Elemental and molecular imaging of human hair using secondary ion mass spectrometry

Gillen, Greg; Roberson, Sonya; Ng, Calista Keow Leng; Stranick, Michael

doi:10.1002/sca.4950210301

Cited by 21 publications

(13 citation statements)

References 16 publications

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“…By using a statistical grouping method, these authors were able to identify the mineral phases present on the basalt surface. Secondary ion mass spectrometry imaging was also used to determine the spatial distribution of elemental and molecular species on the surface of human hair with submicrometer spatial resolution, as in the present study, without metallic coating of the sample surface prior to analysis (Gillen et al 1999).…”

Section: Resultsmentioning

confidence: 99%

The use of secondary ion mass spectrometry coupled with image analysis to identify and locate chemical elements in soil minerals: The example of phosphorus

Bertrand

Grignon

Hinsinger³

et al. 2001

Scanning

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Summary:The mobility and bioavailability of elements in soils and sediments largely depends on their distribution on the diverse inorganic and organic constituents. This work addresses the example of phosphorus (P) associated to goethite and calcite, that is, to the major minerals involved in the retention of P in soils and sediments in calcareous environments. Synthetic goethite (FeOOH) and calcite (CaCO 3 ) were reacted with P prior to being analysed by dynamic secondary ion mass spectrometry (SIMS). Powdery samples were embedded in resin, cut in thin sections, and imaged with a CAMECA IMS 4F ion microscope used in scanning mode with a primary ion beam of caesium that produced negatively charged secondary ions ( − ) (Cameca, Cedex, France). Carbon, O, P, and calcium (Ca) were directly imaged at m/z 12, 16, 31, and 40, respectively, while Fe was imaged via the polyatomic ion FeO − ion at m/z 72. The SIMS data were treated by image analysis procedures. The visual comparison of images and the scatterplot method showed that P strongly interacted with goethite, probably following an adsorption process, and was thus evenly distributed at its surface. Conversely, P was not evenly distributed at the surface of calcite which rather suggests a precipitation process, and the scatterplot method confirmed a poor relationship between P and Ca. For the goethite-calcite mixture, visual examination suggested that P occurred as clusters which were largely associated with calcite, whereas a statistical analysis of the various images showed that the distribution of P was largely related to that of goethite particles. This work confirms the potential contribution of iron oxides in the retention of P in calcareous environments and shows that coupling image analysis to sensitive analytical techniques such as SIMS is a powerful approach for providing quantitative information on the location of elements at low bulk concentrations.

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Section: Resultsmentioning

confidence: 99%

The use of secondary ion mass spectrometry coupled with image analysis to identify and locate chemical elements in soil minerals: The example of phosphorus

Bertrand

Grignon

Hinsinger³

et al. 2001

Scanning

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“…A number of techniques have been used to study the hair cuticle, including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) (Swift & Brown, 1972;Swift & Bews, 1976;Hess et al ., 1990;Ruetsch et al ., 2000;Ahn & Lee, 2002), X-ray photoelectron spectroscopy (Goddard & Harris, 1987), confocal microscopy (Hadjur et al ., 2002), microdiffraction (Kreplak et al ., 2001), secondary ion mass spectrometry (Gillen et al ., 1999), goniometry (Feughelman & Willis, 2001) and lateral force microscopy (LFM) (McMullen et al ., 2000;McMullen & Kelty, 2001). One other technique that has been of particular interest recently is atomic force microscopy (AFM) (Binnig et al ., 1986;Rugar & Hansma, 1990).…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis and classification of AFM images of human hair

Gurden

Monteiro

Longo

et al. 2004

Journal of Microscopy

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SummaryThe surface topography of human hair, as defined by the outer layer of cellular sheets, termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the ease of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density, allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.

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“…Therefore, SIMS (bio)imaging has the possibility of filling a niche for the analysis of low-molecular-weight compounds and biomolecules at high spatial resolution for biomedical studies. (Bio)imaging by the SIMS method can be applied to a wide range of biological tissues including whole brain sections, the aorta, liver, hair, and kidney Gillen et al, 1999;Kurczy et al, 2008;Locker, 2014;McDonnell et al, 2005;Nygren et al, 2005Nygren et al, , 2007Solon et al, 2010) The SIMS method can be applied to the (bio)imaging of metallic elements (alkali and also heavy) in different biological samples such as organelles, organs, and plants (Chandra et al, 2013;Derue et al, 2006;Heard et al, 2001;Nygren et al, 2005Nygren et al, , 2014Smith et al, 2013;Wang et al, 2014;Wu and Becker, 2012). However, analyzing elements in isolation offers only limited functional information about any given sample.…”

Section: Application Of the Sims Methods In (Bio)imaging/mapping Elemementioning

confidence: 96%

Bioanalytics in Quantitive (Bio)imaging/Mapping of Metallic Elements in Biological Samples

Jurowski

Buszewski

Piekoszewski

2014

Critical Reviews in Analytical Chemistry

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The aim of this article is to describe selected analytical techniques and their applications in the quantitative mapping/(bio)imaging of metals in biological samples. This work presents the advantages and disadvantages as well as the appropriate methods of scope for research. Distribution of metals in biological samples is currently one of the most important issues in physiology, toxicology, pharmacology, and other disciplines where functional information about the distribution of metals is essential. This issue is a subject of research in (bio)imaging/mapping studies, which use a variety of analytical techniques for the identification and determination of metallic elements. Increased interest in analytical techniques enabling the (bio)imaging of metals in a variety of biological material has been observed more recently. Measuring the distribution of trace metals in tissues after a drug dose or ingestion of poison-containing metals allows for the studying of pathomechanisms and the pathophysiology of various diseases and disorders related to the management of metals in human and animal systems.

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Elemental and molecular imaging of human hair using secondary ion mass spectrometry

Cited by 21 publications

References 16 publications

The use of secondary ion mass spectrometry coupled with image analysis to identify and locate chemical elements in soil minerals: The example of phosphorus

The use of secondary ion mass spectrometry coupled with image analysis to identify and locate chemical elements in soil minerals: The example of phosphorus

Quantitative analysis and classification of AFM images of human hair

Bioanalytics in Quantitive (Bio)imaging/Mapping of Metallic Elements in Biological Samples

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