Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Experimental and theoretical investigation of ligand effects on the synthesis of ZnO nanoparticles

ZnO nanoparticles with highly controllable particle sizes(less than 10 nm) were synthesized using organic capping ligands in Zn(Ac)2 ethanolic solution. The molecular structure of the ligands was found to have significant influence on the particle size. The multi-functional molecule tris(hydroxymethyl)-aminomethane (THMA) favoured smaller particle distributions compared with ligands possessing long hydrocarbon chains that are more frequently employed. The adsorption of capping ligands on ZnnOn crystal nuclei (where n = 4 or 18 molecular clusters of(0001) ZnO surfaces) was modelled by ab initio methods at the density functional theory (DFT) level. For the molecules examined, chemisorption proceeded via the formation of Zn...O, Zn...N, or Zn...S chemical bonds between the ligands and active Zn2+ sites on ZnO surfaces. The DFT results indicated that THMA binds more strongly to the ZnO surface than other ligands, suggesting that this molecule is very effective at stabilizing ZnO nanoparticle surfaces. This study, therefore, provides new insight into the correlation between the molecular structure of capping ligands and the morphology of metal oxide nanostructures formed in their presence

A systematic review of longitudinal studies on the association between depression and smoking in adolescents

<p>Abstract</p> <p>Background</p> <p>It is well-established that smoking and depression are associated in adolescents, but the temporal ordering of the association is subject to debate.</p> <p>Methods</p> <p>Longitudinal studies in English language which reported the onset of smoking on depression in non clinical populations (age 13-19) published between January 1990 and July 2008 were selected from PubMed, OVID, and PsychInfo databases. Study characteristics were extracted. Meta-analytic pooling procedures with random effects were used.</p> <p>Results</p> <p>Fifteen studies were retained for analysis. The pooled estimate for smoking predicting depression in 6 studies was 1.73 (95% CI: 1.32, 2.40; p < 0.001). The pooled estimate for depression predicting smoking in 12 studies was 1.41 (95% CI: 1.21, 1.63; p < 0.001). Studies that used clinical measures of depression were more likely to report a bidirectional effect, with a stronger effect of depression predicting smoking.</p> <p>Conclusion</p> <p>Evidence from longitudinal studies suggests that the association between smoking and depression is bidirectional. To better estimate these effects, future research should consider the potential utility of: (a) shorter intervals between surveys with longer follow-up time, (b) more accurate measurement of depression, and (c) adequate control of confounding.</p

The DNA glycosylase AlkD uses a non-base-flipping mechanism to excise bulky lesions

Threats to genomic integrity arising from DNA damage are mitigated by DNA glycosylases, which initiate the base excision repair pathway by locating and excising aberrant nucleobases. How these enzymes find small modifications within the genome is a current area of intensive research. A hallmark of these and other DNA repair enzymes is their use of base flipping to sequester modified nucleotides from the DNA helix and into an active site pocket. Consequently, base flipping is generally regarded as an essential aspect of lesion recognition and a necessary precursor to base excision. Here we present the first, to our knowledge, DNA glycosylase mechanism that does not require base flipping for either binding or catalysis. Using the DNA glycosylase AlkD from Bacillus cereus, we crystallographically monitored excision of an alkylpurine substrate as a function of time, and reconstructed the steps along the reaction coordinate through structures representing substrate, intermediate and product complexes. Instead of directly interacting with the damaged nucleobase, AlkD recognizes aberrant base pairs through interactions with the phosphoribose backbone, while the lesion remains stacked in the DNA duplex. Quantum mechanical calculations revealed that these contacts include catalytic charge-dipole and CH-π interactions that preferentially stabilize the transition state. We show in vitro and in vivo how this unique means of recognition and catalysis enables AlkD to repair large adducts formed by yatakemycin, a member of the duocarmycin family of antimicrobial natural products exploited in bacterial warfare and chemotherapeutic trials. Bulky adducts of this or any type are not excised by DNA glycosylases that use a traditional base-flipping mechanism. Hence, these findings represent a new model for DNA repair and provide insights into catalysis of base excision