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Transverse momentum (pT) spectra of pions, kaons, and protons up to pT=20 GeV/c have been measured in Pb-Pb collisions at sNN−−−√=2.76 TeV using the ALICE detector for six different centrality classes covering 0-80%. The proton-to-pion and the kaon-to-pion ratios both show a distinct peak at pT≈3 GeV/c in central Pb-Pb collisions that decreases towards more peripheral collisions. For pT>10 GeV/c, the nuclear modification factor is found to be the same for all three particle species in each centrality interval within systematic uncertainties of 10-20%. This suggests there is no direct interplay between the energy loss in the medium and the particle species composition in the hard core of the quenched jet. For pT<10 GeV/c, the data provide important constraints for models aimed at describing the transition from soft to hard physics.
Multiplicity dependence of inclusive J/ψ production at midrapidity in pp collisions at √s = 13 TeV
(2020)
Measurements of the inclusive J/ψ yield as a function of charged-particle pseudorapidity density dNch/dη in pp collisions at √s = 13 TeV with ALICE at the LHC are reported. The J/ψ meson yield is measured at midrapidity (|y| < 0.9) in the dielectron channel, for events selected based on the charged-particle multiplicity at midrapidity (|η| < 1) and at forward rapidity (−3.7 < η < −1.7 and 2.8 < η < 5.1); both observables are normalized to their corresponding averages in minimum bias events. The increase of the normalized J/ψ yield with normalized dNch/dη is significantly stronger than linear and dependent on the transverse momentum. The data are compared to theoretical predictions, which describe the observed trends well, albeit not always quantitatively.
GABARAP belongs to an evolutionary highly conserved gene family that has a fundamental role in autophagy. There is ample evidence for a crosstalk between autophagy and apoptosis as well as the immune response. However, the molecular details for these interactions are not fully characterized. Here, we report that the ablation of murine GABARAP, a member of the Atg8/LC3 family that is central to autophagosome formation, suppresses the incidence of tumor formation mediated by the carcinogen DMBA and results in an enhancement of the immune response through increased secretion of IL-1β, IL-6, IL-2 and IFN-γ from stimulated macrophages and lymphocytes. In contrast, TGF-β1 was significantly reduced in the serum of these knockout mice. Further, DMBA treatment of these GABARAP knockout mice reduced the cellularity of the spleen and the growth of mammary glands through the induction of apoptosis. Gene expression profiling of mammary glands revealed significantly elevated levels of Xaf1, an apoptotic inducer and tumor-suppressor gene, in knockout mice. Furthermore, DMBA treatment triggered the upregulation of pro-apoptotic (Bid, Apaf1, Bax), cell death (Tnfrsf10b, Ripk1) and cell cycle inhibitor (Cdkn1a, Cdkn2c) genes in the mammary glands. Finally, tumor growth of B16 melanoma cells after subcutaneous inoculation was inhibited in GABARAP-deficient mice. Together, these data provide strong evidence for the involvement of GABARAP in tumorigenesis in vivo by delaying cell death and its associated immune-related response.
Aims: Heart failure (HF) leads to repeat hospitalisations and reduces the duration and quality of life. Pulmonary artery pressure (PAP)‐guided HF management using the CardioMEMS™ HF system was shown to be safe and reduce HF hospitalisation (HFH) rates in New York Heart Association (NYHA) class III patients. However, these findings have not been replicated in health systems outside the United States. Therefore, the CardioMEMS European Monitoring Study for Heart Failure (MEMS‐HF) evaluated the safety, feasibility, and performance of this device in Germany, The Netherlands, and Ireland.
Methods and results: A total of 234 NYHA class III patients (68 ± 11 years, 22% female, ≥1 HFH in the preceding year) from 31 centres were implanted with a CardioMEMS sensor and underwent PAP‐guided HF management. One‐year rates of freedom from device‐ or system‐related complications and from sensor failure (co‐primary outcomes) were 98.3% [95% confidence interval (CI) 95.8–100.0] and 99.6% (95% CI 97.6–100.0), respectively. Survival rate was 86.2%. For the 12 months post‐ vs. pre‐implant, HFHs decreased by 62% (0.60 vs. 1.55 events/patient‐year; hazard ratio 0.38, 95% CI 0.31–0.48; P < 0.0001). After 12 months, mean PAP decreased by 5.1 ± 7.4 mmHg, Kansas City Cardiomyopathy Questionnaire (KCCQ) overall/clinical summary scores increased from 47.0 ± 24.0/51.2 ± 24.8 to 60.5 ± 24.3/62.4 ± 24.1 (P < 0.0001), and the 9‐item Patient Health Questionnaire sum score improved from 8.7 ± 5.9 to 6.3 ± 5.1 (P < 0.0001).
Conclusion: Haemodynamic‐guided HF management proved feasible and safe in the health systems of Germany, The Netherlands, and Ireland. Physician‐directed treatment modifications based on remotely obtained PAP values were associated with fewer HFH, sustainable PAP decreases, marked KCCQ improvements, and remission of depressive symptoms.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.
An experiment addressing electron capture (EC) decay of hydrogen-like 142Pm60+ions has been conducted at the experimental storage ring (ESR) at GSI. The decay appears to be purely exponential and no modulations were observed. Decay times for about 9000 individual EC decays have been measured by applying the single-ion decay spectroscopy method. Both visually and automatically analysed data can be described by a single exponential decay with decay constants of 0.0126(7)s−1 for automatic analysis and 0.0141(7)s−1 for manual analysis. If a modulation superimposed on the exponential decay curve is assumed, the best fit gives a modulation amplitude of merely 0.019(15), which is compatible with zero and by 4.9 standard deviations smaller than in the original observation which had an amplitude of 0.23(4).