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The acceptance-corrected dielectron excess mass spectra, where the known hadronic sources have been subtracted from the inclusive dielectron mass spectra, are reported for the first time at mid-rapidity |yee|<1 in minimum-bias Au+Au collisions at sNN−−−−√ = 19.6 and 200 GeV. The excess mass spectra are consistently described by a model calculation with a broadened ρ spectral function for Mee<1.1 GeV/c2. The integrated dielectron excess yield at sNN−−−−√ = 19.6 GeV for 0.4<Mee<0.75 GeV/c2, normalized to the charged particle multiplicity at mid-rapidity, has a value similar to that in In+In collisions at sNN−−−−√ = 17.3 GeV. For sNN−−−−√ = 200 GeV, the normalized excess yield in central collisions is higher than that at sNN−−−−√ = 17.3 GeV and increases from peripheral to central collisions. These measurements indicate that the lifetime of the hot, dense medium created in central Au+Au collisions at sNN−−−−√ = 200 GeV is longer than those in peripheral collisions and at lower energies.
The inclusive J/ψ transverse momentum spectra and nuclear modification factors are reported at midrapidity (|y| < 1.0) in Au+Au collisions at √sN N = 39, 62.4 and 200 GeV taken by the STAR experiment. A suppression of J/ψ production, with respect to the production in p + p scaled by the number of binary nucleon–nucleon collisions, is observed in central Au+Au collisions at these three energies. No significant energy dependence of nuclear modification factors is found within uncertainties. The measured nuclear modification factors can be described by model calculations that take into account both suppression of direct J/ψ production due to the color screening effect and J/ψ regeneration from recombination of uncorrelated charm–anticharm quark pairs.
The transversity distribution, which describes transversely polarized quarks in transversely polarized nucleons, is a fundamental component of the spin structure of the nucleon, and is only loosely constrained by global fits to existing semi-inclusive deep inelastic scattering (SIDIS) data. In transversely polarized p↑+p collisions it can be accessed using transverse polarization dependent fragmentation functions which give rise to azimuthal correlations between the polarization of the struck parton and the final state scalar mesons.This letter reports on spin dependent di-hadron correlations measured by the STAR experiment. The new dataset corresponds to 25 pb−1 integrated luminosity of p↑+p collisions at s=500 GeV, an increase of more than a factor of ten compared to our previous measurement at s=200 GeV. Non-zero asymmetries sensitive to transversity are observed at a Q2 of several hundred GeV and are found to be consistent with the former measurement and a model calculation. We expect that these data will enable an extraction of transversity with comparable precision to current SIDIS datasets but at much higher momentum transfers where subleading effects are suppressed.
We report the direct virtual photon invariant yields in the transverse momentum ranges 1 < pT < 3 GeV/c and 5 < pT < 10 GeV/c at mid-rapidity derived from the dielectron invariant mass continuum region 0.10 < Mee < 0.28 GeV/c2 for 0–80% minimum-bias Au+Au collisions at √sN N = 200 GeV. A clear excess in the invariant yield compared to the nuclear overlap function T A A scaled p + p reference is observed in the pT range 1 < pT < 3 GeV/c. For pT > 6 GeV/c the production follows T A A scaling. Model calculations with contributions from thermal radiation and initial hard parton scattering are consistent ithin uncertainties with the direct virtual photon invariant yield.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
The nucleosynthesis of elements beyond iron is dominated by neutron captures in the s and r processes. However, 32 stable, proton-rich isotopes cannot be formed during those processes, because they are shielded from the s-process flow and r-process β-decay chains. These nuclei are attributed to the p and rp process.
For all those processes, current research in nuclear astrophysics addresses the need for more precise reaction data involving radioactive isotopes. Depending on the particular reaction, direct or inverse kinematics, forward or time-reversed direction are investigated to determine or at least to constrain the desired reaction cross sections.
The Facility for Antiproton and Ion Research (FAIR) will offer unique, unprecedented opportunities to investigate many of the important reactions. The high yield of radioactive isotopes, even far away from the valley of stability, allows the investigation of isotopes involved in processes as exotic as the r or rp processes.
In March 2019 the HADES experiment recorded 14 billion Ag+Ag collisions at √sNN = 2.55 GeV as a part of the FAIR phase-0 physics program. In this contribution, we present and investigate our capabilities to reconstruct and analyze weakly decaying strange hadrons and hypernuclei emerging from these collisions. The focus is put on measuring the mean lifetimes of these particles.
Simple Summary: Mutations in RAS-family genes frequently cause different types of human cancers. Inhibitors of the MEK (mitogen-activated protein kinase) and ERK (extracellular signal-regulated kinase) protein kinases that function downstream of RAS proteins have shown some clinical benefits when used for the treatment of these cancers, but drug resistance frequently emerges. Here we show that combined treatment with MEK and ERK inhibitors blocks the emergence of resistance to either drug alone. However, if cancer cells have already developed resistance to MEK inhibitors or to ERK inhibitors, the combined therapy is frequently ineffective. These findings imply that these inhibitors should be used together for cancer therapy. We also show that drug resistance involves complex patterns of rewiring of cellular kinase signaling networks that do not overlap between each different cancer cell line. Nonetheless, we show that MAP4K4 is required for efficient cell proliferation in several different MEK/ERK inhibitor resistant cancer cell lines, uncovering a potential new therapeutic target.
Abstract: Oncogenic mutations in RAS family genes arise frequently in metastatic human cancers. Here we developed new mouse and cellular models of oncogenic HrasG12V-driven undifferentiated pleomorphic sarcoma metastasis and of KrasG12D-driven pancreatic ductal adenocarcinoma metastasis. Through analyses of these cells and of human oncogenic KRAS-, NRAS- and BRAF-driven cancer cell lines we identified that resistance to single MEK inhibitor and ERK inhibitor treatments arise rapidly but combination therapy completely blocks the emergence of resistance. The prior evolution of resistance to either single agent frequently leads to resistance to dual treatment. Dual MEK inhibitor plus ERK inhibitor therapy shows anti-tumor efficacy in an HrasG12V-driven autochthonous sarcoma model but features of drug resistance in vivo were also evident. Array-based kinome activity profiling revealed an absence of common patterns of signaling rewiring in single or double MEK and ERK inhibitor resistant cells, showing that the development of resistance to downstream signaling inhibition in oncogenic RAS-driven tumors represents a heterogeneous process. Nonetheless, in some single and double MEK and ERK inhibitor resistant cell lines we identified newly acquired drug sensitivities. These may represent additional therapeutic targets in oncogenic RAS-driven tumors and provide general proof-of-principle that therapeutic vulnerabilities of drug resistant cells can be identified.
TRPC channels are a family of nonselective cation channels that regulate ion homeostasis and intracellular Ca2+ signaling in numerous cell types. Important physiological functions such as vasoregulation, neuronal growth, and pheromone recognition have been assigned to this class of ion channels. Despite their physiological relevance, few selective pharmacological tools are available to study TRPC channel function. We, therefore, screened a selection of pharmacologically active compounds for TRPC modulating activity. We found that the synthetic gestagen norgestimate inhibited diacylglycerol-sensitive TRPC3 and TRPC6 with IC50s of 3–5 µM, while half-maximal inhibition of TRPC5 required significantly higher compound concentrations (>10 µM). Norgestimate blocked TRPC-mediated vasopressin-induced cation currents in A7r5 smooth muscle cells and caused vasorelaxation of isolated rat aorta, indicating that norgestimate could be an interesting tool for the investigation of TRP channel function in native cells and tissues. The steroid hormone progesterone, which is structurally related to norgestimate, also inhibited TRPC channel activity with IC50s ranging from 6 to 18 µM but showed little subtype selectivity. Thus, TRPC channel inhibition by high gestational levels of progesterone may contribute to the physiological decrease of uterine contractility and immunosuppression during pregnancy.
Introduction: Acute kidney injury (AKI) can evolve quickly and clinical measures of function often fail to detect AKI at a time when interventions are likely to provide benefit. Identifying early markers of kidney damage has been difficult due to the complex nature of human AKI, in which multiple etiologies exist. The objective of this study was to identify and validate novel biomarkers of AKI.
Methods: We performed two multicenter observational studies in critically ill patients at risk for AKI - discovery and validation. The top two markers from discovery were validated in a second study (Sapphire) and compared to a number of previously described biomarkers. In the discovery phase, we enrolled 522 adults in three distinct cohorts including patients with sepsis, shock, major surgery, and trauma and examined over 300 markers. In the Sapphire validation study, we enrolled 744 adult subjects with critical illness and without evidence of AKI at enrollment; the final analysis cohort was a heterogeneous sample of 728 critically ill patients. The primary endpoint was moderate to severe AKI (KDIGO stage 2 to 3) within 12 hours of sample collection.
Results: Moderate to severe AKI occurred in 14% of Sapphire subjects. The two top biomarkers from discovery were validated. Urine insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases-2 (TIMP-2), both inducers of G1 cell cycle arrest, a key mechanism implicated in AKI, together demonstrated an AUC of 0.80 (0.76 and 0.79 alone). Urine [TIMP-2].[IGFBP7] was significantly superior to all previously described markers of AKI (P <0.002), none of which achieved an AUC >0.72. Furthermore, [TIMP-2].[IGFBP7] significantly improved risk stratification when added to a nine-variable clinical model when analyzed using Cox proportional hazards model, generalized estimating equation, integrated discrimination improvement or net reclassification improvement. Finally, in sensitivity analyses [TIMP-2].[IGFBP7] remained significant and superior to all other markers regardless of changes in reference creatinine method.
Conclusions: Two novel markers for AKI have been identified and validated in independent multicenter cohorts. Both markers are superior to existing markers, provide additional information over clinical variables and add mechanistic insight into AKI. Trial registration: ClinicalTrials.gov number NCT01209169.