Exciton bimolecular annihilation dynamics in supramolecular nanostructures of conjugated oligomers

We present femtosecond transient absorption measurements on $\pi$-conjugated supramolecular assemblies in a high pump fluence regime. Oligo(\emph{p}-phenylenevinylene) monofunctionalized with ureido-\emph{s}-triazine (MOPV) self-assembles into chiral stacks in dodecane solution below 75$^{\circ}$C at a concentration of $4\times 10^{-4}$ M. We observe exciton bimolecular annihilation in MOPV stacks at high excitation fluence, indicated by the fluence-dependent decay of $1^1$B$_{u}$-exciton spectral signatures, and by the sub-linear fluence dependence of time- and wavelength-integrated photoluminescence (PL) intensity. These two characteristics are much less pronounced in MOPV solution where the phase equilibrium is shifted significantly away from supramolecular assembly, slightly below the transition temperature. A mesoscopic rate-equation model is applied to extract the bimolecular annihilation rate constant from the excitation fluence dependence of transient absorption and PL signals. The results demonstrate that the bimolecular annihilation rate is very high with a square-root dependence in time. The exciton annihilation results from a combination of fast exciton diffusion and resonance energy transfer. The supramolecular nanostructures studied here have electronic properties that are intermediate between molecular aggregates and polymeric semiconductors

Dynamic Modelling under Uncertainty: The Case of Trypanosoma brucei Energy Metabolism

Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Glycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies

TLR9 ligation in pancreatic stellate cells promotes tumorigenesis

Modulation of Toll-like receptor (TLR) signaling can have protective or protumorigenic effects on oncogenesis depending on the cancer subtype and on specific inflammatory elements within the tumor milieu. We found that TLR9 is widely expressed early during the course of pancreatic transformation and that TLR9 ligands are ubiquitous within the tumor microenvironment. TLR9 ligation markedly accelerates oncogenesis, whereas TLR9 deletion is protective. We show that TLR9 activation has distinct effects on the epithelial, inflammatory, and fibrogenic cellular subsets in pancreatic carcinoma and plays a central role in cross talk between these compartments. Specifically, TLR9 activation can induce proinflammatory signaling in transformed epithelial cells, but does not elicit oncogene expression or cancer cell proliferation. Conversely, TLR9 ligation induces pancreatic stellate cells (PSCs) to become fibrogenic and secrete chemokines that promote epithelial cell proliferation. TLR9-activated PSCs mediate their protumorigenic effects on the epithelial compartment via CCL11. Additionally, TLR9 has immune-suppressive effects in the tumor microenvironment (TME) via induction of regulatory T cell recruitment and myeloid-derived suppressor cell proliferation. Collectively, our work shows that TLR9 has protumorigenic effects in pancreatic carcinoma which are distinct from its influence in extrapancreatic malignancies and from the mechanistic effects of other TLRs on pancreatic oncogenesis