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Secularism in Iran is not just a form of Western 'imperialism'
No full texthttps://aeon.co/essays/secularism-in-iran-is-not-just-a-form-of-western-imperialis
Probabilistic predictions of SIS epidemics on networks based on population-level observations
Get PDFWe predict the future course of ongoing susceptible–infected–susceptible (SIS) epidemics on regular, Erdős–Rényi and Barabási–Albert networks. It is known that the contact network influences the spread of an epidemic within a population. Therefore, observations of an epidemic, in this case at the population-level, contain information about the underlying network. This information, in turn, is useful for predicting the future course of an ongoing epidemic. To exploit this in a prediction framework, the exact high-dimensional stochastic model of an SIS epidemic on a network is approximated by a lower-dimensional surrogate model. The surrogate model is based on a birth-and-death process; the effect of the underlying network is described by a parametric model for the birth rates. We demonstrate empirically that the surrogate model captures the intrinsic stochasticity of the epidemic once it reaches a point from which it will not die out. Bayesian parameter inference allows for uncertainty about the model parameters and the class of the underlying network to be incorporated directly into probabilistic predictions. An evaluation of a number of scenarios shows that in most cases the resulting prediction intervals adequately quantify the prediction uncertainty. As long as the population-level data is available over a long-enough period, even if not sampled frequently, the model leads to excellent predictions where the underlying network is correctly identified and prediction uncertainty mainly reflects the intrinsic stochasticity of the spreading epidemic. For predictions inferred from shorter observational periods, uncertainty about parameters and network class dominate prediction uncertainty. The proposed method relies on minimal data at population-level, which is always likely to be available. This, combined with its numerical efficiency, makes the proposed method attractive to be used either as a standalone inference and prediction scheme or in conjunction with other inference and/or predictive models
Proposal for a consistent definition of aphantasia and hyperphantasia: A response to Lambert and Sibley (2022) and Simner and Dance(2022)
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Cvm1 is a component of multiple vacuolar contact sites required for sphingolipid homeostasis
Get PDFMembrane contact sites are specialized platforms formed between most organelles that enable them to exchange metabolites and influence the dynamics of each other. The yeast vacuole is a degradative organelle equivalent to the lysosome in higher eukaryotes with important roles in ion homeostasis and metabolism. Using a high-content microscopy screen, we identified Ymr160w (Cvm1, for contact of the vacuole membrane 1) as a novel component of three different contact sites of the vacuole: with the nuclear endoplasmic reticulum, the mitochondria, and the peroxisomes. At the vacuole–mitochondria contact site, Cvm1 acts as a tether independently of previously known tethers. We show that changes in Cvm1 levels affect sphingolipid homeostasis, altering the levels of multiple sphingolipid classes and the response of sphingolipid-sensing signaling pathways. Furthermore, the contact sites formed by Cvm1 are induced upon a decrease in sphingolipid levels. Altogether, our work identifies a novel protein that forms multiple contact sites and supports a role of lysosomal contacts in sphingolipid homeostasis
