Major and Trace Element Composition Differences Revealed in Porcine Intestine by Dynamic Analysis and MeV Ion Microscopy

Physiologically relevant concentrations in biological tissue, in the in vivo, state are of the order of μmol L −1 and mmol L −1 . Up to the present, mapping the major elements in the matrix and its thickness has been neglected, despite their importance for quantification of lesser and trace element concentrations. Ryan and Jamieson's dynamic analysis, statistical spectral decomposition approach, is developed to quantitatively measure ex vivo tissue sections cut using a cryomicrotome. This mitigates the problem that physical analysis methods require a vacuum environment. This approach is used to quantitatively image the major matrix elements H, C, N, and O as well as trace maps of Ca, Fe, and Zn in a tissue section of porcine intestine. This sample is selected as it exhibits a complex morphology with multiple tissue compartments (such as muscle and mucosa, as well as void areas from blood vessels, lymph ducts, sinuses crypts, and villi. In the results, it is demonstrated that different tissue types can have a different matrix composition and thickness. Using this information, quantitative maps and elemental molarities for the lesser and trace elements Ca, Fe, and Zn are obtained.

Authors

Institutions

Publication Details

Journal
physica status solidi (a)
Published
2024-08-12
DOI
https://doi.org/10.1002/pssa.202400161
Citations
2
Primary Topic
Trace Elements in Health
Type
article
Field-Weighted Citation Impact
0.62

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Major and Trace Element Composition Differences Revealed in Porcine Intestine by Dynamic Analysis and MeV Ion Microscopy

C.G. Ryan, Andrej Kuznetsov, Wanwisa Sudprasert, T. Osipowicz et al.
2 citations
physica status solidi (a)
Trace Elements in Health
0.62
article

Major and Trace Element Composition Differences Revealed in Porcine Intestine by Dynamic Analysis and MeV Ion Microscopy

C.G. Ryan, Andrej Kuznetsov, Wanwisa Sudprasert, T. Osipowicz, Wimonrut Insuan, François Villinger, Alexander Azarov, Gyula Nagy, R.J.W. Frost, Harry J. Whitlow, Karen Smith, Sumittra Amphalop, Sakulchit Wichianchot, Min‐Quin Ren
article en
2 citations

Abstract

Physiologically relevant concentrations in biological tissue, in the in vivo, state are of the order of μmol L −1 and mmol L −1 . Up to the present, mapping the major elements in the matrix and its thickness has been neglected, despite their importance for quantification of lesser and trace element concentrations. Ryan and Jamieson's dynamic analysis, statistical spectral decomposition approach, is developed to quantitatively measure ex vivo tissue sections cut using a cryomicrotome. This mitigates the problem that physical analysis methods require a vacuum environment. This approach is used to quantitatively image the major matrix elements H, C, N, and O as well as trace maps of Ca, Fe, and Zn in a tissue section of porcine intestine. This sample is selected as it exhibits a complex morphology with multiple tissue compartments (such as muscle and mucosa, as well as void areas from blood vessels, lymph ducts, sinuses crypts, and villi. In the results, it is demonstrated that different tissue types can have a different matrix composition and thickness. Using this information, quantitative maps and elemental molarities for the lesser and trace elements Ca, Fe, and Zn are obtained.

physica status solidi (a)Vol. 222(12)
Uppsala University (SE), Commonwealth Scientific and Industrial Research Organisation (AU), National University of Singapore (SG), University of Oslo (NO), Kasetsart University (TH), Mineral Resources (AU), Australian Resources Research Centre (AU), University of Louisiana at Lafayette (US)
Stiftelsen för Strategisk Forskning, Vetenskapsrådet, Kasetsart University, Norges Forskningsråd
Openalex Percentile: Top 34%
Trace Elements in Health
0.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.