Uncoupling proteins, dietary fat and the metabolic syndrome

There has been intense interest in defining the functions of UCP2 and UCP3 during the nine years since the cloning of these UCP1 homologues. Current data suggest that both UCP2 and UCP3 proteins share some features with UCP1, such as the ability to reduce mitochondrial membrane potential, but they also have distinctly different physiological roles. Human genetic studies consistently demonstrate the effect of UCP2 alleles on type-2 diabetes. Less clear is whether UCP2 alleles influence body weight or body mass index (BMI) with many studies showing a positive effect while others do not. There is strong evidence that both UCP2 and UCP3 protect against mitochondrial oxidative damage by reducing the production of reactive oxygen species. The evidence that UCP2 protein is a negative regulator of insulin secretion by pancreatic β-cells is also strong: increased UCP2 decreases glucose stimulated insulin secretion ultimately leading to β-cell dysfunction. UCP2 is also neuroprotective, reducing oxidative stress in neurons. UCP3 may also transport fatty acids out of mitochondria thereby protecting the mitochondria from fatty acid anions or peroxides. Current data suggest that UCP2 plays a role in the metabolic syndrome through down-regulation of insulin secretion and development of type-2 diabetes. However, UCP2 may protect against atherosclerosis through reduction of oxidative stress and both UCP2 and UCP3 may protect against obesity. Thus, these UCP1 homologues may both contribute to and protect from the markers of the metabolic syndrome

Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice

<p>Abstract</p> <p>Background</p> <p>Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia.</p> <p>Results</p> <p>In order to determine the genetic factors that contribute to these T2D related characteristics in TH mice, we interbred TH mice with C57BL/6J (B6) mice. The parental, F1, and F2 mice were phenotyped at 8, 12, 16, 20, and 24 weeks of age for 4-hour fasting plasma triglyceride, cholesterol, insulin, and glucose levels and body, fat pad and carcass weights. The F2 mice were genotyped genome-wide and used for quantitative trait locus (QTL) mapping. We also applied a genetical genomic approach using a subset of the F2 mice to seek candidate genes underlying the QTLs. Major QTLs were detected on chromosomes (Chrs) 1, 11, 4, and 8 for hypertriglyceridemia, 1 and 3 for hypercholesterolemia, 4 for hyperglycemia, 11 and 1 for body weight, 1 for fat pad weight, and 11 and 14 for carcass weight. Most alleles, except for Chr 3 and 14 QTLs, increased phenotypic values when contributed by the TH strain. Fourteen pairs of interacting loci were detected, none of which overlapped the major QTLs. The QTL interval linked to hypercholesterolemia and hypertriglyceridemia on distal Chr 1 contains <it>Apoa2 </it>gene. Sequencing analysis revealed polymorphisms of <it>Apoa2 </it>in TH mice, suggesting <it>Apoa2 </it>as the candidate gene for the hyperlipidemia QTL. Gene expression analysis added novel information and aided in selection of candidates underlying the QTLs.</p> <p>Conclusions</p> <p>We identified several genetic loci that affect the quantitative variations of plasma lipid and glucose levels and obesity traits in a TH × B6 intercross. Polymorphisms in <it>Apoa2 </it>gene are suggested to be responsible for the Chr 1 QTL linked to hypercholesterolemia and hypertriglyceridemia. Further, genetical genomic analysis led to potential candidate genes for the QTLs.</p

The uncoupling protein 1 gene, UCP1, is expressed in mammalian islet cells and associated with acute insulin response to glucose in African American families from the IRAS Family Study

BACKGROUND: Variants of uncoupling protein genes UCP1 and UCP2 have been associated with a range of traits. We wished to evaluate contributions of known UCP1 and UCP2 variants to metabolic traits in the Insulin Resistance and Atherosclerosis (IRAS) Family Study. METHODS: We genotyped five promoter or coding single nucleotide polymorphisms (SNPs) in 239 African American (AA) participants and 583 Hispanic participants from San Antonio (SA) and San Luis Valley. Generalized estimating equations using a sandwich estimator of the variance and exchangeable correlation to account for familial correlation were computed for the test of genotypic association, and dominant, additive and recessive models. Tests were adjusted for age, gender and BMI (glucose homeostasis and lipid traits), or age and gender (obesity traits), and empirical P-values estimated using a gene dropping approach. RESULTS: UCP1 A-3826G was associated with AIR(g )in AA (P = 0.006) and approached significance in Hispanic families (P = 0.054); and with HDL-C levels in SA families (P = 0.0004). Although UCP1 expression is reported to be restricted to adipose tissue, RT-PCR indicated that UCP1 is expressed in human pancreas and MIN-6 cells, and immunohistochemistry demonstrated co-localization of UCP1 protein with insulin in human islets. UCP2 A55V was associated with waist circumference (P = 0.045) in AA, and BMI in SA (P = 0.018); and UCP2 G-866A with waist-to-hip ratio in AA (P = 0.016). CONCLUSION: This study suggests a functional variant of UCP1 contributes to the variance of AIR(g )in an AA population; the plausibility of this unexpected association is supported by the novel finding that UCP1 is expressed in islets

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO's second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h095%=3.47×10-25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering. © 2019 American Physical Society

Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO’s second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h95%0=3.47×10−25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

A preprint version of the article is available at: arXiv:2402.15366v2 [physics.ins-det], https://arxiv.org/abs/2402.15366 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/MLG-23-001 (CMS Public Pages). Report numbers: CMS-MLG-23-001, CERN-EP-2023-303.Data Availability: No datasets were generated or analyzed during the current study.Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.SCOAP3. Open access funding provided by CERN (European Organization for Nuclear Research

First Measurement of the Hubble Constant from a Dark Standard Siren using the Dark Energy Survey Galaxies and the LIGO/Virgo Binary-Black-hole Merger GW170814

We present a multi-messenger measurement of the Hubble constant H 0 using the binary–black-hole merger GW170814 as a standard siren, combined with a photometric redshift catalog from the Dark Energy Survey (DES). The luminosity distance is obtained from the gravitational wave signal detected by the Laser Interferometer Gravitational-Wave Observatory (LIGO)/Virgo Collaboration (LVC) on 2017 August 14, and the redshift information is provided by the DES Year 3 data. Black hole mergers such as GW170814 are expected to lack bright electromagnetic emission to uniquely identify their host galaxies and build an object-by-object Hubble diagram. However, they are suitable for a statistical measurement, provided that a galaxy catalog of adequate depth and redshift completion is available. Here we present the first Hubble parameter measurement using a black hole merger. Our analysis results in ${H}_{0}={75}_{-32}^{+40}\,\mathrm{km}\,{{\rm{s}}}^{-1}\,{\mathrm{Mpc}}^{-1}$, which is consistent with both SN Ia and cosmic microwave background measurements of the Hubble constant. The quoted 68% credible region comprises 60% of the uniform prior range [20, 140] km s−1 Mpc−1, and it depends on the assumed prior range. If we take a broader prior of [10, 220] km s−1 Mpc−1, we find {H}_{0 {78}_{-24}^{+96}\,\mathrm{km}\,{{\rm{s}}}^{-1}\,{\mathrm{Mpc}}^{-1} (57% of the prior range). Although a weak constraint on the Hubble constant from a single event is expected using the dark siren method, a multifold increase in the LVC event rate is anticipated in the coming years and combinations of many sirens will lead to improved constraints on H 0