Kinetic Uncertainty Relations for the Control of Stochastic Reaction Networks.

Nonequilibrium stochastic reaction networks are commonly found in both biological and nonbiological systems, but have remained hard to analyze because small differences in rate functions or topology can change the dynamics drastically. Here, we conjecture exact quantitative inequalities that relate the extent of fluctuations in connected components, for various network topologies. Specifically, we find that regardless of how two components affect each other's production rates, it is impossible to suppress fluctuations below the uncontrolled equivalents for both components: one must increase its fluctuations for the other to be suppressed. For systems in which components control each other in ringlike structures, it appears that fluctuations can only be suppressed in one component if all other components instead increase fluctuations, compared to the case without control. Even the general N-component system-with arbitrary connections and parameters-must have at least one component with increased fluctuations to reduce fluctuations in others. In connected reaction networks it thus appears impossible to reduce the statistical uncertainty in all components, regardless of the control mechanisms or energy dissipation

Constraints on Fluctuations in Sparsely Characterized Biological Systems.

Biochemical processes are inherently stochastic, creating molecular fluctuations in otherwise identical cells. Such "noise" is widespread but has proven difficult to analyze because most systems are sparsely characterized at the single cell level and because nonlinear stochastic models are analytically intractable. Here, we exactly relate average abundances, lifetimes, step sizes, and covariances for any pair of components in complex stochastic reaction systems even when the dynamics of other components are left unspecified. Using basic mathematical inequalities, we then establish bounds for whole classes of systems. These bounds highlight fundamental trade-offs that show how efficient assembly processes must invariably exhibit large fluctuations in subunit levels and how eliminating fluctuations in one cellular component requires creating heterogeneity in another.The work was supported by grant 1137676 from the Division of Mathematical Sciences at the National Science Foundation, and grant GM081563 from the National Institutes of Health.This is the final version of the article. It first appeared from the American Physical Society via http://dx.doi.org/10.1103/PhysRevLett.116.05810

Thrombostatin Fm19 ‐ A Thrombin Receptor Activation Antagonist

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106110/1/jth01272.pd

Acculturation, Body Mass Index, Waist Circumference, and Physical Activity in Mexican Origin Women

Purpose: Longer time in the United States (US) is associated with increased risk of obesity in Hispanic immigrants, particularly for women. Although previous research has established an association between nutrition and acculturation, little attention has focused on physical activity. In this study, we examine the associations between acculturation on Mexican origin women’s body mass index (BMI), waist circumference (WC), and report of moderate to vigorous physical activity (MVPA). Method: Mexican origin women ≥18 years (n=120) from South Carolina (n=60) and Texas Lower Rio Grande Valley (n=60) completed a survey and anthropometric measures. Participants reported MVPA in hours per week, country of birth, age at migration (\u3c16\u3eyears, 16-25 years, and ≥26 years), and language use. Using these latter two as indicators of acculturation, we evaluated associations between acculturation and BMI, WC, and MVPA. Results: Age standardized means for BMI indicated lowest BMI and waist circumference measures among women either with middle-range English language proficiency or who had immigrated to the US between the ages of 16-25; however, the relationship with BMI was more robust. Age standardized means for MVPA show that women who migrated at younger ages (\u3c16\u3eyears) had the lowest MVPA levels, followed by those migrating as younger adults (16-25 years), then adults (≥26 years). Similarly, women with lowest English proficiency levels had the lowest reported MVPA and those with highest English proficiency had highest reported MVPA. Conclusions: The relationship between acculturation and obesity and MVPA is multifaceted. While the relationship between MVPA and the two indicators of acculturation appear to be linear, the direction of association varied by acculturation indicator. Moreover, the association with acculturation indicators and measures of obesity was not linear. The findings from this study have implications in how researchers interpret the relationship between acculturation, obesity and obesity risk factors

Amino Acid Ester Prodrugs of Floxuridine: Synthesis and Effects of Structure, Stereochemistry, and Site of Esterification on the Rate of Hydrolysis

Purpose . To synthesize amino acid ester prodrugs of floxuridine (FUdR) and to investigate the effects of structure, stereochemistry, and site of esterification of promoiety on the rates of hydrolysis of these prodrugs in Caco-2 cell homogenates.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41502/1/11095_2004_Article_471011.pd

The interplay of intrinsic and extrinsic bounded noises in genetic networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: $(i)$ the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, $(ii)$ a model of enzymatic futile cycle and $(iii)$ a genetic toggle switch. In $(ii)$ and $(iii)$ we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

Scanning micro-X-ray fluorescence elemental mapping : a new tool for the study of laminated sediment records

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 9 (2008): Q02016, doi:10.1029/2007GC001800.The utility of elemental mapping by scanning X-ray fluorescence (XRF) in the study of annual laminated sedimentary records was investigated on eight annually laminated sediment types. The examples were chosen to illustrate the potential of this approach in environments dominated by terrigenous, biological and chemical deposition. Individual laminae were identifiable in elemental maps of all sediment types and were enhanced through the use of data reduction techniques (e.g., principal components transformation). Laminae were least apparent in clastic dominated systems with no seasonal changes in sediment sources. In biologically dominated systems, element maps provided insights into the composition of the varve subcomponents, related to alternating terrigenous and biologically dominated seasonal periods of deposition. Chemically precipitated structures were more prevalent than expected from visual investigations alone and may provide an underutilized paleoenvironmental signature of changing limnological conditions. Elemental mapping offers a valuable tool for the study of laminated records that complements existing techniques (e.g., SEM, digital image analysis).Funding was provided through NSF Earth System History grants and an NSF Instrumentation grant awarded to J.T.O

A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.

As modeling becomes a more widespread practice in the life sciences and biomedical sciences, researchers need reliable tools to calibrate models against ever more complex and detailed data. Here we present an approximate Bayesian computation (ABC) framework and software environment, ABC-SysBio, which is a Python package that runs on Linux and Mac OS X systems and that enables parameter estimation and model selection in the Bayesian formalism by using sequential Monte Carlo (SMC) approaches. We outline the underlying rationale, discuss the computational and practical issues and provide detailed guidance as to how the important tasks of parameter inference and model selection can be performed in practice. Unlike other available packages, ABC-SysBio is highly suited for investigating, in particular, the challenging problem of fitting stochastic models to data. In order to demonstrate the use of ABC-SysBio, in this protocol we postulate the existence of an imaginary reaction network composed of seven interrelated biological reactions (involving a specific mRNA, the protein it encodes and a post-translationally modified version of the protein), a network that is defined by two files containing 'observed' data that we provide as supplementary information. In the first part of the PROCEDURE, ABC-SysBio is used to infer the parameters of this system, whereas in the second part we use ABC-SysBio's relevant functionality to discriminate between two different reaction network models, one of them being the 'true' one. Although computationally expensive, the additional insights gained in the Bayesian formalism more than make up for this cost, especially in complex problems

Cell-Cycle Dependence of Transcription Dominates Noise in Gene Expression

The large variability in mRNA and protein levels found from both static and dynamic measurements in single cells has been largely attributed to random periods of transcription, often occurring in bursts. The cell cycle has a pronounced global role in affecting transcriptional and translational output, but how this influences transcriptional statistics from noisy promoters is unknown and generally ignored by current stochastic models. Here we show that variable transcription from the synthetic tetO promoter in S. cerevisiae is dominated by its dependence on the cell cycle. Real-time measurements of fluorescent protein at high expression levels indicate tetO promoters increase transcription rate ~2-fold in S/G2/M similar to constitutive genes. At low expression levels, where tetO promoters are thought to generate infrequent bursts of transcription, we observe random pulses of expression restricted to S/G2/M, which are correlated between homologous promoters present in the same cell. The analysis of static, single-cell mRNA measurements at different points along the cell cycle corroborates these findings. Our results demonstrate that highly variable mRNA distributions in yeast are not solely the result of randomly switching between periods of active and inactive gene expression, but instead largely driven by differences in transcriptional activity between G1 and S/G2/M.GM095733BBBE 103316MIT Startup Fun