Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy

The Tri-Trophic Interactions Hypothesis: Interactive Effects of Host Plant Quality, Diet Breadth and Natural Enemies on Herbivores

Several influential hypotheses in plant-herbivore and herbivore-predator interactions consider the interactive effects of plant quality, herbivore diet breadth, and predation on herbivore performance. Yet individually and collectively, these hypotheses fail to address the simultaneous influence of all three factors. Here we review existing hypotheses, and propose the tri-trophic interactions (TTI) hypothesis to consolidate and integrate their predictions. The TTI hypothesis predicts that dietary specialist herbivores (as compared to generalists) should escape predators and be competitively dominant due to faster growth rates, and that such differences should be greater on low quality (as compared to high quality) host plants. To provide a preliminary test of these predictions, we conducted an empirical study comparing the effects of plant (Baccharis salicifolia) quality and predators between a specialist (Uroleucon macolai) and a generalist (Aphis gossypii) aphid herbivore. Consistent with predictions, these three factors interactively determine herbivore performance in ways not addressed by existing hypotheses. Compared to the specialist, the generalist was less fecund, competitively inferior, and more sensitive to low plant quality. Correspondingly, predator effects were contingent upon plant quality only for the generalist. Contrary to predictions, predator effects were weaker for the generalist and on low-quality plants, likely due to density-dependent benefits provided to the generalist by mutualist ants. Because the TTI hypothesis predicts the superior performance of specialists, mutualist ants may be critical to A. gossypii persistence under competition from U. macolai. In summary, the integrative nature of the TTI hypothesis offers novel insight into the determinants of plant-herbivore and herbivore-predator interactions and the coexistence of specialist and generalist herbivores

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Combined measurement of the Higgs boson mass from the H → γγ and H → ZZ∗ → 4ℓ decay channels with the ATLAS detector using √s = 7, 8, and 13 TeV pp collision data

A measurement of the mass of the Higgs boson combining the H → Z Z ∗ → 4 ℓ and H → γ γ decay channels is presented. The result is based on 140     fb − 1 of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11 ± 0.09 ( stat ) ± 0.06 ( syst ) = 125.11 ± 0.11     GeV . This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics