A double-spike MC TIMS measurement procedure for low-amount Ca isotopic analysis of limited biological tissue samples

The application of Ca isotopic analysis in biomedical studies has great potential to identify changes in Ca metabolism and bone metabolism. Reliable measurement of Ca isotope-amount ratios is challenging considering limited Ca amounts and significant procedural blank levels. In this study, Ca purification was performed using the DGA Resin, optimized for low procedural blanks and separation of Ca from matrix elements and isobaric interferences (Na, Mg, K, Ti, Fe, Ba), while maintaining quasi-quantitative recoveries which are sufficient since a Ca-42-Ca-48 double-spike (DS) was applied. Ca isotopic analysis was performed using multicollector thermal ionization mass spectrometry (MC TIMS). The obtained procedural Ca blank of <= 10 ng enables processing of limited Ca amounts down to 670 ng. Data reduction of the measured Ca isotope-amount ratios was performed using an in-house developed software solving the DS algorithm. Data quality was improved by extension of equilibration time of the sample-DS mixture and implementation of a normalization strategy for raw isotopic data. The reported delta(Ca-44/Ca-40)(NIST SRM 915a) of NIST SRM 915a processed as a sample was found to be 0.01 parts per thousand +/- 0.08 parts per thousand (2 SD, n = 15). Ca isotope-amount ratios of the reference material NIST SRM 1400 (bone ash), NIST SRM 1486 (bone meal), GBW07601 (human hair), and IAPSO (seawater) were in good agreement within uncertainty with literature data. Novel data on additional reference materials for biological tissues (hair) is presented, which might indicate a potential fractionation of Ca incorporated into hair tissue when compared to the blood pool.

Automated summary

The application of Ca isotopic analysis in biomedical studies has great potential to identify changes in Ca metabolism and bone metabolism. By employing DGA resin for Ca purification, a double-spike technique, and MC TIMS for analysis, data quality was improved and the potential of the new detection method was confirmed.