Experimental models of sepsis and their clinical relevance

Sepsis remains a major cause of morbidity and mortality mainly because of sepsis-induced multiple organ dysfunction. In contrast to preclinical studies, most clinical trials of promising new treatment strategies for sepsis have failed to demonstrate efficacy. Although many reasons could account for this discrepancy, the misinterpretation of preclinical data obtained from experimental studies and especially the use of animal models that do not adequately mimic human sepsis may have been contributing factors. In this review, the potentials and limitations of various animal models of sepsis are discussed to clarify to which extent these findings are relevant to human sepsis. Such models include intravascular infusion of endotoxin or live bacteria, bacterial peritonitis, cecal ligation and perforation, soft tissue infection, pneumonia or meningitis models using different animal species including rats, mice, rabbits, dogs, pigs, sheep, and nonhuman primates. Despite several limitations, animal models remain essential in the development of all new therapies for sepsis and septic shock because they provide fundamental information about the pharmacokinetics, toxicity, and mechanism of drug action that cannot be replaced by other methods. New therapeutic agents should be studied in infection models, even after the initiation of the septic process. Furthermore, debility conditions need to be reproduced to avoid the exclusive use of healthy animals, which often do not represent the human septic patient.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

A defense of backwards in time causation models in quantum mechanics

This paper offers a defense of backwards in time causation models in quantum mechanics. Particular attention is given to Cramer's transactional account, which is shown to have the threefold virtue of solving the Bell problem, explaining the complex conjugate aspect of the quantum mechanical formalism, and explaining various quantum mysteries such as Schrodinger's cat. The question is therefore asked, why has this model not received more attention from physicists and philosophers? One objection given by physicists in assessing Cramer's theory was that it is not testable. This paper seeks to answer this concern by utilizing an argument that backwards causation models entail a fork theory of causal direction. From the backwards causation model together with the fork theory one can deduce empirical predictions. Finally, the objection that this strategy is questionable because of its appeal to philosophy is deflected.

Risk Estimates of Dengue in Travelers to Dengue Endemic Areas Using Mathematical Models

Dengue has emerged as a frequent problem in international travelers. The risk depends on destination, duration, and season of travel. However, data to quantify the true risk for travelers to acquire dengue are lacking. We used mathematical models to estimate the risk of nonimmune persons to acquire dengue when traveling to Singapore. From the force of infection, we calculated the risk of dengue dependent on duration of stay and season of arrival. Our data highlight that the risk for nonimmune travelers to acquire dengue in Singapore is substantial but varies greatly with seasons and epidemic cycles. For instance, for a traveler who stays in Singapore for 1 week during the high dengue season in 2005, the risk of acquiring dengue was 0.17%, but it was only 0.00423% during the low season in a nonepidemic year such as 2002. Risk estimates based on mathematical modeling will help the travel medicine provider give better evidence-based advice for travelers to dengue endemic countries.

Predictive models for diagnosis of pleural effusions secondary to tuberculosis or cancer

Background and objective: Tuberculosis (TB) and cancer are two of the main causes of pleural effusions which frequently share similar clinical features and pleural fluid profiles. This study aimed to identify diagnostic models based on clinical and laboratory variables to differentiate tuberculous from malignant pleural effusions. Methods: A retrospective study of 403 patients (200 with TB; 203 with cancer) was undertaken. Univariate analysis was used to select the clinical variables relevant to the models composition. Variables beta coefficients were used to define a numerical score which presented a practical use. The performances of the most efficient models were tested in a sample of pleural exudates (64 new cases). Results: Two models are proposed for the diagnosis of effusions associated with each disease. For TB: (i) adenosine deaminase (ADA), globulins and the absence of malignant cells in the pleural fluid; and (ii) ADA, globulins and fluid appearance. For cancer: (i) patient age, fluid appearance, macrophage percentage and presence of atypical cells in the pleural fluid; and (ii) as for (i) excluding atypical cells. Application of the models to the 64 pleural effusions showed accuracy higher than 85% for all models. Conclusions: The proposed models were effective in suggesting pleural tuberculosis or cancer.

Targeted Mutagenesis in Pathogenic Leptospira Species: Disruption of the LigB Gene Does Not Affect Virulence in Animal Models of Leptospirosis

The pathogenic mechanisms of Leptospira interrogans, the causal agent of leptospirosis, remain largely unknown. This is mainly due to the lack of tools for genetically manipulating pathogenic Leptospira species. Thus, homologous recombination between introduced DNA and the corresponding chromosomal locus has never been demonstrated for this pathogen. Leptospiral immunoglobulin-like repeat (Lig) proteins were previously identified as putative Leptospira virulence factors. In this study, a ligB mutant was constructed by allelic exchange in L. interrogans; in this mutant a spectinomycin resistance (Spc(r)) gene replaced a portion of the ligB coding sequence. Gene disruption was confirmed by PCR, immunoblot analysis, and immunofluorescence studies. The ligB mutant did not show decrease virulence compared to the wild-type strain in the hamster model of leptospirosis. In addition, inoculation of rats with the ligB mutant induced persistent colonization of the kidneys. Finally, LigB was not required to mediate bacterial adherence to cultured cells. Taken together, our data provide the first evidence of site-directed homologous recombination in pathogenic Leptospira species. Furthermore, our data suggest that LigB does not play a major role in dissemination of the pathogen in the host and in the development of acute disease manifestations or persistent renal colonization.