Potential of a cyclone prototype spacer to improve in vitro dry powder delivery

Copyright The Author(s) 2013. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are creditedPurpose: Low inspiratory force in patients with lung disease is associated with poor deagglomeration and high throat deposition when using dry powder inhalers (DPIs). The potential of two reverse flow cyclone prototypes as spacers for commercial carrierbased DPIs was investigated. Methods: Cyclohaler®, Accuhaler® and Easyhaler® were tested with and without the spacers between 30-60 Lmin-1. Deposition of particles in the next generation impactor and within the devices was determined by high performance liquid chromatography. Results: Reduced induction port deposition of the emitted particles from the cyclones was observed due to the high retention of the drug within the spacers (e.g. salbutamol sulphate (SS): 67.89 ± 6.51 % at 30 Lmin-1 in Cheng 1). Fine particle fractions of aerosol as emitted from the cyclones were substantially higher than the DPIs alone. Moreover, the aerodynamic diameters of particles emitted from the cyclones were halved compared to the DPIs alone (e.g. SS from the Cyclohaler® at 4 kPa: 1.08 ± 0.05 μm vs. 3.00 ± 0.12 μm, with and without Cheng 2, respectively) and unaltered with increased flow rates. Conclusion: This work has shown the potential of employing a cyclone spacer for commercial carrier-based DPIs to improve inhaled drug delivery.Peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in Covid-19.

Host-mediated lung inflammation is present,1 and drives mortality,2 in critical illness caused by Covid-19. Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development.3 Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study(GWAS) in 2244 critically ill Covid-19 patients from 208 UK intensive care units (ICUs). We identify and replicate novel genome-wide significant associations, on chr12q24.13 (rs10735079, p=1.65 [Formula: see text] 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), on chr19p13.2 (rs2109069, p=2.3 [Formula: see text] 10-12) near the gene encoding tyrosine kinase 2 (TYK2), on chr19p13.3 (rs2109069, p=3.98 [Formula: see text] 10-12) within the gene encoding dipeptidyl peptidase 9 (DPP9), and on chr21q22.1 (rs2236757, p=4.99 [Formula: see text] 10-8) in the interferon receptor gene IFNAR2. We identify potential targets for repurposing of licensed medications: using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease; transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice

Dexmedetomidine- or Clonidine-Based Sedation Compared With Propofol in Critically Ill Patients

Importance Whether α2-adrenergic receptor agonist–based sedation, compared with propofol-based sedation, reduces time to extubation in patients receiving mechanical ventilation in the intensive care unit (ICU) is uncertain. Objective To evaluate whether dexmedetomidine- or clonidine-based sedation reduces duration of mechanical ventilation compared with propofol-based sedation (usual care). Design, Setting, and Participants Pragmatic, open-label randomized clinical trial conducted at 41 ICUs in the UK including adults who were within 48 hours of starting mechanical ventilation, were receiving propofol plus an opioid for sedation and analgesia, and were expected to require mechanical ventilation for 48 hours or longer. The median time from intubation to randomization was 21.0 (IQR, 13.2-31.3) hours. Recruitment occurred from December 2018 to October 2023; the last follow-up occurred on December 10, 2023. Interventions The bedside algorithms used targeted a Richmond Agitation-Sedation Scale score of −2 to 1 (unless clinicians requested deeper sedation). The algorithms supported uptitration in the dexmedetomidine- and clonidine-based sedation intervention groups and supported downtitration for propofol-based sedation followed by sedation primarily with the allocated sedation (dexmedetomidine or clonidine). If required, supplemental use of propofol was permitted. Main Outcomes and Measures The primary outcome was time from randomization to successful extubation. The secondary outcomes included mortality, sedation quality, rates of delirium, and cardiovascular adverse events. Results Among the 1404 patients in the analysis population (mean age, 59.2 [SD, 14.9] years; 901 [64%] were male; and the mean APACHE II score was 20.3 [SD, 8.2]), the subdistribution hazard ratio (HR) for time to successful extubation was 1.09 (95% CI, 0.96-1.25; P = .20) for dexmedetomidine (n = 457) vs propofol (n = 471) and was 1.05 (95% CI, 0.95-1.17; P = .34) for clonidine (n = 476) vs propofol (n = 471). The median time from randomization to successful extubation was 136 (95% CI, 117-150) hours for dexmedetomidine, 146 (95% CI, 124-168) hours for clonidine, and 162 (95% CI, 136-170) hours for propofol. In the predefined subgroup analyses, there were no interactions with age, sepsis status, median Sequential Organ Failure Assessment score, or median delirium risk score. Among the secondary outcomes, agitation occurred at a higher rate with dexmedetomidine vs propofol (risk ratio [RR], 1.54 [95% CI, 1.21-1.97]) and with clonidine vs propofol (RR, 1.55 [95% CI, 1.22-1.97]). Compared with propofol, the rates of severe bradycardia (heart rate <50/min) were higher with dexmedetomidine (RR, 1.62 [95% CI, 1.36-1.93]) and clonidine (RR, 1.58 [95% CI, 1.33-1.88]). Compared with propofol, mortality was similar over 180 days for dexmedetomidine (HR, 0.98 [95% CI, 0.77-1.24]) and clonidine (HR, 1.04 [95% CI, 0.82-1.31]). Conclusions and Relevance In critically ill patients, neither dexmedetomidine nor clonidine was superior to propofol in reducing time to successful extubation. Trial Registration ClinicalTrials.gov Identifier: NCT0365383

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease