Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

The ratios of branching fractions $\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu})$ and $\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu})$ are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb${ }^{-1}$ of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode $\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}$. The measured values are $\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024$ and $\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066$, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is $\rho=-0.43$. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

New advances in the management of acute coronary syndromes: 1. Matching treatment to risk

The case Mrs. D is a 58-year-old woman who presents to the emergency department because of a 2-hour episode of tightness in her chest, which had spontaneously resolved 1 hour before her arrival at the hospital. She has adult-onset diabetes mellitus and hypercholesterolemia, both of which have been controlled with medications. Her blood pressure is normal (120/75 mm Hg), as are the other findings at physical examination. An electrocardiogram (ECG) shows T-wave flattening in the lateral leads and a 1.5-mm T-wave inversion in leads II, III and aVF. The creatine kinase (CK) level and CK MB fraction are normal, but the cardiac troponin I level is 0.9 µg/L (lower limit of detection 0.3 µg/L). The emergency physician assesses Mrs. D&apos;s risk status and decides on treatment. A n acute coronary syndrome (ACS) -unstable angina or myocardial infarction -is an important cause of illness and premature death and a common reason for hospital admission. Recent advances in treatment, such as the glycoprotein IIb/IIIa inhibitors eptifibatide and tirofiban, low-molecular-weight heparin, direct thrombin inhibitors, clopidogrel, and the safer and more widespread application of percutaneous coronary intervention, have raised questions about the optimal use of these new management strategies. Tailoring treatment to match risk not only ensures that the patient who will benefit most receives appropriate therapy, it also avoids potentially hazardous treatment in patients with a good prognosis. Patients with an acute coronary syndrome (ACS) and those with similar clinical presentations have a wide spectrum of clinical outcomes. We examine how the physician can use information available in the first few hours after the onset of symptoms to choose appropriate treatment based on diagnosis and risk assessment. Unstable angina and myocardial infarction are often clinically indistinguishable and usually present with a prolonged episode of chest pain that starts without provocation. Myocardial infarction is diagnosed by detecting evidence of myocardial injury with the presence of abnormal levels of circulating biochemical markers such as creatine kinase (CK) or one of the troponins. However, with the development of increasingly sensitive biochemical markers of cardiac injury, the distinction between unstable angina and myocardial infarction has become less well defined. Both unstable angina and myocardial infarction usually result from atherosclerotic plaque disruption and thrombotic occlusion of a coronary artery. The outcome depends on the site and magnitude of plaque rupture, the resulting flow disturbance, the extent and duration of the thrombotic occlusion, and the presence or absence of an adequate collateral coronary circulation. Consequent to the interaction of these factors, plaque rupture results in a range of symptoms (from none to prolonged chest pain) and various outcomes (no detectable event, unstable angina, myocardial infarction or sudden death). The subsequent course and outcome will depend on the severity of the initial coronary event and the baseline condition of the patient (his or her age, previous coronary event, left ventricular function and other comorbidity). An accurate diagnosis and estimation of the risk of an adverse outcome are prerequisites to selecting the most appropriate treatment. Early triage of patients by history and electrocardiogram (ECG) findings initiates a clinical suspicion of ACS and distinguishes ACS patients from those with non-coronary chest pain or stable angina. Diagnosis and risk assessment of the patient presenting with chest pain an