Heavy quarkonium: progress, puzzles, and opportunities

A golden age for heavy quarkonium physics dawned a decade ago, initiated by the confluence of exciting advances in quantum chromodynamics (QCD) and an explosion of related experimental activity. The early years of this period were chronicled in the Quarkonium Working Group (QWG) CERN Yellow Report (YR) in 2004, which presented a comprehensive review of the status of the field at that time and provided specific recommendations for further progress. However, the broad spectrum of subsequent breakthroughs, surprises, and continuing puzzles could only be partially anticipated. Since the release of the YR, the BESII program concluded only to give birth to BESIII; the $B$-factories and CLEO-c flourished; quarkonium production and polarization measurements at HERA and the Tevatron matured; and heavy-ion collisions at RHIC have opened a window on the deconfinement regime. All these experiments leave legacies of quality, precision, and unsolved mysteries for quarkonium physics, and therefore beg for continuing investigations. The plethora of newly-found quarkonium-like states unleashed a flood of theoretical investigations into new forms of matter such as quark-gluon hybrids, mesonic molecules, and tetraquarks. Measurements of the spectroscopy, decays, production, and in-medium behavior of c\bar{c}, b\bar{b}, and b\bar{c} bound states have been shown to validate some theoretical approaches to QCD and highlight lack of quantitative success for others. The intriguing details of quarkonium suppression in heavy-ion collisions that have emerged from RHIC have elevated the importance of separating hot- and cold-nuclear-matter effects in quark-gluon plasma studies. This review systematically addresses all these matters and concludes by prioritizing directions for ongoing and future efforts.Comment: 182 pages, 112 figures. Editors: N. Brambilla, S. Eidelman, B. K. Heltsley, R. Vogt. Section Coordinators: G. T. Bodwin, E. Eichten, A. D. Frawley, A. B. Meyer, R. E. Mitchell, V. Papadimitriou, P. Petreczky, A. A. Petrov, P. Robbe, A. Vair

Inclusive J/psi production in pp collisions at sqrt(s) = 2.76 TeV

The ALICE Collaboration has measured inclusive J/psi production in pp collisions at a center of mass energy sqrt(s)=2.76 TeV at the LHC. The results presented in this Letter refer to the rapidity ranges |y|<0.9 and 2.5<y<4 and have been obtained by measuring the electron and muon pair decay channels, respectively. The integrated luminosities for the two channels are L^e_int=1.1 nb^-1 and L^mu_int=19.9 nb^-1, and the corresponding signal statistics are N_J/psi^e+e-=59 +/- 14 and N_J/psi^mu+mu-=1364 +/- 53. We present dsigma_J/psi/dy for the two rapidity regions under study and, for the forward-y range, d^2sigma_J/psi/dydp_t in the transverse momentum domain 0<p_t<8 GeV/c. The results are compared with previously published results at sqrt(s)=7 TeV and with theoretical calculations.Comment: 7 figures, 3 tables, accepted for publication in Phys. Lett.

J/psi Production as a Function of Charged Particle Multiplicity in pp Collisions at sqrt{s} = 7 TeV

The ALICE collaboration reports the measurement of the inclusive J/psi yield as a function of charged particle pseudorapidity density dN_{ch}/deta in pp collisions at sqrt{s} = 7 TeV at the LHC. J/psi particles are detected for p_t > 0, in the rapidity interval |y| < 0.9 via decay into e+e-, and in the interval 2.5 < y < 4.0 via decay into mu+mu- pairs. An approximately linear increase of the J/psi yields normalized to their event average (dN_{J/psi}/dy)/ with (dN_{ch}/deta)/ is observed in both rapidity ranges, where dN_{ch}/deta is measured within |eta| < 1 and p_t > 0. In the highest multiplicity interval with = 24.1, corresponding to four times the minimum bias multiplicity density, an enhancement relative to the minimum bias J/psi yield by a factor of about 5 at 2.5 < y < 4 (8 at |y| < 0.9) is observed.Comment: Submitted to Phys. Lett.

Analysis of perfusion MRI in stroke: To deconvolve, or not to deconvolve

Item does not contain fulltextPurpose There is currently controversy regarding the benefits of deconvolution-based parameters in stroke imaging, with studies suggesting a similar infarct prediction using summary parameters. We investigate here the performance of deconvolution-based parameters and summary parameters for dynamic-susceptibility contrast (DSC) MRI analysis, with particular emphasis on precision. Methods Numerical simulations were used to assess the contribution of noise and arterial input function (AIF) variability to measurement precision. A realistic AIF range was defined based on in vivo data from an acute stroke clinical study. The simulated tissue curves were analyzed using two popular singular value decomposition (SVD) based algorithms, as well as using summary parameters. Results SVD-based deconvolution methods were found to considerably reduce the AIF-dependency, but a residual AIF bias remained on the calculated parameters. Summary parameters, in turn, show a lower sensitivity to noise. The residual AIF-dependency for deconvolution methods and the large AIF-sensitivity of summary parameters was greatly reduced when normalizing them relative to normal tissue. Conclusion Consistent with recent studies suggesting high performance of summary parameters in infarct prediction, our results suggest that DSC-MRI analysis using properly normalized summary parameters may have advantages in terms of lower noise and AIF-sensitivity as compared to commonly used deconvolution methods

Functional Outcome Prediction in Acute Ischemic Stroke Using a Fused Imaging and Clinical Deep Learning Model.

Predicting long-term clinical outcome based on the early acute ischemic stroke information is valuable for prognostication, resource management, clinical trials, and patient expectations. Current methods require subjective decisions about which imaging features to assess and may require time-consuming postprocessing. This study's goal was to predict ordinal 90-day modified Rankin Scale (mRS) score in acute ischemic stroke patients by fusing a Deep Learning model of diffusion-weighted imaging images and clinical information from the acute period. A total of 640 acute ischemic stroke patients who underwent magnetic resonance imaging within 1 to 7 days poststroke and had 90-day mRS follow-up data were randomly divided into 70% (n=448) for model training, 15% (n=96) for validation, and 15% (n=96) for internal testing. Additionally, external testing on a cohort from Lausanne University Hospital (n=280) was performed to further evaluate model generalization. Accuracy for ordinal mRS, accuracy within ±1 mRS category, mean absolute prediction error, and determination of unfavorable outcome (mRS score &gt;2) were evaluated for clinical only, imaging only, and 2 fused clinical-imaging models. The fused models demonstrated superior performance in predicting ordinal mRS score and unfavorable outcome in both internal and external test cohorts when compared with the clinical and imaging models. For the internal test cohort, the top fused model had the highest area under the curve of 0.92 for unfavorable outcome prediction and the lowest mean absolute error (0.96 [95% CI, 0.77-1.16]), with the highest proportion of mRS score predictions within ±1 category (79% [95% CI, 71%-88%]). On the external Lausanne University Hospital cohort, the best fused model had an area under the curve of 0.90 for unfavorable outcome prediction and outperformed other models with an mean absolute error of 0.90 (95% CI, 0.79-1.01), and the highest percentage of mRS score predictions within ±1 category (83% [95% CI, 78%-87%]). A Deep Learning-based imaging model fused with clinical variables can be used to predict 90-day stroke outcome with reduced subjectivity and user burden

Elevated Hypoperfusion Intensity Ratio (HIR) observed in patients with a large vessel occlusion (LVO) presenting in the evening.

Circadian variability has been implicated in timing of stroke onset, yet the full impact of underlying biological rhythms on acute stroke perfusion patterns is not known. We aimed to describe the relationship between time of stroke onset and perfusion profiles in patients with large vessel occlusion (LVO). A retrospective observational study was conducted using prospective registries of four stroke centers across North America and Europe with systematic use of perfusion imaging in clinical care. Included patients had stroke due to ICA, M1 or M2 occlusion and baseline perfusion imaging performed within 24h from last-seen-well (LSW). Stroke onset was divided into eight hour intervals: (1) Night: 23:00-6:59, (2) Day: 7:00-14:59, (3) Evening: 15:00-22:59. Core volume was estimated on CT perfusion (rCBF &lt;30%) or DWI-MRI (ADC &lt;620) and the collateral circulation was estimated with the Hypoperfusion Intensity Ratio (HIR = [Tmax&gt;10s]/[Tmax&gt;6s]). Non-parametric testing was conducted using SPSS to account for the non-normalized dependent variables. A total of 1506 cases were included (median age 74.9 years, IQR 63.0-84.0). Median NIHSS, core volumes, and HIR were 14.0 (IQR 8.0-20.0), 13.0mL (IQR 0.0-42.0), and 0.4 (IQR 0.2-0.6) respectively. Most strokes occurred during the Day (n = 666, 44.2%), compared to Night (n = 360, 23.9%), and Evening (n = 480, 31.9%). HIR was highest, indicating worse collaterals, in the Evening compared to the other timepoints (p = 0.006). Controlling for age and time to imaging, Evening strokes had significantly higher HIR compared to Day (p = 0.013). Our retrospective analysis suggests that HIR is significantly higher in the evening, indicating poorer collateral activation which may lead to larger core volumes in these patients