Monitoring Cognitive Workload Using Vocal Tract and Voice Source Features

Monitoring cognitive workload from speech signals has received much attention from researchers in the past few years as it has the potential to improve performance and fidelity in human decision making. The bulk of the research has focused on classifying speech from talkers participating in cognitive workload experiments using simple reading tasks, memory span tests and the Stroop test, typically into three levels of low, medium and high cognitive workload. This study focuses on using parameters extracted from the vocal tract and the voice source components of the speech signal for cognitive workload monitoring. The experiment used in this study contains 98 participants, the levels were obtained by using a reading task and three Stroop tasks which were randomly ordered for each participant and an adequate rest time was used inbetween tasks to mitigate the effect of cognitive workload from one task affecting the subsequent one. Vocal tract features were obtained from the first three formants and voice source features were extracted using signal analysis on the inverse filtered speech signal. The results show that on their own, the vocal tract features outperform the voice source features. The MCR of 33.92% ± 1.05 was achieved with a SVM classifier. A weighted combination of vocal tract and voice source features classified with SWM classifier fused at the output level achieved the lowest MCR of  32.5%

Metabolic re-wiring of isogenic breast epithelial cell lines following epithelial to mesenchymal transition.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesEpithelial to mesenchymal transition (EMT) has implications in tumor progression and metastasis. Metabolic alterations have been described in cancer development but studies focused on the metabolic re-wiring that takes place during EMT are still limited. We performed metabolomics profiling of a breast epithelial cell line and its EMT derived mesenchymal phenotype to create genome-scale metabolic models descriptive of both cell lines. Glycolysis and OXPHOS were higher in the epithelial phenotype while amino acid anaplerosis and fatty acid oxidation fueled the mesenchymal phenotype. Through comparative bioinformatics analysis, PPAR-γ1, PPAR- γ2 and AP-1 were found to be the most influential transcription factors associated with metabolic re-wiring. In silico gene essentiality analysis predicts that the LAT1 neutral amino acid transporter is essential for mesenchymal cell survival. Our results define metabolic traits that distinguish an EMT derived mesenchymal cell line from its epithelial progenitor and may have implications in cancer progression and metastasis. Furthermore, the tools presented here can aid in identifying critical metabolic nodes that may serve as therapeutic targets aiming to prevent EMT and inhibit metastatic dissemination.Icelandic Research Counci

The high catalytic rate of the cold-active Vibrio alkaline phosphatase requires a hydrogen bonding network involving a large interface loop

The role of surface loops in mediating communication through residue networks is still a relatively poorly understood part in the study of cold adaptation of enzymes, especially in terms of their quaternary interactions. Alkaline phosphatase (AP) from the psychrophilic marine bacterium Vibrio splendidus (VAP) is characterized by an analogous large surface loop in each monomer, referred to as the large loop, that hovers over the active site of the other monomer. It presumably has a role in the high catalytic efficiency of VAP which accompanies its extremely low thermal stability. Here, we designed several different variants of VAP with the aim of removing intersubunit interactions at the dimer interface. Breaking the intersubunit contacts from one residue in particular (Arg336) reduced the temperature stability of the catalytically potent conformation and caused a 40% drop in catalytic rate. The high catalytic rates of enzymes from cold‐adapted organisms are often associated with increased dynamic flexibility. Comparison of the relative B‐factors of the R336L crystal structure to that of the wild‐type confirmed surface flexibility was increased in a loop on the opposite monomer, but not in the large loop. The increase in flexibility resulted in a reduced catalytic rate. The large loop increases the area of the interface between the subunits through its contacts and may facilitate an alternating structural cycle demanded by a half‐of‐sites reaction mechanism through stronger ties, as the dimer oscillates between high affinity (active) or low phosphoryl group affinity (inactive)

Inferring the metabolism of human orphan metabolites from their metabolic network context affirms human gluconokinase activity.

Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational approach to identify human metabolites whose metabolism is incomplete on the basis of their detection in humans but exclusion from the human metabolic network reconstruction RECON 1. Candidate solutions, composed of metabolic reactions capable of explaining the metabolism of these compounds, were then identified computationally from a global biochemical reaction database. Solutions were characterized with respect to how metabolites were incorporated into RECON 1 and their biological relevance. Through detailed case studies we show that biologically plausible non-intuitive hypotheses regarding the metabolism of these compounds can be proposed in a semi-automated manner, in an approach that is similar to de novo network reconstruction. We subsequently experimentally validated one of the proposed hypotheses and report that C9orf103, previously identified as a candidate tumour suppressor gene, encodes a functional human gluconokinase. The results of the present study demonstrate how semi-automatic gap filling can be used to refine and extend metabolic reconstructions, thereby increasing their biological scope. Furthermore, we illustrate how incomplete human metabolic knowledge can be coupled with gene annotation in order to prioritize and confirm gene functions

Photo-Oxidative Stress-Driven Mutagenesis and Adaptive Evolution on the Marine Diatom Phaeodactylum tricornutum for Enhanced Carotenoid Accumulation

Marine diatoms have recently gained much attention as they are expected to be a promising resource for sustainable production of bioactive compounds such as carotenoids and biofuels as a future clean energy solution. To develop photosynthetic cell factories, it is important to improve diatoms for value-added products. In this study, we utilized UVC radiation to induce mutations in the marine diatom Phaeodactylum tricornutum and screened strains with enhanced accumulation of neutral lipids and carotenoids. Adaptive laboratory evolution (ALE) was also used in parallel to develop altered phenotypic and biological functions in P. tricornutum and it was reported for the first time that ALE was successfully applied on diatoms for the enhancement of growth performance and productivity of value-added carotenoids to date. Liquid chromatography-mass spectrometry (LC-MS) was utilized to study the composition of major pigments in the wild type P. tricornutum, UV mutants and ALE strains. UVC radiated strains exhibited higher accumulation of fucoxanthin as well as neutral lipids compared to their wild type counterpart. In addition to UV mutagenesis, P. tricornutum strains developed by ALE also yielded enhanced biomass production and fucoxanthin accumulation under combined red and blue light. In short, both UV mutagenesis and ALE appeared as an effective approach to developing desired phenotypes in the marine diatoms via electromagnetic radiation-induced oxidative stress

Intracellular metabolite profiling of platelets: evaluation of extraction processes and chromatographic strategies.

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel

Monitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS).

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by testing 86 metabolites, including amino acids, organic acids, sugars, purines, pyrimidines, vitamins, and nucleosides, that can be resolved by combining chromatographic and m/z dimensions. Subsequently, a targeted quantitative method was developed for 80 metabolites. The presented method combines a UPLC approach using hydrophilic interaction liquid chromatography (HILIC) and MS detection achieved by a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer. The optimal setup was achieved by evaluating reproducibility and repeatability of the analytical platforms using pooled quality control samples to minimize the drift in instrumental performance over time. Then, the method was validated by analyzing extracellular metabolites from acute lymphoblastic leukemia cell lines (MOLT-4 and CCRF-CEM) treated with direct (A-769662) and indirect (AICAR) AMP activated kinase (AMPK) activators, monitoring uptake and secretion of the targeted compound over time. This analysis pointed towards a perturbed purine and pyrimidine catabolism upon AICAR treatment. Our data suggest that the method presented can be used for qualitative and quantitative analysis of extracellular metabolites and it is suitable for routine applications such as in vitro drug screening

Metabolic Profiling as a Screening Tool for Cytotoxic Compounds: Identification of 3-Alkyl Pyridine Alkaloids from Sponges Collected at a Shallow Water Hydrothermal Vent Site North of Iceland

Twenty-eight sponge specimens were collected at a shallow water hydrothermal vent site north of Iceland. Extracts were prepared and tested in vitro for cytotoxic activity, and eight of them were shown to be cytotoxic. A mass spectrometry (MS)-based metabolomics approach was used to determine the chemical composition of the extracts. This analysis highlighted clear differences in the metabolomes of three sponge specimens, and all of them were identified as Haliclona (Rhizoniera) rosea (Bowerbank, 1866). Therefore, these specimens were selected for further investigation. Haliclona rosea metabolomes contained a class of potential key compounds, the 3-alkyl pyridine alkaloids (3-APA) responsible for the cytotoxic activity of the fractions. Several 3-APA compounds were tentatively identified including haliclamines, cyclostellettamines, viscosalines and viscosamines. Among these compounds, cyclostellettamine P was tentatively identified for the first time by using ion mobility MS in time-aligned parallel (TAP) fragmentation mode. In this work, we show the potential of applying metabolomics strategies and in particular the utility of coupling ion mobility with MS for the molecular characterization of sponge specimens