Local Magnetic Anomalies Explain Bias in Paleomagnetic Data: Consequences for Sampling

Volcanic rocks are considered reliable recorders of past changes in the Earth's magnetic field. Recent flows, however, sometimes fail to produce the known magnetic field at the time of cooling. Previous research on Mt. Etna suggests paleomagnetic data might not be accurately recorded. Here we test the accuracy of paleomagnetic data obtained from Mt. Etna lavas by comparing paleomagnetic data from historical flows to direct measurements of the magnetic field above the current topography. The inclinations and intensities in both data sets are biased toward lower values, while there is no such trend for the declination. Inclinations are on average 2.9° lower than expected; intensities are on average 8.8 µT lower. The deviations from the expected values depend on the height above the flow. Moreover, the inclinations and intensities vary as a function of topography. Both are higher above ridges and lower in gullies; the variations within a site are up to 14.1° in inclination and 12.9 µT for intensity. To suppress this paleomagnetic data bias it is important to take samples several meters apart and from different parts of the flow whenever possible. While this leads to a higher degree of scatter in paleodirections, the results better represent the Earth's magnetic field at the time of cooling. This emphasizes the importance of reporting paleomagnetic sampling strategies in detail

An end-member modelling approach to pseudo-Thellier palaeointensity data

Absolute palaeointensities are notoriously hard to obtain, because conventional thermal Thellier palaeointensity experiments often have low success rates for volcanic samples. The thermal treatments necessary for these experiments potentially induce (magnetic) alteration in the samples, preventing a reliable palaeointensity estimate. These heating steps can be avoided by pseudo-Thellier measurements, where samples are demagnetized and remagnetized with alternating fields. However, pseudo-Thellier experiments intrinsically produce relative palaeointensities. Over the past years, attempts were made to calibrate pseudo-Thellier results into absolute palaeointensities for lavas by mapping laboratory induced anhysteretic remanent magnetizations (ARMs) to the thermally acquired natural remanent magnetizations (NRMs). Naturally occurring volcanic rocks, however, are assemblages of minerals differing in grain size, shape and chemistry. These different minerals all have their own characteristic mapping between ARMs and thermal NRMs. Here, we show that it is possible to find these characteristic mappings by unmixing the NRM demagnetization and the ARM acquisition curves into end-members, with an iterative method of non-negative matrix factorization. In turn, this end-member modelling approach (EMMA) allows for the calculation of absolute palaeointensities from pseudo-Thellier measurements. We tested our EMMA using a noise-free numerical data set, yielding a perfect reconstruction of the palaeointensities. When adding noise up to levels beyond what is expected in natural samples, the end-member model still produces the known palaeointensities well. In addition, we made a synthetic data set with natural volcanic samples from different volcanic edifices that were given a magnetization by heating and cooling them in a controlled magnetic field in the lab. The applied fields ranged between 10 and 70 μT. The average absolute difference between the calculated palaeointensity and the known lab field is around 10 μT for the models with 2-4 end-members, while the palaeointensity of almost all flows can be retrieved within a deviation of ±20 μT. The deviations between the palaeointensities and the known lab fields are almost Gaussian distributed around the expected values. Although the two data sets in our study show that there is potential for using this end-member modelling technique for finding absolute palaeointensities from pseudo-Thellier data, these synthetic data sets cannot be directly related to natural samples. Therefore, it is necessary to compile a data set of known palaeointensities from different volcanic sites that recently cooled in a known magnetic field to find the universal end-members in future studies

Modeling the Distribution of Iron-oxides in Basalt by combining FIB-SEM and MicroCT Measurements

Micromagnetic tomography (MMT) aims to go beyond paleomagnetic measurements on bulk samples by obtaining magnetic moments for individual iron-oxide grains present in a sample. To obtain accurate MMT results all magnetic sources and all their magnetic signals should be known. Small particles (750 nm. The FIB-SEM and MicroCT data are combined through normalizing the grain-size distribution using the surface area of non-magnetic minerals that are characterised in both datasets. Then, a lognormal-like grain-size distribution is acquired for the entire grain-size range. Our dataset enables future studies to populate (MMT) models with a realistic distribution of even the smallest iron-oxide grains, which ultimately may shed light on the confounding influence of such ghost grains on MMT results

The Impact of Grain‐Size Distributions of Iron‐Oxides on Paleomagnetic Measurements

Magnetic signals in igneous rocks arise from assemblages of iron-oxide bearing minerals that differ in for example, size, shape, and chemistry. Paleomagnetic measurements on bulk samples measure millions of such grains simultaneously, producing a statistical ensemble of the magnetic moments of the individual grains. Scanning magnetometry techniques such as the Quantum Diamond Microscope (QDM) measure magnetic signals on micrometer scales, allowing the identification of magnetic moments of individual grains in a sample using for example, Micromagnetic Tomography (MMT). Here we produce a grain-size distribution of iron-oxides in a typical Hawaiian basalt from the superparamagnetic threshold (∼40 nm) to grains with a diameter of 10 µm. This grain-size distribution is obtained by combining FIB-SEM and MicroCT data from sister specimens, and normalizing them to the mineral surface area of non-magnetic minerals. Then we use this grain-size distribution to determine the contributions of individual magnetic carriers to bulk magnetic measurements and surface magnetometry. We found that measurements on bulk samples are sensitive to relatively small grain sizes in the realm of single domain or vortex states (1 µm. This implies that bulk measurements cannot be compared straightforwardly to signals from surface magnetometry from the same sample. Moreover, our observations explain why MMT results are insensitive to the presence of many small grains in a sample that intuitively should hamper their outcome

Paleointensity.org: An Online, Open Source, Application for the Interpretation of Paleointensity Data

AbstractPaleointensity.org is an online, open source, application to analyze paleointensity data produced by the most common paleointensity techniques. Our application currently supports four different methods: thermal Thellier (all variations), microwave Thellier, pseudo‐Thellier, and the multispecimen protocol. Data can be imported using a variety of input file formats such as ThellierTool files, the generic PmagPy file format, and a number of lab‐specific formats. The data for the individual paleointensity methods are visualized by the relevant graphs and parameters, which are updated dynamically while interpreting the data. Beyond manual interpretation, Paleointensity.org features an autointerpreter for specimen level Thellier‐type data. Interpretations and data can be exported to csv and MagIC files. Moreover, it is possible to export the local storage containing all data, saved interpretations, and settings. This file can be shared among researchers or attached to a paper as supporting information. Because of its many features and ease of use, Paleointensity.org is a major step forward in enhancing an open paleomagnetic community in which data can be shared, checked, and reused in line with the findable, accessible, interoperable, and reusable data principles.</jats:p

Micromagnetic tomography: Numerical libraries

Micromagnetic tomography (MMT) is an emerging technique in rock and paleomagnetism to determine individual magnetic moments of tomographically defined magnetic source regions within a natural sample by means of surface scans of the magnetic field above the sample. MMT relies on combining large high-resolution data sets from X-ray tomography and magnetic scanning devices, like quantum diamond magnetometers, together with advanced inversion algorithms potentially capable to solve for millions of individual magnetic moment vectors. We here provide an overview of existing algorithms that have been developed to tackle different aspects of MMT-related problems and discuss recent advances and future challenges of MMT

Unraveling the Magnetic Signal of Individual Grains in a Hawaiian Lava Using Micromagnetic Tomography

Micromagnetic Tomography (MMT) is a new technique that allows the determination of magnetic moments of individual grains in volcanic rocks. Current MMT studies either showed that it is possible to obtain magnetic moments of relatively small numbers of grains in ideal sample material or provided important theoretical advances in MMT inversion theory and/or its statistical framework. Here, we present a large-scale application of MMT on a sample from the 1907-flow from Hawaii's Kilauea volcano producing magnetic moments of 1,646 grains. We produced 261,305 magnetic moments in total for these 1,646 grains, an increase of three orders of magnitude compared to earlier studies to assess the robustness of the MMT results, and a major step toward the number of grains that is necessary for paleomagnetic applications of MMT. Furthermore, we show that the recently proposed signal strength ratio is a powerful tool to scrutinize and select MMT results. Despite this progress, still only relatively large iron-oxide grains with diameters >1.5–2 μm can be reliably resolved, impeding a reliable paleomagnetic interpretation. To determine the magnetic moments of smaller (<1 μm) grains that may exhibit pseudo-single domain behavior and are therefore better paleomagnetic recorders, the resolution of the microcomputed tomography and magnetic scans necessary for MMT must be improved. Therefore, it is necessary to reduce the sample size in future MMT studies. Nevertheless, our study is an important step toward making MMT a useful paleomagnetic and rock-magnetic technique

Micromagnetic Tomography for Paleomagnetism and Rock-Magnetism.

Our understanding of the past behavior of the geomagnetic field arises from magnetic signals stored in geological materials, e.g., (volcanic) rocks. Bulk rock samples, however, often contain magnetic grains that differ in chemistry, size, and shape; some of them record the Earth's magnetic field well, others are unreliable. The presence of a small amount of adverse behaved magnetic grains in a sample may already obscure important information on the past state of the geomagnetic field. Recently it was shown that it is possible to determine magnetizations of individual grains in a sample by combining X-ray computed tomography and magnetic surface scanning measurements. Here we establish this new Micromagnetic Tomography (MMT) technique and make it suitable for use with different magnetic scanning techniques, and for both synthetic and natural samples. We acquired reliable magnetic directions by selecting subsets of grains in a synthetic sample, and we obtained rock-magnetic information of individual grains in a volcanic sample. This illustrates that MMT opens up entirely new venues of paleomagnetic and rock-magnetic research. MMT's unique ability to determine the magnetization of individual grains in a nondestructive way allows for a systematic analysis of how geological materials record and retain information on the past state of the Earth's magnetic field. Moreover, by interpreting only the contributions of known magnetically well-behaved grains in a sample, MMT has the potential to unlock paleomagnetic information from even the most complex, crucial, or valuable recorders that current methods are unable to recover

Identification of novel translational urinary biomarkers for acetaminophen-induced acute liver injury using proteomic profiling in mice

Contains fulltext : 108207.pdf (publisher's version ) (Open Access)Drug-induced liver injury (DILI) is the leading cause of acute liver failure. Currently, no adequate predictive biomarkers for DILI are available. This study describes a translational approach using proteomic profiling for the identification of urinary proteins related to acute liver injury induced by acetaminophen (APAP). Mice were given a single intraperitoneal dose of APAP (0-350 mg/kg bw) followed by 24 h urine collection. Doses of >/=275 mg/kg bw APAP resulted in hepatic centrilobular necrosis and significantly elevated plasma alanine aminotransferase (ALT) values (p<0.0001). Proteomic profiling resulted in the identification of 12 differentially excreted proteins in urine of mice with acute liver injury (p<0.001), including superoxide dismutase 1 (SOD1), carbonic anhydrase 3 (CA3) and calmodulin (CaM), as novel biomarkers for APAP-induced liver injury. Urinary levels of SOD1 and CA3 increased with rising plasma ALT levels, but urinary CaM was already present in mice treated with high dose of APAP without elevated plasma ALT levels. Importantly, we showed in human urine after APAP intoxication the presence of SOD1 and CA3, whereas both proteins were absent in control urine samples. Urinary concentrations of CaM were significantly increased and correlated well with plasma APAP concentrations (r = 0.97; p<0.0001) in human APAP intoxicants, who did not present with elevated plasma ALT levels. In conclusion, using this urinary proteomics approach we demonstrate CA3, SOD1 and, most importantly, CaM as potential human biomarkers for APAP-induced liver injury