Comparison of four mathematical models to analyze indicator-dilution curves in the coronary circulation

While several models have proven to result in accurate estimations when measuring cardiac output using indicator dilution, the mono-exponential model has primarily been chosen for deriving coronary blood/plasma volume. In this study, we compared four models to derive coronary plasma volume using indicator dilution; the mono-exponential, power-law, gamma-variate, and local density random walk (LDRW) model. In anesthetized goats (N = 14), we determined the distribution volume of high molecular weight (2,000 kDa) dextrans. A bolus injection (1.0 ml, 0.65 mg/ml) was given intracoronary and coronary venous blood samples were taken every 0.5–1.0 s; outflow curves were analyzed using the four aforementioned models. Measurements were done at baseline and during adenosine infusion. Absolute coronary plasma volume estimates varied by ~25% between models, while the relative volume increase during adenosine infusion was similar for all models. The gamma-variate, LDRW, and mono-exponential model resulted in volumes corresponding with literature, whereas the power-model seemed to overestimate the coronary plasma volume. The gamma-variate and LDRW model appear to be suitable alternative models to the mono-exponential model to analyze coronary indicator-dilution curves, particularly since these models are minimally influenced by outliers and do not depend on data of the descending slope of the curve only

Bub1 Is a Fission Yeast Kinetochore Scaffold Protein, and Is Sufficient to Recruit other Spindle Checkpoint Proteins to Ectopic Sites on Chromosomes

The spindle checkpoint delays anaphase onset until all chromosomes have attached in a bi-polar manner to the mitotic spindle. Mad and Bub proteins are recruited to unattached kinetochores, and generate diffusible anaphase inhibitors. Checkpoint models propose that Mad1 and Bub1 act as stable kinetochore-bound scaffolds, to enhance recruitment of Mad2 and Mad3/BubR1, but this remains untested for Bub1. Here, fission yeast FRAP experiments confirm that Bub1 stably binds kinetochores, and by tethering Bub1 to telomeres we demonstrate that it is sufficient to recruit anaphase inhibitors in a kinase-independent manner. We propose that the major checkpoint role for Bub1 is as a signalling scaffold

Breast cancer chemoprevention: beyond tamoxifen

A large number of new potential chemoprevention agents are available that target molecular abnormalities found in estrogen receptor (ER)-negative and/or ER-positive precancerous breast tissue and have side effect profiles that differ from tamoxifen. Classes of agents currently undergoing evaluation in clinical prevention trials or those for which testing is planned in the near future include new selective ER modulators, aromatase inactivators/inhibitors, gonadotrophin-releasing hormone agonists, monoterpenes, isoflavones, retinoids, rexinoids, vitamin D derivatives, and inhibitors of tyrosine kinase, cyclooxygenase-2, and polyamine synthesis. New clinical testing models will use morphological and molecular biomarkers to select candidates at highest short-term risk, to predict the response to a particular class of agent, and to assess the response in phase II prevention trials. If validated, morphological and molecular markers could eventually replace cancer incidence as an indicator of efficacy in future phase III trials

A Network-Based Approach to Prioritize Results from Genome-Wide Association Studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses

The LOFAR Two-metre Sky Survey V. Second data release

In this data release from the ongoing LOw-Frequency ARray (LOFAR) Two-metre Sky Survey we present 120a 168 MHz images covering 27% of the northern sky. Our coverage is split into two regions centred at approximately 12h45m +44 30a and 1h00m +28 00a and spanning 4178 and 1457 square degrees respectively. The images were derived from 3451 h (7.6 PB) of LOFAR High Band Antenna data which were corrected for the direction-independent instrumental properties as well as direction-dependent ionospheric distortions during extensive, but fully automated, data processing. A catalogue of 4 396 228 radio sources is derived from our total intensity (Stokes I) maps, where the majority of these have never been detected at radio wavelengths before. At 6a resolution, our full bandwidth Stokes I continuum maps with a central frequency of 144 MHz have: a median rms sensitivity of 83 μJy beama 1; a flux density scale accuracy of approximately 10%; an astrometric accuracy of 0.2a; and we estimate the point-source completeness to be 90% at a peak brightness of 0.8 mJy beama 1. By creating three 16 MHz bandwidth images across the band we are able to measure the in-band spectral index of many sources, albeit with an error on the derived spectral index of > a ±a 0.2 which is a consequence of our flux-density scale accuracy and small fractional bandwidth. Our circular polarisation (Stokes V) 20a resolution 120a168 MHz continuum images have a median rms sensitivity of 95 μJy beama 1, and we estimate a Stokes I to Stokes V leakage of 0.056%. Our linear polarisation (Stokes Q and Stokes U) image cubes consist of 480a A a 97.6 kHz wide planes and have a median rms sensitivity per plane of 10.8 mJy beama 1 at 4a and 2.2 mJy beama 1 at 20a; we estimate the Stokes I to Stokes Q/U leakage to be approximately 0.2%. Here we characterise and publicly release our Stokes I, Q, U and V images in addition to the calibrated uv-data to facilitate the thorough scientific exploitation of this unique dataset

Marine Biodiversity in the Caribbean: Regional Estimates and Distribution Patterns

This paper provides an analysis of the distribution patterns of marine biodiversity and summarizes the major activities of the Census of Marine Life program in the Caribbean region. The coastal Caribbean region is a large marine ecosystem (LME) characterized by coral reefs, mangroves, and seagrasses, but including other environments, such as sandy beaches and rocky shores. These tropical ecosystems incorporate a high diversity of associated flora and fauna, and the nations that border the Caribbean collectively encompass a major global marine biodiversity hot spot. We analyze the state of knowledge of marine biodiversity based on the geographic distribution of georeferenced species records and regional taxonomic lists. A total of 12,046 marine species are reported in this paper for the Caribbean region. These include representatives from 31 animal phyla, two plant phyla, one group of Chromista, and three groups of Protoctista. Sampling effort has been greatest in shallow, nearshore waters, where there is relatively good coverage of species records; offshore and deep environments have been less studied. Additionally, we found that the currently accepted classification of marine ecoregions of the Caribbean did not apply for the benthic distributions of five relatively well known taxonomic groups. Coastal species richness tends to concentrate along the Antillean arc (Cuba to the southernmost Antilles) and the northern coast of South America (Venezuela – Colombia), while no pattern can be observed in the deep sea with the available data. Several factors make it impossible to determine the extent to which these distribution patterns accurately reflect the true situation for marine biodiversity in general: (1) highly localized concentrations of collecting effort and a lack of collecting in many areas and ecosystems, (2) high variability among collecting methods, (3) limited taxonomic expertise for many groups, and (4) differing levels of activity in the study of different taxa

PENELLOPE: The ESO data legacy program to complement the Hubble UV Legacy Library of Young Stars (ULLYSES)

The evolution of young stars and disks is driven by the interplay of several processes, notably the accretion and ejection of material. These processes, critical to correctly describe the conditions of planet formation, are best probed spectroscopically. Between 2020 and 2022, about 500orbits of the Hubble Space Telescope (HST) are being devoted in to the ULLYSES public survey of about 70 low-mass (M⋆ ≤ 2 M⊙) young (age < 10 Myr) stars at UV wavelengths. Here, we present the PENELLOPE Large Program carried out with the ESO Very Large Telescope (VLT) with the aim of acquiring, contemporaneously to the HST, optical ESPRESSO/UVES high-resolution spectra for the purpose of investigating the kinematics of the emitting gas, along with UV-to-NIR X-shooter medium-resolution flux-calibrated spectra to provide the fundamental parameters that HST data alone cannot provide, such as extinction and stellar properties. The data obtained by PENELLOPE have no proprietary time and the fully reduced spectra are being made available to the whole community. Here, we describe the data and the first scientific analysis of the accretion properties for the sample of 13 targets located in the Orion OB1 association and in the σ-Orionis cluster, observed in November–December 2020. We find that the accretion rates are in line with those observed previously in similarly young star-forming regions, with a variability on a timescale of days (≲3). The comparison of the fits to the continuum excess emission obtained with a slab model on the X-shooter spectra and the HST/STIS spectra shows a shortcoming in the X-shooter estimates of ≲10%, which is well within the assumed uncertainty. Its origin can be either due to an erroneous UV extinction curve or to the simplicity of the modeling and, thus, this question will form the basis of the investigation undertaken over the course of the PENELLOPE program. The combined ULLYSES and PENELLOPE data will be key in attaining a better understanding of the accretion and ejection mechanisms in young stars

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution