Metoprolol exerts a non-class effect against ischaemia-reperfusion injury by abrogating exacerbated inflammation.

Clinical guidelines recommend early intravenous β-blockers during ongoing myocardial infarction; however, it is unknown whether all β-blockers exert a similar cardioprotective effect. We experimentally compared three clinically approved intravenous β-blockers. Mice undergoing 45 min/24 h ischaemia-reperfusion (I/R) received vehicle, metoprolol, atenolol, or propranolol at min 35. The effect on neutrophil infiltration was tested in three models of exacerbated inflammation. Neutrophil migration was evaluated in vitro and in vivo by intravital microscopy. The effect of β-blockers on the conformation of the β1 adrenergic receptor was studied in silico. Of the tested β-blockers, only metoprolol ameliorated I/R injury [infarct size (IS) = 18.0% ± 0.03% for metoprolol vs. 35.9% ± 0.03% for vehicle; P < 0.01]. Atenolol and propranolol had no effect on IS. In the three exacerbated inflammation models, neutrophil infiltration was significantly attenuated only in the presence of metoprolol (60%, 50%, and 70% reductions vs. vehicle in myocardial I/R injury, thioglycolate-induced peritonitis, and lipopolysaccharide-induced acute lung injury, respectively). Migration studies confirmed the particular ability of metoprolol to disrupt neutrophil dynamics. In silico analysis indicated different intracellular β1 adrenergic receptor conformational changes when bound to metoprolol than to the other two β-blockers. Metoprolol exerts a disruptive action on neutrophil dynamics during exacerbated inflammation, resulting in an infarct-limiting effect not observed with atenolol or propranolol. The differential effect of β-blockers may be related to distinct conformational changes in the β1 adrenergic receptor upon metoprolol binding. If these data are confirmed in a clinical trial, metoprolol should become the intravenous β-blocker of choice for patients with ongoing infarction.Ministry of Science and Innovation (‘RETOS 2019’ grant N_ PID2019-107332RB-I00), Instituto de Salud Carlos III (ISCIII; PI16/02110), and European Regional Development Fund (# AC16/00021), Comunidad de Madrid (S2017/BMD-3867 RENIM-CM). B.I. is supported by an ERCCoG grant (819775). E.O. is supported by funds from the Comunidad de Madrid Programa de Atraccion de Talento (2017-T1/BMD-5185). A.C-M. and R.V-G are supported by fellowships from the Ministerio de Ciencia e Innovacion (MCN) and ISCIII (FPU2017/01932 and PFIS FI17/00045). D.V.L. is supported by an Iniciativa de Empleo Juvenil grant (PEJ-2017-TL/BMD-6463) from the Comunidad de Madrid. The CNIC is supported by the ISCIII, the MCN, and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (SEV-2015-0505).S

Bosutinib versus imatinib for newly diagnosed chronic phase chronic myeloid leukemia: final results from the BFORE trial

This analysis from the multicenter, open-label, phase 3 BFORE trial reports efficacy and safety of bosutinib in patients with newly diagnosed chronic phase (CP) chronic myeloid leukemia (CML) after five years' follow-up. Patients were randomized to 400-mg once-daily bosutinib (n = 268) or imatinib (n = 268; three untreated). At study completion, 59.7% of bosutinib- and 58.1% of imatinib-treated patients remained on study treatment. Median duration of treatment and time on study was 55 months in both groups. Cumulative major molecular response (MMR) rate by 5 years was higher with bosutinib versus imatinib (73.9% vs. 64.6%; odds ratio, 1.57 [95% CI, 1.08-2.28]), as were cumulative MR4 (58.2% vs. 48.1%; 1.50 [1.07-2.12]) and MR4.5 (47.4% vs. 36.6%; 1.57 [1.11-2.22]) rates. Superior MR with bosutinib versus imatinib was consistent across Sokal risk groups, with greatest benefit seen in patients with high risk. Treatment-emergent adverse events (TEAEs) were consistent with 12-month data. After 5 years of follow-up there was an increase in the incidence of cardiac, effusion, renal, and vascular TEAEs in bosutinib- and imatinib-treated patients, but overall, no new safety signals were identified. These final results support 400-mg once-daily bosutinib as standard-of-care in patients with newly diagnosed CP CML.This trial was registered at www.clinicaltrials.gov as #NCT02130557

Ruxolitinib for Glucocorticoid-Refractory Acute Graft-versus-Host Disease

BACKGROUND: Acute graft-versus-host disease (GVHD) remains a major limitation of allogeneic stem-cell transplantation; not all patients have a response to standard glucocorticoid treatment. In a phase 2 trial, ruxolitinib, a selective Janus kinase (JAK1 and JAK2) inhibitor, showed potential efficacy in patients with glucocorticoid-refractory acute GVHD. METHODS: We conducted a multicenter, randomized, open-label, phase 3 trial comparing the efficacy and safety of oral ruxolitinib (10 mg twice daily) with the investigator's choice of therapy from a list of nine commonly used options (control) in patients 12 years of age or older who had glucocorticoid-refractory acute GVHD after allogeneic stem-cell transplantation. The primary end point was overall response (complete response or partial response) at day 28. The key secondary end point was durable overall response at day 56. RESULTS: A total of 309 patients underwent randomization; 154 patients were assigned to the ruxolitinib group and 155 to the control group. Overall response at day 28 was higher in the ruxolitinib group than in the control group (62% [96 patients] vs. 39% [61]; odds ratio, 2.64; 95% confidence interval [CI], 1.65 to 4.22; P<0.001). Durable overall response at day 56 was higher in the ruxolitinib group than in the control group (40% [61 patients] vs. 22% [34]; odds ratio, 2.38; 95% CI, 1.43 to 3.94; P<0.001). The estimated cumulative incidence of loss of response at 6 months was 10% in the ruxolitinib group and 39% in the control group. The median failure-free survival was considerably longer with ruxolitinib than with control (5.0 months vs. 1.0 month; hazard ratio for relapse or progression of hematologic disease, non-relapse-related death, or addition of new systemic therapy for acute GVHD, 0.46; 95% CI, 0.35 to 0.60). The median overall survival was 11.1 months in the ruxolitinib group and 6.5 months in the control group (hazard ratio for death, 0.83; 95% CI, 0.60 to 1.15). The most common adverse events up to day 28 were thrombocytopenia (in 50 of 152 patients [33%] in the ruxolitinib group and 27 of 150 [18%] in the control group), anemia (in 46 [30%] and 42 [28%], respectively), and cytomegalovirus infection (in 39 [26%] and 31 [21%]). CONCLUSIONS: Ruxolitinib therapy led to significant improvements in efficacy outcomes, with a higher incidence of thrombocytopenia, the most frequent toxic effect, than that observed with control therapy

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Measurement of the (eta c)(1S) production cross-section in proton-proton collisions via the decay (eta c)(1S) -&gt; p(p)over-bar

The production of the $\eta_c (1S)$ state in proton-proton collisions is probed via its decay to the $p \bar{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5$ GeV/c. The cross-section for prompt production of $\eta_c (1S)$ mesons relative to the prompt $J/\psi$ cross-section is measured, for the first time, to be $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.74 \pm 0.29 \pm 0.28 \pm 0.18 _{B}$ at a centre-of-mass energy $\sqrt{s} = 7$ TeV using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$, and $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{B}$ at $\sqrt{s} = 8$ TeV using 2.0 fb$^{-1}$. The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta_c (1S)$ and $J/\psi$ decays to the $p \bar{p}$ final state. In addition, the inclusive branching fraction of $b$-hadron decays into $\eta_c (1S)$ mesons is measured, for the first time, to be $B ( b \rightarrow \eta_c X ) = (4.88 \pm 0.64 \pm 0.25 \pm 0.67 _{B}) \times 10^{-3}$, where the third uncertainty includes also the uncertainty on the $J/\psi$ inclusive branching fraction from $b$-hadron decays. The difference between the $J/\psi$ and $\eta_c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1$ MeV/c$^2$.The production of the $\eta _c (1S)$ state in proton-proton collisions is probed via its decay to the $p\overline{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5 \mathrm{{\,GeV/}{ c}}$ . The cross-section for prompt production of $\eta _c (1S)$ mesons relative to the prompt ${{ J}}/{\psi }$ cross-section is measured, for the first time, to be $\sigma _{\eta _c (1S)}/\sigma _{{{{ J}}/{\psi }}} = 1.74\, \pm \,0.29\, \pm \, 0.28\, \pm \,0.18 _{{\mathcal{B}}}$ at a centre-of-mass energy ${\sqrt{s}} = 7 {~\mathrm{TeV}}$ using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$ , and $\sigma _{\eta _c (1S)}/\sigma _{{{{ J}}/{\psi }}} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{{\mathcal{B}}}$ at ${\sqrt{s}} = 8 {~\mathrm{TeV}}$ using 2.0 fb$^{-1}$ . The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta _c (1S)$ and ${{ J}}/{\psi }$ decays to the $p\overline{p}$ final state. In addition, the inclusive branching fraction of ${b}$ -hadron decays into $\eta _c (1S)$ mesons is measured, for the first time, to be ${\mathcal{B}}( b {\rightarrow } \eta _c X ) = (4.88\, \pm \,0.64\, \pm \,0.29\, \pm \, 0.67 _{{\mathcal{B}}}) \times 10^{-3}$ , where the third uncertainty includes also the uncertainty on the ${{ J}}/{\psi }$ inclusive branching fraction from ${b}$ -hadron decays. The difference between the ${{ J}}/{\psi }$ and $\eta _c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1 {\mathrm {\,MeV\!/}c^2}$ .The production of the $\eta_c (1S)$ state in proton-proton collisions is probed via its decay to the $p \bar{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5$ GeV/c. The cross-section for prompt production of $\eta_c (1S)$ mesons relative to the prompt $J/\psi$ cross-section is measured, for the first time, to be $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.74 \pm 0.29 \pm 0.28 \pm 0.18 _{B}$ at a centre-of-mass energy $\sqrt{s} = 7$ TeV using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$, and $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{B}$ at $\sqrt{s} = 8$ TeV using 2.0 fb$^{-1}$. The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta_c (1S)$ and $J/\psi$ decays to the $p \bar{p}$ final state. In addition, the inclusive branching fraction of $b$-hadron decays into $\eta_c (1S)$ mesons is measured, for the first time, to be $B ( b \rightarrow \eta_c X ) = (4.88 \pm 0.64 \pm 0.29 \pm 0.67 _{B}) \times 10^{-3}$, where the third uncertainty includes also the uncertainty on the $J/\psi$ inclusive branching fraction from $b$-hadron decays. The difference between the $J/\psi$ and $\eta_c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1$ MeV/c$^2$

Angular analysis of the B-0 -&gt; K*(0) e(+) e(-) decay in the low-q(2) region

An angular analysis of the $B^0 \rightarrow K^{*0} e^+ e^-$ decay is performed using a data sample, corresponding to an integrated luminosity of 3.0 {\mbox{fb}^{-1}}, collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of 7 and 8 TeV during 2011 and 2012. For the first time several observables are measured in the dielectron mass squared ($q^2$) interval between 0.002 and 1.120${\mathrm{\,Ge\kern -0.1em V^2\!/}c^4}$. The angular observables $F_{\mathrm{L}}$ and $A_{\mathrm{T}}^{\mathrm{Re}}$ which are related to the $K^{*0}$ polarisation and to the lepton forward-backward asymmetry, are measured to be $F_{\mathrm{L}}= 0.16 \pm 0.06 \pm0.03$ and $A_{\mathrm{T}}^{\mathrm{Re}} = 0.10 \pm 0.18 \pm 0.05$, where the first uncertainty is statistical and the second systematic. The angular observables $A_{\mathrm{T}}^{(2)}$ and $A_{\mathrm{T}}^{\mathrm{Im}}$ which are sensitive to the photon polarisation in this $q^2$ range, are found to be $A_{\mathrm{T}}^{(2)} = -0.23 \pm 0.23 \pm 0.05$ and $A_{\mathrm{T}}^{\mathrm{Im}} =0.14 \pm 0.22 \pm 0.05$. The results are consistent with Standard Model predictions.An angular analysis of the B$^{0}$ → K^{*}^{0} e$^{+}$ e$^{−}$ decay is performed using a data sample, corresponding to an integrated luminosity of 3.0 fb$^{−1}$, collected by the LHCb experiment in pp collisions at centre-of-mass energies of 7 and 8 TeV during 2011 and 2012. For the first time several observables are measured in the dielectron mass squared (q$^{2}$) interval between 0.002 and 1.120 GeV$^{2}$ /c$^{4}$. The angular observables F$_{L}$ and A$_{T}^{Re}$ which are related to the K^{*}^{0} polarisation and to the lepton forward-backward asymmetry, are measured to be F$_{L}$ = 0.16 ± 0.06 ± 0.03 and A$_{T}^{Re}$  = 0.10 ± 0.18 ± 0.05, where the first uncertainty is statistical and the second systematic. The angular observables A$_{T}^{(2)}$ and A$_{T}^{Im}$ which are sensitive to the photon polarisation in this q$^{2}$ range, are found to be A$_{T}^{(2)}$  = − 0.23 ± 0.23 ± 0.05 and A$_{T}^{Im}$  = 0.14 ± 0.22 ± 0.05. The results are consistent with Standard Model predictions.An angular analysis of the $B^0 \rightarrow K^{*0} e^+ e^-$ decay is performed using a data sample, corresponding to an integrated luminosity of 3.0 {\mbox{fb}^{-1}}, collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of 7 and 8 TeV during 2011 and 2012. For the first time several observables are measured in the dielectron mass squared ($q^2$) interval between 0.002 and 1.120${\mathrm{\,Ge\kern -0.1em V^2\!/}c^4}$. The angular observables $F_{\mathrm{L}}$ and $A_{\mathrm{T}}^{\mathrm{Re}}$ which are related to the $K^{*0}$ polarisation and to the lepton forward-backward asymmetry, are measured to be $F_{\mathrm{L}}= 0.16 \pm 0.06 \pm0.03$ and $A_{\mathrm{T}}^{\mathrm{Re}} = 0.10 \pm 0.18 \pm 0.05$, where the first uncertainty is statistical and the second systematic. The angular observables $A_{\mathrm{T}}^{(2)}$ and $A_{\mathrm{T}}^{\mathrm{Im}}$ which are sensitive to the photon polarisation in this $q^2$ range, are found to be $A_{\mathrm{T}}^{(2)} = -0.23 \pm 0.23 \pm 0.05$ and $A_{\mathrm{T}}^{\mathrm{Im}} =0.14 \pm 0.22 \pm 0.05$. The results are consistent with Standard Model predictions