Refractive Index of Hemoglobin Analysis: A Comparison of Alternating Conditional Expectations and Computational Intelligence Models.

Hemoglobin is one of the most important blood elements, and its optical properties will determine all other optical properties of human blood. Since the refractive index (RI) of hemoglobin plays a vital role as a non-invasive indicator of some illnesses, accurate calculation of it would be of great importance. Moreover, measurement of the RI of hemoglobin in the laboratory is time-consuming and expensive; thus, developing a smart approach to estimate this parameter is necessary.

MOGSA: Integrative Single Sample Gene-set Analysis of Multiple Omics Data.

Gene-set analysis (GSA) summarizes individual molecular measurements to more interpretable pathways or gene-sets and has become an indispensable step in the interpretation of large-scale omics data. However, GSA methods are limited to the analysis of single omics data. Here, we introduce a new computation method termed multi-omics gene-set analysis (MOGSA), a multivariate single sample gene-set analysis method that integrates multiple experimental and molecular data types measured over the same set of samples.

Motor reaction time and accuracy in patients with multiple sclerosis: effects of an active computerized training program.

In this study, we aimed to determine the difference of motor reaction time and accuracy between the patients with moderate multiple sclerosis (MS) and healthy subjects and to determine whether a specified cognitive-motor training can improve the speed and accuracy of information processing in patients with MS. A total of 205 patients (30% males) and 276 age-/gender-matched healthy subjects (31% males) were included in the study. Furthermore, using a stratified randomization method, patients with MS were randomly assigned to one of two groups: active information processing training (AIPT) (n = 49) or post-control (n = 55).

Dynamic Proteome Alteration and Functional Modulation of Human Saliva Induced by Dietary Chemosensory Stimuli.

Saliva flow measurements and SDS-PAGE separation of human whole saliva freshly collected after oral stimulation with citric acid (sour), aspartame (sweet), iso-α-acids (bitter), mono sodium l-glutamate (umami), NaCl (salty), 6-gingerol (pungent), hydroxy-α-sanshool (tingling), and hydroxy-β-sanshool (numbing), followed by tryptic digestion, nano-HPLC-MS/MS, and label-free protein quantitation demonstrated a stimulus- and time-dependent influence of the dietary chemosensates on salivation and the salivary proteome composition. Gene ontology enrichment analysis showed evidence for stimulus-induced alterations of the saliva proteome to boot an efficient molecular defense network of the oral cavity, e.g.

Development of Asthma in Inner-City Children: Possible Roles of MAIT Cells and Variation in the Home Environment.

Humans have populations of innate-like T lymphocytes with an invariant TCR α-chain that recognize nonpeptide Ags, including invariant NKT (iNKT) cells and mucosal-associated invariant T (MAIT) cells. iNKT cell involvement in human asthma is controversial, whereas there has been little analysis of MAIT cells. Using peripheral blood cells from 110 participants from the Urban Environment and Childhood Asthma (URECA) birth cohort study, these cells were analyzed for number and function.

CCR5+T-bet+FoxP3+ Effector CD4 T Cells Drive Atherosclerosis.

Rationale: CD4 T cells are involved in the pathogenesis of atherosclerosis, but atherosclerosis-specific CD4 T cells have not been described. Moreover, the chemokine(s) that regulates T-cell trafficking to the atherosclerotic lesions is also unknown.

Objective: In Apoe(-/-) mice with mature atherosclerotic lesions (5 months of high fat diet), we find that most aortic T cells express CCR5 and interferon-γ with a unique combination of cell surface markers (CD4(+)CD25(-)CD44(hi)CD62L(lo)) and transcription factors (FoxP3(+)T-bet(+)).

Dimension reduction techniques for the integrative analysis of multi-omics data.

State-of-the-art next-generation sequencing, transcriptomics, proteomics and other high-throughput 'omics' technologies enable the efficient generation of large experimental data sets. These data may yield unprecedented knowledge about molecular pathways in cells and their role in disease. Dimension reduction approaches have been widely used in exploratory analysis of single omics data sets.

Quantitative proteome profiling of human myoma and myometrium tissue reveals kinase expression signatures with potential for therapeutic intervention.

Uterine leiomyomas are benign tumors affecting a large proportion of the female population. Despite the very high prevalence, the molecular basis for understanding the onset and development of the disease are still poorly understood. In this study, we profiled the proteomes and kinomes of leiomyoma as well as myometrium samples from patients to a depth of >7000 proteins including 200 kinases.

A multivariate approach to the integration of multi-omics datasets.

Background: To leverage the potential of multi-omics studies, exploratory data analysis methods that provide systematic integration and comparison of multiple layers of omics information are required. We describe multiple co-inertia analysis (MCIA), an exploratory data analysis method that identifies co-relationships between multiple high dimensional datasets. Based on a covariance optimization criterion, MCIA simultaneously projects several datasets into the same dimensional space, transforming diverse sets of features onto the same scale, to extract the most variant from each dataset and facilitate biological interpretation and pathway analysis.

Mass-spectrometry-based draft of the human proteome.

Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs).

High-fat diet alters gut microbiota physiology in mice.

The intestinal microbiota is known to regulate host energy homeostasis and can be influenced by high-calorie diets. However, changes affecting the ecosystem at the functional level are still not well characterized. We measured shifts in cecal bacterial communities in mice fed a carbohydrate or high-fat (HF) diet for 12 weeks at the level of the following: (i) diversity and taxa distribution by high-throughput 16S ribosomal RNA gene sequencing; (ii) bulk and single-cell chemical composition by Fourier-transform infrared- (FT-IR) and Raman micro-spectroscopy and (iii) metaproteome and metabolome via high-resolution mass spectrometry.

Global proteome analysis of the NCI-60 cell line panel.

The NCI-60 cell line collection is a very widely used panel for the study of cellular mechanisms of cancer in general and in vitro drug action in particular. It is a model system for the tissue types and genetic diversity of human cancers and has been extensively molecularly characterized. Here, we present a quantitative proteome and kinome profile of the NCI-60 panel covering, in total, 10,350 proteins (including 375 protein kinases) and including a core cancer proteome of 5,578 proteins that were consistently quantified across all tissue types.

Comprehensive identification of proteins from MALDI imaging.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics.

Diagnostic values of GHSR DNA methylation pattern in breast cancer.

DNA methylation patterns have been recognised as cancer-specific markers with high potential for clinical applications. We aimed at identifying methylation variations that differentiate between breast cancers and other breast tissue entities to establish a signature for diagnosis. Candidate genomic loci were analysed in 117 fresh-frozen breast specimens, which included cancer, benign and normal breast tissues from patients as well as material from healthy individuals.

Discovery of O-GlcNAc-modified proteins in published large-scale proteome data.

The attachment of N-acetylglucosamine to serine or threonine residues (O-GlcNAc) is a post-translational modification on nuclear and cytoplasmic proteins with emerging roles in numerous cellular processes, such as signal transduction, transcription, and translation. It is further presumed that O-GlcNAc can exhibit a site-specific, dynamic and possibly functional interplay with phosphorylation. O-GlcNAc proteins are commonly identified by tandem mass spectrometry following some form of biochemical enrichment.

Systematic identification of the HSP90 candidate regulated proteome.

HSP90 is a central player in the folding and maturation of many proteins. More than two hundred HSP90 clients have been identified by classical biochemical techniques including important signaling proteins with high relevance to human cancer pathways. HSP90 inhibition has thus become an attractive therapeutic concept and multiple molecules are currently in clinical trials.

Quantitative chemical proteomics reveals new potential drug targets in head and neck cancer.

Tumors of the head and neck represent a molecularly diverse set of human cancers, but relatively few proteins have actually been shown to drive the disease at the molecular level. To identify new targets for individualized diagnosis or therapeutic intervention, we performed a kinase centric chemical proteomics screen and quantified 146 kinases across 34 head and neck squamous cell carcinoma (HNSCC) cell lines using intensity-based label-free mass spectrometry. Statistical analysis of the profiles revealed significant intercell line differences for 42 kinases (p < 0.

Sulfite reductase defines a newly discovered bottleneck for assimilatory sulfate reduction and is essential for growth and development in Arabidopsis thaliana.

The role of sulfite reductase (SiR) in assimilatory reduction of inorganic sulfate to sulfide has long been regarded as insignificant for control of flux in this pathway. Two independent Arabidopsis thaliana T-DNA insertion lines (sir1-1 and sir1-2), each with an insertion in the promoter region of SiR, were isolated. sir1-2 seedlings had 14% SiR transcript levels compared with the wild type and were early seedling lethal.

Cross-species common regulatory network inference without requirement for prior gene affiliation.

Motivation: Cross-species meta-analyses of microarray data usually require prior affiliation of genes based on orthology information that often relies on sequence similarity.

Results: We present an algorithm merging microarray datasets on the basis of co-expression alone, without any requirement for orthology information to affiliate genes. Combining existing methods such as co-inertia analysis, back-transformation, Hungarian matching and majority voting in an iterative non-greedy hill-climbing approach, it affiliates arrays and genes at the same time, maximizing the co-structure between the datasets.