Impact of maternal high fat diet on hypothalamic transcriptome in neonatal Sprague Dawley rats

Maternal consumption of a high fat diet during early development has been shown to impact the formation of hypothalamic neurocircuitry, thereby contributing to imbalances in appetite and energy homeostasis and increasing the risk of obesity in subsequent generations. Early in postnatal life, the neuronal projections responsible for energy homeostasis develop in response to appetite-related peptides such as leptin. To date, no study characterises the genome-wide transcriptional changes that occur in response to exposure to high fat diet during this critical window. We explored the effects of maternal high fat diet consumption on hypothalamic gene expression in Sprague Dawley rat offspring at postnatal day 10. RNA-sequencing enabled discovery of differentially expressed genes between offspring of dams fed a high fat diet and offspring of control diet fed dams. Female high fat diet offspring displayed altered expression of 86 genes (adjusted P-value<0.05), including genes coding for proteins of the extra cellular matrix, particularly Collagen 1a1 (Col1a1), Col1a2, Col3a1, and the imprinted Insulin-like growth factor 2 (Igf2) gene. Male high fat diet offspring showed significant changes in collagen genes (Col1a1 and Col3a1) and significant upregulation of two genes involved in regulation of dopamine availability in the brain, tyrosine hydroxylase (Th) and dopamine reuptake transporter Slc6a3 (also known as Dat1). Transcriptional changes were accompanied by increased body weight, body fat and body length in the high fat diet offspring, as well as altered blood glucose and plasma leptin. Transcriptional changes identified in the hypothalamus of offspring of high fat diet mothers could alter neuronal projection formation during early development leading to abnormalities in the neuronal circuitry controlling appetite in later life, hence priming offspring to the development of obesity

Improved Standardization of Type II-P Supernovae: Application to an Expanded Sample

In the epoch of precise and accurate cosmology, cross-confirmation using a variety of cosmographic methods is paramount to circumvent systematic uncertainties. Owing to progenitor histories and explosion physics differing from those of Type Ia SNe (SNe Ia), Type II-plateau supernovae (SNe II-P) are unlikely to be affected by evolution in the same way. Based on a new analysis of 17 SNe II-P, and on an improved methodology, we find that SNe II-P are good standardizable candles, almost comparable to SNe Ia. We derive a tight Hubble diagram with a dispersion of 10% in distance, using the simple correlation between luminosity and photospheric velocity introduced by Hamuy & Pinto 2002. We show that the descendent method of Nugent et al. 2006 can be further simplified and that the correction for dust extinction has low statistical impact. We find that our SN sample favors, on average, a very steep dust law with total to selective extinction R_V<2. Such an extinction law has been recently inferred for many SNe Ia. Our results indicate that a distance measurement can be obtained with a single spectrum of a SN II-P during the plateau phase combined with sparse photometric measurements.Comment: ApJ accepted version. Minor change

Neighborhood socioeconomic status, Medicaid coverage and medical management of myocardial infarction: Atherosclerosis risk in communities (ARIC) community surveillance

<p>Abstract</p> <p>Background</p> <p>Pharmacologic treatments are efficacious in reducing post-myocardial infarction (MI) morbidity and mortality. The potential influence of socioeconomic factors on the receipt of pharmacologic therapy has not been systematically examined, even though healthcare utilization likely influences morbidity and mortality post-MI. This study aims to investigate the association between socioeconomic factors and receipt of evidence-based treatments post-MI in a community surveillance setting.</p> <p>Methods</p> <p>We evaluated the association of census tract-level neighborhood household income (nINC) and Medicaid coverage with pharmacologic treatments (aspirin, beta [β]-blockers and angiotensin converting enzyme [ACE] inhibitors; optimal therapy, defined as receipt of two or more treatments) received during hospitalization or at discharge among 9,608 MI events in the ARIC community surveillance study (1993-2002). Prevalence ratios (PR, 95% CI), adjusted for the clustering of hospitalized MI events within census tracts and within patients, were estimated using Poisson regression.</p> <p>Results</p> <p>Seventy-eight percent of patients received optimal therapy. Low nINC was associated with a lower likelihood of receiving β-blockers (0.93, 0.87-0.98) and a higher likelihood of receiving ACE inhibitors (1.13, 1.04-1.22), compared to high nINC. Patients with Medicaid coverage were less likely to receive aspirin (0.92, 0.87-0.98), compared to patients without Medicaid coverage. These findings were independent of other key covariates.</p> <p>Conclusions</p> <p>nINC and Medicaid coverage may be two of several socioeconomic factors influencing the complexities of medical care practice patterns.</p

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice