Generator Power Optimisation for a More-Electric Aircraft by Use of a Virtual Iron Bird

A prodedure is developed to minimise the generator design power within the electric power system of a future more-/ all-electric aircraft. This allows to save weight on the generators and on other equipment of the electic power system. Execution of the optimisation procedure by hand demonstrates the complexity of the problem. An automation of the process shows the capabilities of integrated modelling, simulation and optimisation tools

Physiologically-Based Pharmacokinetic (PBPK) Modeling Providing Insights into Fentanyl Pharmacokinetics in Adults and Pediatric Patients

Fentanyl is widely used for analgesia, sedation, and anesthesia both in adult and pediatric populations. Yet, only few pharmacokinetic studies of fentanyl in pediatrics exist as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling is a mechanistic approach to explore drug pharmacokinetics and allows extrapolation from adult to pediatric populations based on age-related physiological differences. The aim of this study was to develop a PBPK model of fentanyl and norfentanyl for both adult and pediatric populations. The adult PBPK model was established in PK-Sim® using data from 16 clinical studies and was scaled to several pediatric subpopulations. ~93% of the predicted AUClast values in adults and ~88% in pediatrics were within 2-fold of the corresponding value observed. The adult PBPK model predicted a fraction of fentanyl dose metabolized to norfentanyl of ~33% and a fraction excreted in urine of ~7%. In addition, the pediatric PBPK model was used to simulate differences in peak plasma concentrations after bolus injections and short infusions. The novel PBPK models could be helpful to further investigate fentanyl pharmacokinetics in both adult and pediatric populations

Comparison of isoflurane and propofol sedation in critically ill COVID-19 patients-a retrospective chart review

Purpose In this retrospective study, we compared inhaled sedation with isoflurane to intravenous propofol in invasively ventilated COVID-19 patients with ARDS (Acute Respiratory Distress Syndrome). Methods Charts of all 20 patients with COVID-19 ARDS admitted to the ICU of a German University Hospital during the first wave of the pandemic between 22/03/2020 and 21/04/2020 were reviewed. Among screened 333 days, isoflurane was used in 97 days, while in 187 days, propofol was used for 12 h or more. The effect and dose of these two sedatives were compared. Mixed sedation days were excluded. Results Patients’ age (median [interquartile range]) was 64 (60–68) years. They were invasively ventilated for 36 [21–50] days. End-tidal isoflurane concentrations were high (0.96 ± 0.41 Vol %); multiple linear regression yielded the ratio (isoflurane infusion rate)/(minute ventilation) as the single best predictor. Infusion rates were decreased under ECMO (3.5 ± 1.4 versus 7.1 ± 3.2 ml∙h−1; p < 0.001). In five patients, the maximum recommended dose of propofol of 4 mg∙hour−1∙kg−1ABW was exceeded on several days. On isoflurane compared to propofol days, neuro-muscular blocking agents (NMBAs) were used less frequently (11% versus 21%; p < 0.05), as were co-sedatives (7% versus 31%, p < 0.001); daily opioid doses were lower (720 [720–960] versus 1080 [720–1620] mg morphine equivalents, p < 0.001); and RASS scores indicated deeper levels of sedation (− 4.0 [− 4.0 to − 3.0] versus − 3.0 [− 3.6 to − 2.5]; p < 0.01). Conclusion Isoflurane provided sufficient sedation with less NMBAs, less polypharmacy and lower opioid doses compared to propofol. High doses of both drugs were needed in severely ill COVID-19 patients

Shape from Projections via Differentiable Forward Projector for Computed Tomography

In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data

Cigarette smoke and electronic cigarettes differentially activate bronchial epithelial cells

Background: The use of electronic cigarettes (ECIGs) is increasing, but the impact of ECIG-vapor on cellular processes like inflammation or host defense are less understood. The aim of the present study was to compare the acute effects of traditional cigarettes (TCIGs) and ECIG-exposure on host defense, inflammation, and cellular activation of cell lines and primary differentiated human airway epithelial cells (pHBE). Methods: We exposed pHBEs and several cell lines to TCIG-smoke or ECIG-vapor. Epithelial host defense and barrier integrity were determined. The transcriptome of airway epithelial cells was compared by gene expression array analysis. Gene interaction networks were constructed and differential gene expression over all groups analyzed. The expression of several candidate genes was validated by qRT-PCR. Results: Bacterial killing, barrier integrity and the expression of antimicrobial peptides were not affected by ECIG-vapor compared to control samples. In contrast, TCIGs negatively affected host defense and reduced barrier integrity in a significant way. Furthermore ECIG-exposure significantly induced IL-8 secretion from Calu-3 cells but had no effect on NCI-H292 or primary cells. The gene expression based on array analysis distinguished TCIG-exposed cells from ECIG and room air-exposed samples. Conclusion: The transcriptome patterns of host defense and inflammatory genes are significantly distinct between ECIG-exposed and TCIG-treated cells. The overall effects of ECIGs on epithelial cells are less in comparison to TCIG, and ECIG-vapor does not affect host defense. Nevertheless, although acute exposure to ECIG-vapor induces inflammation, and the expression of S100 proteins, long term in vivo data is needed to evaluate the chronic effects of ECIG use

IL-17C contributes to NTHi-induced inflammation and lung damage in experimental COPD and is present in sputum during acute exacerbations

Neutrophilic inflammation results in loss of lung function in chronic obstructive pulmonary disease (COPD). Gram-negative bacteria, such as nontypeable Haemophilus influenzae (NTHi), trigger acute exacerbations of COPD (AECOPD) and contribute to chronic lung inflammation. The pro-inflammatory cytokine interleukin-17C (IL-17C) is expressed by airway epithelial cells and regulates neutrophilic chemotaxis. Here, we explored the function of IL-17C in NTHi- and cigarette smoke (CS)-induced models of COPD. Neutrophilic inflammation and tissue destruction were decreased in lungs of IL-17C-deficient mice (Il-17c-/-) chronically exposed to NTHi. Numbers of pulmonary neutrophils were decreased in Il-17c-/- mice after acute exposure to the combination of NTHi and CS. However, Il-17c-/- mice were not protected from CS-induced lung inflammation. In a preliminary patient study, we show that IL-17C is present in sputum samples obtained during AECOPD and associates with disease severity. Concentrations of IL-17C were significantly increased during advanced COPD (GOLD III/IV) compared to moderate COPD (GOLD I/II). Concentrations of IL-17A and IL-17E did not associate with disease severity. Our data suggest that IL-17C promotes harmful pulmonary inflammation triggered by bacteria in COPD

Geometric reconstruction methods for electron tomography

Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is seriously affected by the problems of missing wedge artefacts and nonlinear projection intensities due to diffraction effects. The former refers to the fact that data cannot be acquired over the full $180^\circ$ tilt range; the latter implies that for some orientations, crystalline structures can show strong contrast changes. To overcome these problems we introduce and discuss several algorithms from the mathematical fields of geometric and discrete tomography. The algorithms incorporate geometric prior knowledge (mainly convexity and homogeneity), which also in principle considerably reduces the number of tilt angles required. Results are discussed for the reconstruction of an InAs nanowire

The composition of the pulmonary microbiota in sarcoidosis - an observational study

Background: Sarcoidosis is a systemic disease of unknown etiology. The disease mechanisms are largely speculative and may include the role microbial patterns that initiate and drive an underlying immune process. The aim of this study was to characterize the microbiota of the lung of patients with sarcoidosis and compare its composition and diversity with the results from patients with other interstitial lung disease (ILD) and historic healthy controls. Methods: Patients (sarcoidosis, n = 31; interstitial lung disease, n = 19) were recruited within the PULMOHOM study, a prospective cohort study to characterize inflammatory processes in pulmonary diseases. Bronchoscopy of the middle lobe or the lingula was performed and the recovered fluid was immediately sent for analysis of the pulmonary microbiota by 16sRNA gene sequencing. Subsequent bioinformatic analysis was performed to compare the groups. Results: There were no significant differences between patients with sarcoidosis or other ILDs with regard to microbiome composition and diversity. In addition, the abundance of the genera Atopobium, Fusobacterium, Mycobacterium or Propionibacterium were not different between the two groups. There were no gross differences to historical healthy controls. Conclusion: The analysis of the pulmonary microbiota based on 16sRNA gene sequencing did not show a significant dysbiosis in patients with sarcoidosis as compared to other ILD patients. These data do not exclude a microbiological component in the pathogenesis of sarcoidosis

IL-17C-mediated innate inflammation decreases the response to PD-1 blockade in a model of Kras-driven lung cancer

Chronic obstructive pulmonary disease (COPD) is associated with neutrophilic lung infammation and CD8 T cell exhaustion and is an important risk factor for the development of non-small cell lung cancer (NSCLC). The clinical response to programmed cell death-1 (PD-1) blockade in NSCLC patients is variable and likely afected by a coexisting COPD. The pro-infammatory cytokine interleukin-17C (IL-17C) promotes lung infammation and is present in human lung tumors. Here, we used a Krasdriven lung cancer model to examine the function of IL-17C in infammation-promoted tumor growth. Genetic ablation of Il-17c resulted in a decreased recruitment of infammatory cells into the tumor microenvironment, a decreased expression of tumor-promoting cytokines (e.g. interleukin-6 (IL-6)), and a reduced tumor proliferation in the presence of Haemophilus infuenzae- (NTHi) induced COPD-like lung infammation. Chronic COPD-like infammation was associated with the expression of PD-1 in CD8 lymphocytes and the membrane expression of the programmed death ligand (PD-L1) independent of IL-17C. Tumor growth was decreased in Il-17c defcient mice but not in wildtype mice after anti-PD-1 treatment. Our results suggest that strategies targeting innate immune mechanisms, such as blocking of IL-17C, may improve the response to anti-PD-1 treatment in lung cancer patients

Micro-rheological properties of lung homogenates correlate with infection severity in a mouse model of Pseudomonas aeruginosa lung infection

Lung infections caused by Pseudomonas aeruginosa pose a serious threat to patients suffering from, among others, cystic fibrosis, chronic obstructive pulmonary disease, or bronchiectasis, often leading to life-threatening complications. The establishment of a chronic infection is substantially related to communication between bacteria via quorum-sensing networks. In this study, we aimed to assess the role of quorum-sensing signaling molecules of the Pseudomonas quinolone signal (PQS) and to investigate the viscoelastic properties of lung tissue homogenates of PA-infected mice in a prolonged acute murine infection model. Therefore, a murine infection model was successfully established via intra-tracheal infection with alginate-supplemented Pseudomonas aeruginosa NH57388A. Rheological properties of lung homogenates were analyzed with multiple particle tracking (MPT) and quorum-sensing molecules were quantified with LC–MS/MS. Statistical analysis of bacterial load and quorum-sensing molecules showed a strong correlation between these biomarkers in infected lungs. This was accompanied by noticeable changes in the consistency of lung homogenates with increasing infection severity. Furthermore, viscoelastic properties of the lung homogenates strongly correlated with bacterial load and quorum sensing molecules. Considering the strong correlation between the viscoelasticity of lung homogenates and the aforementioned biomarkers, the viscoelastic properties of infected lungs might serve as reliable new biomarker for the evaluation of the severity of P. aeruginosa infections in murine models