Adipose Tissue Mast Cells Promote Human Adipose Beiging in Response to Cold

In a recent study, repeated cold application induced beiging in subcutaneous white adipose tissue (SC WAT) of humans independent of body mass index. To identify factors that promote or inhibit beiging, we performed multiplex analysis of gene expression with the Nanostring nCounter system (the probe set contained genes for specific immune cell markers, cytokines, and chemokines) on the SC WAT from lean subjects. Multiple correlations analysis identified mast cell tryptase and CCL26, a chemokine for mast cells, as genes whose change correlated positively with the change in UCP1 in SC WAT, leading to the hypothesis that mast cells promote SC WAT beiging in response to cold. We quantified mast cell recruitment into SC WAT and degranulation. Mast cells increased in number in SC WAT in lean subjects, and there was an increase in the number of degranulated mast cells in both lean subjects and subjects with obesity. We determined that norepinephrine stimulated mast cell degranulation and histamine release in vitro. In conclusion, cold stimulated adipose tissue mast cell recruitment in lean subjects and mast cell degranulation in SC WAT of all research participants independent of baseline body mass index, suggesting that mast cells promote adipose beiging through the release of histamine or other products

The circumpolar impacts of climate change and anthropogenic stressors on Arctic cod (Boreogadus saida) and its ecosystem

Arctic cod biomass are predicted. In most Arctic seas, the relative abundance of Arctic cod within the fish community will likely fluctuate in accordance with cold and warm periods. A reduced abundance of Arctic cod will negatively affect the abundance, distribution, and physiological condition of certain predators, whereas some predators will successfully adapt to a more boreal diet. Regional management measures that recognize thecritical roleof Arcticcod arerequiredtoensure that increased anthropogenic activities do not exacerbate the impacts of climate change on Arctic marine ecosystems. Ultimately, the mitigation of habitat loss for Arctic cod will only be achieved through a global reduction in carbon emissions

Normal Human Pluripotent Stem Cell Lines Exhibit Pervasive Mosaic Aneuploidy

Human pluripotent stem cell (hPSC) lines have been considered to be homogeneously euploid. Here we report that normal hPSC – including induced pluripotent - lines are karyotypic mosaics of euploid cells intermixed with many cells showing non-clonal aneuploidies as identified by chromosome counting, spectral karyotyping (SKY) and fluorescent in situ hybridization (FISH) of interphase/non-mitotic cells. This mosaic aneuploidy resembles that observed in progenitor cells of the developing brain and preimplantation embryos, suggesting that it is a normal, rather than pathological, feature of stem cell lines. The karyotypic heterogeneity generated by mosaic aneuploidy may contribute to the reported functional and phenotypic heterogeneity of hPSCs lines, as well as their therapeutic efficacy and safety following transplantation

MEDEAS: a new modeling framework integrating global biophysical and socioeconomic constraints

Producción CientíficaA diversity of integrated assessment models (IAMs) coexists due to the different approaches developed to deal with the complex interactions, high uncertainties and knowledge gaps within the environment and human societies. This paper describes the open-source MEDEAS modeling framework, which has been developed with the aim of informing decision-making to achieve the transition to sustainable energy systems with a focus on biophysical, economic, social and technological restrictions and tackling some of the limitations identified in the current IAMs. MEDEAS models include the following relevant characteristics: representation of biophysical constraints to energy availability; modeling of the mineral and energy investments for the energy transition, allowing a dynamic assessment of the potential mineral scarcities and computation of the net energy available to society; consistent representation of climate change damages with climate assessments by natural scientists; integration of detailed sectoral economic structure (input–output analysis) within a system dynamics approach; energy shifts driven by physical scarcity; and a rich set of socioeconomic and environmental impact indicators. The potentialities and novel insights that this framework brings are illustrated by the simulation of four variants of current trends with the MEDEAS-world model: the consideration of alternative plausible assumptions and methods, combined with the feedback-rich structure of the model, reveal dynamics and implications absent in classical models. Our results suggest that the continuation of current trends will drive significant biophysical scarcities and impacts which will most likely derive in regionalization (priority to security concerns and trade barriers), conflict, and ultimately, a severe global crisis which may lead to the collapse of our modern civilization. Despite depicting a much more worrying future than conventional projections of current trends, we however believe it is a more realistic counterfactual scenario that will allow the design of improved alternative sustainable pathways in future work.Ministerio de Economía, Industria y Competitividad (Project CO2017-85110-R)Ministerio de Economía, Industria y Competitividad (Project JCI-2016–28833)MEDEAS project, funded by the European Union’s Horizon2020 research and innovation programme under grant agree-ment no. 691287.LOCOMOTION project, funded by the EuropeanUnion’s Horizon 2020 research and innovation programmeunder grant agreement no. 82110

CropPol: a dynamic, open and global database on crop pollination

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry weight, number of fruits and kg per hectare, among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), Northern America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-05 (21 studies), 2006-10 (40), 2011-15 (88), and 2016-20 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA). This article is protected by copyright. All rights reserved

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| &lt; 0.03 at 95% confidence level. [Figure not available: see fulltext.

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

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An embedding technique to determine ττ backgrounds in proton-proton collision data

An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe