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Mutations of the isocitrate dehydrogenase-1 (IDH1) and IDH2 genes are among the most frequent alterations in acute myeloid leukemia (AML) and can be found in ∼20% of patients at diagnosis. Among 4930 patients (median age, 56 years; interquartile range, 45-66) with newly diagnosed, intensively treated AML, we identified IDH1 mutations in 423 (8.6%) and IDH2 mutations in 575 (11.7%). Overall, there were no differences in response rates or survival for patients with mutations in IDH1 or IDH2 compared with patients without mutated IDH1/2. However, distinct clinical and comutational phenotypes of the most common subtypes of IDH1/2 mutations could be associated with differences in outcome. IDH1-R132C was associated with increased age, lower white blood cell (WBC) count, less frequent comutation of NPM1 and FLT3 internal tandem mutation (ITD) as well as with lower rate of complete remission and a trend toward reduced overall survival (OS) compared with other IDH1 mutation variants and wild-type (WT) IDH1/2. In our analysis, IDH2-R172K was associated with significantly lower WBC count, more karyotype abnormalities, and less frequent comutations of NPM1 and/or FLT3-ITD. Among patients within the European LeukemiaNet 2017 intermediate- and adverse-risk groups, relapse-free survival and OS were significantly better for those with IDH2-R172K compared with WT IDH, providing evidence that AML with IDH2-R172K could be a distinct entity with a specific comutation pattern and favorable outcome. In summary, the presented data from a large cohort of patients with IDH1/2 mutated AML indicate novel and clinically relevant findings for the most common IDH mutation subtypes.
(1) Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who are biologically at high risk for the development of loco–regional recurrences after postoperative radiotherapy (PORT) but at intermediate risk according to clinical risk factors may benefit from additional concurrent chemotherapy. In this matched-pair study, we aimed to identify a corresponding predictive gene signature. (2) Methods: Gene expression analysis was performed on a multicenter retrospective cohort of 221 patients that were treated with postoperative radiochemotherapy (PORT-C) and 283 patients who were treated with PORT alone. Propensity score analysis was used to identify matched patient pairs from both cohorts. From differential gene expression analysis and Cox regression, a predictive gene signature was identified. (3) Results: 108 matched patient pairs were selected. We identified a 2-metagene signature that stratified patients into risk groups in both cohorts. The comparison of the high-risk patients between the two types of treatment showed higher loco–regional control (LRC) after treatment with PORT-C (p < 0.001), which was confirmed by a significant interaction term in Cox regression (p = 0.027), i.e., the 2-metagene signature was indicative for the type of treatment. (4) Conclusion: We have identified a novel gene signature that may be helpful to identify patients with high-risk HNSCC amongst those at intermediate clinical risk treated with PORT, who may benefit from additional concurrent chemotherapy.
Innovation is considered essential for today's organizations to survive and thrive. Researchers have also stressed the importance of leadership as a driver of followers' innovative work behavior (FIB). Yet, despite a large amount of research, three areas remain understudied: (a) The relative importance of different forms of leadership for FIB; (b) the mechanisms through which leadership impacts FIB; and (c) the degree to which relationships between leadership and FIB are generalizable across cultures. To address these lacunae, we propose an integrated model connecting four types of positive leadership behaviors, two types of identification (as mediating variables), and FIB. We tested our model in a global data set comprising responses of N = 7,225 participants from 23 countries, grouped into nine cultural clusters. Our results indicate that perceived LMX quality was the strongest relative predictor of FIB. Furthermore, the relationships between both perceived LMX quality and identity leadership with FIB were mediated by social identification. The indirect effect of LMX on FIB via social identification was stable across clusters, whereas the indirect effects of the other forms of leadership on FIB via social identification were stronger in countries high versus low on collectivism. Power distance did not influence the relations.
The optimal follow-up care for relapse detection in acute myeloid leukemia (AML) patients in first remission after consolidation therapy with intensive chemotherapy is not established. In this retrospective study, we evaluate the diagnostic value of an intensive relapse surveillance strategy by regular bone marrow aspirations (BMA) in these patients. We identified 86 patients with newly diagnosed non-promyelocytic AML who had reached complete remission (CR) after intensive induction and consolidation chemotherapy between 2007 and 2019. Annual relapse rates were 40%, 17%, and 2% in years 1–3, respectively. Patients in CR were surveilled by BMA scheduled every 3 months for 2 years, followed by BMA every 6 months. This surveillance regimen detected 29 of 55 relapses (53%), 11 of which were molecular relapses (20%). The remaining 26 of 55 relapses (47%) were diagnosed by non-surveillance BMA prompted by specific suspicion of relapse. Most patients showed concurrent morphological abnormalities in peripheral blood (PB) at time of relapse. Seven percent of all morphological relapses occurred without simultaneous PB abnormalities and would have been delayed without surveillance BMA. Intensified monthly PB assessment paired with BMA every 3 months during the first 2 years may be a highly sensitive relapse surveillance strategy.
The measurement of the azimuthal-correlation function of prompt D mesons with charged particles in pp collisions at s√ = 5.02 TeV and p-Pb collisions at sNN−−−√ = 5.02 TeV with the ALICE detector at the LHC is reported. The D0, D+, and D∗+ mesons, together with their charge conjugates, were reconstructed at midrapidity in the transverse momentum interval 3 < pT < 24 GeV/c and correlated with charged particles having pT > 0.3 GeV/c and pseudorapidity |η|< 0.8. The properties of the correlation peaks appearing in the near- and away-side regions (for Δφ≈ 0 and Δφ≈π, respectively) were extracted via a fit to the azimuthal correlation functions. The shape of the correlation functions and the near- and away-side peak features are found to be consistent in pp and p-Pb collisions, showing no modifications due to nuclear effects within uncertainties. The results are compared with predictions from Monte Carlo simulations performed with the PYTHIA, POWHEG+PYTHIA, HERWIG, and EPOS 3 event generators.
The first evidence of spin alignment of vector mesons (K∗0 and ϕ) in heavy-ion collisions at the Large Hadron Collider (LHC) is reported. The spin density matrix element ρ00 is measured at midrapidity (|y|< 0.5) in Pb-Pb collisions at a center-of-mass energy (sNN−−−√) of 2.76 TeV with the ALICE detector. ρ00 values are found to be less than 1/3 (1/3 implies no spin alignment) at low transverse momentum (pT< 2 GeV/c) for K∗0 and ϕ at a level of 3σ and 2σ, respectively. No significant spin alignment is observed for the K0S meson (spin = 0) in Pb-Pb collisions and for the vector mesons in pp collisions. The measured spin alignment is unexpectedly large but qualitatively consistent with the expectation from models which attribute it to a polarization of quarks in the presence of angular momentum in heavy-ion collisions and a subsequent hadronization by the process of recombination.
Systematic studies of charge-dependent two- and three-particle correlations in Pb-Pb collisions at sNN−−−√= 2.76 and 5.02 TeV used to probe the Chiral Magnetic Effect (CME) are presented. These measurements are performed for charged particles in the pseudorapidity (η) and transverse momentum (pT) ranges |η|<0.8 and 0.2<pT<5 GeV/c. A significant charge-dependent signal that becomes more pronounced for peripheral collisions is reported for the CME-sensitive correlators γ1,1=⟨cos(φα+φβ−2Ψ2)⟩ and γ1,−3=⟨cos(φα−3φβ+2Ψ2)⟩. The results are used to estimate the contribution of background effects, associated with local charge conservation coupled to anisotropic flow modulations, to measurements of the CME. A blast-wave parametrisation that incorporates local charge conservation tuned to reproduce the centrality dependent background effects is not able to fully describe the measured γ1,1. Finally, the charge and centrality dependence of mixed-harmonics three-particle correlations, of the form γ1,2=⟨cos(φα+2φβ−3Ψ3)⟩, which are insensitive to the CME signal, verify again that background contributions dominate the measurement of γ1,1.
This article reports measurements of the pT-differential inclusive jet cross-section in pp collisions at s√ = 5.02 TeV and the pT-differential inclusive jet yield in Pb-Pb 0-10% central collisions at sNN−−−√ = 5.02 TeV. Jets were reconstructed at mid-rapidity with the ALICE tracking detectors and electromagnetic calorimeter using the anti-kT algorithm. For pp collisions, we report jet cross-sections for jet resolution parameters R=0.1−0.6 over the range 20<pT,jet<140 GeV/c, as well as the jet cross-section ratios of different R, and comparisons to two next-to-leading-order (NLO)-based theoretical predictions. For Pb-Pb collisions, we report the R=0.2 and R=0.4 jet spectra for 40<pT,jet<140 GeV/c and 60<pT,jet<140 GeV/c, respectively. The scaled ratio of jet yields observed in Pb-Pb to pp collisions, RAA, is constructed, and exhibits strong jet quenching and a clear pT-dependence for R=0.2. No significant R-dependence of the jet RAA is observed within the uncertainties of the measurement. These results are compared to several theoretical predictions.
In the original paper, the sign used to determine the global polarization PH was opposite to the convention used in previous papers, particularly, published by the STAR Collaboration to which the results are compared to in Fig. 5. The correct version of Eq. (3) in the paper for PH is...
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.