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Rationale: Potassium (K) is a major component of several silicate minerals and seawater, and, therefore, constraining past changes in the potassium cycle is a promising way of tracing large-scale geological processes on Earth. However, [K] measurement using inductively coupled plasma mass spectrometry (ICP-MS) is challenging due to an ArH+ interference, which may be of a similar magnitude to the K+ ion beam in samples with <0.1% m/m [K].
Methods: In this work, we investigated the effect of the ArH+ interference on K/Ca data quality by comparing results from laser-ablation (LA)-ICP-MS measured in medium and high mass resolution modes and validating our LA results via solution ICP-optical emission spectroscopy (OES) and solution ICP-MS measurements. To do so, we used a wide range of geological reference materials, with a particular focus on marine carbonates, which are potential archives of past changes in the K cycle but are typically characterised by [K] < 200 μg/g. In addition, we examine the degree to which trace-element data quality is driven by downhole fractionation during LA-ICP-MS measurements.
Results: Our results show that medium mass resolution (MR) mode is sufficiently capable of minimising the effect of the ArH+ interference on K+. However, the rate of downhole fractionation for Na and K varies between different samples as a result of their differing bulk composition, resulting in matrix-specific inaccuracy. We show how this can be accounted for via downhole fractionation corrections, resulting in an accuracy of better than 1% and a long-term reproducibility (intermediate precision) of <6% (relative standard deviation) in JCp-1NP using LA-ICP-MS in MR mode.
Conclusion: Our [K] measurement protocol is demonstrably precise and accurate and applicable to a wide range of materials. The measurement of K/Ca in relatively low-[K] marine carbonates is presented here as a key example of a new application opened up by these advances.
The free energy of TAP-solutions for the SK-model of mean field spin glasses can be expressed as a nonlinear functional of local terms: we exploit this feature in order to contrive abstract REM-like models which we then solve by a classical large deviations treatment. This allows to identify the origin of the physically unsettling quadratic (in the inverse of temperature) correction to the Parisi free energy for the SK-model, and formalizes the true cavity dynamics which acts on TAP-space, i.e. on the space of TAP-solutions. From a non-spin glass point of view, this work is the first in a series of refinements which addresses the stability of hierarchical structures in models of evolving populations.
The photoelectric effect describes the ejection of an electron upon absorption of one or several photons. The kinetic energy of this electron is determined by the photon energy reduced by the binding energy of the electron and, if strong laser fields are involved, by the ponderomotive potential in addition. It has therefore been widely taken for granted that for atoms and molecules, the photoelectron energy does not depend on the electron’s emission direction, but theoretical studies have questioned this since 1990. Here, we provide experimental evidence that the energies of photoelectrons emitted against the light propagation direction are shifted toward higher values, while those electrons that are emitted along the light propagation direction are shifted to lower values. We attribute the energy shift to a nondipole contribution to the ponderomotive potential that is due to the interaction of the moving electrons with the incident photons.
Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.