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The 2011–2012 eruption at Cordón Caulle in Chile produced crystal-poor rhyolitic magma with crystal-rich mafic enclaves whose interstitial glass is of identical composition to the host rhyolite. Eruptible rhyolites are thought to be genetically associated with crystal-rich magma mushes, and the enclaves within the Cordón Caulle rhyolite support the existence of a magma mush from which the erupted magma was derived. Moreover, towards the end of the 2011–2012 eruption, subsidence gave way to inflation that has on average been continuous through at least 2020. We hypothesize that magma segregation from a crystal mush could be the source of the observed inflation. Conceptually, magma withdrawal from a crystal-poor rhyolite reservoir caused its depressurization, which could have led to upward flow of interstitial melt within an underlying crystal mush, causing a new batch of magma to segregate and partially recharge the crystal-poor rhyolite body. Because the compressibility of the crystalline matrix of the mush is expected to be lower than that of the interstitial melt, which likely contains some fraction of volatile bubbles, this redistribution of melt would result in a net increase in volume of the system and in the observed inflation. We use numerical modelling of subsurface magma flow and storage to show under which conditions such a scenario is supported by geodetic and petrologic observations.

To use next-generation sequencing technology such as RNA-seq for medical and health applications, choosing proper analysis methods for biomarker identification remains a critical challenge for most users. The US Food and Drug Administration (FDA) has led the Sequencing Quality Control (SEQC) project to conduct a comprehensive investigation of 278 representative RNA-seq data analysis pipelines consisting of 13 sequence mapping, three quantification, and seven normalization methods. In this article, we focused on the impact of the joint effects of RNA-seq pipelines on gene expression estimation as well as the downstream prediction of disease outcomes. First, we developed and applied three metrics (i.e., accuracy, precision, and reliability) to quantitatively evaluate each pipeline’s performance on gene expression estimation. We then investigated the correlation between the proposed metrics and the downstream prediction performance using two real-world cancer datasets (i.e., SEQC neuroblastoma dataset and the NIH/NCI TCGA lung adenocarcinoma dataset). We found that RNA-seq pipeline components jointly and significantly impacted the accuracy of gene expression estimation, and its impact was extended to the downstream prediction of these cancer outcomes. Specifically, RNA-seq pipelines that produced more accurate, precise, and reliable gene expression estimation tended to perform better in the prediction of disease outcome. In the end, we provided scenarios as guidelines for users to use these three metrics to select sensible RNA-seq pipelines for the improved accuracy, precision, and reliability of gene expression estimation, which lead to the improved downstream gene expression-based prediction of disease outcome.

Cyclical ground deformation, associated seismicity, and elevated degassing are important precursors to explosive eruptions at silicic volcanoes. Regular intervals for elevated activity (6–30 hr) have been observed at volcanoes such as Mount Pinatubo in the Philippines and Soufrière Hills in Montserrat. Here, we explore a hypothesis originally proposed by Michaut et al. (2013,https://doi.org/10.1038/ngeo1928) where porosity waves containing magmatic gas are responsible for the observed periodic behavior. We use two‐phase theory to construct a model where volatile‐rich, bubbly, viscous magma rises and decompresses. We conduct numerical experiments where magma gas waves with various frequencies are imposed at the base of the model volcanic conduit. We numerically verify the results of Michaut et al. (2013,https://doi.org/10.1038/ngeo1928) and then expand on the model by allowing magma viscosity to vary as a function of dissolved water and crystal content. Numerical experiments show that gas exsolution tends to damp the growth of porosity waves during decompression. The instability and resultant growth or decay of gas wave amplitude depends strongly on the gas density gradient and the ratio of the characteristic magma extraction rate to the characteristic magma degassing rate (Damköhler number, Da). We find that slow degassing can lead to a previously unrecognized filtering effect, where low‐frequency gas waves may grow in amplitude. These waves may set the periodicity of the eruptive precursors, such as those observed at Soufrière Hills Volcano. We demonstrate that degassed, crystal‐rich magma is susceptible to the growth of gas waves which may result in the periodic behavior.