Development and optimization of quantitative PCR for the diagnosis of invasive aspergillosis with bronchoalveolar lavage fluid

Background: The diagnosis of invasive pulmonary aspergillosis (IPA) remains challenging. Culture and histopathological examination of bronchoalveolar lavage (BAL) fluid are useful but have suboptimal sensitivity and in the case of culture may require several days for fungal growth to be evident. Detection of Aspergillus DNA in BAL fluid by quantitative PCR (qPCR) offers the potential for earlier diagnosis and higher sensitivity. It is important to adopt quality control measures in PCR assays to address false positives and negatives which can hinder accurate evaluation of diagnostic performance. Methods: BAL fluid from 94 episodes of pneumonia in 81 patients was analyzed. Thirteen episodes were categorized as proven or probable IPA using Mycoses Study Group criteria. The pellet and the supernatant fractions of the BAL were separately assayed. A successful extraction was confirmed with a human 18S rRNA gene qPCR. Inhibition in each qPCR was measured using an exogenous DNA based internal amplification control (IAC). The presence of DNA from pathogens in the Aspergillus genus was detected using qPCR targeting fungal 18S rRNA gene. Results: Human 18S rRNA gene qPCR confirmed successful DNA extraction of all samples. IAC detected some degree of initial inhibition in 11 samples. When culture was used to diagnose IPA, the sensitivity and specificity were 84.5% and 100% respectively. Receiver-operating characteristic analysis of qPCR showed that a cutoff of 13 fg of Aspergillus genomic DNA generated a sensitivity, specificity, positive and negative predictive value of 77%, 88%, 50%, 96% respectively. BAL pellet and supernatant analyzed together resulted in sensitivity and specificity similar to BAL pellet alone. Some patients did not meet standard criteria for IPA, but had consistently high levels of Aspergillus DNA in BAL fluid by qPCR. Conclusion: The Aspergillus qPCR assay detected Aspergillus DNA in 76.9% of subjects with proven or probable IPA when the concentrated BAL fluid pellet fraction was used for diagnosis. There was no benefit from analyzing the BAL supernatant fraction. Use of both extraction and amplification controls provided optimal quality control for interpreting qPCR results and therefore may increase our understanding of the true potential of qPCR for the diagnosis of IPA.Supported by NIH grant R01 AI054703 from the National Institute of Allergy and Infectious Diseases

An overview of harms associated with β-lactam antimicrobials: where do the carbapenems fit in?

The US Institute of Medicine's focus on patient safety has motivated hospital administrators to facilitate a culture of safety. As a result, subcommittees of the pharmacy and therapeutics committee have emerged in many hospitals to focus on adverse events and patient safety. Antimicrobial harms have gained the attention of practicing clinicians and hospital formulary committees, because they top the list of drugs that are associated with adverse events and because of certain serious harms that have ultimately led to the withdrawal of some antimicrobial agents. In the near future, several antimicrobials in the late phase of development will become available for clinical use (ceftobiprole, ceftaroline, and telavancin), and others (doripenem and dalbavancin) have recently joined the armamentarium. Because new antimicrobials will become part of the treatment armamentarium, it is important to discuss our current understanding of antimicrobial harms in general. Although not thought of as traditional adverse events, Clostridium difficile infection and development of resistance during therapy are adverse events that occur as a result of antimicrobial exposure and therefore are discussed. In addition, a distillation of our current understanding of β-lactam specific adverse events will be provided. Finally, new methods of administration are being evaluated that may influence peak concentration-related antimicrobial adverse events

Trade-Off between Toxicity and Signal Detection Orchestrated by Frequency- and Density-Dependent Genes

Behaviors in insects are partly highly efficient Bayesian processes that fulfill exploratory tasks ending with the colonization of new ecological niches. The foraging (for) gene in Drosophila encodes a cGMP-dependent protein kinase (PKG). It has been extensively described as a frequency-dependent gene and its transcripts are differentially expressed between individuals, reflecting the population density context. Some for transcripts, when expressed in a population at high density for many generations, concomitantly trigger strong dispersive behavior associated with foraging activity. Moreover, genotype-by-environment interaction (GEI) analysis has highlighted a dormant role of for in energetic metabolism in a food deprivation context. In our current report, we show that alleles of for encoding different cGMP-dependent kinase isoforms influence the oxidation of aldehyde groups of aromatic molecules emitted by plants via Aldh-III and a phosphorylatable adaptor. The enhanced efficiency of oxidation of aldehyde odorants into carboxyl groups by the action of for lessens their action and toxicity, which should facilitate exploration and guidance in a complex odor environment. Our present data provide evidence that optimal foraging performance requires the fast metabolism of volatile compounds emitted by plants to avoid neurosensory saturation and that the frequency-dependent genes that trigger dispersion influence these processes

Jumping genes for water distribution system design optimization

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Robust multi-objective optimization for water distribution system design using a meta-metaheuristic

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Water distribution systems design optimisation using metaheuristics and hyperheuristics

The topic of multi-objective water distribution systems (WDS) design optimisation using metaheuristics is investigated, comparing numerous modern metaheuristics, including sev- eral multi-objective evolutionary algorithms, an estimation of distribution algorithm and a recent hyperheuristic named AMALGAM (an evolutionary framework for the simultaneous incorporation of multiple metaheuristics), in order to determine which approach is most capa- ble with respect to WDS design optimisation. Novel metaheuristics and variants of existing algorithms are developed, for a total of twenty-three algorithms examined. Testing with re- spect to eight small-to-large-sized WDS benchmarks from the literature reveal that the four top-performing algorithms are mutually non-dominated with respect to the various perfor- mance metrics used. These algorithms are NSGA-II, TAMALGAMJndu , TAMALGAMndu and AMALGAMSndp (the last three being novel variants of AMALGAM). However, when these four algorithms are applied to the design of a very large real-world benchmark, the AMALGAM paradigm outperforms NSGA-II convincingly, with AMALGAMSndp exhibiting the best performance overall