Separating common from distinctive variation

BACKGROUND: Joint and individual variation explained (JIVE), distinct and common simultaneous component analysis (DISCO) and O2-PLS, a two-block (X-Y) latent variable regression method with an integral OSC filter can all be used for the integrated analysis of multiple data sets and decompose them in three terms: a low(er)-rank approximation capturing common variation across data sets, low(er)-rank approximations for structured variation distinctive for each data set, and residual noise. In this paper these three methods are compared with respect to their mathematical properties and their respective ways of defining common and distinctive variation. RESULTS: The methods are all applied on simulated data and mRNA and miRNA data-sets from GlioBlastoma Multiform (GBM) brain tumors to examine their overlap and differences. When the common variation is abundant, all methods are able to find the correct solution. With real data however, complexities in the data are treated differently by the three methods. CONCLUSIONS: All three methods have their own approach to estimate common and distinctive variation with their specific strength and weaknesses. Due to their orthogonality properties and their used algorithms their view on the data is slightly different. By assuming orthogonality between common and distinctive, true natural or biological phenomena that may not be orthogonal at all might be misinterpreted

Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies

Partial Least Squares-Discriminant Analysis (PLS-DA) is a PLS regression method with a special binary ‘dummy’ y-variable and it is commonly used for classification purposes and biomarker selection in metabolomics studies. Several statistical approaches are currently in use to validate outcomes of PLS-DA analyses e.g. double cross validation procedures or permutation testing. However, there is a great inconsistency in the optimization and the assessment of performance of PLS-DA models due to many different diagnostic statistics currently employed in metabolomics data analyses. In this paper, properties of four diagnostic statistics of PLS-DA, namely the number of misclassifications (NMC), the Area Under the Receiver Operating Characteristic (AUROC), Q2 and Discriminant Q2 (DQ2) are discussed. All four diagnostic statistics are used in the optimization and the performance assessment of PLS-DA models of three different-size metabolomics data sets obtained with two different types of analytical platforms and with different levels of known differences between two groups: control and case groups. Statistical significance of obtained PLS-DA models was evaluated with permutation testing. PLS-DA models obtained with NMC and AUROC are more powerful in detecting very small differences between groups than models obtained with Q2 and Discriminant Q2 (DQ2). Reproducibility of obtained PLS-DA models outcomes, models complexity and permutation test distributions are also investigated to explain this phenomenon. DQ2 and Q2 (in contrary to NMC and AUROC) prefer PLS-DA models with lower complexity and require higher number of permutation tests and submodels to accurately estimate statistical significance of the model performance. NMC and AUROC seem more efficient and more reliable diagnostic statistics and should be recommended in two group discrimination metabolomic studies

Multivariate statistical process control based on principal component analysis: implementation of framework in R

The interest in multivariate statistical process control (MSPC) has increased as the industrial processes have become more complex. This paper presents an industrial process involving a plastic part in which, due to the number of correlated variables, the inversion of the covariance matrix becomes impossible, and the classical MSPC cannot be used to identify physical aspects that explain the causes of variation or to increase the knowledge about the process behaviour. In order to solve this problem, a Multivariate Statistical Process Control based on Principal Component Analysis (MSPC-PCA) approach was used and an R code was developed to implement it according some commercial software used for this purpose, namely the ProMV (c) 2016 from ProSensus, Inc. (www.prosensus.ca). Based on used dataset, it was possible to illustrate the principles of MSPC-PCA. This work intends to illustrate the implementation of MSPC-PCA in R step by step, to help the user community of R to be able to perform it.FCT - Fundação para a Ciência e a Tecnologia(UID/CEC/00319/2013

Amino Acid Homeostasis and Fatigue in Chronic Hemodialysis Patients

Patients dependent on chronic hemodialysis treatment are prone to malnutrition, at least in part due to insufficient nutrient intake, metabolic derangements, and chronic inflammation. Losses of amino acids during hemodialysis may be an important additional contributor. In this study, we assessed changes in plasma amino acid concentrations during hemodialysis, quantified intradialytic amino acid losses, and investigated whether plasma amino acid concentrations and amino acid losses by hemodialysis and urinary excretion are associated with fatigue. The study included a total of 59 hemodialysis patients (65 +/- 15 years, 63% male) and 33 healthy kidney donors as controls (54 +/- 10 years, 45% male). Total plasma essential amino acid concentration before hemodialysis was lower in hemodialysis patients compared with controls (p = 0.006), while total non-essential amino acid concentration did not differ. Daily amino acid losses were 4.0 +/- 1.3 g/24 h for hemodialysis patients and 0.6 +/- 0.3 g/24 h for controls. Expressed as proportion of protein intake, daily amino acid losses of hemodialysis patients were 6.7 +/- 2.4% of the total protein intake, compared to 0.7 +/- 0.3% for controls (p < 0.001). Multivariable regression analyses demonstrated that hemodialysis efficacy (Kt/V) was the primary determinant of amino acid losses (Std. beta = 0.51; p < 0.001). In logistic regression analyses, higher plasma proline concentrations were associated with higher odds of severe fatigue (OR (95% CI) per SD increment: 3.0 (1.3; 9.3); p = 0.03), while higher taurine concentrations were associated with lower odds of severe fatigue (OR (95% CI) per log2 increment: 0.3 (0.1; 0.7); p = 0.01). Similarly, higher daily taurine losses were also associated with lower odds of severe fatigue (OR (95% CI) per log2 increment: 0.64 (0.42; 0.93); p = 0.03). Lastly, a higher protein intake was associated with lower odds of severe fatigue (OR (95% CI) per SD increment: 0.2 (0.04; 0.5); p = 0.007). Future studies are warranted to investigate the mechanisms underlying these associations and investigate the potential of taurine supplementation

Fibroblast growth factor 21 and protein energy wasting in hemodialysis patients

INTRODUCTION: Protein energy wasting (PEW) is the most important risk factor for morbidity and mortality in hemodialysis patients. Inadequate dietary protein intake is a frequent cause of PEW. Recent studies have identified fibroblast growth factor 21 (FGF21) as an endocrine protein sensor. This study aims to investigate the potential of FGF21 as a biomarker for protein intake and PEW and to investigate intradialytic FGF21 changes. METHODS: Plasma FGF21 was measured using an enzyme-linked immunoassay. Complete intradialytic dialysate and interdialytic urinary collections were used to calculate 24-h urea excretion and protein intake. Muscle mass was assessed using the creatinine excretion rate and fatigue was assessed using the Short Form 36 and the Checklist Individual Strength. RESULTS: Out of 59 hemodialysis patients (65 ± 15 years, 63% male), 39 patients had a low protein intake, defined as a protein intake less than 0.9 g/kg/24-h. Patients with a low protein intake had nearly twofold higher plasma FGF21 compared to those with an adequate protein intake (FGF21 1370 [795-4034] pg/mL versus 709 [405-1077] pg/mL;P < 0.001). Higher plasma FGF21 was associated with higher odds of low protein intake (Odds Ratio: 3.18 [1.62-7.95] per doubling of FGF21; P = 0.004), independent of potential confounders. Higher plasma FGF21 was also associated with lower muscle mass (std β: -0.34 [-0.59;-0.09];P = 0.009), lower vitality (std β: -0.30 [-0.55;-0.05];P = 0.02), and more fatigue (std β: 0.32 [0.07;0.57];P = 0.01). During hemodialysis plasma FGF21 increased by 354 [71-570] pg/mL, corresponding to a 29% increase. CONCLUSION: Higher plasma FGF21 is associated with higher odds of low protein intake in hemodialysis patients. Secondarily, plasma FGF21 is also associated with lower muscle mass, less vitality, and more fatigue. Lastly, there is an intradialytic increase in plasma FGF21. FGF21 could be a valuable marker allowing for objective assessment of PEW

Creatine homeostasis and protein energy wasting in hemodialysis patients

Muscle wasting, low protein intake, hypoalbuminemia, low body mass, and chronic fatigue are prevalent in hemodialysis patients. Impaired creatine status may be an often overlooked, potential contributor to these symptoms. However, little is known about creatine homeostasis in hemodialysis patients. We aimed to elucidate creatine homeostasis in hemodialysis patients by assessing intradialytic plasma changes as well as intra- and interdialytic losses of arginine, guanidinoacetate, creatine and creatinine. Additionally, we investigated associations of plasma creatine concentrations with low muscle mass, low protein intake, hypoalbuminemia, low body mass index, and chronic fatigue. Arginine, guanidinoacetate, creatine and creatinine were measured in plasma, dialysate, and urinary samples of 59 hemodialysis patients. Mean age was 65 ± 15 years and 63% were male. During hemodialysis, plasma concentrations of arginine (77 ± 22 to 60 ± 19 μmol/L), guanidinoacetate (1.8 ± 0.6 to 1.0 ± 0.3 μmol/L), creatine (26 [16–41] to 21 [15–30] μmol/L) and creatinine (689 ± 207 to 257 ± 92 μmol/L) decreased (all P < 0.001). During a hemodialysis session, patients lost 1939 ± 871 μmol arginine, 37 ± 20 μmol guanidinoacetate, 719 [399–1070] μmol creatine and 15.5 ± 8.4 mmol creatinine. In sex-adjusted models, lower plasma creatine was associated with a higher odds of low muscle mass (OR per halving: 2.00 [1.05–4.14]; P = 0.04), low protein intake (OR: 2.13 [1.17–4.27]; P = 0.02), hypoalbuminemia (OR: 3.13 [1.46–8.02]; P = 0.008) and severe fatigue (OR: 3.20 [1.52–8.05]; P = 0.006). After adjustment for potential confounders, these associations remained materially unchanged. Creatine is iatrogenically removed during hemodialysis and lower plasma creatine concentrations were associated with higher odds of low muscle mass, low protein intake, hypoalbuminemia, and severe fatigue, indicating a potential role for creatine supplementation.ISSN:1479-587

Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - A simultaneous near-infrared spectroscopy and positron emission tomography study

Near-infrared spectroscopy (NIRS) is used to monitor cerebral tissue oxygenation (rSO2) depending on cerebral blood flow (CBF), cerebral blood volume and blood oxygen content. We explored whether NIRS might be a more easy applicable proxy to [15O]H2O positron emission tomography (PET) for detecting CBF changes during hemodialysis. Furthermore, we compared potential determinants of rSO2 and CBF. In 12 patients aged ≥ 65 years, NIRS and PET were performed simultaneously: before (T1), early after start (T2), and at the end of hemodialysis (T3). Between T1 and T3, the relative change in frontal rSO2 (ΔrSO2) was -8 ± 9% ( P = 0.001) and -5 ± 11% ( P = 0.08), whereas the relative change in frontal gray matter CBF (ΔCBF) was -11 ± 18% ( P = 0.009) and -12 ± 16% ( P = 0.007) for the left and right hemisphere, respectively. ΔrSO2 and ΔCBF were weakly correlated for the left (ρ 0.31, P = 0.4), and moderately correlated for the right (ρ 0.69, P = 0.03) hemisphere. The Bland-Altman plot suggested underestimation of ΔCBF by NIRS. Divergent associations of pH, pCO2 and arterial oxygen content with rSO2 were found compared to corresponding associations with CBF. In conclusion, NIRS could be a proxy to PET to detect intradialytic CBF changes, although NIRS and PET capture different physiological parameters of the brain

Prevalence of intradialytic hypotension, clinical symptoms and nursing interventions - a three-months, prospective study of 3818 haemodialysis sessions

Background: Intradialytic hypotension (IDH) is considered one of the most frequent complications of haemodialysis with an estimated prevalence of 20-50 %, but studies investigating its exact prevalence are scarce. A complicating factor is that several definitions of IDH are used. The goal of this study was, to assess the prevalence of IDH, primarily in reference to the European Best Practice Guideline (EBPG) on haemodynamic instability: A decrease in systolic blood pressure (SBP) >= 20 mmHg or in mean arterial pressure (MAP) >= 10 mmHg associated with a clinical event and the need for nursing intervention. Methods: During 3 months we prospectively collected haemodynamic data, clinical events, and nursing interventions of 3818 haemodialysis sessions from 124 prevalent patients who dialyzed with constant ultrafiltration rate and dialysate conductivity. Patients were considered as having frequent IDH if it occurred in >20 % of dialysis sessions. Results: Decreases in SBP >= 20 mmHg or MAP >= 10 mmHg occurred in 77.7 %, clinical symptoms occurred in 21.4 %, and nursing interventions were performed in 8.5 % of dialysis sessions. Dialysis hypotension according to the full EBPG definition occurred in only 6.7 % of dialysis sessions. Eight percent of patients had frequent IDH. Conclusions: The prevalence of IDH according to the EBPG definition is low. The dominant determinant of the EBPG definition was nursing intervention since this was the component with the lowest prevalence. IDH seems to be less common than indicated in the literature but a proper comparison with previous studies is complicated by the lack of a uniform definition

Have Anglo-Saxon concepts really influenced the development of European qualifications policy?

This paper considers how far Anglo-Saxon conceptions of have influenced European Union vocational education and training policy, especially given the disparate approaches to VET across Europe. Two dominant approaches can be identified: the dual system (exemplified by Germany); and output based models (exemplified by the NVQ ‘English style’). Within the EU itself, the design philosophy of the English output-based model proved in the first instance influential in attempts to develop tools to establish equivalence between vocational qualifications across Europe, resulting in the learning outcomes approach of the European Qualifications Framework, the credit-based model of European VET Credit System and the task-based construction of occupation profiles exemplified by European Skills, Competences and Occupations. The governance model for the English system is, however, predicated on employer demand for ‘skills’ and this does not fit well with the social partnership model encompassing knowledge, skills and competences that is dominant in northern Europe. These contrasting approaches have led to continual modifications to the tools, as these sought to harmonise and reconcile national VET requirements with the original design. A tension is evident in particular between national and regional approaches to vocational education and training, on the one hand, and the policy tools adopted to align European vocational education and training better with the demands of the labour market, including at sectoral level, on the other. This paper explores these tensions and considers the prospects for the successful operation of these tools, paying particular attention to the European Qualifications Framework, European VET Credit System and European Skills, Competences and Occupations tool and the relationships between them and drawing on studies of the construction and furniture industries

Bacterial associations reveal spatial population dynamics in Anopheles gambiae mosquitoes

The intolerable burden of malaria has for too long plagued humanity and the prospect of eradicating malaria is an optimistic, but reachable, target in the 21st century. However, extensive knowledge is needed about the spatial structure of mosquito populations in order to develop effective interventions against malaria transmission. We hypothesized that the microbiota associated with a mosquito reflects acquisition of bacteria in different environments. By analyzing the whole-body bacterial flora of An. gambiae mosquitoes from Burkina Faso by 16 S amplicon sequencing, we found that the different environments gave each mosquito a specific bacterial profile. In addition, the bacterial profiles provided precise and predicting information on the spatial dynamics of the mosquito population as a whole and showed that the mosquitoes formed clear local populations within a meta-population network. We believe that using microbiotas as proxies for population structures will greatly aid improving the performance of vector interventions around the world