Rapid identification of precursor cDNAs encoding five structural classes of antimicrobial peptides from pickerel frog (Rana palustris) skin secretion by single step “shotgun” cloning.

The skin secretion of the North American pickerel frog (Rana palustris) has long been known to have pronounced noxious/toxic properties and to be highly effective in defence against predators and against other sympatric amphibians. As it consists largely of a complex mixture of peptides, it has been subjected to systematic peptidomic study but there has been little focus on molecular cloning of peptide-encoding cDNAs and by deduction, the biosynthetic precursors that they encode. Here, we demonstrate that the cDNAs encoding the five major structural families of antimicrobial peptides can be elucidated by a single step “shotgun” cloning approach using a cDNA library constructed from the source material of the peptidomic studies—the defensive skin secretion itself. Using a degenerate primer pool designed to a highly conserved nucleic acid sequence 5' to the initiation codon of known antimicrobial peptide precursor transcripts, we amplified cDNA sequences representing five major classes of antimicrobial peptides, such as esculentins, brevinins, ranatuerins, palustrins and temporins. Bioinformatic comparisons of precursor open-reading frames and nucleic acid sequences revealed high degrees of structural similarities between analogous peptides of R. palustris and the Chinese bamboo odorous frog, Rana versabilis. This approach thus constitutes a robust technique that can be used either alone or ideally, in parallel with peptidomic analysis of skin secretion, to rapidly extract primary structural information on amphibian skin secretion peptides and their biosynthetic precursors.

Towards variance-matrix characterization of complementarity relations in a continuous variable system

We discuss complementarity relations in a bipartite continuous variable system. Building up from the work done on discrete d-dimensional systems, we prove that for symmetric two-mode states, quantum complementarity relations can be put in a simple relation with the elements of the variance matrix. When this condition is not satisfied, such a connection becomes non-trivial. Our investigation is the first step towards an operative characterization of the complementarity in a scenario that has not been investigated so far.

Noise resilience and entanglement evolution in two nonequivalent classes of quantum algorithms

The speedup provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speedup are not yet completely understood and deserve further attention. In this context, the classical simulation of quantum algorithms is a useful tool that can help us in gaining insight. Starting from the study of general conditions for classical simulation, we highlight several important differences between two nonequivalent classes of quantum algorithms. We investigate their performance under realistic conditions by quantitatively studying their resilience with respect to static noise. This latter refers to errors affecting the initial preparation of the register used to run an algorithm. We also compare the evolution of the entanglement involved in the different computational processes.

Modelling the impact of antibiotic use and infection control practices on the incidence of hospital-acquired methicillin-resistant Staphylococcus aureus: a time-series analysis

Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a major nosocomial pathogen worldwide. A wide range of factors have been suggested to influence the spread of MRSA. The objective of this study was to evaluate the effect of antimicrobial drug use and infection control practices on nosocomial MRSA incidence in a 426-bed general teaching hospital in Northern Ireland.

Methods: The present research involved the retrospective collection of monthly data on the usage of antibiotics and on infection control practices within the hospital over a 5 year period (January 2000–December 2004). A multivariate ARIMA (time-series analysis) model was built to relate MRSA incidence with antibiotic use and infection control practices.

Results: Analysis of the 5 year data set showed that temporal variations in MRSA incidence followed temporal variations in the use of fluoroquinolones, third-generation cephalosporins, macrolides and amoxicillin/clavulanic acid (coefficients = 0.005, 0.03, 0.002 and 0.003, respectively, with various time lags). Temporal relationships were also observed between MRSA incidence and infection control practices, i.e. the number of patients actively screened for MRSA (coefficient = -0.007), the use of alcohol-impregnated wipes (coefficient = -0.0003) and the bulk orders of alcohol-based handrub (coefficients = -0.04 and -0.08), with increased infection control activity being associated with decreased MRSA incidence, and between MRSA incidence and the number of new patients admitted with MRSA (coefficient = 0.22). The model explained 78.4% of the variance in the monthly incidence of MRSA.

Conclusions: The results of this study confirm the value of infection control policies as well as suggest the usefulness of restricting the use of certain antimicrobial classes to control MRSA.

Quasiexperimental Study of the Effects of Antibiotic Use, Gastric Acid-Suppressive Agents, and Infection Control Practices on the Incidence of Clostridium difficile-Associated Diarrhea in Hospitalized Patients

The objective of this study was to evaluate the effects of antimicrobial drug use, gastric acid-suppressive agent use, and infection control practices on the incidence of Clostridium difficile-associated diarrhea (CDAD) in a 426-bed general teaching hospital in Northern Ireland. The study was retrospective and ecological in design. A multivariate autoregressive integrated moving average (time-series analysis) model was built to relate CDAD incidence with antibiotic use, gastric acid-suppressive agent use, and infection control practices within the hospital over a 5-year period (February 2002 to March 2007). The findings of this study showed that temporal variation in CDAD incidence followed temporal variations in expanded-spectrum cephalosporin use (average delay = 2 months; variation of CDAD incidence = 0.01/100 bed-days), broad-spectrum cephalosporin use (average delay = 2 months; variation of CDAD incidence = 0.02/100 bed-days), fluoroquinolone use (average delay = 3 months; variation of CDAD incidence = 0.004/100 bed-days), amoxicillin-clavulanic acid use (average delay = 1 month; variation of CDAD incidence = 0.002/100 bed-days), and macrolide use (average delay = 5 months; variation of CDAD incidence = 0.002/100 bed-days). Temporal relationships were also observed between CDAD incidence and use of histamine-2 receptor antagonists (H2RAs; average delay = 1 month; variation of CDAD incidence = 0.001/100 bed-days). The model explained 78% of the variance in the monthly incidence of CDAD. The findings of this study highlight a temporal relationship between certain classes of antibiotics, H2RAs, and CDAD incidence. The results of this research can help hospitals to set priorities for restricting the use of specific antibiotic classes, based on the size-effect of each class and the delay necessary to observe an effect.