A mathematical model for breath gas analysis of volatile organic compounds with special emphasis on acetone

Recommended standardized procedures for determining exhaled lower respiratory nitric oxide and nasal nitric oxide have been developed by task forces of the European Respiratory Society and the American Thoracic Society. These recommendations have paved the way for the measurement of nitric oxide to become a diagnostic tool for specific clinical applications. It would be desirable to develop similar guidelines for the sampling of other trace gases in exhaled breath, especially volatile organic compounds (VOCs) which reflect ongoing metabolism. The concentrations of water-soluble, blood-borne substances in exhaled breath are influenced by: (i) breathing patterns affecting gas exchange in the conducting airways; (ii) the concentrations in the tracheo-bronchial lining fluid; (iii) the alveolar and systemic concentrations of the compound. The classical Farhi equation takes only the alveolar concentrations into account. Real-time measurements of acetone in end-tidal breath under an ergometer challenge show characteristics which cannot be explained within the Farhi setting. Here we develop a compartment model that reliably captures these profiles and is capable of relating breath to the systemic concentrations of acetone. By comparison with experimental data it is inferred that the major part of variability in breath acetone concentrations (e.g., in response to moderate exercise or altered breathing patterns) can be attributed to airway gas exchange, with minimal changes of the underlying blood and tissue concentrations. Moreover, it is deduced that measured end-tidal breath concentrations of acetone determined during resting conditions and free breathing will be rather poor indicators for endogenous levels. Particularly, the current formulation includes the classical Farhi and the Scheid series inhomogeneity model as special limiting cases.Comment: 38 page

Thiolutin is a zinc chelator that inhibits the Rpn11 and other JAMM metalloproteases

Thiolutin is a disulfide-containing antibiotic and anti-angiogenic compound produced by Streptomyces. Its biological targets are not known. We show that reduced thiolutin is a zinc chelator that inhibits the JAB1/MPN/Mov34 (JAMM) domain–containing metalloprotease Rpn11, a deubiquitinating enzyme of the 19S proteasome. Thiolutin also inhibits the JAMM metalloproteases Csn5, the deneddylase of the COP9 signalosome; AMSH, which regulates ubiquitin-dependent sorting of cell-surface receptors; and BRCC36, a K63-specific deubiquitinase of the BRCC36-containing isopeptidase complex and the BRCA1–BRCA2-containing complex. We provide evidence that other dithiolopyrrolones also function as inhibitors of JAMM metalloproteases

Resolution of inflammation: a new therapeutic frontier

Dysregulated inflammation is a central pathological process in diverse disease states. Traditionally, therapeutic approaches have sought to modulate the pro- or anti-inflammatory limbs of inflammation, with mixed success. However, insight into the pathways by which inflammation is resolved has highlighted novel opportunities to pharmacologically manipulate these processes — a strategy that might represent a complementary (and perhaps even superior) therapeutic approach. This Review discusses the state of the art in the biology of resolution of inflammation, highlighting the opportunities and challenges for translational research in this field

Family Businesses and Adaptation: A Dynamic Capabilities Approach

The main objective of this research was to propose a framework centred on the dynamic capabilities approach, and to be applied in the context of family businesses’ adaption to their changing business environment. Data were gathered through interviews with ten FBs operating in Western Australia. Based on the findings, the clusters of activities, sensing, seizing, and transforming emerged as key factors for firms’ adaptation, and were reinforced by firms’ open culture, signature processes, idiosyncratic knowledge, and valuable, rare, inimitable and non-substitutable attributes. Thus, the usefulness of the proposed framework was confirmed. Implications and future research opportunities are presented. © 2018, The Author(s)

Neurospora COP9 Signalosome Integrity Plays Major Roles for Hyphal Growth, Conidial Development, and Circadian Function

The COP9 signalosome (CSN) is a highly conserved multifunctional complex that has two major biochemical roles: cleaving NEDD8 from cullin proteins and maintaining the stability of CRL components. We used mutation analysis to confirm that the JAMM domain of the CSN-5 subunit is responsible for NEDD8 cleavage from cullin proteins in Neurospora crassa. Point mutations of key residues in the metal-binding motif (EXnHXHX10D) of the CSN-5 JAMM domain disrupted CSN deneddylation activity without interfering with assembly of the CSN complex or interactions between CSN and cullin proteins. Surprisingly, CSN-5 with a mutated JAMM domain partially rescued the phenotypic defects observed in a csn-5 mutant. We found that, even without its deneddylation activity, the CSN can partially maintain the stability of the SCFFWD-1 complex and partially restore the degradation of the circadian clock protein FREQUENCY (FRQ) in vivo. Furthermore, we showed that CSN containing mutant CSN-5 efficiently prevents degradation of the substrate receptors of CRLs. Finally, we found that deletion of the CAND1 ortholog in N. crassa had little effect on the conidiation circadian rhythm. Our results suggest that CSN integrity plays major roles in hyphal growth, conidial development, and circadian function in N. crassa

"Hook"-calibration of GeneChip-microarrays: Chip characteristics and expression measures

<p>Abstract</p> <p>Background</p> <p>Microarray experiments rely on several critical steps that may introduce biases and uncertainty in downstream analyses. These steps include mRNA sample extraction, amplification and labelling, hybridization, and scanning causing chip-specific systematic variations on the raw intensity level. Also the chosen array-type and the up-to-dateness of the genomic information probed on the chip affect the quality of the expression measures. In the accompanying publication we presented theory and algorithm of the so-called hook method which aims at correcting expression data for systematic biases using a series of new chip characteristics.</p> <p>Results</p> <p>In this publication we summarize the essential chip characteristics provided by this method, analyze special benchmark experiments to estimate transcript related expression measures and illustrate the potency of the method to detect and to quantify the quality of a particular hybridization. It is shown that our single-chip approach provides expression measures responding linearly on changes of the transcript concentration over three orders of magnitude. In addition, the method calculates a detection call judging the relation between the signal and the detection limit of the particular measurement. The performance of the method in the context of different chip generations and probe set assignments is illustrated. The hook method characterizes the RNA-quality in terms of the 3'/5'-amplification bias and the sample-specific calling rate. We show that the proper judgement of these effects requires the disentanglement of non-specific and specific hybridization which, otherwise, can lead to misinterpretations of expression changes. The consequences of modifying probe/target interactions by either changing the labelling protocol or by substituting RNA by DNA targets are demonstrated.</p> <p>Conclusion</p> <p>The single-chip based hook-method provides accurate expression estimates and chip-summary characteristics using the natural metrics given by the hybridization reaction with the potency to develop new standards for microarray quality control and calibration.</p

Making Informed Choices about Microarray Data Analysis

This article describes the typical stages in the analysis of microarray data for non-specialist researchers in systems biology and medicine. Particular attention is paid to significant data analysis issues that are commonly encountered among practitioners, some of which need wider airing. The issues addressed include experimental design, quality assessment, normalization, and summarization of multiple-probe data. This article is based on the ISMB 2008 tutorial on microarray data analysis. An expanded version of the material in this article and the slides from the tutorial can be found at http://www.people.vcu.edu/~mreimers/OGMDA/index.html

Hearing and dementia

Hearing deficits associated with cognitive impairment have attracted much recent interest, motivated by emerging evidence that impaired hearing is a risk factor for cognitive decline. However, dementia and hearing impairment present immense challenges in their own right, and their intersection in the auditory brain remains poorly understood and difficult to assess. Here, we outline a clinically oriented, symptom-based approach to the assessment of hearing in dementias, informed by recent progress in the clinical auditory neuroscience of these diseases. We consider the significance and interpretation of hearing loss and symptoms that point to a disorder of auditory cognition in patients with dementia. We identify key auditory characteristics of some important dementias and conclude with a bedside approach to assessing and managing auditory dysfunction in dementia

Identifying Determinants of Cullin Binding Specificity Among the Three Functionally Different Drosophila melanogaster Roc Proteins via Domain Swapping

BACKGROUND: Cullin-dependent E3 ubiquitin ligases (CDL) are key regulators of protein destruction that participate in a wide range of cell biological processes. The Roc subunit of CDL contains an evolutionarily conserved RING domain that binds ubiquitin charged E2 and is essential for ubiquitylation. Drosophila melanogaster contains three highly related Roc proteins: Roc1a and Roc2, which are conserved in vertebrates, and Roc1b, which is specific to Drosophila. Our previous genetic data analyzing Roc1a and Roc1b mutants suggested that Roc proteins are functionally distinct, but the molecular basis for this distinction is not known. METHODOLOGY/PRINCIPAL FINDINGS: Using co-immunoprecipitation studies we show that Drosophila Roc proteins bind specific Cullins: Roc1a binds Cul1-4, Roc1b binds Cul3, and Roc2 binds Cul5. Through domain swapping experiments, we demonstrate that Cullin binding specificity is strongly influenced by the Roc NH(2)-terminal domain, which forms an inter-molecular beta sheet with the Cullin. Substitution of the Roc1a RING domain with that of Roc1b results in a protein with similar Cullin binding properties to Roc1a that is active as an E3 ligase but cannot complement Roc1a mutant lethality, indicating that the identity of the RING domain can be an important determinant of CDL function. In contrast, the converse chimeric protein with a substitution of the Roc1b RING domain with that of Roc1a can rescue the male sterility of Roc1b mutants, but only when expressed from the endogenous Roc1b promoter. We also identified mutations of Roc2 and Cul5 and show that they cause no overt developmental phenotype, consistent with our finding that Roc2 and Cul5 proteins are exclusive binding partners, which others have observed in human cells as well. CONCLUSIONS: The Drosophila Roc proteins are highly similar, but have diverged during evolution to bind a distinct set of Cullins and to utilize RING domains that have overlapping, but not identical, function in vivo

A Novel Framework for the Comparative Analysis of Biological Networks

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes