Evidence map›Paper›PMID 41533064›Full record

ArticleAnalytical and bioanalytical chemistry2026

Automated methods for multi-isotopic analysis of major cations in biological samples: application to chronic kidney disease of unknown etiology.

Rosa Grigoryan, William Swenson, M Paul Field, Mangala Chatura De Silva, Anna Strasma, Nishad Jayasundara, Michael A Kipp

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Article in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Rosa GrigoryanDivision of Earth and Climate Sciences, Nicholas School of the Environment, Duke University, Durham, NC, USA. rosa.grigoryan@duke.edu.
William SwensonElemental Scientific Inc., Omaha, NE, USA.
M Paul FieldElemental Scientific Inc., Omaha, NE, USA.
Mangala Chatura De SilvaDepartment of Zoology, University of Ruhuna, Matara, Sri Lanka.
Anna StrasmaDivision of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
Nishad JayasundaraDivision of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
Michael A KippDivision of Earth and Climate Sciences, Nicholas School of the Environment, Duke University, Durham, NC, USA. michael.kipp@duke.edu.

Funding

American Chemical Society Petroleum Research Fund 67594-DNI2Division of Ocean Sciences 2441483
6 · The paper itself

Abstract

Natural variability in stable isotope ratios provides critical constraints on elemental cycling in nature without the need for the introduction of artificial tracers. While such data are widely used in environmental studies, they are not as widely employed in biomedical research, despite vast potential. One critical hurdle to the adoption of such techniques in biomedical studies is sample throughput. Elemental purification via ion-exchange chromatography and isotopic analysis via multiple collector inductively coupled plasma mass spectrometry (MC-ICP-MS) are time-consuming, requiring long hours from experienced researchers to generate datasets. Here we present new methods to improve the throughput of both elemental purification and sample introduction to mass spectrometers. We use an automated, low-pressure ion exchange chromatography system to isolate purified fractions of potassium, magnesium, and calcium from one sample in a single sequence with high yields (80-100%) and low blanks (<0.5% carryover). Modification of flow rates and column volumes also enables recovery of purified strontium, lithium, and sodium in the same routine. Solutions are introduced to the MC-ICP-MS via syringe injection and with automated removal of vial caps to minimize evaporation. We find that syringe injection from capped vials gives a >10 × more stable signal (0.7% RSD) over a 9-h sequence than self-aspirated, uncapped solutions (8.0% RSD). Syringe injection also enables modification of signal intensity by changing the injection rate, with a linear response of signal to flow rate. We demonstrate the potential of these methods by analyzing calcium, magnesium, and potassium isotope ratios at high precision (<0.1 ‰) from single 0.5 mL aliquots of urine samples from individuals with chronic kidney disease. These data show a change in calcium reabsorption, highlighting avenues for further research as well as the value of these multi-isotopic analysis methods.

Indexed as

CationsMass SpectrometryRenal Insufficiency, ChronicAutomationCalciumChromatography, Ion ExchangeHumansIsotopesMagnesiumPotassiumCalciumCationsIsotopesMagnesiumPotassiumCalciumChromatographyMagnesiumPotassiumSpectrometry

Identifiers

PMID41533064

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.