Impaired post-stroke collateral circulation in sickle cell anemia mice

Patients with sickle cell anemia (SCA) have a high incidence of ischemic stroke, but are usually excluded from thrombolytic therapy due to concerns for cerebral hemorrhage. Maladaptation to cerebral ischemia may also contribute to the stroke propensity in SCA. Here we compared post-stroke cortical collateral circulation in transgenic sickle (SS) mice, bone marrow grafting-derived SS-chimera, and wildtype (AA) controls, because collateral circulation is a critical factor for cell survival within the ischemic penumbra. Further, it has been shown that SS mice develop poorer neo-collateral perfusion after limb ischemia. We used the middle cerebral artery (MCA)-targeted photothrombosis model in this study, since it is better tolerated by SS mice and creates a clear infarct core versus peri-infarct area. Compared to AA mice, SS mice showed enlarged infarction and lesser endothelial proliferation after photothrombosis. SS-chimera showed anemia, hypoxia-induced erythrocyte sickling, and attenuated recovery of blood flow in the ipsilateral cortex after photothrombosis. In AA chimera, cerebral blood flow in the border area between MCA and the anterior cerebral artery (ACA) and posterior cerebral artery (PCA) trees improved from 44% of contralateral level after stroke to 78% at 7 d recovery. In contrast, blood flow in the MCA-ACA and MCA-PCA border areas only increased from 35 to 43% at 7 d post-stroke in SS chimera. These findings suggest deficits of post-stroke collateral circulation in SCA. Better understanding of the underpinnings may suggest novel stroke therapies for SCA patients

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

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

Peer reviewe

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

Measurement of electroweak WZ boson production and search for new physics in WZ + two jets events in pp collisions at √s=13TeV

A measurement of WZ electroweak (EW) vector boson scattering is presented. The measurement is performed in the leptonic decay modes WZ→ℓνℓ′ℓ′, where ℓ,ℓ′=e,μ. The analysis is based on a data sample of proton-proton collisions at √s=13 TeV at the LHC collected with the CMS detector and corresponding to an integrated luminosity of 35.9 fb−1. The WZ plus two jet production cross section is measured in fiducial regions with enhanced contributions from EW production and found to be consistent with standard model predictions. The EW WZ production in association with two jets is measured with an observed (expected) significance of 2.2 (2.5) standard deviations. Constraints on charged Higgs boson production and on anomalous quartic gauge couplings in terms of dimension-eight effective field theory operators are also presented

Measurement of nuclear modification factors of gamma(1S)), gamma(2S), and gamma(3S) mesons in PbPb collisions at root s(NN)=5.02 TeV

The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead-lead (PbPb) and proton-proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date. © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3.Peer reviewe

Studies of Beauty Suppression via Nonprompt D-0 Mesons in Pb-Pb Collisions at root s(NN)=5.02 TeV

The transverse momentum spectra of D-0 mesons from b hadron decays are measured at midrapidity (vertical bar y vertical bar D-0 yield is found to be suppressed in the measured p(T) range from 2 to 100 GeV/c as compared to pp collisions. The suppression is weaker than that of prompt D-0 mesons and charged hadrons for p(T) around 10 GeV/c. While theoretical calculations incorporating partonic energy loss in the quark-gluon plasma can successfully describe the measured B -> D-0 suppression at higher p(T), the data show an indication of larger suppression than the model predictions in the range of 2 <p(T) <5 GeV/c.Peer reviewe

Bose-Einstein correlations of charged hadrons in proton-proton collisions at s\sqrt s = 13 TeV

Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $\sqrt{s}$ = 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functions of particle multiplicity as well as average pair transverse momentum and mass. The results are compared with data from both CMS and ATLAS at $\sqrt{s}$ = 7 TeV, as well as with theoretical predictions.[graphic not available: see fulltext]Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $\sqrt{s} =$ 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functions of particle multiplicity as well as average pair transverse momentum and mass. The results are compared with data from both CMS and ATLAS at $\sqrt{s} =$ 7 TeV, as well as with theoretical predictions