Metabolomics of chronic obstructive pulmonary disease and obstructive sleep apnea syndrome : response to Maniscalco and Motta

We appreciate Maniscalco and Motta’s comments on our recently published article ‘‘Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome’’ (Zabek et al. 2015) and we are grateful for the opportunity to clarify a number of points from our work. We are glad that the authors appreciated our data analysis and interpretation[…

Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome

Chronic obstructive pulmonary disease, COPD, affects the condition of the entire human organism and causes multiple comorbidities. Pathological lung changes lead to quantitative changes in the composition of the metabolites in different body fluids. The obstructive sleep apnea syndrome, OSAS, occurs in conjunction with chronic obstructive pulmonary disease in about 10–20 % of individuals who have COPD. Both conditions share the same comorbidities and this makes differentiating them difficult. The aim of this study was to investigate whether it is possible to diagnose a patient with either COPD or the OSA syndrome using a set of selected metabolites and to determine whether the metabolites that are present in one type of biofluid (serum, exhaled breath condensate or urine) or whether a combination of metabolites that are present in two biofluids or whether a set of metabolites that are present in all three biofluids are necessary to correctly diagnose a patient. A quantitative analysis of the metabolites in all three biofluid samples was performed using 1H NMR spectroscopy. A multivariate bootstrap approach that combines partial least squares regression with the variable importance in projection score (VIP-score) and selectivity ratio (SR) was adopted in order to construct discriminant diagnostic models for the groups of individuals with COPD and OSAS. A comparison study of all of the discriminant models that were constructed and validated showed that the discriminant partial least squares model using only ten urine metabolites (selected with the SR approach) has a specificity of 100 % and a sensitivity of 86.67 %. This model (AUCtest = 0.95) presented the best prediction performance. The main conclusion of this study is that urine metabolites, among the others, present the highest probability for correctly identifying patents with COPD and the lowest probability for an incorrect identification of the OSA syndrome as developed COPD. Another important conclusion is that the changes in the metabolite levels of exhaled breath condensates do not appear to be specific enough to differentiate between patients with COPD and OSA

The impact of gender on in-hospital mortality and long-term mortality in patients undergoing surgical aortic valve replacement: SAVR and SEX Study

Background: Surgical aortic valve replacement (SAVR) is among the most commonly performed valve valvular surgeries. Despite many previous studies conducted in this setting, the impact of gender on outcomes in the patients undergoing SAVR is still unclear. Aims: To define gender differences in short- and long-term mortality in patients undergoing SAVR. Methods: We analyzed retrospectively all the patients undergoing isolated SAVR from January 2006 to March 2020 in the Department of Cardiovascular Surgery and Transplantology in John Paul II Hospital in Cracow. The primary end point was in-hospital and long-term mortality. Secondary end points included the length duration of hospital stay and perioperative complications. Groups of men and women with regard to the prosthesis type were compared. Propensity score matching was performed to adjust for differences in baseline characteristics. Results: A total number of 4 510 patients undergoing isolated surgical SAVR were analyzed. A follow-up median (interquartile range [IQR]) was 2120 (1000–3452) days. Females constituted 41.55% of the cohort and were  older, displayed more non-cardiac comorbidities and faced a higher operative risk. In both genders, bioprostheses were more often applied (55.5% vs. 44.5%; P < 0.0001). In univariable analysis, gender was not associated linked to in-hospital fatality (3.7% vs. 3%; P = 0.15) and late mortality (rates) (23.37% vs. 23.52 %; P = 0.9). Upon adjustment for baseline characteristics (propensity score matching analysis) and considering 5-year survival, a long-term prognosis proved to be better in women with 86.8% comparing to 82.7% in men (P = 0.03). Conclusions: A key finding from this study suggests that the female gender was not associated with a higher in-hospital and late mortality rate compared to men. Further studies are needed to confirm long-term benefits  in women undergoing SAVR

Multi-Criteria Comparative Analysis of the Use of Subtractive and Additive Technologies in the Manufacturing of Offshore Machinery Components

The dynamic development of additive manufacturing technologies, especially over the last few years, has increased the range of possible industrial applications of 3D printed elements. This is a consequence of the distinct advantages of additive techniques, which include the possibility of improving the mechanical strength of products and shortening lead times. Offshore industry is one of these promising areas for the application of additive manufacturing. This paper presents a decision support method for the manufacturing of offshore equipment components, and compares a standard subtractive method with an additive manufacturing approach. An analytic hierarchy process was applied to select the most effective and efficient production method, considering CNC milling and direct metal laser sintering. A final set of decision criteria that take into account the specifics of the offshore industry sector are provided

Multi-Criteria Comparative Analysis of the Use of Subtractive and Additive Technologies in the Manufacturing of Offshore Machinery Components

The dynamic development of additive manufacturing technologies, especially over the last few years, has increased the range of possible industrial applications of 3D printed elements. This is a consequence of the distinct advantages of additive techniques, which include the possibility of improving the mechanical strength of products and shortening lead times. Offshore industry is one of these promising areas for the application of additive manufacturing. This paper presents a decision support method for the manufacturing of offshore equipment components, and compares a standard subtractive method with an additive manufacturing approach. An analytic hierarchy process was applied to select the most effective and efficient production method, considering CNC milling and direct metal laser sintering. A final set of decision criteria that take into account the specifics of the offshore industry sector are provided

Multi-criteria comparative analysis of the use of subtractive and additive technologies in the manufacturing of offshore machinery components

The dynamic development of additive manufacturing technologies, especially over the last few years, has increased the range of possible industrial applications of 3D printed elements. This is a consequence of the distinct advantages of additive techniques, which include the possibility of improving the mechanical strength of products and shortening lead times. Offshore industry is one of these promising areas for the application of additive manufacturing. This paper presents a decision support method for the manufacturing of offshore equipment components, and compares a standard subtractive method with an additive manufacturing approach. An analytic hierarchy process was applied to select the most effective and efficient production method, considering CNC milling and direct metal laser sintering. A final set of decision criteria that take into account the specifics of the offshore industry sector are provided

Differences in metabolic profiles of planktonic and biofilm cells in Staphylococcus aureus - 1H Nuclear Magnetic Resonance search for candidate biomarkers

Staphylococcus aureus is responsible for many types of infections related to biofilm presence. As the early diagnostics remains the best option for prevention of biofilm infections, the aim of the work presented was to search for differences in metabolite patterns of S. aureus ATCC6538 biofilm vs. free-swimming S. aureus planktonic forms. For this purpose, Nuclear Magnetic Resonance (NMR) spectroscopy was applied. Data obtained were supported by means of Scanning Electron Microscopy, quantitative cultures and X-ray computed microtomography. Metabolic trends accompanying S. aureus biofilm formation were found using Principal Component Analysis (PCA). Levels of isoleucine, alanine and 2,3-butanediol were significantly higher in biofilm than in planktonic forms, whereas level of osmoprotectant glycine-betaine was significantly higher in planktonic forms of S. aureus. Results obtained may find future application in clinical diagnostics of S. aureus biofilm-related infections