission lines for important elements (Fe, Si, Mg, S, etc) are in the soft X-ray range. Soft X-rays are always present in the sun but 100 times brighter during flares, these observations will also lend to understanding the temperature difference between the sun’s corona and photosphere. The solar soft x-rays are also important for the Earth’s Ionosphere, adding to the ionosphere observations made by CIP. The DAXSS instrument has heritage from a NASA calibration rocket experiment and two cubesats, MINXSS 1 and 2. The newer model Amptek X123 has much improved energy resolution for the X-ray spectrum. The primary science objectives of the INSPIRESat-1 are twofold. First, enabling the characterization of the temporal and spatial distributions of small-scale plasma irregularities like plasma bubbles and the Midnight Temperature Maximum (MTM) in season, location, and time by CIP. Second, giving a greater understanding of why the Sun’s corona is orders of magnitude hotter than the photosphere, why there is an abundance of elements change during different solar events, and how these events (observed with greater soft x-ray fidelity) effect the earth’s ionosphere. In this paper, we present science expectations for the INSPIRESat-1 and a concept for coordinated Ionospheric measurements covering several altitudes and local times using three satellite platforms carrying the same CIP instrument (INSPIRESat-1, IDEASat/INSPIRESat-2, INSPIRESat-4, FORMOSat-5). We describe the development of DAXSS and how the dual aperture prevents the need for two X123 to get the similar data. We also highlight the unique development of the INSPIRESat-1 microsat being developed by international collaboration across three different universities

Integration, Launch, and First Results from IDEASSat/INSPIRESat-2 - A 3U CubeSat for Ionospheric Physics and Multi-National Capacity Building

The Ionospheric Dynamics and Attitude Subsystem Satellite (IDEASSat) is a 3U CubeSat carrying a Compact Ionospheric Probe (CIP) to detect ionospheric irregularities that can impact the usability and accuracy of global satellite navigation systems (GNSS), as well as satellite and terrestrial over the horizon communications. The spacecraft was developed by National Central University (NCU) in Taiwan, with additional development and operational support from partners in the International Satellite Program in Science and Education (INSPIRE) consortium. The spacecraft system needed to accommodate these mission objectives required three axis attitude control, dual band communications capable of supporting both tracking, telemetry and command (TT&C) and science data downlink, as well as flight software and ground systems capable of supporting the autonomous operation and short contact times inherent to a low Earth orbit mission developed on a limited university budget with funding agency-imposed constraints. As the first spacecraft developed at NCU, lessons learned during the development, integration, and operation of IDEASSat have proven to be crucial to the objective of developing a sustainable small satellite program. IDEASSat was launched successfully on January 24, 2021 aboard the SpaceX Falcon 9 Transporter 1 flight. and successfully began operations, demonstrating power, thermal, and structural margins, as well as validation of uplink and downlink communications functionality, and autonomous operation. A serious anomaly occurred after 22 days on orbit when communication with the spacecraft were abruptly lost. Communication was re-established after 1.5 months for sufficient time to downlink stored flight data, which allowed the cause of the blackout to be identified to a high level of confidence and precision. In this paper, we will report on experiences and anomalies encountered during the final flight model integration and delivery, commissioning, and operations. The agile support from the international amateur radio community and INSPIRE partners were extremely helpful in this process, especially during the initial commissioning phase following launch. It is hoped that the lessons learned reported here will be helpful for other university teams working to develop spaceflight capacity

Review on the Modeling of Electrostatic MEMS

Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices

Oncologic impact of delay between diagnosis and radical nephroureterectomy

PurposeThis study aimed to evaluate the oncological outcome of delayed surgical wait time from the diagnosis of upper tract urothelial carcinoma (UTUC) to radical nephroureterectomy (RNU).MethodsIn this multicenter retrospective study, medical records were collected between 1988 and 2021 from 18 participating Taiwanese hospitals under the Taiwan UTUC Collaboration Group. Patients were dichotomized into the early (≤90 days) and late (>90 days) surgical wait-time groups. Overall survival, disease-free survival, and bladder recurrence-free survival were calculated using the Kaplan–Meier method and multivariate Cox regression analysis. Multivariate analysis was performed using stepwise linear regression.ResultsOf the 1251 patients, 1181 (94.4%) were classifed into the early surgical wait-time group and 70 (5.6%) into the late surgical wait-time group. The median surgical wait time was 21 days, and the median follow-up was 59.5 months. Our study showed delay-time more than 90 days appeared to be associated with worse overall survival (hazard ratio [HR] 1.974, 95% confidence interval [CI] 1.166−3.343, p = 0.011), and disease-free survival (HR 1.997, 95% CI 1.137−3.507, p = 0.016). This remained as an independent prognostic factor after other confounding factors were adjusted. Age, ECOG performance status, Charlson Comorbidity Index (CCI), surgical margin, tumor location and adjuvant systemic therapy were independent prognostic factors for overall survival. Tumor location and adjuvant systemic therapy were also independent prognostic factors for disease-free survival.ConclusionsFor patients with UTUC undergoing RNU, the surgical wait time should be minimized to less than 90 days. Prolonged delay times may be associated with poor overall and disease-free survival

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

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