Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

Informed baseline subtraction of proteomic mass spectrometry data aided by a novel sliding window algorithm

Proteomic matrix-assisted laser desorption/ionisation (MALDI) linear time-of-flight (TOF) mass spectrometry (MS) may be used to produce protein profiles from biological samples with the aim of discovering biomarkers for disease. However, the raw protein profiles suffer from several sources of bias or systematic variation which need to be removed via pre-processing before meaningful downstream analysis of the data can be undertaken. Baseline subtraction, an early pre-processing step that removes the non-peptide signal from the spectra, is complicated by the following: (i) each spectrum has, on average, wider peaks for peptides with higher mass-to-charge ratios (m/z), and (ii) the time-consuming and error-prone trial-and-error process for optimising the baseline subtraction input arguments. With reference to the aforementioned complications, we present an automated pipeline that includes (i) a novel `continuous' line segment algorithm that efficiently operates over data with a transformed m/z-axis to remove the relationship between peptide mass and peak width, and (ii) an input-free algorithm to estimate peak widths on the transformed m/z scale. The automated baseline subtraction method was deployed on six publicly available proteomic MS datasets using six different m/z-axis transformations. Optimality of the automated baseline subtraction pipeline was assessed quantitatively using the mean absolute scaled error (MASE) when compared to a gold-standard baseline subtracted signal. Near-optimal baseline subtraction was achieved using the automated pipeline. The advantages of the proposed pipeline include informed and data specific input arguments for baseline subtraction methods, the avoidance of time-intensive and subjective piecewise baseline subtraction, and the ability to automate baseline subtraction completely. Moreover, individual steps can be adopted as stand-alone routines.Comment: 50 pages, 19 figure

Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries

Role of adipose tissue in the pathogenesis and treatment of metabolic syndrome

© Springer International Publishing Switzerland 2014. Adipocytes are highly specialized cells that play a major role in energy homeostasis in vertebrate organisms. Excess adipocyte size or number is a hallmark of obesity, which is currently a global epidemic. Obesity is not only the primary disease of fat cells, but also a major risk factor for the development of Type 2 diabetes, cardiovascular disease, hypertension, and metabolic syndrome (MetS). Today, adipocytes and adipose tissue are no longer considered passive participants in metabolic pathways. In addition to storing lipid, adipocytes are highly insulin sensitive cells that have important endocrine functions. Altering any one of these functions of fat cells can result in a metabolic disease state and dysregulation of adipose tissue can profoundly contribute to MetS. For example, adiponectin is a fat specific hormone that has cardio-protective and anti-diabetic properties. Inhibition of adiponectin expression and secretion are associated with several risk factors for MetS. For this purpose, and several other reasons documented in this chapter, we propose that adipose tissue should be considered as a viable target for a variety of treatment approaches to combat MetS

Chemometric tools for automated method-development and data interpretation in liquid chromatography

The thesis explores the challenges and advancements in the field of liquid chromatography (LC), particularly focusing on complex sample analysis using high-resolution mass spectrometry (MS) and two-dimensional (2D) LC techniques. The research addresses the need for efficient optimization and data-handling strategies in modern LC practice. The thesis is divided into several chapters, each addressing specific aspects of LC and polymer analysis. Chapter 2 provides an overview of the need for chemometric tools in LC practice, discussing methods for processing and analyzing data from 1D and 2D-LC systems and how chemometrics can be utilized for method development and optimization. Chapter 3 introduces a novel approach for interpreting the molecular-weight distribution and intrinsic viscosity of polymers, allowing quantitative analysis of polymer properties without prior knowledge of their interactions. This method correlates the curvature parameter of the Mark-Houwink plot with the polymer's structural and chemical properties. Chapters 4 and 5 focus on the analysis of cellulose ethers (CEs), essential in various industrial applications. A new method is presented for mapping the substitution degree and composition of CE samples, providing detailed compositional distributions. Another method involves a comprehensive 2D LC-MS/MS approach for analyzing hydroxypropyl methyl cellulose (HPMC) monomers, revealing subtle differences in composition between industrial HPMC samples. Chapter 6 introduces AutoLC, an algorithm for automated and interpretive development of 1D-LC separations. It uses retention modeling and Bayesian optimization to achieve optimal separation within a few iterations, significantly improving the efficiency of gradient LC separations. Chapter 7 focuses on the development of an open-source algorithm for automated method development in 2D-LC-MS systems. This algorithm improves separation performance by refining gradient profiles and accurately predicting peak widths, enhancing the reliability of complex gradient LC separations. Chapter 8 addresses the challenge of gradient deformation in LC instruments. An algorithm based on the stable function corrects instrument-specific gradient deformations, enabling accurate determination of analyte retention parameters and improving data comparability between different sources. Chapter 9 introduces a novel approach using capacitively-coupled-contactless-conductivity detection (C4D) to measure gradient profiles without adding tracer components. This method enhances inter-system transferability of retention models for polymers, overcoming the limitations of UV-absorbance detectable tracer components. Chapter 10 discusses practical choices and challenges faced in the thesis chapters, highlighting the need for well-defined standard samples in industrial polymer analysis and emphasizing the importance of generalized problem-solving approaches. The thesis identifies future research directions, emphasizing the importance of computational-assisted methods for polymer analysis, the utilization of online reaction modulation techniques, and exploring continuous distributions obtained through size-exclusion chromatography (SEC) in conjunction with triple detection. Chemometric tools are recognized as essential for gaining deeper insights into polymer chemistry and improving data interpretation in the field of LC

Nutraceuticals and Human Health

In this Special Issue, we have published papers on the health-promoting effects of nutraceuticals from different sources, and their effects in different pathologies. Extracts from plants have been analyzed, for example, extracts from olive leaves, Mikania micrantha, the devil’s claw, raspberries and others, alongside marine phytoplankton, egg-yolk and marketed dietary supplements. The effects of these extracts and dietary supplements have been studied in diseases associated with obesity, and in diseases where inflammation pathways are involved. The effectiveness of resveratrol and curcumin to support the anticancer activity of cisplatin has also been reported, as well as the ability of devil’s claw root extract to stimulate the CB2 receptors in synoviocytes in osteoarthritis patients. The anti-oxidant effect of marine phytoplankton has been studied on muscle damage, both in humans and in an animal model, and the effects of the metabolite of antocianin were analyzed in a mouse model of amyotrophic lateral sclerosis. Finally, reviews on the use of lactoferrin, ω3 and ω6 and abscisic acid have been reported, in addition to the crosstalk between prostate cancer and microbiota inflammation. Although it is not yet possible to draw definitive conclusions on the use of nutraceuticals, several mechanisms of action for many of them have been further clarified

Abstracts of 51st EASD Annual Meeting

Background and aims: Presence and frequency of beta cell (BC) dysfunction(BCD) and insulin resistance (IR) in patients with newly diagnosedtype 2 diabetes mellitus (NDT2D) are imperfectly known, becauseprevious studies used small cohorts and/or only surrogate indexes of BCfunction and IR.We sought to assess BC function and IR with state-of-artmethods in the VNDS.Materials and methods: In 712 GADA-negative, drug naïve, consecutiveItalian NDT2D patients we assessed: 1. standard parameters; 2. insulinsensitivity (IS) by the euglycaemic insulin clamp); 3. BC functionby state-of-art modeling of prolonged (5 hours) OGTT-derived glucose/C-peptide curves. Thresholds for BCD and IR were the 25th percentilesof BC function and IS assessed with the same methods of the VNDS inItalian subjects with normal glucose regulation of the GENFIEV (n=340)and GISIR (n=386) studies, respectively.Results: In the VNDS, 89.8% [95% C.I.: 87.6 - 92.0%] and87.8% [85.4 - 90.2] patients had BCD and IR, respectively. Patientswith only one defect were 19.7% [16.8 - 22.6]. IsolatedBCD and isolated IR were present in 10.9% [8.6 - 13.2] and8.9% [6.8 - 11.0] patients, respectively. Coexistence of BCDand IR was observed in 78.9% [75.9 - 81.9] of the patients.1.4% [0.5 - 2.3] of the patients had no detectable alterations inBC function and IS. Patients (19.7%) with only one metabolicdefect had lower BMI, fasting glucose, HbA1c, triglycerides andBC function, and higher HDL-cholesterol and IS than patientswith both BCD and IR (p<0.01 or less after Bonferroni’scorrection).Conclusion: In conclusion, in NDT2DM patients: 1. at least 75.9% haveboth BCD and IR; 2. At least 87.6% and 85.4% have BCD and IR,respectively; 3. At least 16.8% have only one defect and a significantlydifferent (milder) metabolic phenotype compared to patients with bothdefects. These findings may be relevant to therapeutic strategies centeredon the metabolic phenotype of the patient.Clinical Trial Registration Number: NCT00879801; NCT01526720Supported by: University of Veron

Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes

Antioxidant and DPPH-Scavenging Activities of Compounds and Ethanolic Extract of the Leaf and Twigs of Caesalpinia bonduc L. Roxb.

Antioxidant effects of ethanolic extract of Caesalpinia bonduc and its isolated bioactive compounds were evaluated in vitro. The compounds included two new cassanediterpenes, 1α,7α-diacetoxy-5α,6β-dihydroxyl-cass-14(15)-epoxy-16,12-olide (1)and 12α-ethoxyl-1α,14β-diacetoxy-2α,5α-dihydroxyl cass-13(15)-en-16,12-olide(2); and others, bonducellin (3), 7,4’-dihydroxy-3,11-dehydrohomoisoflavanone (4), daucosterol (5), luteolin (6), quercetin-3-methyl ether (7) and kaempferol-3-O-α-L-rhamnopyranosyl-(1Ç2)-β-D-xylopyranoside (8). The antioxidant properties of the extract and compounds were assessed by the measurement of the total phenolic content, ascorbic acid content, total antioxidant capacity and 1-1-diphenyl-2-picryl hydrazyl (DPPH) and hydrogen peroxide radicals scavenging activities.Compounds 3, 6, 7 and ethanolic extract had DPPH scavenging activities with IC50 values of 186, 75, 17 and 102 μg/ml respectively when compared to vitamin C with 15 μg/ml. On the other hand, no significant results were obtained for hydrogen peroxide radical. In addition, compound 7 has the highest phenolic content of 0.81±0.01 mg/ml of gallic acid equivalent while compound 8 showed the highest total antioxidant capacity with 254.31±3.54 and 199.82±2.78 μg/ml gallic and ascorbic acid equivalent respectively. Compound 4 and ethanolic extract showed a high ascorbic acid content of 2.26±0.01 and 6.78±0.03 mg/ml respectively.The results obtained showed the antioxidant activity of the ethanolic extract of C. bonduc and deduced that this activity was mediated by its isolated bioactive compounds