Refine
Document Type
- Preprint (341)
- Article (165)
- Part of Periodical (1)
Language
- English (507)
Has Fulltext
- yes (507)
Is part of the Bibliography
- no (507)
Keywords
- Heavy Ion Experiments (11)
- Hadron-Hadron Scattering (8)
- Hadron-Hadron scattering (experiments) (5)
- Collective Flow (4)
- Quark-Gluon Plasma (4)
- Heavy-ion collision (3)
- Jets (3)
- Jets and Jet Substructure (3)
- Experimental nuclear physics (2)
- Experimental particle physics (2)
- Heavy Quark Production (2)
- Lepton-Nucleon Scattering (experiments) (2)
- Particle Correlations and Fluctuations (2)
- Particle and resonance production (2)
- Acute myeloid leukemia (1)
- Advanced stage (1)
- Bloodstream infections (1)
- Boosted Jets (1)
- Brain tumor (1)
- COVID-19 (1)
- Collective Flow, (1)
- Complicated stage (1)
- Electroweak interaction (1)
- Glioma (1)
- Gram negative bacteria (1)
- Hadron-Hadron Scattering Heavy (1)
- Hadron-hadron interactions (1)
- Hard Scattering (1)
- Heavy Ion Experiment (1)
- Hematopoietic stem cell transplantation (1)
- Intensive care units (1)
- Jet Physics (1)
- Jet Substructure (1)
- LEOSS (1)
- Machine learning (1)
- Material budget (1)
- Molecular matched therapy (1)
- Molecular profiling (1)
- Multi-Parton Interactions (1)
- Multivariate analysis (1)
- Neutropenia (1)
- Particle and Resonance Production (1)
- Particle correlations and fluctuations (1)
- Predictive model (1)
- Properties of Hadrons (1)
- QCD (1)
- Quark Deconfinement (1)
- Quark Gluon Plasma (1)
- Quark Production (1)
- Quarkonium (1)
- Relativistic heavy-ion collisions (1)
- Stenotrophomonas maltophilia (1)
- Targeted therapy (1)
- Vector Boson Production (1)
- detector (1)
- experimental results (1)
Institute
- Physik (502)
- Frankfurt Institute for Advanced Studies (FIAS) (471)
- Informatik (454)
- Medizin (4)
- Informatik und Mathematik (3)
- Gesellschaftswissenschaften (1)
Measurements of the production of muons from heavy-flavour hadron decays in Pb−Pb collisions at sNN−−−√ = 5.02 and 2.76 TeV using the ALICE detector at the LHC are reported. The nuclear modification factor RAA at sNN−−−√ = 5.02 TeV is measured at forward rapidity (2.5<y<4) as a function of transverse momentum pT in central, semi-central, and peripheral collisions over a wide pT interval, 3<pT<20 GeV/c, in which muons from beauty-hadron decays are expected to take over from charm as the dominant source at high pT (pT>7 GeV/c). The RAA shows an increase of the suppression of the yields of muons from heavy-flavour hadron decays with increasing centrality. A suppression by a factor of about three is observed in the 10% most central collisions. The RAA at sNN−−−√ = 5.02 is similar to that at 2.76 TeV. The precise RAA measurements have the potential to distinguish between model predictions implementing different mechanisms of parton energy loss in the high-density medium formed in heavy-ion collisions. They place important constraints for the understanding of the heavy-quark interaction with the hot and dense QCD medium.
Measurements of the production of muons from heavy-flavour hadron decays in Pb−Pb collisions at sNN−−−√ = 5.02 and 2.76 TeV using the ALICE detector at the LHC are reported. The nuclear modification factor RAA at sNN−−−√ = 5.02 TeV is measured at forward rapidity (2.5<y<4) as a function of transverse momentum pT in central, semi-central, and peripheral collisions over a wide pT interval, 3<pT<20 GeV/c, in which a significant contribution of muons from beauty-hadron decays is expected at high pT. With a significantly improved precision compared to the measurements at lower collision energy, the RAA shows an increase of the suppression of the yields of muons from heavy-flavour hadron decays with increasing centrality. A suppression by a factor of about three is observed in the 10% most central collisions. The RAA at sNN−−−√ = 5.02 is similar to that reported at 2.76 TeV in a broader pT interval and with an improved accuracy with respect to previously published measurements. The precise RAA results have the potential to distinguish between model predictions implementing different mechanisms of parton energy loss in the high-density medium formed in heavy-ion collisions. The results place stringent constraints on the relative energy loss between charm and beauty quarks.
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
Germany has experienced a rise in xenophobic attacks since it began to welcome refugees from Syria and elsewhere. Sebastian Jäckle and Pascal D. König have mapped these attacks and drawn some striking conclusions about their causes. They were more common in regions with a strong far-right presence and fewer migrants. One attack also tended to spark others – as did condemnation of xenophobia by national leaders, and Islamist terror. Britain saw a similar spike in xenophobic crime after the referendum. The authors ask whether the UK can learn from Germany’s painful experience.
Purpose: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization.
Methods: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16).
Results: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface.
Conclusion: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) offers potential cure to acute myeloid leukemia (AML) patients. However, infections with commensal bacteria are an important cause for non-relapse mortality (NRM). We have previously described the impact of multidrug-resistant organism (MDRO) colonization on the survival of allo-HSCT patients. In the aforementioned publication, according to consensus, we there did not consider the opportunistic gram-negative bacterium Stenotrophomonas maltophilia (S. maltophilia) to be an MDRO. Since rate of S. maltophilia colonization is increasing, and it is not known whether this poses a risk for allo-HSCT patients, we here analyzed here its effect on the previously described and now extended patient cohort. We report on 291 AML patients undergoing allo-HSCT. Twenty of 291 patients (6.9%) were colonized with S. maltophilia. Colonized patients did not differ from non-colonized patients with respect to their age, remission status before allo-HSCT, donor type and HSCT-comorbidity index. S. maltophilia colonized patients had a worse overall survival (OS) from 6 months up to 60 months (85% vs. 88.1% and 24.7% vs. 59.7%; p = 0.007) due to a higher NRM after allo-HSCT (6 months: 15% vs. 4.8% and 60 months: 40.1% vs. 16.2% p = 0.003). The main cause of mortality in colonized patients was infection (46.2% of all deaths) and in non-colonized patients relapse (58.8% of all deaths). 5/20 colonized patients developed an invasive infection with S. maltophilia. The worse OS after allo-HSCT due to higher infection related mortality might implicate the screening of allo-HSCT patients for S. maltophilia and a closer observation of colonized patients as outpatients.
Purpose: Molecular diagnostics including next generation gene sequencing are increasingly used to determine options for individualized therapies in brain tumor patients. We aimed to evaluate the decision-making process of molecular targeted therapies and analyze data on tolerability as well as signals for efficacy.
Methods: Via retrospective analysis, we identified primary brain tumor patients who were treated off-label with a targeted therapy at the University Hospital Frankfurt, Goethe University. We analyzed which types of molecular alterations were utilized to guide molecular off-label therapies and the diagnostic procedures for their assessment during the period from 2008 to 2021. Data on tolerability and outcomes were collected.
Results: 413 off-label therapies were identified with an increasing annual number for the interval after 2016. 37 interventions (9%) were targeted therapies based on molecular markers. Glioma and meningioma were the most frequent entities treated with molecular matched targeted therapies. Rare entities comprised e.g. medulloblastoma and papillary craniopharyngeoma. Molecular targeted approaches included checkpoint inhibitors, inhibitors of mTOR, FGFR, ALK, MET, ROS1, PIK3CA, CDK4/6, BRAF/MEK and PARP. Responses in the first follow-up MRI were partial response (13.5%), stable disease (29.7%) and progressive disease (46.0%). There were no new safety signals. Adverse events with fatal outcome (CTCAE grade 5) were not observed. Only, two patients discontinued treatment due to side effects. Median progression-free and overall survival were 9.1/18 months in patients with at least stable disease, and 1.8/3.6 months in those with progressive disease at the first follow-up MRI.
Conclusion: A broad range of actionable alterations was targeted with available molecular therapeutics.
However, efficacy was largely observed in entities with paradigmatic oncogenic drivers, in particular with BRAF mutations. Further research on biomarker-informed molecular matched therapies is urgently necessary.