Epidemiology of age-dependent prevalence of Bovine Herpes Virus Type 1 (BoHV-1) in dairy herds with and without vaccination.

Many studies report age as a risk factor for BoHV-1 infection or seropositivity. However, it is unclear whether this pattern reflects true epidemiological causation or is a consequence of study design and other issues. Here, we seek to understand the age-related dynamics of BoHV-1 seroprevalence in seasonal calving Irish dairy herds and provide decision support for the design and implementation of effective BoHV-1 testing strategies. We analysed seroprevalence data from dairy herds taken during two Irish seroprevalence surveys conducted between 2010 and 2017. Age-dependent seroprevalence profiles were constructed for herds that were seropositive and unvaccinated. Some of these profiles revealed a sudden increase in seroprevalence between adjacent age-cohorts, from absent or low to close to 100% of seropositive animals. By coupling the outcome of our data analysis with simulation output of an individual-based model at the herd scale, we have shown that these sudden increases are related to extensive virus circulation within a herd for a limited time, which may then subsequently remain latent over the following years. BoHV-1 outbreaks in dairy cattle herds affect animals independent of age and lead to almost 100% seroconversion in all age groups, or at least in all animals within a single epidemiological unit. In the absence of circulating infection, there is a year-on-year increase in the age-cohort at which seroprevalence changes from low to high. The findings of this study inform recommendations regarding testing regimes in the context of contingency planning or an eradication programme in seasonal calving dairy herds.

Cefuroxime plasma and tissue concentrations in patients undergoing elective cardiac surgery: Continuous vs bolus application. A pilot study.

AIMS: Surgical site infections contribute to morbidity and mortality after surgery. The authors hypothesized that higher antibiotic tissue concentrations can be reached for a prolonged time span by continuous administration of prophylactic cefuroxime compared to bolus administration. METHODS: Twelve patients undergoing elective cardiac surgery were investigated. Group A received 1.5 g cefuroxime as bolus infusions before surgery, and 12 and 24 hours thereafter. In group B, a continuous infusion of 3.0 g cefuroxime was started after a bolus of 1.5 g. Cefuroxim levels were determined in blood and tissue (microdialysis). T-test, Wilcoxon signed rank test and χ2 test were used for statistical analysis. RESULTS: The area under the curve (AUC) of plasma cefuroxime concentrations was greater in group B (399 [333-518]) as compared to group A (257 [177-297] h mg L-1 , [median and interquartile range], P = .026). Furthermore, a significantly longer percentage of time > minimal inhibitory concentrations of 2 mg L-1 (100% vs 50%), 4 mg L-1 (100% vs 42%), 8 mg L-1 (100% vs 17%) and 16 mg L-1 (83% vs 8%) was found for free plasma cefuroxime in group B. In group B, area under the curve in subcutaneous tissue (78 [61-113] h mg L-1 ) and median peak concentration (33 [26-38] mg L-1 ) were markedly higher compared to group A (P = 0.041 and P = .026, respectively). CONCLUSIONS: Higher cefuroxime concentrations were measured in plasma and subcutaneously over a prolonged period of time when cefuroxime was administered continuously. The clinical implication of this finding still has to be elucidated.

Evolutionary Design of Classifiers Made of Droplets Containing a Nonlinear Chemical Medium.

Unconventional computing devices operating on nonlinear chemical media offer an interesting alternative to standard, semiconductor-based computers. In this work we study in-silico a chemical medium composed of communicating droplets that functions as a database classifier. The droplet network can be "programmed" by an externally provided illumination pattern. The complex relationship between the illumination pattern and the droplet behavior makes manual programming hard. We introduce an evolutionary algorithm that automatically finds the optimal illumination pattern for a given classification problem. Notably, our approach does not require us to prespecify the signals that represent the output classes of the classification problem, which is achieved by using a fitness function that measures the mutual information between chemical oscillation patterns and desired output classes. We illustrate the feasibility of our approach in computer simulations by evolving droplet classifiers for three machine learning datasets. We demonstrate that the same medium composed of 25 droplets located on a square lattice can be successfully used for different classification tasks by applying different illumination patterns as its externally supplied program.

Compressing molecular dynamics trajectories: Breaking the one-bit-per-sample barrier.

Molecular dynamics simulations yield large amounts of trajectory data. For their durable storage and accessibility an efficient compression algorithm is paramount. State of the art domain-specific algorithms combine quantization, Huffman encoding and occasionally domain knowledge. We propose the high resolution trajectory compression scheme (HRTC) that relies on piecewise linear functions to approximate quantized trajectories. By splitting the error budget between quantization and approximation, our approach beats the current state of the art by several orders of magnitude given the same error tolerance. It allows storing samples at far less than one bit per sample. It is simple and fast enough to be integrated into the inner simulation loop, store every time step, and become the primary representation of trajectory data. © 2016 Wiley Periodicals, Inc.

Effects of small particle numbers on long-term behaviour in discrete biochemical systems.

MOTIVATION: The functioning of many biological processes depends on the appearance of only a small number of a single molecular species. Additionally, the observation of molecular crowding leads to the insight that even a high number of copies of species do not guarantee their interaction. How single particles contribute to stabilizing biological systems is not well understood yet. Hence, we aim at determining the influence of single molecules on the long-term behaviour of biological systems, i.e. whether they can reach a steady state. RESULTS: We provide theoretical considerations and a tool to analyse Systems Biology Markup Language models for the possibility to stabilize because of the described effects. The theory is an extension of chemical organization theory, which we called discrete chemical organization theory. Furthermore we scanned the BioModels Database for the occurrence of discrete chemical organizations. To exemplify our method, we describe an application to the Template model of the mitotic spindle assembly checkpoint mechanism. AVAILABILITY AND IMPLEMENTATION: http://www.biosys.uni-jena.de/Services.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

About the Therapy of Laryngotracheitis (Croup): Significance of Rectal Dosage Forms.

Glucocorticoids are drugs of choice for treatment of laryngotracheitis (croup). They may be administered orally as tablets or juice, locally as inhalation or rectally as suppository or capsule. If doctors decide to use a rectal administration for practical reasons, it is obvious from a pharmacokinetic and pharmacodynamic point of view that prednisolone capsules have an earlier and stronger anti-inflammatory effect than a prednisone suppository.

Reaction networks and evolutionary game theory.

The powerful mathematical tools developed for the study of large scale reaction networks have given rise to applications of this framework beyond the scope of biochemistry. Recently, reaction networks have been suggested as an alternative way to model social phenomena. In this "socio-chemical metaphor" molecular species play the role of agents' decisions and their outcomes, and chemical reactions play the role of interactions among these decisions. From here, it is possible to study the dynamical properties of social systems using standard tools of biochemical modelling. In this work we show how to use reaction networks to model systems that are usually studied via evolutionary game theory. We first illustrate our framework by modeling the repeated prisoners' dilemma. The model is built from the payoff matrix together with assumptions of the agents' memory and recognizability capacities. The model provides consistent results concerning the performance of the agents, and allows for the examination of the steady states of the system in a simple manner. We further develop a model considering the interaction among Tit for Tat and Defector agents. We produce analytical results concerning the performance of the strategies in different situations of agents' memory and recognizability. This approach unites two important theories and may produce new insights in classical problems such as the evolution of cooperation in large scale systems.

Revealing the hierarchical structure of microbial communities.

Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future.

A dynamical model of the spindle position checkpoint.

The orientation of the mitotic spindle with respect to the polarity axis is crucial for the accuracy of asymmetric cell division. In budding yeast, a surveillance mechanism called the spindle position checkpoint (SPOC) prevents exit from mitosis when the mitotic spindle fails to align along the mother-to-daughter polarity axis. SPOC arrest relies upon inhibition of the GTPase Tem1 by the GTPase-activating protein (GAP) complex Bfa1-Bub2. Importantly, reactions signaling mitotic exit take place at yeast centrosomes (named spindle pole bodies, SPBs) and the GAP complex also promotes SPB localization of Tem1. Yet, whether the regulation of Tem1 by Bfa1-Bub2 takes place only at the SPBs remains elusive. Here, we present a quantitative analysis of Bfa1-Bub2 and Tem1 localization at the SPBs. Based on the measured SPB-bound protein levels, we introduce a dynamical model of the SPOC that describes the regulation of Bfa1 and Tem1. Our model suggests that Bfa1 interacts with Tem1 in the cytoplasm as well as at the SPBs to provide efficient Tem1 inhibition.

Computing all persistent subspaces of a reaction-diffusion system.

An algorithm is presented for computing a reaction-diffusion partial differential equation (PDE) system for all possible subspaces that can hold a persistent solution of the equation. For this, all possible sub-networks of the underlying reaction network that are distributed organizations (DOs) are identified. Recently it has been shown that a persistent subspace must be a DO. The algorithm computes the hierarchy of DOs starting from the largest by a linear programming approach using integer cuts. The underlying constraints use elementary reaction closures as minimal building blocks to guarantee local closedness and global self-maintenance, required for a DO. Additionally, the algorithm delivers for each subspace an affiliated set of organizational reactions and minimal compartmentalization that is necessary for this subspace to persist. It is proved that all sets of organizational reactions of a reaction network, as already DOs, form a lattice. This lattice contains all potentially persistent sets of reactions of all constrained solutions of reaction-diffusion PDEs. This provides a hierarchical structure of all persistent subspaces with regard to the species and also to the reactions of the reaction-diffusion PDE system. Here, the algorithm is described and the corresponding Python source code is provided. Furthermore, an analysis of its run time is performed and all models from the BioModels database as well as further examples are examined. Apart from the practical implications of the algorithm the results also give insights into the complexity of solving reaction-diffusion PDEs.

Cells as semantic systems.

BACKGROUND: We consider cells as biological systems that process information by means of molecular codes. Many studies analyze cellular information processing exclusively in syntactic terms (e.g., by measuring Shannon entropy of sets of macromolecules), and abstract completely from semantic aspects that are related to the meaning of molecular information. METHODS: This mini-review focuses on semantic aspects of molecular information, particularly on codes that organize the semantic dimension of molecular information. First, a general conceptual framework for describing molecular information is proposed. Second, some examples of molecular codes are presented. Third, a mathematical approach that makes the identification of molecular codes in reaction networks possible, is developed. RESULTS: By combining a systematic conceptual framework for describing molecular information and a mathematical approach to identify molecular codes, it is possible to give a formally consistent and empirically adequate model of the code-based semantics of molecular information in cells. GENERAL SIGNIFICANCE: Research on the semantics of molecular information is of great importance particularly to systems biology since molecular codes embedded in systems of interrelated codes govern main traits of cells. Describing cells as semantic systems may thus trigger new experiments and generate new insights into the fundamental processes of cellular information processing. This article is part of a Special Issue entitled Systems Biology of Microorganisms.

Multiple-dose pharmacokinetics of daptomycin during continuous venovenous haemodiafiltration.

OBJECTIVES: Daptomycin is bactericidal against Gram-positive bacteria, with peak-dependent effect but trough-dependent toxicity. This study was performed to develop dosing recommendations in continuous venovenous haemodiafiltration (CVVHDF). PATIENTS AND METHODS: Nine critically ill patients in intensive care units of the Medical University Hospital of Vienna, requiring CVVHDF due to acute renal failure and antimicrobial treatment, were included. Blood and effluent samples were collected over 72 h to determine daptomycin concentrations by HPLC. Pharmacokinetic parameters were based on 10 sampling timepoints during the first 24 h, and peak and trough samples thereafter. An open two-compartment model was fitted to each subject's plasma concentration-time data. Simulations of serum concentration-time profiles after different doses and intervals were performed using ADAPT 5. RESULTS: Peak plasma concentrations with 6 mg/kg daptomycin were 62.2 ± 16.2, 66.1 ± 17.3 and 78.5 ± 22.1 mg/L on days 1, 2 and 3, respectively. The total clearance was 6.1 ± 4.9 mL/min, and the elimination half-life was 17.8 ± 9.7 h. Daptomycin was filtrated and could therefore be measured in the effluent. Protein binding was lower than that seen in healthy volunteers. The unbound fraction was 16 ± 4.5%. All subjects maintained trough serum concentrations above 4 mg/L, at which relevant pathogens are considered daptomycin-susceptible. Accumulation resulted when daptomycin was given every 24 h. Simulation of 8 mg/kg daptomycin given every 48 h resulted in adequate levels without accumulation. CONCLUSIONS: We recommend 8 mg/kg daptomycin every 48 h in patients on CVVHDF and therapeutic drug monitoring, if possible.

Human pharmacokinetics of intravenous recombinant human Cu/Zn superoxide dismutase.

OBJECTIVE: Oxidative stress plays an important role in human disease, but antioxidant therapies are limited. Under physiological conditions superoxide is controlled by the enzyme superoxide dismutase. A recombinant human Cu/Zn superoxide dismutase (rhSOD) might open new therapeutic possibilities. METHODS: Safety profile and pharmacokinetics in plasma and urine were assessed in an open label phase I study with dose-escalation. 18 healthy male volunteers received a single intravenous 10-minute infusion of 150, 300, or 600 mg rhSOD, respectively (n = 6 per dose group). RESULTS: rhSOD was well tolerated. Peak plasma concentrations (cmax; mean ± SD) were reached at the end of infusion, with 32.96 ± 10.31, 51.60 ± 8.23, and 103.90 ± 19.02 µg/ ml, respectively. Non-compartmental halflife was 1.06 ± 0.37, 1.59 ± 0.64, and 1.63 ± 0.28 hours. Urinary excretion (10 h) showed dose-dependent relative increases with 11.28 ± 6.46 (7.5%), 54.93 ± 15.25 (18.3%), and 191.81 ± 104.60 mg (32.0%). CONCLUSIONS: Our results show a good safety profile and predictable pharmacokinetics of rhSOD, suggesting that therapeutic exploratory studies might be safely conducted in humans.

The Concilium of Information Processing Networks of Chemical Oscillators for Determining Drug Response in Patients With Multiple Myeloma.

It can be expected that medical treatments in the future will be individually tailored for each patient. Here we present a step towards personally addressed drug therapy. We consider multiple myeloma treatment with drugs: bortezomib and dexamethasone. It has been observed that these drugs are effective for some patients and do not help others. We describe a network of chemical oscillators that can help to differentiate between non-responsive and responsive patients. In our numerical simulations, we consider a network of 3 interacting oscillators described with the Oregonator model. The input information is the gene expression value for one of 15 genes measured for patients with multiple myeloma. The single-gene networks optimized on a training set containing outcomes of 239 therapies, 169 using bortezomib and 70 using dexamethasone, show up to 71% accuracy in differentiating between non-responsive and responsive patients. If the results of single-gene networks are combined into the concilium with the majority voting strategy, then the accuracy of predicting the patient's response to the therapy increases to ∼ 85%.

High extracellular levels of cefpirome in unaffected and infected lung tissue of patients.

OBJECTIVES: the objective of the present investigation was to measure the extracellular concentrations of cefpirome in unaffected and infected lung tissue of septic patients. METHODS: a single intravenous dose of 30 mg/kg total body weight of cefpirome was administered to eight patients every 12 h prior to insertion of microdialysis probes into lung tissue. RESULTS: the median (minimum, maximum) peak concentration (C(max)), time to C(max) (T(max)), area under the concentration-time curve from 0 to 4 h (AUC(0-4)) and AUC(0-∞) of unbound cefpirome for unaffected lung were 48 (32, 107) mg/L, 0.83 (0.17, 3.17) h, 117 (60, 177) mg ·â€Šh/L and 182 (80, 382) mg ·â€Šh/L, respectively. The corresponding values for infected lung tissue were 45 (6, 122) mg/L, 1.17 (0.83, 2.83) h, 92 (17, 253) mg ·â€Šh/L and 206 (49, 379) mg ·â€Šh/L, respectively. The median apparent terminal elimination half-lives (t(½z)) of cefpirome were 2.61, 3.05 and 3.39 h for plasma, unaffected lung and infected lung, respectively. The median ratios of the AUC(0)(-∞) for lung to the AUC(0)(-∞) for plasma were 0.63 (0.19, 1.55) and 0.46 (0.32, 0.98) for unaffected and infected lung, respectively. CONCLUSIONS: we provide strong evidence that cefpirome penetrates effectively into the extracellular space fluid of lung tissue. Under steady-state conditions, the median concentrations of cefpirome in plasma, unaffected lung and infected lung exceeded the MICs of the majority of relevant bacteria over the entire dosing interval of up to 12 h after intravenous administration of a dose of 30 mg/kg total body weight.

A parallel algorithm to compute chemical organizations in biological networks.

SUMMARY: Analysing genome-scale in silico models with stoichiometry-based methods is computationally demanding. The current algorithms to compute chemical organizations in chemical reaction networks are limited to small-scale networks, prohibiting a thorough analysis of large models. Here, we introduce a parallelized version of the constructive algorithm to determine chemical organizations. The algorithm is implemented in the Standard C programming language and parallelized using the message passing interface (MPI) protocol. The resulting code can be executed on computer clusters making use of an arbitrary number of processors. The algorithm is parallelized in an embarrassing parallel manner, providing good scalability. AVAILABILITY: An implementation of the algorithm including source code can be obtained from http://www.minet.uni-jena.de/csb/prj/ot/tools

Rule-based spatial modeling with diffusing, geometrically constrained molecules.

BACKGROUND: We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. RESULTS: Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. CONCLUSIONS: We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Extracellular concentrations of fosfomycin in lung tissue of septic patients.

OBJECTIVES: The present investigation explored the ability of fosfomycin to penetrate lung tissue of septic patients by utilizing the microdialysis technique. METHODS: After microdialysis probe insertion into healthy and infected lung tissue, a single intravenous dose of 4 g of fosfomycin was administered. RESULTS: The mean C(max), T(max), AUC(0-4) and AUC(0-infinity) for healthy lung were 131.6 +/- 110.6 mg/L, 1.1 +/- 0.4 h, 242.4 +/- 101.6 mgxh/L and 367.6 +/- 111.9 mgxh/L, respectively. The corresponding values for infected lung were 107.5 +/- 60.2 mg/L, 1.4 +/- 0.5 h, 203.5 +/- 118.4 mgxh/L and 315.1 +/- 151.2 mgxh/L. The half-life of fosfomycin ranged from 2.2 to 2.7 h between compartments. The magnitude of lung tissue penetration, as determined by the ratios of the AUC(0-infinity) for lung to the AUC(0-infinity) for plasma, was 0.63 +/- 0.31 and 0.53 +/- 0.31 for healthy and infected lung, respectively. CONCLUSIONS: We conclude that fosfomycin achieves antimicrobially effective concentrations in infected lung tissue.

Using chemical organization theory for model checking.

MOTIVATION: The increasing number and complexity of biomodels makes automatic procedures for checking the models' properties and quality necessary. Approaches like elementary mode analysis, flux balance analysis, deficiency analysis and chemical organization theory (OT) require only the stoichiometric structure of the reaction network for derivation of valuable information. In formalisms like Systems Biology Markup Language (SBML), however, information about the stoichiometric coefficients required for an analysis of chemical organizations can be hidden in kinetic laws. RESULTS: First, we introduce an algorithm that uncovers stoichiometric information that might be hidden in the kinetic laws of a reaction network. This allows us to apply OT to SBML models using modifiers. Second, using the new algorithm, we performed a large-scale analysis of the 185 models contained in the manually curated BioModels Database. We found that for 41 models (22%) the set of organizations changes when modifiers are considered correctly. We discuss one of these models in detail (BIOMD149, a combined model of the ERK- and Wnt-signaling pathways), whose set of organizations drastically changes when modifiers are considered. Third, we found inconsistencies in 5 models (3%) and identified their characteristics. Compared with flux-based methods, OT is able to identify those species and reactions more accurately [in 26 cases (14%)] that can be present in a long-term simulation of the model. We conclude that our approach is a valuable tool that helps to improve the consistency of biomodels and their repositories. AVAILABILITY: All data and a JAVA applet to check SBML-models is available from http://www.minet.uni-jena.de/csb/prj/ot/tools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Developmental robustness by obligate interaction of class B floral homeotic genes and proteins.

DEF-like and GLO-like class B floral homeotic genes encode closely related MADS-domain transcription factors that act as developmental switches involved in specifying the identity of petals and stamens during flower development. Class B gene function requires transcriptional upregulation by an autoregulatory loop that depends on obligate heterodimerization of DEF-like and GLO-like proteins. Because switch-like behavior of gene expression can be displayed by single genes already, the functional relevance of this complex circuitry has remained enigmatic. On the basis of a stochastic in silico model of class B gene and protein interactions, we suggest that obligate heterodimerization of class B floral homeotic proteins is not simply the result of neutral drift but enhanced the robustness of cell-fate organ identity decisions in the presence of stochastic noise. This finding strongly corroborates the view that the appearance of this regulatory mechanism during angiosperm phylogeny led to a canalization of flower development and evolution.