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The adaptive and innate branches of the vertebrate immune system work in close collaboration to protect organisms from harmful pathogens. As an organism ages its immune system undergoes immunosenescence, characterized by declined performance or malfunction in either immune branch, which can lead to disease and death. In this study we develop a mathematical framework of coupled innate and adaptive immune responses, namely the integrated immune branch (IIB) model. This model describes dynamics of immune components in both branches, uses a shape-space representation to encode pathogen-specific immune memory, and exhibits three steady states -- health, septic death, and chronic inflammation -- qualitatively similar to clinically-observed immune outcomes. In this model, the immune system (initialized in the health state) is subjected to a sequence of pathogen encounters, and we use the number of prior pathogen encounters as a proxy for the "age" of the immune system. We find that repeated pathogen encounters may trigger a fragility in which any encounter with a novel pathogen will cause the system to irreversibly switch from health to chronic inflammation. This transition is consistent with the onset of "inflammaging", a condition observed in aged individuals who experience chronic low-grade inflammation even in the absence of pathogens. The IIB model predicts that the onset of chronic inflammation strongly depends on the history of encountered pathogens; the timing of onset differs drastically when the same set of infections occurs in a different order. Lastly, the coupling between the innate and adaptive immune branches generates a trade-off between rapid pathogen clearance and a delayed onset of immunosenescence., Comment: 23 pages, 7 figures

Natural environments can present diverse challenges, but some genotypes remain fit across many environments. Such `generalists' can be hard to evolve, out-competed by specialists fitter in any particular environment. Here, inspired by the search for broadly-neutralising antibodies during B-cell affinity maturation, we demonstrate that environmental changes on an intermediate timescale can reliably evolve generalists, even when faster or slower environmental changes are unable to do so. We find that changing environments on timescales comparable to evolutionary transients in a population enhances the rate of evolving generalists from specialists, without enhancing the reverse process. The yield of generalists is further increased in more complex dynamic environments, such as a `chirp' of increasing frequency. Our work offers design principles for how non-equilibrium fitness `seascapes' can dynamically funnel populations to genotypes unobtainable in static environments.

Graphene/silicon heterostructures have attracted tremendous interest as a new platform for diverse electronic and photonic devices such as barristors, solar cells, optical modulators, and chemical sensors. The studies to date largely focus on junctions between graphene and lightly-doped silicon, where a Schottky barrier is believed to dominate the carrier transport process. Here we report a systematic investigation of carrier transport across the heterojunctions formed between graphene and highly-doped silicon. By varying the silicon doping level and the measurement temperature, we show that the carrier transport across the graphene/p++-Si heterojunction is dominated by tunneling effect through the native oxide. We further demonstrate that the tunneling current can be effectively modulated by the external gate electrical field, resulting in a vertical tunneling transistor. Benefited from the large density of states of highly doped silicon, our tunneling transistors can deliver a current density over 20 A/cm2, about two orders of magnitude higher than previous graphene/insulator/graphene tunneling transistor at the same on/off ratio.