A novel formulation of inhaled sodium cromoglicate (PA101) in idiopathic pulmonary fibrosis and chronic cough: a randomised, double-blind, proof-of-concept, phase 2 trial

Background Cough can be a debilitating symptom of idiopathic pulmonary fibrosis (IPF) and is difficult to treat. PA101 is a novel formulation of sodium cromoglicate delivered via a high-efficiency eFlow nebuliser that achieves significantly higher drug deposition in the lung compared with the existing formulations. We aimed to test the efficacy and safety of inhaled PA101 in patients with IPF and chronic cough and, to explore the antitussive mechanism of PA101, patients with chronic idiopathic cough (CIC) were also studied. Methods This pilot, proof-of-concept study consisted of a randomised, double-blind, placebo-controlled trial in patients with IPF and chronic cough and a parallel study of similar design in patients with CIC. Participants with IPF and chronic cough recruited from seven centres in the UK and the Netherlands were randomly assigned (1:1, using a computer-generated randomisation schedule) by site staff to receive PA101 (40 mg) or matching placebo three times a day via oral inhalation for 2 weeks, followed by a 2 week washout, and then crossed over to the other arm. Study participants, investigators, study staff, and the sponsor were masked to group assignment until all participants had completed the study. The primary efficacy endpoint was change from baseline in objective daytime cough frequency (from 24 h acoustic recording, Leicester Cough Monitor). The primary efficacy analysis included all participants who received at least one dose of study drug and had at least one post-baseline efficacy measurement. Safety analysis included all those who took at least one dose of study drug. In the second cohort, participants with CIC were randomly assigned in a study across four centres with similar design and endpoints. The study was registered with ClinicalTrials.gov (NCT02412020) and the EU Clinical Trials Register (EudraCT Number 2014-004025-40) and both cohorts are closed to new participants. Findings Between Feb 13, 2015, and Feb 2, 2016, 24 participants with IPF were randomly assigned to treatment groups. 28 participants with CIC were enrolled during the same period and 27 received study treatment. In patients with IPF, PA101 reduced daytime cough frequency by 31·1% at day 14 compared with placebo; daytime cough frequency decreased from a mean 55 (SD 55) coughs per h at baseline to 39 (29) coughs per h at day 14 following treatment with PA101, versus 51 (37) coughs per h at baseline to 52 (40) cough per h following placebo treatment (ratio of least-squares [LS] means 0·67, 95% CI 0·48–0·94, p=0·0241). By contrast, no treatment benefit for PA101 was observed in the CIC cohort; mean reduction of daytime cough frequency at day 14 for PA101 adjusted for placebo was 6·2% (ratio of LS means 1·27, 0·78–2·06, p=0·31). PA101 was well tolerated in both cohorts. The incidence of adverse events was similar between PA101 and placebo treatments, most adverse events were mild in severity, and no severe adverse events or serious adverse events were reported. Interpretation This study suggests that the mechanism of cough in IPF might be disease specific. Inhaled PA101 could be a treatment option for chronic cough in patients with IPF and warrants further investigation

Performance of reconstruction and identification of τ leptons decaying to hadrons and vτ in pp collisions at √s=13 TeV

The algorithm developed by the CMS Collaboration to reconstruct and identify τ leptons produced in proton-proton collisions at √s=7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of π⁰ candidates, and improvements in multivariate discriminants to separate τ leptons from jets and electrons. The algorithm is extended to reconstruct τ leptons in highly Lorentz-boosted pair production, and in the high-level trigger. The performance of the algorithm is studied using proton-proton collisions recorded during 2016 at √s=13 TeV, corresponding to an integrated luminosity of 35.9 fb¯¹. The performance is evaluated in terms of the efficiency for a genuine τ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as τ leptons. The results are found to be very close to those expected from Monte Carlo simulation

Search for heavy resonances decaying to a top quark and a bottom quark in the lepton+jets final state in proton–proton collisions at 13 TeV

A search is presented for narrow heavy resonances decaying to a top quark and a bottom quark using data collected by the CMS experiment at √s = 13TeV in 2016. The data set analyzed corresponds to an integrated luminosity of 35.9 fb−1. Final states that include a single lepton (e, μ), multiple jets, and missing transverse momentum are analyzed. No evidence is found for the production of a W′ boson, and the production of right-handed W′ bosons is excluded at 95% confidence level for masses up to 3.6 TeV depending on the scenario considered. Exclusion limits for W′ bosons are also presented as a function of their coupling strength to left- and right-handed fermions. These limits on a W′ boson decaying via a top and a bottom quark are the most stringent published to date

Measurement of angular parameters from the decay B⁰ → K⁎0^{⁎0} μ⁺ μ⁻ in proton–proton collisions at √s 8 TeV

Angular distributions of the decay B⁰  → K$^{⁎0}$ μ⁺ μ⁻ are studied using a sample of proton–proton collisions at √s=8TeV collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 20.5fb⁻¹ . An angular analysis is performed to determine the P₁ and P$^{\u27}$₅ parameters, where the P$^{\u27}$₅ parameter is of particular interest because of recent measurements that indicate a potential discrepancy with the standard model predictions. Based on a sample of 1397 signal events, the P₁ and P$^{\u27}$₅ parameters are determined as a function of the dimuon invariant mass squared. The measurements are in agreement with predictions based on the standard model