Mercury contaminated sediment sites-an evaluation of remedial options

Mercury (Hg) is a naturally-occurring element that is ubiquitous in the aquatic environment. Though efforts have been made in recent years to decrease Hg emissions, historically-emitted Hg can be retained in the sediments of aquatic bodies where they may be slowly converted to methylmercury (MeHg). Consequently, Hg in historically-contaminated sediments can result in high levels of significant exposure for aquatic species, wildlife and human populations consuming fish. Even if source control of contaminated wastewater is achievable, it may take a very long time, perhaps decades, for Hg-contaminated aquatic systems to reach relatively safe Hg levels in both water and surface sediment naturally. It may take even longer if Hg is present at higher concentration levels in deep sediment. Hg contaminated sediment results from previous releases or ongoing contributions from sources that are difficult to identify. Due to human activities or physical, chemical, or biological processes (e.g. hydrodynamic flows, bioturbation, molecular diffusion, and chemical transformation), the buried Hg can be remobilized into the overlying water. Hg speciation in the water column and sediments critically affect the reactivity (i.e. conversion of inorganic Hg(II) to MeHg), transport, and its exposure to living organisms. Also, geochemical conditions affect the activity of methylating bacteria and its availability for methylation. This review paper discusses remedial considerations (e.g. key chemical factors in fate and transport of Hg, source characterization and control, environmental management procedures, remediation options, modeling tools) and includes practical case studies for cleaning up Hg-contaminated sediment sites.

Modeling the regional spread and control of vancomycin-resistant enterococci

BACKGROUND

Because patients can remain colonized with vancomycin-resistant enterococci (VRE) for long periods of time, VRE may spread from one health care facility to another.

METHODS

Using the Regional Healthcare Ecosystem Analyst, an agent-based model of patient flow among all Orange County, California, hospitals and communities, we quantified the degree and speed at which changes in VRE colonization prevalence in a hospital may affect prevalence in other Orange County hospitals.

RESULTS

A sustained 10% increase in VRE colonization prevalence in any 1 hospital caused a 2.8% (none to 62%) average relative increase in VRE prevalence in all other hospitals. Effects took from 1.5 to >10 years to fully manifest. Larger hospitals tended to have greater affect on other hospitals.

CONCLUSIONS

When monitoring and controlling VRE, decision makers may want to account for regional effects. Knowing a hospital's connections with other health care facilities via patient sharing can help determine which hospitals to include in a surveillance or control program.

Exploration of the spatial-Composite Risk Index (CRI) for the characterization of toxicokinetics in petrochemical active areas

The spatial modeling of the petrochemical active regions in the Niger Delta (ND), Nigeria was carried out through the analysis exploration and extraction of geospatial data and resultant risk maps were generated. The pollutants assessed include; heavy metals, polychlorinated aromatic hydrocarbons (PAHs), benzene-toluene-ethylene-xylene (BTEX), and total petroleum hydrocarbons (TPHs) and properties of the pollutants such as bioaccumulation, persistence and toxicity were used to calculate the Hazard Index (HI) and thus created a ranking system. The Composite Risk Index (CRI) was developed successively considering the concentrations of all pollutants and the computed HI using the samples collected in ND areas of Nigeria. The carcinogenic PAHs showed spatial abundance in the areas sampled and elevated levels of soil heavy metals were also observed. In this study, mathematical tool such as the artificial neural network (ANN) self-organizing map (SOM) and geostatistical analysis such as kriging were applied to develop the risk map of the areas which represent the spatial spread of the CRI. The results show that the application of spatially developed integral risk map for pollutant assessment is effective and facilitates with decision making with regards the environment and humans exposed in this region.

Microbially enhanced dissolution and reductive dechlorination of PCE by a mixed culture: model validation and sensitivity analysis

Reductive dechlorination catalyzed by organohalide-respiring bacteria is often considered for remediation of non-aqueous phase liquid (NAPL) source zones due to cost savings, ease of implementation, regulatory acceptance, and sustainability. Despite knowledge of the key dechlorinators, an understanding of the processes and factors that control NAPL dissolution rates and detoxification (i.e., ethene formation) is lacking. A recent column study demonstrated a 5-fold cumulative enhancement in tetrachloroethene (PCE) dissolution and ethene formation (Amos et al., 2009). Spatial and temporal monitoring of key geochemical and microbial (i.e., Geobacter lovleyi and Dehalococcoides mccartyi strains) parameters in the column generated a data set used herein as the basis for refinement and testing of a multiphase, compositional transport model. The refined model is capable of simulating the reactive transport of multiple chemical constituents produced and consumed by organohalide-respiring bacteria and accounts for substrate limitations and competitive inhibition. Parameter estimation techniques were used to optimize the values of sensitive microbial kinetic parameters, including maximum utilization rates, biomass yield coefficients, and endogenous decay rates. Comparison and calibration of model simulations with the experimental data demonstrate that the model is able to accurately reproduce measured effluent concentrations, while delineating trends in dechlorinator growth and reductive dechlorination kinetics along the column. Sensitivity analyses performed on the optimized model parameters indicate that the rates of PCE and cis-1,2-dichloroethene (cis-DCE) transformation and Dehalococcoides growth govern bioenhanced dissolution, as long as electron donor (i.e., hydrogen flux) is not limiting. Dissolution enhancements were shown to be independent of cis-DCE accumulation; however, accumulation of cis-DCE, as well as column length and flow rate (i.e., column residence time), strongly influenced the extent of reductive dechlorination. When cis-DCE inhibition was neglected, the model over-predicted ethene production ten-fold, while reductions in residence time (i.e., a two-fold decrease in column length or two-fold increase in flow rate) resulted in a more than 70% decline in ethene production. These results suggest that spatial and temporal variations in microbial community composition and activity must be understood to model, predict, and manage bioenhanced NAPL dissolution.

Force-driven aggregation of specific bonds on compliant substrates

A thermodynamic model was employed to understand the underlying physics of the force-dependent size of cell's focal adhesions. The model describes the specific adhesion of an elastic membrane to a compliant substrate such that the adhesion site is subjected to the force of a constant pulling traction. The membrane contains mobile adhesion receptors with specific energetic affinities for complimentary ligands on the substrate. The adhesion is resisted by a disjoining pressure induced by a squeezed layer of glycocalyx. The model demonstrates that the enlargement of adhesion area with increasing pulling traction is possible due to a spontaneous response of the adhesion site to attain the state of minimum free energy. The correlation between the force and the adhesion area strongly depends on the rigidity of the substrate.

The molecular basis for the inhibition of phosphodiesterase-4D by three natural resveratrol analogs. Isolation, molecular docking, molecular dynamics simulations, binding free energy, and bioassay

The phosphodiesterase-4 (PDE4) enzyme is a promising therapeutic target for several diseases. Our previous studies found resveratrol and moracin M to be natural PDE4 inhibitors. In the present study, three natural resveratrol analogs [pterostilbene, (E)-2',3,5',5-tetrahydroxystilbene (THSB), and oxyresveratrol] are structurally related to resveratrol and moracin M, but their inhibition and mechanism against PDE4 are still unclear. A combined method consisting of molecular docking, molecular dynamics (MD) simulations, binding free energy, and bioassay was performed to better understand their inhibitory mechanism. The binding pattern of pterostilbene demonstrates that it involves hydrophobic/aromatic interactions with Phe340 and Phe372, and forms hydrogen bond(s) with His160 and Gln369 in the active site pocket. The present work also reveals that oxyresveratrol and THSB can bind to PDE4D and exhibits less negative predicted binding free energies than pterostilbene, which was qualitatively validated by bioassay (IC50=96.6, 36.1, and 27.0μM, respectively). Additionally, a linear correlation (R(2)=0.953) is achieved for five PDE4D/ligand complexes between the predicted binding free energies and the experimental counterparts approximately estimated from their IC50 values (≈RT ln IC50). Our results imply that hydrophobic/aromatic forces are the primary factors in explaining the mechanism of inhibition by the three products. Results of the study help to understand the inhibitory mechanism of the three natural products, and thus help the discovery of novel PDE4 inhibitors from resveratrol, moracin M, and other natural products.

A synthetic biology approach to the development of transcriptional regulatory models and custom enhancer design

Synthetic biology offers novel opportunities for elucidating transcriptional regulatory mechanisms and enhancer logic. Complex cis-regulatory sequences--like the ones driving expression of the Drosophila even-skipped gene--have proven difficult to design from existing knowledge, presumably due to the large number of protein-protein interactions needed to drive the correct expression patterns of genes in multicellular organisms. This work discusses two novel computational methods for the custom design of enhancers that employ a sophisticated, empirically validated transcriptional model, optimization algorithms, and synthetic biology. These synthetic elements have both utilitarian and academic value, including improving existing regulatory models as well as evolutionary questions. The first method involves the use of simulated annealing to explore the sequence space for synthetic enhancers whose expression output fit a given search criterion. The second method uses a novel optimization algorithm to find functionally accessible pathways between two enhancer sequences. These paths describe a set of mutations wherein the predicted expression pattern does not significantly vary at any point along the path. Both methods rely on a predictive mathematical framework that maps the enhancer sequence space to functional output.

Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation

It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation.

Highly time-variable exposure to chemicals--toward an assessment strategy

Organisms in the environment experience fluctuating, pulsed, or intermittent exposure to pollutants. Accounting for effects of such exposures is an important challenge for environmental risk assessment, particularly given the simplified design of standard ecotoxicity tests. Dynamic simulation using toxicokinetic-toxicodynamic (TK-TD) models describes the processes that link exposure with effects in an organism and provides a basis for extrapolation to a range of exposure scenarios. In so doing, TK-TD modeling makes the risk assessment more robust and aids use and interpretation of experimental data. Toxicokinetic-toxicodynamic models are well-developed for predicting survival of individual organisms and are increasingly applied to sublethal endpoints. In the latter case particularly, linkage to individual-based models (IBMs) allows extrapolation to population level as well as accounting for differences in effects of toxicant exposure at different stages in the life cycle. Extrapolation between species remains an important constraint because there is currently no systematic understanding of species traits that cause differences in the relevant processes. Toxicokinetic-toxicodynamic models allow interrogation of exposure profiles to determine intrinsic toxicity potential rather than using absolute maximum concentrations or time-weighted averages as surrogates. A decision scheme is proposed to guide selection of risk assessment approaches using dose extrapolation based on Haber's Law, TK-TD models, and/or IBMs depending on the nature of toxic effect and timing in relation to life history.

Modeling the coupled extracellular and intracellular environments in mammalian cell culture

The regulation of metabolism in mammalian cell culture is closely linked to the process of apoptosis-programmed cell death. Apoptosis negatively impacts culture viability, product yield, and quality. An improved understanding of the interaction between apoptosis and metabolism will give rise to better control over the culture process, and thus improvements in product yield. This study presents a mathematical model that describes both the metabolic fluxes involving the extracellular metabolites and the progression of apoptosis in terms of intracellular caspases, and thus highlights the interactions between these two processes. The model is trained and validated against experimental observations of Chinese Hamster Ovary cell culture producing monoclonal antibody. Importantly, the model describes the continued production of monoclonal antibody in post exponential phase by incorporating different rates of antibody production for separate sub-populations within the culture. A parameter estimability test was applied on the combined model to assess the confidence in parameter estimates.

Herpes simplex virus type 2 cross-sectional seroprevalence and the estimated rate of neonatal infections among a cohort of rural Malawian female adolescents

OBJECTIVE

To assess herpes simplex virus type 2 (HSV-2) seroprevalence among rural Malawian adolescent women and estimate the number of neonatal herpes infections among infants of these adolescents.

METHODS

A longitudinal cohort study of adolescents (14-16 years at entry) residing in rural Malawi was initiated in 2007 with annual observation. HSV-2 testing was introduced in 2010. In this study, we (1) determined, using cross-sectional analysis, risk factors for positive serostatus, (2) adjusted for non-response bias with imputation methods and (3) estimated the incidence of neonatal herpes infection using mathematical models.

RESULTS

A total of 1195 female adolescents (age 17-20 years) were interviewed in 2010, with an observed HSV-2 seroprevalence of 15.2% among the 955 women tested. From a multivariate analysis, risk factors for HSV-2 seropositivity include older age (p=0.037), moving from the baseline village (p=0.020) and report of sexual activity with increasing number of partners (p<0.021). Adjusting for non-response bias, the estimated HSV-2 seroprevalence among the total female cohort (composed of all women interviewed in 2007) was 18.0% (95% CI 16.0% to 20.2%). HSV-2 seropositivity was estimated to be 25.6% (95% CI 19.6% to 32.5%) for women who refused to provide a blood sample. The estimated number of neonatal herpes infections among the total female cohort was 71.8 (95% CI 57.3 to 86.3) per 100 000 live births.

CONCLUSIONS

The risk of HSV-2 seroconversion is high during adolescence, when childbearing is beginning, among rural Malawian women. Research on interventions to reduce horizontal and vertical HSV-2 transmission during adolescence in resource-limited settings is needed.

Dengue dynamics and vaccine cost-effectiveness in Brazil

Recent Phase 2b dengue vaccine trials have demonstrated the safety of the vaccine and estimated the vaccine efficacy with further trials underway. In anticipation of vaccine roll-out, cost-effectiveness analysis of potential vaccination policies that quantify the dynamics of disease transmission are fundamental to the optimal allocation of available doses. We developed a dengue transmission and vaccination model and calculated, for a range of vaccination costs and willingness-to-pay thresholds, the level of vaccination coverage necessary to sustain herd-immunity, the price at which vaccination is cost-effective and is cost-saving, and the sensitivity of our results to parameter uncertainty. We compared two vaccine efficacy scenarios, one a more optimistic scenario and another based on the recent lower-than-expected efficacy from the latest clinical trials. We found that herd-immunity may be achieved by vaccinating 82% (95% CI 58-100%) of the population at a vaccine efficacy of 70%. At this efficacy, vaccination may be cost-effective for vaccination costs up to US$ 534 (95% CI $369-1008) per vaccinated individual and cost-saving up to $204 (95% CI $39-678). At the latest clinical trial estimates of an average of 30% vaccine efficacy, vaccination may be cost-effective and cost-saving at costs of up to $237 (95% CI $159-512) and $93 (95% CI $15-368), respectively. Our model provides an assessment of the cost-effectiveness of dengue vaccination in Brazil and incorporates the effect of herd immunity into dengue vaccination cost-effectiveness. Our results demonstrate that at the relatively low vaccine efficacy from the recent Phase 2b dengue vaccine trials, age-targeted vaccination may still be cost-effective provided the total vaccination cost is sufficiently low.

On the simultaneous adsorption of a reactive dye and hexavalent chromium from aqueous solutions onto grafted chitosan

In the present work, the simultaneous adsorption of Remazol Red 3BS (reactive dye) and Cr(VI) onto chitosan powder grafted with poly(ethylene imine) and cross-linked with epichlorohydrin is experimentally studied. Such a combination of a dye molecule and a heavy metal can be found in real/practical conditions of environmental pollutants' removal, so their mutual interaction on the adsorption efficiencies is very important. The experimental data revealed a competitive type of interaction between the dye molecule and heavy metal ion. An attempt is made to quantitatively describe the data through appropriate isotherms and kinetic equations. The data demonstrated that the common thermodynamic equilibrium is not obtained for the present problem and the final composition of the adsorbed phase depends also on the kinetics. A new scenario of irreversible kinetic-based equilibrium was introduced and examined in detail. None of the scenarios considered here is fully able to cover the whole data, so semi-empirical equations are introduced for their description. It is shown that further development of phenomenological models requires more complicated experimental protocols than simple simultaneous adsorption of the species.

Enabling the use of hereditary information from pedigree tools in medical knowledge-based systems

The use of family information is a key issue to deal with inheritance illnesses. This kind of information use to come in the form of pedigree files, which contain structured information as tree or graphs, which explains the family relationships. Knowledge-based systems should incorporate the information gathered by pedigree tools to assess medical decision making. In this paper, we propose a method to achieve such a goal, which consists on the definition of new indicators, and methods and rules to compute them from family trees. The method is illustrated with several case studies. We provide information about its implementation and integration on a case-based reasoning tool. The method has been experimentally tested with breast cancer diagnosis data. The results show the feasibility of our methodology.

Structural and mechanical multi-scale characterization of white New-Zealand rabbit Achilles tendon

Multi-scale characterization of structures and mechanical behavior of biological tissues are of huge importance in order to evaluate the quality of a biological tissue and/or to provide bio-inspired scaffold for functional tissue engineering. Indeed, the more information on main biological tissue structures we get, the more relevant we will be to design new functional prostheses for regenerative medicine or to accurately evaluate tissues. From this perspective, we have investigated the structures and their mechanical properties from nanoscopic to macroscopic scale of fresh ex-vivo white New-Zealand rabbit Achilles tendon using second harmonic generation (SHG) microscopy, atomic force microscopy (AFM) and tensile tests to provide a "simple" model whose parameters are relevant of its micro or nano structure. Thus, collagen fiber's crimping was identified then measured from SHG images as a plane sine wave with 28.4 ± 5.8 μm of amplitude and 141 ± 41 μm of wavelength. Young's moduli of fibrils (3.0 GPa) and amorphous phases (223 MPa) were obtained using TH-AFM. From these investigations, a non-linear Zener model linking a statistical Weibull's distribution of taut fibers under traction to crimp fibers were developed. This model showed that for small strain (<0.1), the amorphous inter-fibrils phase in collagen fibers is more solicited than collagen fibrils themselves. The results open the way to modeled macroscopic mechanical behavior of aligned-crimped collagen soft tissues using multi-scale tendon observations under static or dynamic solicitations.

Vaccinomics, adversomics, and the immune response network theory: individualized vaccinology in the 21st century

Vaccines, like drugs and medical procedures, are increasingly amenable to individualization or personalization, often based on novel data resulting from high throughput "omics" technologies. As a result of these technologies, 21st century vaccinology will increasingly see the abandonment of a "one size fits all" approach to vaccine dosing and delivery, as well as the abandonment of the empiric "isolate-inactivate-inject" paradigm for vaccine development. In this review, we discuss the immune response network theory and its application to the new field of vaccinomics and adversomics, and illustrate how vaccinomics can lead to new vaccine candidates, new understandings of how vaccines stimulate immune responses, new biomarkers for vaccine response, and facilitate the understanding of what genetic and other factors might be responsible for rare side effects due to vaccines. Perhaps most exciting will be the ability, at a systems biology level, to integrate increasingly complex high throughput data into descriptive and predictive equations for immune responses to vaccines. Herein, we discuss the above with a view toward the future of vaccinology.

Analysis of HRCT-derived xylem network reveals reverse flow in some vessels

Long distance water and nutrient transport in plants is dependent on the proper functioning of xylem networks, a series of interconnected pipe-like cells that are vulnerable to hydraulic dysfunction as a result of drought-induced embolism and/or xylem-dwelling pathogens. Here, flow in xylem vessels was modeled to determine the role of vessel connectivity by using three dimensional xylem networks derived from High Resolution Computed Tomography (HRCT) images of grapevine (Vitis vinifera cv. 'Chardonnay') stems. Flow in 4-27% of the vessel segments (i.e. any section of vessel elements between connection points associated with intervessel pits) was found to be oriented in the direction opposite to the bulk flow under normal transpiration conditions. In order for the flow in a segment to be in the reverse direction, specific requirements were determined for the location of connections, distribution of vessel endings, diameters of the connected vessels, and the conductivity of the connections. Increasing connectivity and decreasing vessel length yielded increasing numbers of reverse flow segments until a maximum value was reached, after which more interconnected networks and smaller average vessel lengths yielded a decrease in the number of reverse flow segments. Xylem vessel relays also encouraged the formation of reverse flow segments. Based on the calculated flow rates in the xylem network, the downward spread of Xylella fastidiosa bacteria in grape stems was modeled, and reverse flow was shown to be an additional mechanism for the movement of bacteria to the trunk of grapevine.

[Geometrical growth models of the fetal forebrain, cerebellum, brainstem and change of the cranial base angles during fetal period]

INTRODUCTION

Brain growth plays likely an important role for the skull growth. In the fetus, there exists an heterochrony for the growth of supratentorial (forebrain) and infratentorial regions (brainstem and cerebellum). The aim of the study was thus to model geometrically the growth of these two regions and to compare it with the inflection of the base of skull.

MATERIAL AND METHODS

Brain growth measurements were performed from midsagittal photographs of fetal brains obtained from an Anatomical Atlas over a period from 10 to 40 amenorrhea weeks (AW). After countouring and pointing anatomical and geometrical landmarks, we have developed a linear growth model based on principal component analysis (PCA). Besides, the variation of the sphenoidal and clivo-foraminal angles was studied from anatomical midsagittal slices of fetal heads sampled over a period from 16 to 39 AW.

RESULTS

The PCA model brings to light the radial expansion of the forebrain growth (first component) associated with an inferior and posterior rotation of the occipital lobe. The growth of the infratentoriel region presents an inferior and posterior expansion associated with a second component corresponding to inferior and anterior expansions. From the 17 AW, appears an heterochrony between the supra- and infratentorial growths and an inversion of the ratio between the infra- and supratentorial dimensions after 30 AW. The sphenoidal and clivo-foraminal angles decrease slightly until 25 AW, and then increase quickly until the 39 AW.

CONCLUSIONS

The growth of brain is accompanied by morphological change between the compartments supra- and infratentoriel but also on the level of the base of skull. The possible interactions will be discussed.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Diagnosing Alzheimer's disease: a systematic review of economic evaluations

BACKGROUND

The objective of this study is to systematically review the literature on economic evaluations of interventions for the early diagnosis of Alzheimer's disease (AD) and related disorders and to describe their general and methodological characteristics. We focused on the diagnostic aspects of the decision models to assess the applicability of existing decision models for the evaluation of the recently revised diagnostic research criteria for AD.

METHODS

PubMed and the National Institute for Health Research Economic Evaluation database were searched for English-language publications related to economic evaluations on diagnostic technologies. Trial-based economic evaluations were assessed using the Consensus on Health Economic Criteria list. Modeling studies were assessed using the framework for quality assessment of decision-analytic models.

RESULTS

The search retrieved 2109 items, from which eight decision-analytic modeling studies and one trial-based economic evaluation met all eligibility criteria.

CONCLUSIONS

Diversity among the study objective and characteristics was considerable and, despite considerable methodological quality, several flaws were indicated. Recommendations were focused on diagnostic aspects and the applicability of existing models for the evaluation of recently revised diagnostic research criteria for AD.

Modeling of the MAPK machinery activation in response to various abiotic and biotic stresses in plants by a system biology approach

Mitogen-Activated Protein Kinases (MAPKs) cascade plays an important role in regulating plant growth and development, generating cellular responses to the extracellular stimuli. MAPKs cascade mainly consist of three sub-families i.e. mitogen-activated protein kinase kinase kinase (MAPKKK), mitogen-activated protein kinase kinase (MAPKK) and mitogen activated protein kinase (MAPK), several cascades of which are activated by various abiotic and biotic stresses. In this work we have modeled the holistic molecular mechanisms essential to MAPKs activation in response to several abiotic and biotic stresses through a system biology approach and performed its simulation studies. As extent of abiotic and biotic stresses goes on increasing, the process of cell division, cell growth and cell differentiation slow down in time dependent manner. The models developed depict the combinatorial and multicomponent signaling triggered in response to several abiotic and biotic factors. These models can be used to predict behavior of cells in event of various stresses depending on their time and exposure through activation of complex signaling cascades.

Thermal model to investigate the temperature in bone grinding for skull base neurosurgery

This study develops a thermal model utilizing the inverse heat transfer method (IHTM) to investigate the bone grinding temperature created by a spherical diamond tool used for skull base neurosurgery. Bone grinding is a critical procedure in the expanded endonasal approach to remove the cranial bone and access to the skull base tumor via nasal corridor. The heat is generated during grinding and could damage the nerve or coagulate the blood in the carotid artery adjacent to the bone. The finite element analysis is adopted to investigate the grinding-induced bone temperature rise. The heat source distribution is defined by the thermal model, and the temperature distribution is solved using the IHTM with experimental inputs. Grinding experiments were conducted on a bovine cortical bone with embedded thermocouples. Results show significant temperature rise in bone grinding. Using 50°C as the threshold, the thermal injury can propagate about 3mm in the traverse direction, and 3mm below the ground surface under the dry grinding condition. The presented methodology demonstrated the capability of being a thermal analysis tool for bone grinding study.

On the limitations of biological knowledge

Scientific knowledge is grounded in a particular epistemology and, owing to the requirements of that epistemology, possesses limitations. Some limitations are intrinsic, in the sense that they depend inherently on the nature of scientific knowledge; others are contingent, depending on the present state of knowledge, including technology. Understanding limitations facilitates scientific research because one can then recognize when one is confronted by a limitation, as opposed to simply being unable to solve a problem within the existing bounds of possibility. In the hope that the role of limiting factors can be brought more clearly into focus and discussed, we consider several sources of limitation as they apply to biological knowledge: mathematical complexity, experimental constraints, validation, knowledge discovery, and human intellectual capacity.

Rule-based modeling and simulations of the inner kinetochore structure

BACKGROUND

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins.

RESULTS

Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts.

CONCLUSIONS

Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores.

Genomically and biochemically accurate metabolic reconstruction of Methanosarcina barkeri Fusaro, iMG746

Methanosarcina barkeri is an Archaeon that produces methane anaerobically as the primary byproduct of its metabolism. M. barkeri can utilize several substrates for ATP and biomass production including methanol, acetate, methyl amines, and a combination of hydrogen and carbon dioxide. In 2006, a metabolic reconstruction of M. barkeri, iAF692, was generated based on a draft genome annotation. The iAF692 reconstruction enabled the first genome-Scale simulations for Archaea. Since the publication of the first metabolic reconstruction of M. barkeri, additional genomic, biochemical, and phenotypic data have clarified several metabolic pathways. We have used this newly available data to improve the M. barkeri metabolic reconstruction. Modeling simulations using the updated model, iMG746, have led to increased accuracy in predicting gene knockout phenotypes and simulations of batch growth behavior. We used the model to examine knockout lethality data and make predictions about metabolic regulation under different growth conditions. Thus, the updated metabolic reconstruction of M. barkeri metabolism is a useful tool for predicting cellular behavior, studying the methanogenic lifestyle, guiding experimental studies, and making predictions relevant to metabolic engineering applications.