Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of sets of clinically relevant biomarkers. As tractable example we define the measurable proteomic differences between apparently healthy adult males and females. We choose urine as body-fluid of interest and CE-MS, a thoroughly validated platform technology, allowing for routine analysis of a large number of samples. The second urine of the morning was collected from apparently healthy male and female volunteers (aged 21-40) in the course of the routine medical check-up before recruitment at the Hannover Medical School.Results: We found that the Wilcoxon-test is best suited for the definition of potential biomarkers. Adjustment for multiple testing is necessary. Sample size estimation can be performed based on a small number of observations via resampling from pilot data. Machine learning algorithms appear ideally suited to generate classifiers. Assessment of any results in an independent test set is essential.Conclusions: Valid proteomic biomarkers for diagnosis and prognosis only can be defined by applying proper statistical data mining procedures. In particular, a justification of the sample size should be part of the study design

Quantum Correlations in NMR systems

In conventional NMR experiments, the Zeeman energy gaps of the nuclear spin ensembles are much lower than their thermal energies, and accordingly exhibit tiny polarizations. Generally such low-purity quantum states are devoid of quantum entanglement. However, there exist certain nonclassical correlations which can be observed even in such systems. In this chapter, we discuss three such quantum correlations, namely, quantum contextuality, Leggett-Garg temporal correlations, and quantum discord. In each case, we provide a brief theoretical background and then describe some results from NMR experiments.Comment: 21 pages, 7 figure

Renal artery stenosis-when to screen, what to stent?

Renal artery stensosis (RAS) continues to be a problem for clinicians, with no clear consensus on how to investigate and assess the clinical significance of stenotic lesions and manage the findings. RAS caused by fibromuscular dysplasia is probably commoner than previously appreciated, should be actively looked for in younger hypertensive patients and can be managed successfully with angioplasty. Atheromatous RAS is associated with increased incidence of cardiovascular events and increased cardiovascular mortality, and is likely to be seen with increasing frequency. Evidence from large clinical trials has led clinicians away from recommending interventional revascularisation towards aggressive medical management. There is now interest in looking more closely at patient selection for intervention, with focus on intervening only in patients with the highest-risk presentations such as flash pulmonary oedema, rapidly declining renal function and severe resistant hypertension. The potential benefits in terms of improving hard cardiovascular outcomes may outweigh the risks of intervention in this group, and further research is needed

DFT-inspired methods for quantum thermodynamics

In the framework of quantum thermodynamics, we propose a method to quantitatively describe thermodynamic quantities for out-of-equilibrium interacting many-body systems. The method is articulated in various approximation protocols which allow to achieve increasing levels of accuracy, it is relatively simple to implement even for medium and large number of interactive particles, and uses tools and concepts from density functional theory. We test the method on the driven Hubbard dimer at half filling, and compare exact and approximate results. We show that the proposed method reproduces the average quantum work to high accuracy: for a very large region of parameter space (which cuts across all dynamical regimes) estimates are within 10% of the exact results

bioNMF: a versatile tool for non-negative matrix factorization in biology

BACKGROUND: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insights and relevant information about the complex latent relationships in experimental data sets. This method, and some of its variants, has been successfully applied to gene expression, sequence analysis, functional characterization of genes and text mining. Even if the interest on this technique by the bioinformatics community has been increased during the last few years, there are not many available simple standalone tools to specifically perform these types of data analysis in an integrated environment. RESULTS: In this work we propose a versatile and user-friendly tool that implements the NMF methodology in different analysis contexts to support some of the most important reported applications of this new methodology. This includes clustering and biclustering gene expression data, protein sequence analysis, text mining of biomedical literature and sample classification using gene expression. The tool, which is named bioNMF, also contains a user-friendly graphical interface to explore results in an interactive manner and facilitate in this way the exploratory data analysis process. CONCLUSION: bioNMF is a standalone versatile application which does not require any special installation or libraries. It can be used for most of the multiple applications proposed in the bioinformatics field or to support new research using this method. This tool is publicly available at

Prevalence and clinical outcomes of dystrophin-associated dilated cardiomyopathy without severe skeletal myopathy

Aims: Dilated cardiomyopathy (DCM) associated with dystrophin gene (DMD) mutations in individuals with mild or absent skeletal myopathy is often indistinguishable from other DCM forms. We sought to describe the phenotype and prognosis of DMD associated DCM in DMD mutation carriers without severe skeletal myopathy. Methods and results: At 26 European centres, we retrospectively collected clinical characteristics and outcomes of 223 DMD mutation carriers (83% male, 33 ± 15 years). A total of 112 individuals (52%) had DCM at first evaluation [n = 85; left ventricular ejection fraction (LVEF) 34 ± 11.2%] or developed DCM (n = 27; LVEF 41.3 ± 7.5%) after a median follow-up of 96 months (interquartile range 5–311 months). DCM penetrance was 45% in carriers older than 40 years. DCM appeared earlier in males and was independent of the type of mutation, presence of skeletal myopathy, or elevated serum creatine kinase levels. Major adverse cardiac events (MACE) occurred in 22% individuals with DCM, 18% developed end-stage heart failure and 9% sudden cardiac death or equivalent. Skeletal myopathy was not associated with survival free of MACE in patients with DCM. Decreased LVEF and increased left ventricular end-diastolic diameter at baseline were associated with MACE. Individuals without DCM had favourable prognosis without MACE or death during follow-up. Conclusions: DMD-associated DCM without severe skeletal myopathy is characterized by incomplete penetrance but high risk of MACE, including progression to end-stage heart failure and ventricular arrhythmias. DCM onset is the major determinant of prognosis with similar survival regardless of the presence of skeletal myopathy

Hierarchical Bayesian level set inversion

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to the length and amplitude scales in the prior probabilistic model. This paper demonstrates how the scale-sensitivity can be cir- cumvented by means of a hierarchical approach, using a single scalar parameter. Together with careful con- sideration of the development of algorithms which en- code probability measure equivalences as the hierar- chical parameter is varied, this leads to well-defined Gibbs based MCMC methods found by alternating Metropolis-Hastings updates of the level set function and the hierarchical parameter. These methods demon- strably outperform non-hierarchical Bayesian level set methods

Neonicotinoid Insecticides and Their Impacts on Bees: A Systematic Review of Research Approaches and Identification of Knowledge Gaps

It has been suggested that the widespread use of neonicotinoid insecticides threatens bees, but research on this topic has been surrounded by controversy. In order to synthesize which research approaches have been used to examine the effect of neonicotinoids on bees and to identify knowledge gaps, we systematically reviewed research on this subject that was available on the Web of Science and PubMed in June 2015. Most of the 216 primary research studies were conducted in Europe or North America (82%), involved the neonicotinoid imidacloprid (78%), and concerned the western honey bee Apis mellifera (75%). Thus, little seems to be known about neonicotinoids and bees in areas outside Europe and North America. Furthermore, because there is considerable variation in ecological traits among bee taxa, studies on honey bees are not likely to fully predict impacts of neonicotinoids on other species. Studies on crops were dominated by seed-treated maize, oilseed rape (canola) and sunflower, whereas less is known about potential side effects on bees from the use of other application methods on insect pollinated fruit and vegetable crops, or on lawns and ornamental plants. Laboratory approaches were most common, and we suggest that their capability to infer real-world consequences are improved when combined with information from field studies about realistic exposures to neonicotinoids. Studies using field approaches often examined only bee exposure to neonicotinoids and more field studies are needed that measure impacts of exposure. Most studies measured effects on individual bees. We suggest that effects on the individual bee should be linked to both mechanisms at the sub-individual level and also to the consequences for the colony and wider bee populations. As bees are increasingly facing multiple interacting pressures future research needs to clarify the role of neonicotinoids in relative to other drivers of bee declines

Mobilization of healthy donors with plerixafor affects the cellular composition of T-cell receptor (TCR)-αβ/CD19-depleted haploidentical stem cell grafts

Background: HLA-haploidentical hematopoietic stem cell transplantation (HSCT) is suitable for patients lacking related or unrelated HLA-matched donors. Herein, we investigated whether plerixafor (MZ), as an adjunct to G-CSF, facilitated the collection of mega-doses of hematopoietic stem cells (HSC) for TCR-αβ/CD19-depleted haploidentical HSCT, and how this agent affects the cellular graft composition. Methods: Ninety healthy donors were evaluated. Single-dose MZ was given to 30 ‘poor mobilizers’ (PM) failing to attain ≥40 CD34+ HSCs/μL after 4 daily G-CSF doses and/or with predicted apheresis yields ≤12.0x106 CD34+ cells/kg recipient’s body weight. Results: MZ significantly increased CD34+ counts in PM. Naïve/memory T and B cells, as well as natural killer (NK) cells, myeloid/plasmacytoid dendritic cells (DCs), were unchanged compared with baseline. MZ did not further promote the G-CSF-induced mobilization of CD16+ monocytes and the down-regulation of IFN-γ production by T cells. HSC grafts harvested after G-CSF + MZ were enriched in myeloid and plasmacytoid DCs, but contained low numbers of pro-inflammatory 6-sulfo-LacNAc+ (Slan)-DCs. Finally, children transplanted with G-CSF + MZ-mobilized grafts received greater numbers of monocytes, myeloid and plasmacytoid DCs, but lower numbers of NK cells, NK-like T cells and Slan-DCs. Conclusions: MZ facilitates the collection of mega-doses of CD34+ HSCs for haploidentical HSCT, while affecting graft composition

Nutritional profile and obesity: results from a random‑sample population‑based study in Córdoba, Argentina

Introduction Obesity is a chronic, heterogeneous, multifactorial disease, which has sharply increased in prevalence in both developed and developing countries. This study aimed to estimate the prevalence of obesity and to identify socio-demographic risk factors associated with it, with special emphasis on diet. Methods Nutritional status, demographic characteristics, lifestyle habits, and food consumption patterns derived from a Food Frequency Questionnaire were investigated. Exhaustive exploratory analyses were performed in order to describe dietary patterns, and logistic regression models were used for odds ratio estimation. Results The study included 4328 subjects, over 18 years old and resident in Cordoba city. The prevalence of overweight and obesity was 34 and 17 %, respectively, with 60 % in men and 45 % in women of BMI ≥ 25. Obesity risk factors were high intake of sodium, refined grains, starchy vegetables, and snacks. A lower risk of overweight and obesity was associated with an adequate, moderate intake of meats, eggs, alcoholic beverages, sugar and sweets, milk, yogurt, and pulses. Conclusions A high intake of snacks, refined grains, starchy vegetables and sodium and low intake of yogurt, milk, pulses, and whole grains seem to be associated with the emergence and high prevalence of obesity in Cordoba, Argentina.publishedVersionFil: Aballay, Laura Rosana. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas. Escuela de Nutrición. Estadística y Bioestadística; ArgentinaFil: Aballay, Laura Rosana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: De la Quintana, Ana Gabriela. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas. Escuela de Nutrición; Argentina.Fil: Díaz, María del Pilar. Universidad Nacional de Córdoba. Facultad de Ciencias Médicas. Escuela de Nutrición. Estadística y Bioestadística; Argentina.Fil: Díaz, María del Pilar. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias de la Salud; Argentina.Fil: Osella, Alberto R. Hospital Saverio de Bellis. Laboratorio de Epidemiologia y Bioestadística; Italia