Dugganboll8511

Nonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basis of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization-a well-known source of nonlinear dynamics. Specifically, our approach focuses on modelling co-translational dimerization the formation of protein dimers during-and not after-translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e. post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.The basic reproductive number, R0, is one of the most common and most commonly misapplied numbers in public health. Often used to compare outbreaks and forecast pandemic risk, this single number belies the complexity that different epidemics can exhibit, even when they have the same R0. Here, we reformulate and extend a classic result from random network theory to forecast the size of an epidemic using estimates of the distribution of secondary infections, leveraging both its average R0 and the underlying heterogeneity. Importantly, epidemics with lower R0 can be larger if they spread more homogeneously (and are therefore more robust to stochastic fluctuations). We illustrate the potential of this approach using different real epidemics with known estimates for R0, heterogeneity and epidemic size in the absence of significant intervention. Further, we discuss the different ways in which this framework can be implemented in the data-scarce reality of emerging pathogens. Lastly, we demonstrate that without data on the heterogeneity in secondary infections for emerging infectious diseases like COVID-19 the uncertainty in outbreak size ranges dramatically. Taken together, our work highlights the critical need for contact tracing during emerging infectious disease outbreaks and the need to look beyond R0.Many biological and social systems show significant levels of collective action. Several cooperation mechanisms have been proposed, yet they have been mostly studied independently. Among these, direct reciprocity supports cooperation on the basis of repeated interactions among individuals. Signals and quorum dynamics may also drive cooperation. Here, we resort to an evolutionary game-theoretical model to jointly analyse these two mechanisms and study the conditions in which evolution selects for direct reciprocity, signalling, or their combination. We show that signalling alone leads to higher levels of cooperation than when combined with reciprocity, while offering additional robustness against errors. Specifically, successful strategies in the realm of direct reciprocity are often not selected in the presence of signalling, and memory of past interactions is only exploited opportunistically in the case of earlier coordination failure. Differently, signalling always evolves, even when costly. In the light of these results, it may be easier to understand why direct reciprocity has been observed only in a limited number of cases among non-humans, whereas signalling is widespread at all levels of complexity.Comparative laboratory sliding wear tests on extracted human molar teeth in artificial saliva with third-body particulates demonstrate that phytoliths can be as effective as silica grit in the abrasion of enamel. this website A pin-on-disc wear testing configuration is employed, with an extracted molar cusp as a pin on a hard disc antagonist, under loading conditions representative of normal chewing forces. Concentrations and sizes of phytoliths in the wear test media match those of silica particles. Cusp geometries and ensuing abrasion volumes are measured by digital profilometry. The wear data are considered in relation to a debate by evolutionary biologists concerning the relative capacities of intrinsic mineral bodies within plant tissue and exogenous grit in the atmosphere to act as agents of tooth wear in various animal species.In the field of reproductive biology, there is a strong need for a suitable tool capable of non-destructive evaluation of oocyte viability and function. We studied the application of brilliant cresyl blue (BCB) as an intra-vital exogenous contrast agent using multispectral optoacoustic tomography (MSOT) for visualization of porcine ovarian follicles. The technique provided excellent molecular sensitivity, enabling the selection of competent oocytes without disrupting the follicles. We further conducted in vitro embryo culture, molecular analysis (real-time and reverse transcriptase polymerase chain reaction) and DNA fragmentation analysis to comprehensively establish the safety of BCB-enhanced MSOT imaging in monitoring oocyte viability. Overall, the experimental results suggest that the method offers a significant advance in the use of contrast agents and molecular imaging for reproductive studies. Our technique improves the accurate prediction of ovarian reserve significantly and, once standardized for in vivo imaging, could provide an effective tool for clinical infertility management.Empirical studies have shown that particular irrigation/fertilization regimes can reduce pest populations in agroecosystems. This appears to promise that the ecological concept of bottom-up control can be applied to pest management. However, a conceptual framework is necessary to develop a mechanistic basis for empirical evidence. Here, we couple a mechanistic plant growth model with a pest population model. We demonstrate its utility by applying it to the peach-green aphid system. Aphids are herbivores which feed on the plant phloem, deplete plants' resources and (potentially) transmit viral diseases. The model reproduces system properties observed in field studies and shows under which conditions the diametrically opposed plant vigour and plant stress hypotheses find support. We show that the effect of fertilization/irrigation on the pest population cannot be simply reduced as positive or negative. In fact, the magnitude and direction of any effect depend on the precise level of fertilization/irrigation and on the date of observation.