Procalcitonin for diagnosis of infection and guide to antibiotic decisions: past, present and future

There are a number of limitations to using conventional diagnostic markers for patients with clinical suspicion of infection. As a consequence, unnecessary and prolonged exposure to antimicrobial agents adversely affect patient outcomes, while inappropriate antibiotic therapy increases antibiotic resistance. A growing body of evidence supports the use of procalcitonin (PCT) to improve diagnosis of bacterial infections and to guide antibiotic therapy. For patients with upper and lower respiratory tract infection, post-operative infections and for severe sepsis patients in the intensive care unit, randomized-controlled trials have shown a benefit of using PCT algorithms to guide decisions about initiation and/or discontinuation of antibiotic therapy. For some other types of infections, observational studies have shown promising first results, but further intervention studies are needed before use of PCT in clinical routine can be recommended. The aim of this review is to summarize the current evidence for PCT in different infections and clinical settings, and discuss the reliability of this marker when used with validated diagnostic algorithms

Description of inclusive scattering of 4.045 GeV electrons from D

We exploit a relationship between the Structure Functions of nucleons, the physical deuteron and of a deuteron, composed of point-nucleons to compute angular distributions of inclusive cross sections of 4.05 GeV electrons. We report general agreement with data and interpret the remaining discrepancies. We discuss the potential of the data for information on neutron structure functions $F_k^n(x,Q^2)$ and the static form factor $G_M^n(Q^2)$.Comment: 9 pages,1 Fig., PS fil

Terahertz spin-to-charge current conversion in stacks of ferromagnets and the transition-metal dichalcogenide NbSe₂

Transition-metal dichalcogenides (TMDCs) are an aspiring class of materials with unique electronic and optical properties and potential applications in spin-based electronics. Here, we use terahertz emission spectroscopy to study spin-to-charge current conversion (S2C) in the TMDC NbSe$_2$ in ultra-high-vacuum-grown F|NbSe$_2$ thin-film stacks, where F is a layer of ferromagnetic Fe or Ni. Ultrafast laser excitation triggers an ultrafast spin current that is converted into an in-plane charge current and, thus, a measurable THz electromagnetic pulse. The THz signal amplitude as a function of the NbSe$_2$ thickness shows that the measured signals are fully consistent with an ultrafast optically driven injection of an in-plane-polarized spin current into NbSe$_2$. Modeling of the spin-current dynamics reveals that a sizable fraction of the total S2C originates from the bulk of NbSe$_2$ with the same, negative, sign as the spin Hall angle of pure Nb. By quantitative comparison of the emitted THz radiation from F|NbSe$_2$ to F|Pt reference samples and the results of ab-initio calculations, we estimate that the spin Hall angle of NbSe$_2$ for an in-plane polarized spin current lies between -0.2% and -1.1%, while the THz spin-current relaxation length is of the order of a few nanometers

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium. 15-18 March 2016.

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Characterization of growth and metabolism of the haloalkaliphile Natronomonas pharaonis

Natronomonas pharaonis is an archaeon adapted to two extreme conditions: high salt concentration and alkaline pH. It has become one of the model organisms for the study of extremophilic life. Here, we present a genome-scale, manually curated metabolic reconstruction for the microorganism. The reconstruction itself represents a knowledge base of the haloalkaliphile's metabolism and, as such, would greatly assist further investigations on archaeal pathways. In addition, we experimentally determined several parameters relevant to growth, including a characterization of the biomass composition and a quantification of carbon and oxygen consumption. Using the metabolic reconstruction and the experimental data, we formulated a constraints-based model which we used to analyze the behavior of the archaeon when grown on a single carbon source. Results of the analysis include the finding that Natronomonas pharaonis, when grown aerobically on acetate, uses a carbon to oxygen consumption ratio that is theoretically near-optimal with respect to growth and energy production. This supports the hypothesis that, under simple conditions, the microorganism optimizes its metabolism with respect to the two objectives. We also found that the archaeon has a very low carbon efficiency of only about 35%. This inefficiency is probably due to a very low P/O ratio as well as to the other difficulties posed by its extreme environment

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Knocking down gene function with an RNA aptamer expressed as part of an intron

We developed a powerful expression system to produce aptamers and other types of functional RNA in yeast to examine their effects. Utilizing the intron homing process, the aptamer-coding sequences were integrated into hundreds of rRNA genes, and the aptamers were transcribed at high levels by RNA polymerase I without any additional promoter being introduced into the cell. We used this system to express an aptamer against the heat shock factor 1 (HSF1), a conserved transcription factor responsible for mobilizing specific genomic expression programs in response to stressful conditions such as elevated temperature. We observed a temperature sensitive growth retardation phenotype and specific decrease of heat shock gene expression. As HSF1 enables and promotes malignant growth and metastasis in mammals, and this aptamer binds yeast HSF1 and its mammalian ortholog with equal affinity, the results presented here attest to the potential of this aptamer as a specific and effective inhibitor of HSF1 activity