Standards for the care of people with cystic fibrosis (CF); Planning for a longer life.

This is the final of four papers updating standards for the care of people with CF. That this paper "Planning a longer life" was considered necessary, highlights how much CF care has progressed over the past decade. Several factors underpin this progress, notably increased numbers of people with CF with access to CFTR modulator therapy. As the landscape for CF changes, so do the hopes and aspirations of people with CF and their families. This paper reflects the need to consider people with CF not as a "problem" to be solved, but as a success, a potential and a voice to be heard. People with CF and the wider CF community have driven this approach, reflecting many of the topics in this paper. This exercise involved wide stakeholder engagement. People with CF are keen to contribute to research priorities and be involved in all stages of research. People with CF want healthcare professionals to respect them as individuals and consider the impact of our actions on the world around us. Navigating life presents challenges to all, but for people with CF these challenges are heightened and complex. In this paper we highlight the concerns and life moments that impact people with CF, and events that the CF team should aim to support, including the challenges around having a family. People with CF and their care teams must embrace the updated standards outlined in these four papers to enjoy the full potential for a healthier life.

Impact of lumacaftor/ivacaftor on the bacterial and fungal respiratory pathogens in cystic fibrosis: a prospective multicenter cohort study in Sweden.

BACKGROUND: A significant decline in pulmonary exacerbation rates has been reported in CF patients homozygous for F508del treated with lumacaftor/ivacaftor. However, it is still unclear whether this reduction reflects a diminished microbiological burden. OBJECTIVES: The aim of this study was to determine the impact of lumacaftor/ivacaftor on the bacterial and fungal burden. DESIGN: The study is a prospective multicenter cohort study including 132 CF patients homozygous for F508del treated with lumacaftor/ivacaftor. METHODS: Clinical parameters as well as bacterial and fungal outcomes 1 year after initiation of lumacaftor/ivacaftor were compared to data from 2 years prior to initiation of the treatment. Changes in the slope of the outcomes before and after the onset of treatment were assessed. RESULTS: Lung function measured as ppFEV1 (p < 0.001), body mass index (BMI) in adults (p < 0.001), and BMI z-score in children (p = 0.007) were improved after initiation of lumacaftor/ivacaftor. In addition, the slope of the prevalence of Streptococcus pneumoniae (p = 0.007) and Stenotrophomonas maltophilia (p < 0.001) shifted from positive to negative, that is, became less prevalent, 1 year after treatment, while the slope for Candida albicans (p = 0.009), Penicillium spp (p = 0.026), and Scedosporium apiospermum (p < 0.001) shifted from negative to positive. CONCLUSION: The current study showed a significant improvement in clinical parameters and a reduction of some of CF respiratory microorganisms 1 year after starting with lumacaftor/ivacaftor. However, no significant changes were observed for Pseudomonas aeruginosa, Staphylococcus aureus, or Aspergillus fumigatus, key pathogens in the CF context.

Towards better process management in wastewater treatment plants: Process analytics based on SHAP values for tree-based machine learning methods.

Understanding the mechanisms of pollutant removal in Wastewater Treatment Plants (WWTPs) is crucial for controlling effluent quality efficiently. However, the numerous treatment units, operational factors, and the underlying interactions between these units and factors usually obfuscate the comprehensive and precise understanding of the processes. We have previously proposed a machine learning (ML) framework to uncover complex cause-and-effect relationships in WWTPs. However, only one interpretable ML model, Random forest (RF), was studied and the interpretation method was not granular enough to reveal very detailed relationships between operational factors and effluent parameters. Thus, in this paper, we present an upgraded framework involving three interpretable tree-based models (RF, XGboost and LightGBM), three metrics (R2, Root mean squared error (RMSE), and Mean absolute error (MAE)) and a more advanced interpretation system SHapley Additive exPlanations (SHAP). Details of the framework are provided along with a demonstration of its practical applicability based on a case study of the Umeå WWTP in Sweden. Results show that, for both labels TSSe (Total suspended solids in effluent) and PO4e (Phosphate in effluent), the XGBoost models are optimal whereas the RF models are the least optimal, due to overfitting and polarized fitting. This study has yielded multiple new and significant findings with respect to the control of TSSe and PO4e in the Umeå WWTP and other similarly configured WWTPs. Additionally, this study has produced two important generic findings relating to ML applications for WWTPs (or even other process industries) in terms of cause-and-effect investigations. First, the model comparison should be carried out from multiple perspectives to ensure that underlying details are fully revealed and examined. Second, using a precise, robust, and granular (feature attribution available for individual instances) explanation method can bring extra insight into both model comparison and model interpretation. SHAP is recommended as we found it to be of great value in this study.

A machine learning framework to improve effluent quality control in wastewater treatment plants.

Due to the intrinsic complexity of wastewater treatment plant (WWTP) processes, it is always challenging to respond promptly and appropriately to the dynamic process conditions in order to ensure the quality of the effluent, especially when operational cost is a major concern. Machine Learning (ML) methods have therefore been used to model WWTP processes in order to avoid various shortcomings of conventional mechanistic models. However, to the best of the authors' knowledge, no ML applications have focused on investigating how operational factors can affect effluent quality. Additionally, the time lags between process steps have always been neglected, making it difficult to explain the relationships between operational factors and effluent quality. Therefore, this paper presents a novel ML-based framework designed to improve effluent quality control in WWTPs by clarifying the relationships between operational variables and effluent parameters. The framework consists of Random Forest (RF) models, Deep Neural Network (DNN) models, Variable Importance Measure (VIM) analyses, and Partial Dependence Plot (PDP) analyses, and uses a novel approach to account for the impact of time lags between processes. Details of the framework are provided along with a demonstration of its practical applicability based on a case study of the Umeå WWTP in Sweden involving a large number of samples (105763) representing the full scale of the plant's operations. Two effluent parameters, Total Suspended Solids in effluent (TSSe) and Phosphate in effluent (PO4e), and thirty-two operational variables are studied. RF models are developed, validated using DNN models as references, and shown to be suitable for VIM and PDP analyses. VIM identifies the variables that most strongly influence TSSe and PO4e, while PDP elucidates their specific effects on TSSe and PO4e. The major findings are: (1) Influent temperature is the most influential variable for both TSSe and PO4e, but it affects them in different ways; (2) PO4e depends strongly on the TSS in aeration basins - higher TSS concentrations in aeration basins generally promote PO4 removal, but excess TSS can have negative effects; (3) In general, the impact of TSS in aeration basins on TSSe and PO4e increases with the distances of the basin from the merging outlet, so more attention should be paid to the TSS concentration in the third or fourth aeration basins than the first and second ones; (4) Returning excessive amounts of sludge through the second return sludge pipe should be avoided because of its adverse impact on TSSe removal. These results could support the development of more advanced control strategies to increase control precision and reduce running costs in the Umeå WWTP and other similarly configured WWTPs. The framework could also be applied to other parameters in WWTPs and industrial processes in general if sufficient high-resolution data are available.

BPI-ANCA is expressed in the airways of cystic fibrosis patients and correlates to platelet numbers and Pseudomonas aeruginosa colonization.

BACKGROUND: Autoantibodies to bactericidal/permeability-increasing protein (BPI), BPI-ANCA, are often present in serum of patients with cystic fibrosis (CF), and correlate to airway colonization with Pseudomonas aeruginosa. The aim of the study was to investigate if BPI-ANCA IgA is also present in the airways of CF patients, and if its presence correlates with neutrophil counts, platelets, and P. aeruginosa DNA in sputum. METHODS: BPI-ANCA IgA was quantified in serum and sputum samples from adult CF patients (n = 45) by ELISA. Sputum neutrophil counts, platelets, and platelet-neutrophil complexes were assessed by flow cytometry, and P. aeruginosa DNA was analysed with RT-PCR. RESULTS: Serum BPI-ANCA IgA was present in 44% of the study participants, and this group also had significantly enhanced BPI-ANCA levels in sputum compared to serum negative patients. Sputum levels of BPI-ANCA IgA correlated with P. aeruginosa DNA (r = 0.63, p = 0.0003) and platelet counts in sputum (r = 0.60, p = 0.0002). CONCLUSIONS: BPI-ANCA is expressed in the airways of CF patients and correlates with P. aeruginosa load and platelet counts, suggesting a link to airway inflammation and mucosal immunity.

Increased platelet activation occurs in cystic fibrosis patients and correlates to clinical status.

Cystic fibrosis (CF) is an inflammatory lung disease. Platelets have an emerging role in inflammation, however previous studies of platelet activation in CF have generated conflicting results. In this study, we determined platelet function in CF patients and correlated platelet activation to establish clinical and laboratory parameters. Twenty-two patients, aged 20.7 to 54.4 (mean 34.0, SD 9.45) years and with a mean FEV1%pred (forced expiratory volume in one second, % of predicted) of 72 (SD 21.4, range 32-110) were recruited. A combination of platelet assays was used: platelet aggregation, platelet activation and platelet-leukocyte complex formation. Platelets from CF patients exhibited significantly increased aggregation when stimulated ex-vivo, a tendency towards increased platelet upregulation of CD62P, but no increase of GPIIb/IIIa activation (PAC-1). Platelet-monocyte complex (PMC) formation was significantly increased in CF patients compared to controls, while platelet-neutrophil complex formation was not. In the CF group, platelet aggregation correlates with levels of anti-neutrophil cytoplasmic antibodies (ANCA) with specificity for bactericidal/permeability-increasing protein (BPI), BPI-ANCA (r=0.56). The formation of PMCs correlates with lung function decline (1-FEV1%), CRP and BPI-ANCA (r=0.61, 0.55, 0.5). We therefore confirm the presence of increased platelet activation in CF patients, and determine that further evaluation of platelet activation in relation to prognostic factors in CF is warranted.

BPI-ANCA Provides Additional Clinical Information to Anti-Pseudomonas Serology: Results from a Cohort of 117 Swedish Cystic Fibrosis Patients.

Patients with cystic fibrosis (CF) colonized with Pseudomonas aeruginosa (P. aeruginosa) have worse prognosis compared with patients who are not. BPI-ANCA is an anti-neutrophil cytoplasmic antibody against BPI (bactericidal/permeability increasing protein) correlating with P. aeruginosa colonization and adverse long time prognosis. Whether it provides additional information as compared to standard anti-P. aeruginosa serology tests is not known. 117 nontransplanted CF patients at the CF centre in Lund, Sweden, were followed prospectively for ten years. Bacterial colonisation was classified according to the Leeds criteria. IgA BPI-ANCA was compared with assays for antibodies against alkaline protease (AP), Elastase (ELA), and Exotoxin A (ExoA). Lung function and patient outcome, alive, lung transplanted, or dead, were registered. BPI-ANCA showed the highest correlation with lung function impairment with an r-value of 0.44. Forty-eight of the 117 patients were chronically colonized with P. aeruginosa. Twenty of these patients experienced an adverse outcome. Receiver operator curve (ROC) analysis revealed that this could be predicted by BPI-ANCA (AUC = 0.77), (p = 0.002) to a better degree compared with serology tests. BPI-ANCA correlates better with lung function impairment and long time prognosis than anti-P. aeruginosa serology and has similar ability to identify patients with chronic P. aeruginosa.

BPI-ANCA and long-term prognosis among 46 adult CF patients: a prospective 10-year follow-up study.

INTRODUCTION: Anti-neutrophil cytoplasmic antibodies specific for bactericidal/permeability-increasing protein (BPI-ANCA) are frequent in CF patients and mainly develop in response to infection with Pseudomonas aeruginosa. It is not known to what extent BPI-ANCA correlates to prognosis. OBJECTIVES: To evaluate the prognostic value of IgA-BPI-ANCA, measured at the beginning of the study, for transplantation-free survival. METHODS: A cohort of 46 adult, nontransplanted CF patients was generated, 1995-1998, and characterized using Leeds criteria, lung function, and IgA-BPI-ANCA levels measured by ELISA. The cohort was followed until December 2009, using the combined endpoint of death or lung transplantation. RESULTS: Lung function and IgA-BPI-ANCA, but not Leeds criteria, were significantly associated with adverse outcome. No patient with normal lung function at baseline reached endpoint. Within 10 years 8/11 with high BPI-ANCA reached an endpoint compared to 3/17 ANCA-negative patients. A similar result was seen within the Leeds I group where 7 out of 9 BPI-ANCA-positive patients reached endpoint, compared to none of the 5 patients without BPI-ANCA. CONCLUSIONS: IgA-BPI-ANCA is associated with adverse outcome among Pseudomonas aeruginosa infected CF patients, suggesting that BPI-ANCA is a biomarker of an unfavourable host-pathogen interaction.

Simultaneous multiple immunoassays in a compact disc-shaped microfluidic device based on centrifugal force.

BACKGROUND: We explored the potential of a microfluidic device based on centrifugal force as an immunoassay platform by examining the imprecision of assays carried out with 200 nL of sample. METHODS: Biotinylated antibodies against alpha-fetoprotein (AFP), interleukin-6 (IL-6), and carcinoembryonic antigen [(CEA); 0.1 g/L each in 15 mmol/L phosphate-buffered saline (PBS) containing 0.1 mL/L Tween 20] were attached to a microcolumn packed with streptavidin-coated particles. A 200-nL sample was then allowed to pass through the microcolumn for 240 s, followed by Alexa 647-labeled detection antibody (7.5 mg/L in 15 mmol/L PBS containing 10 g/L bovine serum albumin). The flow rate was controlled by altering the rotational speed. Up to 104 sandwich type immunoassays were completed within 50 min. RESULTS: For AFP, IL-6, and CEA the detection limits were, respectively, 0.15, 1.25, and 1.31 pmol/L. Inter- and intraassay imprecisions (CVs) were <10% and <20%, respectively, for analyte concentrations >5 pmol/L. The CEA antibody had the lowest affinity according to fluorescence image analysis of the microcolumn region. The result was confirmed in a comparative study using BIAcore 3000. CONCLUSIONS: Day-to-day (total) imprecision (CV) of immunoassays on the compact disc-shaped device are <20%. Analysis of fluorescence images allows rapid ranking of antibodies according to their affinities.

Comparison of different IMAC techniques used for enrichment of phosphorylated peptides.

Four commercially available immobilized metal ion affinity chromatography (IMAC) methods for phosphopeptide enrichment were compared using small volumes and concentrations of phosphopeptide mixtures with or without extra-added bovine serum albumin (BSA) nonphosphorylated peptides. Addition of abundant tryptic BSA peptides to the phosphopeptide mixture increases the demand for selective IMAC capture. While SwellGel gallium Discs, IPAC Metal Chelating Resin, and ZipTipMC Pipette Tips allow for the possibility of enriching phosphopeptides, the Gyrolab MALDI IMAC1 also presents the possibility of verifying existing phosphopeptides after a dephosphorylation step. Phosphate-containing peptides are identified through a mass shift between phosphorylated and dephosphorylated spectra of 80 Da (or multiples of 80 Da). This verification is useful if the degree of phosphorylation is low in the sample or if the ionization is unfavorable, which often is the case for phosphopeptides. A peptide mixture in which phosphorylated serine, threonine, and tyrosine were represented was diluted in steps and thereafter enriched using the four different IMAC methods prior to analyses with matrix assisted laser desorption/ionization mass spectrometry. The enrichment of phosphopeptides using SwellGel Gallium Discs or Gyrolab MALDI IMAC1 was not significantly affected by the addition of abundant BSA peptides added to the sample mixture, and the achieved detection limits using these techniques were also the lowest. All four of the included phosphopeptides were detected by MALDI-MS only after enrichment using the Gyrolab MALDI IMAC1 compact disc (CD) and detection down to low femtomole levels was possible. Furthermore, selectivity, reproducibility, and detection for a number of other phosphopeptides using the IMAC CD are reported herein. For example, two phosphopeptides sent out in a worldwide survey performed by the Proteomics Research Group (PRG03) of the Association of Biomolecular Resource Facilities (ABRF) were detected and verified by means of the 80 Da mass shift achieved by on-column dephosphorylation.