The contribution of proteomics towards deciphering the enigma of Coxiella burnetii

Coxiella burnetii, the causative agent of Q fever, is an intracellular bacterium and a potential weapon for bioterrorism. The widespread throughout the world, zoonosis is manifested clinically as a self-limited febrile illness, as pneumonia (acute Q fever) or as a chronic illness with endocarditis being its major complication. The recent Netherlands Q fever outbreak has driven the bacterium from a relatively cryptic, underappreciated, “niche” microorganism on the sideline of bacteriology, to one of possibly great impact on public health. Advances in the study of this microorganism proceeded slowly, primarily due to the, until recently, obligatory intracellular nature of the pathogen that in its virulent phase I must be manipulated under biosafety level-3 conditions. Proteomic studies, in particular, have generated a vast amount of information concerning several aspects of the bacterium such as virulence factors, detection/diagnostic and immunogenic biomarkers, inter-/intraspecies variation, resistance to antibiotics, and secreted effector proteins with significant clinical impact. The phenomenon observed following the genomics era, that of generation and accumulation of huge amount of data that ultimately end up unexploited on several databases, begins to emerge in the proteomics field as well. This review will focus on the advances in the field of C. burnetii proteomics through MS, attempting in parallel to utilize some of the proteomics findings by suggesting future directions for the improvement of Q fever diagnosis and therapy.     

Sparse CCA using a Lasso with positivity constraints

Canonical correlation analysis (CCA) describes the relationship between two sets of variables by finding linear combinations of the variables with maximal correlation. A sparse version of CCA is proposed that reduces the chance of including unimportant variables in the canonical variates and thus improves their interpretation. A version of the Lasso algorithm incorporating positivity constraints is implemented in tandem with alternating least squares (ALS), to obtain sparse canonical variates. The proposed method is demonstrated on simulation studies and a data set from market basket analysis.     

Secure electronic bills of lading: blind counts and digital signatures

Electronic documents used in the framework of the goods delivery industry—i.e. electronic bills of lading (e-BOLs)—are the enablers of any payment, and therefore exposed to frauds. As of today, e-BOLs are handled by special private companies, which provide paperless trading services through their trade chains. This paper contributes a zero-knowledge open solution to the problem of designing secure electronic bills of lading, in the framework of a shipper-carrier-buyer transmission model. The suggested solution is a cryptographic protocol based on digital signatures and blind merchandise counts—that is, counts that do not reveal any information about actually counted quantities. The model is designed to mitigate a number of security threats and assumes the existence of both a trusted third party and a bank in charge of payment procedures. The paper discusses the drawbacks of the existing proprietary solutions and shows how the suggested open protocol addresses them.     

GPR55 Receptor Activation by the N-Acyl Dopamine Family Lipids Induces Apoptosis in Cancer Cells via the Nitric Oxide Synthase (nNOS) Over-Stimulation

GPR55 is a GPCR of the non-CB1/CB2 cannabinoid receptor family, which is activated by lysophosphatidylinositol (LPI) and stimulates the proliferation of cancer cells. Anandamide, a bioactive lipid endocannabinoid, acts as a biased agonist of GPR55 and induces cancer cell death, but is unstable and psychoactive. We hypothesized that other endocannabinoids and structurally similar compounds, which are more hydrolytically stable, could also induce cancer cell death via GPR55 activation. We chemically synthesized and tested a set of fatty acid amides and esters for cell death induction via GPR55 activation. The most active compounds appeared to be N-acyl dopamines, especially N-docosahexaenoyl dopamine (DHA-DA). Using a panel of cancer cell lines and a set of receptor and intracellular signal transduction machinery inhibitors together with cell viability, Ca²⁺, NO, ROS (reactive oxygen species) and gene expression measurement, we showed for the first time that for these compounds, the mechanism of cell death induction differed from that published for anandamide and included neuronal nitric oxide synthase (nNOS) overstimulation with concomitant oxidative stress induction. The combination of DHA-DA with LPI, which normally stimulates cancer proliferation and is increased in cancer setting, had an increased cytotoxicity for the cancer cells indicating a therapeutic potential.     

A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification

Severe bioprosthetic mitral valve calcification is a significant problem in cardiovascular surgery. Unfortunately, clinical markers did not demonstrate efficacy in prediction of severe bioprosthetic mitral valve calcification. Here, we examined whether a genomics-based approach is efficient in predicting the risk of severe bioprosthetic mitral valve calcification. A total of 124 consecutive Russian patients who underwent mitral valve replacement surgery were recruited. We investigated the associations of the inherited variation in innate immunity, lipid metabolism and calcium metabolism genes with severe bioprosthetic mitral valve calcification. Genotyping was conducted utilizing the TaqMan assay. Eight gene polymorphisms were significantly associated with severe bioprosthetic mitral valve calcification and were therefore included into stepwise logistic regression which identified male gender, the T/T genotype of the rs3775073 polymorphism within the TLR6 gene, the C/T genotype of the rs2229238 polymorphism within the IL6R gene, and the A/A genotype of the rs10455872 polymorphism within the LPA gene as independent predictors of severe bioprosthetic mitral valve calcification. The developed genomics-based model had fair predictive value with area under the receiver operating characteristic (ROC) curve of 0.73. In conclusion, our genomics-based approach is efficient for the prediction of severe bioprosthetic mitral valve calcification.     

Brewer’s spent grain as a functional ingredient for breadsticks

Brewer’s spent grain (BSG) was evaluated for its potential as a functional baking ingredient. Scanning electron microscopy (SEM) was used to examine the microstructure of BSG and wheat flours. Baked snacks (breadsticks) were prepared using 15%, 25% and 35% BSG and evaluated for their baking quality and fibre and protein content (over a period of 3 months). The addition of BSG altered the baking characteristics of the breadsticks by affecting their structure and texture. The snacks appeared to lack in cellular structure and crispiness. However, they had quite a stable shelf‐life, as changes in texture, moisture and a_w progressed at a low rate. Addition of 25% and 35% BSG significantly increased the protein content of the snacks, and addition of 15% BSG more than doubled the content of dietary fibre in the samples.     

Calculation of the Thermoelectric Properties of n- and p-Type Lead Telluride Using a Three-Band Model of the Electron Energy Spectrum

In this paper, we study theoretically the thermoelectric properties of n- and p-type PbTe in the wide temperature interval of 300–900 K. A three-band model of the PbTe electron energy spectrum is used in these calculations. The full set of the relevant kinetic characteristics is calculated including the electrical and thermal conductivities, the Seebeck coefficient, and the thermoelectric figure-of-merit. The calculated thermoelectric quantities are in good agreement with the available experimental data.     

Syngas production from H2O and CO2 over Zn particles in a packed‐bed reactor

The solar thermochemical production of H₂ and CO (syngas) from H₂O and CO₂ is examined via a two‐step cycle based on Zn/ZnO redox reactions. The first, endothermic step is the thermolysis of the ZnO driven by concentrated solar energy. The second, nonsolar step is the exothermic reaction of Zn with a mixture of H₂O and CO₂ yielding syngas and ZnO; the latter is recycled to the first step. A series of experimental runs of the second step was carried out in a packed‐bed reactor where ZnO particles provided an effective inert support for preventing sintering and enabling simple and complete recycling to the first, solar step. Experimentation was performed for Zn mass fractions in the range of 33–67 wt % Zn‐ZnO, and inlet gas concentrations in the range 0–75% H₂O–CO₂, yielding molar Zn‐to‐ZnO conversions up to 91%. A 25 wt % Zn‐ZnO sample mixture produced from the solar thermolysis of ZnO was tested in the same reactor setup and exhibited high reactivity and conversions up to 96%. © 2011 American Institute of Chemical Engineers AIChE J, 2012