Near-optimal experimental design for model selection in systems biology

Motivation: Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. Results: We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Availability: Toolbox ‘NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Near-optimal experimental design for model selection in systems biology

Motivation: Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. Results: We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Availability: Toolbox ‘NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

A data acquisition system for parallel readout of delay line detectors based on space–time–space conversion

First tests of a data acquisition system for linear position-sensitive gas proportional detectors based on an ASIC (application specific integrated circuit) implementing the space–time–space conversion method for parallel readout of delay lines are presented. Using a standard delay line detector a spatial resolution of 0.3 mm/channel was achieved corresponding to a time resolution of ≅0.4 ns/channel in the ASIC

Saliva enhances infection of gingival fibroblasts by herpes simplex virus 1.

Oral herpes is a highly prevalent infection caused by herpes simplex virus 1 (HSV-1). After an initial infection of the oral cavity, HSV-1 remains latent in sensory neurons of the trigeminal ganglia. Episodic reactivation of the virus leads to the formation of mucocutaneous lesions (cold sores), but asymptomatic reactivation accompanied by viral shedding is more frequent and allows virus spread to new hosts. HSV-1 DNA has been detected in many oral tissues. In particular, HSV-1 can be found in periodontal lesions and several studies associated its presence with more severe periodontitis pathologies. Since gingival fibroblasts may become exposed to salivary components in periodontitis lesions, we analyzed the effect of saliva on HSV-1 and -2 infection of these cells. We observed that human gingival fibroblasts can be infected by HSV-1. However, pre-treatment of these cells with saliva extracts from some but not all individuals led to an increased susceptibility to infection. Furthermore, the active saliva could expand HSV-1 tropism to cells that are normally resistant to infection due to the absence of HSV entry receptors. The active factor in saliva was partially purified and comprised high molecular weight complexes of glycoproteins that included secretory Immunoglobulin A. Interestingly, we observed a broad variation in the activity of saliva between donors suggesting that this activity is selectively present in the population. The active saliva factor, has not been isolated, but may lead to the identification of a relevant biomarker for susceptibility to oral herpes. The presence of a salivary factor that enhances HSV-1 infection may influence the risk of oral herpes and/or the severity of associated oral pathologies

Saliva enhances infection of gingival fibroblasts by herpes simplex virus 1.

Oral herpes is a highly prevalent infection caused by herpes simplex virus 1 (HSV-1). After an initial infection of the oral cavity, HSV-1 remains latent in sensory neurons of the trigeminal ganglia. Episodic reactivation of the virus leads to the formation of mucocutaneous lesions (cold sores), but asymptomatic reactivation accompanied by viral shedding is more frequent and allows virus spread to new hosts. HSV-1 DNA has been detected in many oral tissues. In particular, HSV-1 can be found in periodontal lesions and several studies associated its presence with more severe periodontitis pathologies. Since gingival fibroblasts may become exposed to salivary components in periodontitis lesions, we analyzed the effect of saliva on HSV-1 and -2 infection of these cells. We observed that human gingival fibroblasts can be infected by HSV-1. However, pre-treatment of these cells with saliva extracts from some but not all individuals led to an increased susceptibility to infection. Furthermore, the active saliva could expand HSV-1 tropism to cells that are normally resistant to infection due to the absence of HSV entry receptors. The active factor in saliva was partially purified and comprised high molecular weight complexes of glycoproteins that included secretory Immunoglobulin A. Interestingly, we observed a broad variation in the activity of saliva between donors suggesting that this activity is selectively present in the population. The active saliva factor, has not been isolated, but may lead to the identification of a relevant biomarker for susceptibility to oral herpes. The presence of a salivary factor that enhances HSV-1 infection may influence the risk of oral herpes and/or the severity of associated oral pathologies