Quantitative analysis of human hairs and nails

Abstract

Hair and nails are human biomarkers capable of providing a continuous assessment of the concentrations of elements inside the human body to indicate the nutritional status, metabolic changes, and the pathogenesis of various human diseases. Laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XRF) spectrometry are robust and multi-element analytical techniques able to analyze biological samples of various kinds for disease diagnosis. The primary objective of this review article is to focus on the major developments and advances in LIBS and XRF for the elemental analysis of hair and nails over the last 10-year period. The developments in the qualitative and quantitative analyses of human hair and nail samples are discussed in detail, with special emphasis on the key aspects of elemental imaging and distribution of essential and non-essential elements within the hair and nail tissue samples. Microchemical imaging applications by LIBS and XRF (including micro-XRF and scanning electron microscopy, SEM) are also presented for healthy as well as diseased tissue hair and nail samples in the context of disease diagnosis. In addition, main challenges, prospects, and complementarities of LIBS and XRF toward analyzing human hair and nails for disease diagnosis are also thoroughly discussed here.

Introduction

Biomonitoring is the process of observing and assessing hazardous elements, chemicals, their metabolites, and reaction products in human tissues to predict the prevalence of the biological nature of a disease and to measure human exposure to chemicals and their toxic effects to human health (Hulka 1990). The concept of biomarkers has lately been widened to encompass biological traits that may be objectively examined and assessed as a sign of healthy biological functions and disease-causing processes (Naylor 2003). The studies of these biomarkers can help in determining the likelihood of disease to develop, its etiology, its diagnosis, and how it will develop, regress, and respond to treatment. For many years, researchers, scientists, and epidemiologists have used a variety of biomarkers to estimate the dangers of metal exposures and to understand the pathogenesis of various human diseases (Mehra and Juneja 2005; Sisodia et al., 2014). There are many factors that cause the metal contamination of the environment such as mining activities, urbanization, increased automotive traffic, and the use of pesticides and fertilizers in agriculture (Mehra and Juneja 2005). Although many important trace metal elements are necessary for a variety of biological functions at very small levels, these micronutrients have a tendency to be toxic at higher concentrations, which can disrupt a number of biological processes and cause disorders and diseases (Sisodia et al., 2014; Bali et al. 2023) and therefore it is critical to establish metal concentrations in individuals in order to monitor and evaluate their effects on human health (Jaswal et al. 2016a; Gondal et al., 2016a; Jaswal et al. 2016b; Gondal et al. 2020). Blood, hair, nails, teeth, and other body fluids are examples of biopsy materials that can be employed as biomarkers for this purpose.

In epidemiological investigations, hair, blood, nails, and urine have been found to be easily available biomarkers to evaluate the prevalence of disease and to measure human exposure to toxic elements. There are major challenges in using urine and blood as biomarkers for epidemiological investigations including the requirement to freeze the obtained urine samples, the invasiveness of blood sample collection techniques, and the problems related to the storage of these samples. In the next section, we describe the reasons behind the use of human nails and hairs for the investigation of trace and heavy metals, and for understanding the prevalence of certain diseases. We then describe the basic fundamentals of laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XRF).

Nails and hairs as biomarkers

There are numerous advantages of using nails and hairs as a biomarker to measure human exposure to toxic elements and to understand the pathogenesis of various human diseases (Chen and Amarasiriwardena 1999). The use of nail samples as bioindicators has greater benefits because they are less likely to be contaminated from the outside and grow at a much slower rate (0.9–1.5 mm/month). Due to the extremely irregular growth rate of hair and its greater potential to be contaminated by a toxic environment (as compared to nail samples), hair samples have been frequently used in epidemiological studies (Slotnick & Nriagu 2006). These properties of hair and nails means that they are regarded as two of the most significant biomarkers by the Environmental Protection Agency (EPA) (Rashed and Hossam 2007). The advantages of analyzing nail and hair samples are their simple and non-invasive collection and easy storage at room temperature for a long time. In addition, the availability of standardized procedures for hair and nail sample collection, their cleaning, and advanced instrumentation for their analysis gives them advantages to be used as biomarkers (Chaudhary et al. 1995; Doğan-Sağlamtimur and Kumbur 2010).

In contrast to blood, once chemical components and/or elements are absorbed into the keratin present in nails and hairs, their levels remain separate from other metabolic processes in the body and do not fluctuate. Nails and hair are resistant to decay and they preserve trace element composition patterns beyond the lifespan of cells. They are the byproduct of skin metabolism and contain semi-rigid cornified cells with trace elements in the same ratio as in the cells from which they were generated (Howard C.Hopps 1977). The spatial pattern of element distribution in the nails and hair, then, reflects changes in the elemental composition of cells as a function of their growth rate and time (He 2011).

Nails have not been as thoroughly examined for element concentration as hair samples (Vance and Ehmann 1988). Even though, nails are still preferred to hair because nails are more resistant to external contamination (Karagas et al. 2000) and hair has a large range of biological factors that can affect elemental levels, such as their growth rate, length, type, and color (Sukumar 2002). On the other hand, the biological factors that influence the element content in nails are very few. Human nails have been used to evaluate the prevalence of diseases based on their elemental studies such as studies on alcoholism and drug addiction, patients suffering from diabetes and thyroidism (Vance, and Ehmann 1988; Karagas et al. 2000; Sukumar 2002; He 2011; Bahreini et al. 2013). In recent years, elemental studies of nails have gained much attention as indicators for human disease diagnosis (Bahreini and Tavassoli 2012; Bahreini et al. 2012, 2013; Martinez and Baudelet 2020).

Many researchers have analyzed human scalp hair to investigate the presence of heavy metal (Teresa et al. 1997; Apostoli 2002; Sera et al. 2002; Morton et al. 2002; Harkins and Susten 2003; Pereira et al. 2004; Agusa et al. 2005; Chojnacka et al. 2005; Rashed and Hossam 2007; Ferré-Huguet et al. 2009; Doğan-Sağlamtimur and Kumbur 2010; Onuwa et al. 2012). Onuwa et al. 2012 examined heavy metal elements in human hair samples and their association with age, height, and body weight. Hair samples are also useful to investigate the potential exposure of organic pollutants including polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyl (PCBs) to people living in e-waste recycling locations and employees involved in waste treatment and processing (Wen et al. 2008; Zhao et al. 2008).

Due to the similar structure and growth, nails and hair samples have been used together over the past few decades to measure elemental levels for the assessment of healthy biological functions, disease diagnosis, and human exposure to toxic elements and polluted environments (Mahler et al. 1970; Kumar and Sharma 2015). Even though hair and nails have comparable elemental structures, the intensity of the spectral lines related to carbon (C) and magnesium (Mg) has been observed to be higher in nail samples than in hair samples. In spite of the non-availability of matrix matched standards for nails and hair, quantitative studies of the elements present in hair and nails are possible using calibration-free laser-induced breakdown spectroscopy (CF-LIBS) (Gondal et al. 2010; Gondal et al. 2014a; Alhasmi et al. 2015; Gondal et al. 2016c; Almessiere et al. 2018). The analysis of nails and hair to monitor elements present in these samples can be done using a variety of analytical methods, such as atomic absorption spectroscopy (AAS) (Onuwa et al. 2012; Fleming et al. 2013; Salwa et al., 2014) and inductively coupled plasma mass spectrometry/optical emission spectrometry (ICP-MS/OES) (Golasik et al. 2015). However, there are many disadvantages to using these techniques to analyze nail and hair samples such as the complex and lengthy procedures of pretreatment of digestion, and the requirement of standard samples to generate calibration curves, which is difficult to acquire. Additionally, it is essential to create a vacuum or a particular atmosphere during the analysis processes. As compared with AAS and ICP-MS/OES, LIBS and XRF have many advantages over these techniques to analyze the nails and hair.

In recent years, analysis of hair and nails using LIBS and XRF has been reported. In 1981, X-ray fluorescence was used to measure the concentration of trace elements in human hair (Kubo 1981). Elemental analysis of women’s hair samples was used to predict breast hyperplasia and cancer (Kolmogorov et al. 2000). More recently, the elemental concentrations of nail samples of healthy and cancerous patients were successfully correlated with cancer development and disease (Al-saedi et al. 2020). In recent years, Almessiere et al. (2018) and Al-Najjar et al. (2022) also used CF-LIBS to know the level of elemental concentrations in hair and nails. Chemometric methods such as neural networks (NN) were also being used in combination with spectroscopic data to discriminate between samples, e.g., nails from smokers and nonsmokers (Suchoňová et al. 2014). Therefore, collating information on the elemental studies on nail samples using LIBS and XRF in one place would be potentially useful for their use in the context of disease diagnosis and forensic science.

Laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is an atomic emission technique for multi-elemental analysis that utilizes high-energy nano-, pico-, and femto-second laser pulses in order to create plasma by irradiating a variety of target materials (Cremers and Radziemski 2006; Gondal et al. 2014b; Musazzi and Perini 2014; Gondal et al., 2016b; Mehder et al. 2016a; Mehder et al. 2016b; Dakheel et al. 2020; Aldakheel et al. 2021a; Al-Najjar et al. 2022). As the laser intensity surpasses the target material breakdown threshold, the interaction of laser pulses with the sample produces hot plasma on the surface of the target. The atoms in the plasma generate spectral lines as it cools, which can serve as a “spectral signature” of the elemental composition of the target material. This method is fast and effective and capable of being used with a variety of materials, whether they are solid, liquid, or gaseous. The plasma can be recorded and analyzed in the form of a spectrum for qualitative and quantitative investigations of the samples. A schematic diagram of the instrumentation of LIBS is depicted in Fig. 1.

Fig. 1.

Schematic diagram of laser-induced breakdown spectroscopy (LIBS) to study biological samples such as hair and nails

The LIBS technique does not require any pretreatment of materials, in contrast to other methods of elemental analysis which makes LIBS a good choice for analyzing highly dense materials that are challenging to dissolve or digest. Hence, LIBS is an ideal method for analyzing dense biological materials like gallstones, kidney stones, nails, hair, teeth, cells, and even germs (Singh et al. 2008; Gondal et al. 2014a; Singh et al. 2014; Alhasmi et al. 2015; Almessiere et al. 2018). In addition to this, LIBS has also been used for the detection of toxic and carcinogenic elements in plants, herbal medicines, and cosmetic products (Singh et al. 2017a; Rehan et al. 2019; Aldakheel et al. 2020; Rehan et al. 2020; Aldakheel et al. 2021b; Aldakheel et al. 2022; Rehan et al. 2022). Due to its potential utility in numerous applications, LIBS has attracted attention as a diagnostic tool in biological studies (Jaswal et al. 2016a; Jaswal et al. 2016b; Singh et al. 2018). LIBS presents itself as a useful technique for elemental analysis of easily collected biological samples (such as nails and hair) (Kearton and Mattley 2008).

X-ray fluorescence spectrometry

X-ray fluorescence (XRF) spectrometry is a versatile and non-destructive technique employed for the qualitative and quantitative analysis of a variety of samples including biological and environmental materials. This technique is capable of detecting the presence of major, minor, and trace elements (West et al. 2012; Singh et al. 2017b; Bali et al. 2022; Singh et al. 2022a). XRF is based on the interaction of sample material with the incident X-rays of sufficiently high energy. After the interaction, secondary X-rays (fluorescent) are emitted that are characteristic of the elements present in the sample. The elemental composition and their concentration can be determined by analyzing the energy and intensity of the characteristic secondary X-rays. Since XRF has so many special features, it is now frequently used in applications requiring precise elemental analysis to adhere to stringent requirements at high concentration levels. A schematic diagram of the instrumentation of XRF is shown in Fig. 2.

Fig. 2.

Schematic diagram of wavelength dispersive X-ray fluorescence (WDXRF) spectrometry for analysis of hair and nails

The X-ray fluorescence technique is used in two modes mainly, energy dispersive mode (EDXRF) and wavelength dispersive mode (WDXRF). The main difference between these two types of XRF is the type of detector used. In energy dispersive X-ray fluorescence (EDXRF), semiconductor detectors with a high energy resolution are used whereas in WDXRF, crystal-based detectors are employed. Wavelength dispersive X-ray fluorescence (WDXRF) is not typically used as frequently as EDXRF (Beckhoff et al. 2006). Due to its non-destructive nature and the ability of both qualitative and quantitative analysis of elements ranging from Beryllium to uranium, many researchers have employed XRF for the analysis of biological samples such as nails, teeth, and hairs (Khuder et al. 2007; Maziar et al. 2015; Fleming et al. 2018; Santos et al. 2018; Singh et al. 2019; Al-saedi et al. 2020).

In this review article, we have tried to draw the attention of reader to the biological applications of LIBS and XRF for the analysis of hair and nail samples by gathering and presenting literature from the last 10 years. The published literature is divided into four sub-sections as follows: “Analysis of nails using LIBS,” “Analysis of hairs using LIBS,” Analysis of nails using XRF,” and “Analysis of hairs using XRF.”

Applications of LIBS and XRF for analysis of nail and hair samples

Analysis of nails using LIBS

Hamzaoui et al. (2011) used LIBS technique to study onychomycosis-affected nail samples by comparing the concentration of elements detected in nail samples with that of healthy nail samples of the same person. A clear distinction between normal and diseased nails in terms of the concentration distribution of sodium (Na), calcium (Ca), and potassium (K) was reported. For this, the authors used the B² Σ⁺→ X² Σ⁺ violet band of CN observed in the LIBS spectra of nail samples.

Pathak and Rai (2010) employed LIBS technique for the in vivo investigation of nail samples that are remodeled after injury. A noticeable variation in the concentration of elements such as Na, Ca, and K between normal and remodeled nails was reported in the study. The LIBS data were also subjected to principal component analysis (PCA) in order to distinguish between normal and injured nails. Hosseinimakarem and Tavassoli (2011) analyzed human fingernails using LIBS and detected the elements Ca, magnesium (Mg), Na, aluminum (Al), iron (Fe), titanium (Ti), strontium (Sr), and silicon (Si). The lighter elements such as carbon (C), oxygen (O), hydrogen (H), and nitrogen (N) were also detected in nail samples. Nail samples were divided into two groups based on gender and age. Discriminant function analysis (DFA) was used to discriminate the samples based on the concentrations of the detected elements. Higher concentration of Na and K has been found in the nail samples of patients suffering from hyperthyroidism as compared with the nails from a healthy person. From the Pearson correlations method, they found a positive correlation in the concentrations of Na and K and a negative correlation between Ca and Mg in the studied nail samples. Between men and women, they reported that the concentrations of Ca and Ti were higher in women whereas the concentrations of Fe, H, Mg, Al, Na, and K were higher in men. Shadman et al. (2012) also used DFA along with LIBS elemental data to discriminate the nail samples of opium-addicted persons. They compared the elemental concentration of the nail samples of opium-addicted people and healthy persons. Elements such as C, O, Ca, Mg, Ti, Si, Na, Al, H, and K along with CN were specifically analyzed in the nail samples. The authors observed no significant difference in the concentration of H, Na, K, and Mg. However, a noticeable difference was found in the concentration levels of Ca, Fe, C, O, Si, Al, and Ti in the nail samples of healthy and opium-addicted persons. The concentration of Ca and Fe was reported to be higher in healthy nails, whereas the concentration of C, Al, Si, and Ti was higher in nails of opium-addicted persons.

The LIBS technique is used by Bahreini et al. (2012) who find the relationship between the elemental composition of fingernails and osteoporosis. The authors analyzed nail samples of osteopenic and osteoporotic patients and then compared the results with that from the healthy persons. That study specifically detected the following elements: C, O, N, H, Ca, Na, Mg, Si, K, Sr, Al, Fe, and Ti. The Pearson correlations between nail element intensities and bone mineral densities (BMD) were calculated.

The LIBS technique was successfully used for the fast determination of lead (Pb) in human nails (Ye et al. 2012). The authors carried out the experiment under different optimum conditions for the nail analysis such as single laser pulse energy and time delay. Rusak et al. (2013) used LIBS technique to quantify Ca, Mg, and Zn in human finger nails.

Laser-induced breakdown spectroscopy (LIBS) has also been used to examine nail samples in an effort to diagnose thyroidism through nails (Bahreini and Tavassoli 2012). The authors collected the nail samples of patients with hypo- and hyper-thyroidism along with healthy persons for LIBS analysis and specifically analyzed for the elements C, O, Ca, H, K, Mg, Ti, Si, Na, Sr, Fe, Al, and N. The DFA method was used to discriminate the nail samples and reported 100% accuracy in the classification of nail samples by DFA (however, the sample size was very small). Higher levels of Na and K were observed in the nail samples of patients with thyroidism as compared with the healthy nails. Bahreini et al. (2013) also used LIBS technique in combination with DFA to discriminate fingernails of diabetic patients compared to healthy nails. The capabilities of LIBS for the analysis of nail samples in determining health issues were successfully shown. The authors concluded that monitoring the level of elements Mg, K, and Si in nail samples may help in the diagnosis of diabetes.

Bahreini et al. (2014) used LIBS to study nail samples of alcoholics and other drug addicted persons. Suchoňová et al. (2014) also employed LIBS technique in combination with the chemometric methods (neural networks) for the classification of fingernail samples. The following elements were specifically analyzed in nail samples: heavy elements Ca, Na, Mg, K, Si, Al, Ti, and Fe and lighter elements C, H, O, and Kumar and Sharma (2015) analyzed nails as well as hair samples using LIBS technique and reported similar elemental structures for both samples. Intense spectral lines corresponding to C, Ca, and Mg and weak lines corresponding to K and Na have been reported in the LIB spectra of hairs and nails. Despite similar elemental structure, the intensity of spectral lines corresponding to C and Mg has been reported to be higher in the nail spectrum than in hair samples. Harun et al. (2017) demonstrated that LIBS could be a useful technique for spotting different nail problems by analyzing elemental compositions of diseased and normal nail samples. In those studies, the elements Ca, Al, Mg, K, P, Na, and Ti were analyzed. The concentration of Al, Ca, K, P, and Ti was found to be higher in females, whereas Na and Mg were elevated in men. The authors reported the decreasing order of Ca and K with the age of the individuals and studied different defective nail samples involving conditions such as melanonychia, onycholysis, and Leukonychia. In comparison to normal nails, melanonychia nails were reported to have higher Ca and lower K levels. On the other hand, onycholysis nails had slightly lower intensity levels of almost all detected elements than normal nails. Mg concentration in leukonychia nails was reported to be higher than in normal nails while the concentration level of the other elements was the same.

Laser-induced breakdown spectroscopy (LIBS) in conjunction with specified isotope dilution mass spectrometry has been used by Riberdy et al. (2017) to quantify Zn in human fingernails. The authors showed the variation of LIBS signal intensity of Zn as a function of lateral distance across the fingernail. During LIBS analysis, the authors observed an exceptionally huge scatter, and scanning electron microscopy (SEM) studies revealed that this scatter was caused by the fingernails’ layered fibrous structure, which led to non-uniform ablation. They also showed that the energy-dispersive X-ray measurement of the Zn-Ka line strength superimposed on an SEM image of the nail with LIBS craters which was clearly visible. The impacts of nail surface roughness and nail hydration (dehydrated vs. overhydrated) on LIBS analysis of nail samples have been explained by the authors. Partial least squares regression (PLSR) model was used to the specified isotope dilution mass spectrometry (SIDMS) data.

Utilizing LIBS and ICP-AES, Almessiere et al. (2018) carried out elemental studies on nail samples and related the levels of mineral nutrients with deficiency of vitamin D. The mineral components detected using LIBS were Ca, O, Mg, K, Fe, Na, Ti, Cr, N, Cl, Zn, S, Cu, and P. Using LIBS, authors reported a negative correlation between vitamin D level and intensity of the K line. Recently, Martinez et al. (Martinez and Baudelet 2020) employed LIBS method to quantify Zn in human fingernails by creating a reliable matrix-matched material to draw calibration curves. In order to make a reliable matrix-matched material, the authors mixed zinc oxide nanoparticles with a solution of alginic acid and keratin, which was then cross-linked and dried to produce a rigid film. The similarity between the sample and reference material has been confirmed by obtaining the same-sized crater in both materials created after laser blasts under the LIBS settings (can be seen in Fig. 3). This experiment were carried out after optimizing the parameter gate width (GW) and gate delay (GD) in order to obtain the optimal LIBS signal using a factorial approach with the reference material at highest Zn concentration (182 μg g⁻¹). Figure 4 shows the signal-to-noise ratio (SNR) of the 213.85 nm Zn I line as a function of GD and GW. Furthermore, the authors used this matrix-matched material to generate a calibration curve and quantified Zn in nail samples which were further verified with the results obtained using ICP-MS.

Fig. 3.

Crater morphology obtained by digital microscopy for (a) fingernail sample and (b) matrix-matched reference material after 10 laser shots. (c) Photograph of the reference material. The black scale bar represents 1 cm. Reproduced from Martinez et al. (Martinez and Baudelet 2020) with the permission from Elsevier

Fig. 4.

Signal-to-noise ratio of Zn I signal as a function of LIBS detection parameters for a matrix-matched reference material. The inset shows the LIBS spectrum at optimized condition. The pink region is the spectral range in which the noise for SNR is evaluated. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.). Reproduced from Martinez et al. (Martinez and Baudelet 2020) with the permission from Elsevier

Analysis of nails using XRF

Katsikini et al. (2010) studied the distribution of Fe and observed the changes in the bonding environment and valence of Fe which were correlated with a concentration in fingernails by using micro-XRF (μ-XRF) and μ-X-ray absorption near edge structure (μ-XANES) techniques. They studied the nail samples of healthy and lung cancer-affected persons. The authors reported the presence of spots of Fe where its concentration is more than six times its concentration in other locations within the sample and showed that Fe has a propensity to concentrate in certain areas with concentrations that are roughly six times higher than rest of the sample. The sample from a lung cancer patient appears to have a somewhat higher spatial density than those from healthy donors, despite the fact that there is no clear variation in the size distribution of the iron-rich patches.

Pearce et al. also used μ-XRF and μ-XANES to investigate the distribution and valance of arsenic (As) present in the toenail samples of children living near gold mining areas. The existence of two different As species in nail samples was reported, one with a lower oxidation state and perhaps mixed sulfur and methyl coordination, and the other with a higher oxidation state. The distribution of Cu, Zn, and Ca was also reported using SR-XRF. The authors also studied the soil samples of that area and concluded that children who lived near gold mining areas were more likely to absorb arsenic from the soil (Pearce et al. 2010).

Uo et al. (2010) used XRF and X-ray absorption fine structure analysis (XAFS) to investigate the presence of Zn in discolored nails (yellow and blacked). The authors reported that a portion of the yellow nails had a significantly greater Ca content than the normal nails, whereas the nails that were black had more Ca and Zn. They also found a higher concentration of S in normal nails compared to discolored nails. Zn in yellow nails was at a level akin to that of normal nails.

Gherase and Fleming (2011) proposed a calibration technique for XRF analyses of nail samples based on their mass. As and selenium (Se) were frequently discovered in human nails and quantified by drawing the calibration curves. In 2013, Fleming et al. employed portable-XRF (pXRF) to measure the elemental concentrations in nail samples using the calibration method (Fleming et al. 2013). Gherase et al. (2013) investigated the micro-distribution of As in nail samples using nail samples of healthy persons using XRF technique. The calibration method was used to estimate the concentration of As in nails. Those authors used the same technique as used by Gherase and Fleming (Gherase and Fleming 2011) to create nail phantom clippings with varying As concentrations. These phantom clippings were utilized to develop a calibration line for the K_α peaks corresponding to As. From the obtained results, they concluded inhomogeneous distribution of Asin the nail samples with As accumulation predominantly in the ventral and dorsal sections of human nails.

Figueroa et al. (2014) employed in vivo element scan analysis to study the human nail samples with a specially designed EDXRF spectrometer. The elements detected in this study include Ca, S, Cu, Zn, Pb, Fe, and Ti. On a whole nail sample, the authors employed a bidimensional (x,y) scan that allowed the 2D spatial distribution of the identified elements within the nail samples (Fig. 5). They reported that the majority of the elements were distributed irregularly throughout the nail, with varying concentrations. Fe and Cu have been reported to be concentrated more strongly near the proximal end of nail samples. At the distal end of the nail, Zn and Ca have been reported to be present in larger concentrations than in other areas of the nails. Pb has been reported to be more concentrated at the proximal and distal ends, whereas S has been reported to be distributed evenly throughout the nail samples.

Fig. 5.

EDXRF images showing the bidimensional distribution of sulfur (S), calcium (Ca), iron (Fe), copper (Cu), zinc (Zn), and lead (Pb) in whole nail. Reproduced from Figueroa et al. (2014) with the permission from John Wiley & Sons

Roy et al. used a new approach for the measurement of As and Se levels in nail phantoms simultaneously. A portable X-ray tube and a PiN diode detector were used by the authors in this study. To replicate the attenuation characteristics of the human nails, a two-component nail substitute was selected. The mass of the nail substitute was composed of a polyester resin content of 95% and a table salt content of 5%. Using this approach, they obtained good minimum instrumental detection limits for nail phantoms having different thicknesses (Roy et al. 2010). A portable XRF device was also recently used by Specht et al. for the in vivo toenail measurements of Mn and Hg in the toenails of welders and nail salon workers. The detection limits achieved by this XRF approach were 0.5 μg/g and 2.6 μg/g for Hg and Mn respectively (Specht et al. 2021).

Fleming and Ware (2017) used pXRF method to investigate Cr content in human nails by analyzing human nails and phantoms’ nail samples. Phantom nails having different chromium (Cr) concentrations were used to create a calibration line. In order to create the calibration lines, they plotted the amplitude of the K_α line corresponding to the Cr with respect to the concentration of Cr. By using this method, the authors successfully achieved the minimum detection limit (LoD) of ~1.2 μg/g for Cr detection in human nails. Using pXRF, Zhang et al. (2018) performed non-invasive and in vivo mercury (Hg) and manganese (Mn) quantification in human toenail samples. The development and validation of the approach, which takes into account system calibration, spectrum analysis, the impact of the nail thickness, and the system’s detection limit, were the key areas of focus in this work. The authors developed phantom nails doped with Hg and Mn and generated calibration curves for the quantification of the elements. The authors achieved the detection limit of around 3.65 μg/g for manganese and for mercury, the detection limit achieved was ~ 0.55 μg/g. Fleming et al. (2018) also evaluated the viability of employing a pXRF instrument to measure the concentration of Zn in human fingernails and toenails.

Specht et al. (2018) compared the results of XRF analysis and ICP-MS for the detection of metals in toe-nail clippings. In this investigation, the authors took toenail samples from 20 people living in a polluted region of Nigeria and analyzed these samples for investigating the Pb and Mn contents in toenails using ICP-MS and XRF. A unique calibration approach was used that reduced the variability in XRF measurements of toenail clippings by calibrating for the weight and thickness of the toenail. In this work, the authors have utilized the pXRF technique to quantify the level of metals (Pb and Mn) present in nail clippings with a detection limit of 0.6 μg/g for Pb and for Mn, the detection limit achieved was ~3.2 μg/g. Strong correlations between the concentrations of Mn present in toenail clipping acquired from XRF results and ICP-MS results were reported. Since the concentration of Pb in the nails was lower than the detection limit of the portable XRF, a weaker correlation between XRF and ICP-MS was reported for Pb (Specht et al. 2018).

Hamouda and Sharaf el-Din (2019) studied the nail and hair samples of males and females from Kassala, Sudan, and detected metal elements Fe, Zn, Pb, and Cu in nail samples using XRF technique. Fe was reported to have the highest concentration of the four detected elements in fingernail samples, followed by Cu and Zn, and Pb. Cu and Fe were reported to be higher in males than in females, whereas Pb was the same in both sexes. Whereas, Zn levels have been reported higher in the nails of females than that in the nails of males.

Recently, Al-saedi et al. (2020) used XRF technique to measure the concentration of trace elements in nail samples of cancer patients and healthy persons and reported a difference between them. The specific elements analyzed were Ca, Si, Mg, Se, K, Fe, Cu, Pb, Zn, Cr, Cd, Mn, and As. Average concentrations of elements Ca, Si, Mg, K, Se, and Fe were found lower in nail samples of cancer patients than that in healthy persons, whereas the average concentrations of Mn, Pb, Zn, Cd, Cr, and Cu were found higher in nail samples of cancer patients.

Recently, Bhatia et al. used the pXRF technique to determine the concentration of trace elements Ni, Zn, As, Pb, and Se in human toenail samples and verified from ICP-MS which is in good agreement. The measurements of Zn, Ni, and Pb using Passing-Bablok regression revealed that the XRF and ICP-MS analysis methods might be used interchangeably (Bhatia et al. 2021).

Analysis of hairs using LIBS

Hair is another target tissue for LIBS analysis because of the higher concentration of trace minerals in hairs as compared with other biological tissues. Ohmi et al. (2000) explored the capabilities of LIBS technique for the analysis of calcified tissue samples including hairs. They reported the detection of Ca in calcified tissues such as hairs, nails, and teeth samples with high sensitivity. The authors reported the decreasing pattern of Ca in hair samples with the age which is in good agreement with the available medical reports. Ca along with C and Na were also detected in human hair and nails using LIBS by Haruna et al. (2000). The authors demonstrated that the determination of Ca in hair samples may be a tool to monitor the daily intake of Ca and also for the detection of osteoporosis.

Calibration-free LIBS (CF-LIBS) has proven it is suitable for the quantitative measurements of minerals in biological samples where certified matrix matched reference materials are not available for a proper calibration approach. It is a very promising technique for hair tissue mineral analysis (HTMA). CF-LIBS technique was used by Corsi et al. (2003) for HTMA. The authors measured the concentrations of Na, Mg, K, and Ca, by analyzing the intensity ratios of Na/Mg, Na/K, and Ca/K in the LIBS spectra of hair samples.

The potential of LIBS for the diagnosis of cancer has been demonstrated by Kumar et al. (Kumar and Sharma 2006). The LIBS technique has been used as an automated, real-time diagnostic approach for cancer, considerably facilitating the identification and categorization of the disease. A considerable difference in trace element levels between tissue cells from malignant and healthy tissue has been reported. It has been noted that normal cells have a higher concentration of trace elements like Ca, Fe, and Na than malignant cells. The spectral lines in the LIB spectra of hairs and nails have also been observed by the authors, where they reported higher C and Mg in nails as compared to hair samples.

Recently, Zhang et al. (2020) used LIBS technique in combination with ultrasound-assisted alkali dissolution and reported the presence of Cu and Zn in human hairs and precisely quantified these elements. The achieved LoDs for Cu and Zn reported were 0.3517 μg/g and 0.0146 μg/g respectively. The results obtained were in good agreement with results from ICP-OES.

Zhang et al. (2021) developed the CF-LIBS method for the quantitative analysis of hair and nail samples. Figure 6 shows the LIB spectra of hair, silicon wafer, and nails indicating the presence of mineral elements Ca, Mg, and Na along with C, H, and O. The intensity ratio Ca/Na and Mg/Na method was used to measure the relative concentrations of the elements present in hair and nails and the results obtained from LIBS were compared with the results from ICP-OES. The authors reported the accuracy of CF-LIBS in association with the standard reference line method after observing less than 10% relative error in the concentration of elements detected by CF-LIBS and ICP-OES techniques (Zhang et al. 2021). Finally, the authors explored the capability of LIBS as an alternative technique for the future medical detection of nutrition and diseases.

Fig. 6.

LIBS spectra of (a) hair (b) silicon wafer, (c) and nail. Reproduced from Zhang et al. (2021) with the permission from Elsevier

In situ analysis of trace minerals in human hair was recently carried out by Nakagawa et al. (Nakagawa and Matsuura 2021) using LIBS by utilizing a microchip laser for plasma creation. The intensity of C in the LIB spectra was used as a reference to determine the relative mass concentrations of Mg, Ca, and Zn in hair collected from five persons. The authors reported the LoDs of the proposed system for Ca, Mg, and Zn as710 ppm, 9.0 ppm, and 27 ppm respectively.

Analysis of hairs using XRF

Nowadays XRF technique has gained much attention for HTMA. Kubo et al. (Kubo 1981) investigated the concentration of trace elements in human hair using XRF and proposed a method to reduce the attenuation of the characteristic X-rays having low energies. Toribara (1995) used XRF to investigate trace elements in hair samples at different distances on the hairs from the root ends. They were able to quantify the elements Hg, Zn, Fe, and Cu at different positions on hair samples.

Kolmogorov et al. (2000) investigated the role of trace elements in breast hyperplasia and cancer by analyzing women’s hairs using EDXRF and synchrotron radiation-XRF techniques. The findings of the study showed that Se and Zn levels significantly drop in people with mammary gland oncological disorders whereas Cr levels rise. Among those who have breast cancer, the Se deficiency is more noticeable compared to those with breast hyperplasia. Carvalho et al. (Carvalho et al. 2003) also studied bone and hair samples by SR and EDXRF techniques and quantified a large number of elements including Ca, Mn, Zn, Sr, Cu, K, Fe, As, Se, Br, Pb, and Rb.

Baranowska et al. (2004) investigated the elemental composition of hairs and teeth using XRF technique specifically examining Ca, Sr, Fe, Na, K, Pb, Mg, P, S, Cu, Zn, and Mn. The XRF results obtained for hair and teeth samples were verified using the ICP-OES technique. The authors were able to establish a relationship among the concentrations of the elements with age, sex, smoking history, and as environmental contaminants. The concentrations of S, Na, and K were found lower in hair samples of females and the concentrations of Cr, Mg, Sr, Ni, and Cd were found lower in the hair samples of males. Age-related changes in hair composition included a rise in Fe and Cd content, a decrease in Ni and Ca content, and an increase in Cr and K content followed by a drop at the age of 60.

To distinguish contaminations caused by toxic metal in human hairs resulting from endogenous uptake from a person exposed to a polluted environment, Kempson et al. used a combination of different techniques including SEM-EDX, SR-XRF, and time-of-flight secondary ion mass spectrometry (ToF-SIMS) (Kempson et al. 2006). The elements detected in hair samples included Na, Cl, Si, Al, S, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Se, and Pb. The different elemental distribution patterns at the outer layer of the hair samples elemental were reported using ToF-SIMS imaging method. Khuder et al. performed multi-elemental analysis of human hair and blood samples by using XRF and total reflection XRF (TXRF). The authors employed different secondary targets for the X-ray excitations such as Mo- and Cu-secondary targets and measured the LoDs for different elements and showed the suitability of different secondary targets. For example, the authors reported that for the analysis of Cu, Br, Zn, Rb, and Fe with a Mo-secondary target, the LLD value was 1.0 μg/g and for Ca, K, Ti, Mn, and Cr, Cu-secondary target was a better choice. Using TXRF, they obtained quantitative results for Ca, S, P, K, Fe, Br, Rb, Ni, Cu, Zn, and Pb in blood and for Ni, Fe, Zn, Cu, Sr, and Pb in hair samples (Khuder et al. 2007).

The micro-XRF imaging method has been used to reveal new details on the Ca status in human scalp hair. In addition to this, the information about the distribution of Ca across the hair section and the occurrence of its bonding types was also deduced. In this study, two distinct forms of Ca were reported to be found in scalp hair, with one relating to atoms (or ions) that hydrochloric acid may readily dissolve and that are found in the interior of the medulla, in the cortex (granules), and in the cuticle zone. The second type consists of Ca atoms (or ions) that are difficult to remove and are found in the cortex, the cuticle, and the medulla wall (Mérigoux et al. 2003).

Khudzari et al. (Khudzari et al. 2011; Khudzari et al. 2013) investigated the presence of heavy metal elements such as Cu, Ni, Mn, Zn, and Fein the hair samples of sanitation workers using EDXRF and compared the level of metal elements in the hairs of sanitation workers and a control group. A higher concentration of Zn, Fe, and Cu and a lower concentration of Ni were observed between sanitation workers and the control group. Additionally, Cu was found in higher concentration as compared to other elements in the hair samples of both exposed and healthy persons. Mn was found to be the same in both groups. Onawa et al. (Onuwa et al. 2012) used EDXRF to examine heavy metals Cu, Mn, Zn, Mo, Ni, and Cr in human hair samples and reported their associations with age, height, and body weight. The higher mean concentrations of Ni, Zn, and Mn were reported in males whereas higher mean concentrations of Cu, Mo, and Cr were observed in females.

Aldroobi et al. (2013) used the XRF technique as a method of assessing potential exposure to contaminants in the form of undesired trace elements. Thus, to determine the potential levels of human contamination, the authors examined As and Hg contents in the scalp hair samples of Malaysian residents (Aldroobi et al. 2013).

Maziar et al. (2015) investigated the capabilities of WDXRF for early-stage breast cancer diagnosis and compared the results with those obtained from other common diagnostic techniques like mammography and reported the lower concentrations of P, Ca, Mg, and Zn in the hairs of cancerous patients as compared to that from healthy persons. This study showed the better suitability of XRF to diagnose breast cancer with a sensitivity of about 96% which is much better than XRD and mammography. Santos et al. (2018) performed a study investigating the effect of cosmetic treatment on human hairs employing WDXRF with principal component analysis (PCA). The detected elements were Fe, Ca, Si, Cu, and K. In order to develop a prostate cancer screening tool, Birgani et al. (2020) used XRF technique and signal processing methods to measure trace elements in scalp hairs. Santos and Pereira (Santos and Pereira 2020) studied the hair samples to investigate the elemental changes occurred in human hairs after hair modifications using WDXRF in combination with LIBS. The authors used chemometric method PCA for the LIBS data and successfully discriminated the bleached and modified hair samples.

Very recently Bolortuya and Zuzaan (2022) presented an XRF analysis method to analyze hair samples (including sample preparation methods). The authors showed two images of single hair fiber on the flat measured by EDX-SEM (Fig. 7). The authors recorded the X-ray spectra (Fig. 8) of hair fibers measured by EDXRF with Mo secondary target as excitation source. In the spectra (Fig. 8), characteristics X-ray lines of Ca, Zn, S, Sr, and Br in hair samples are highly detected. The authors study revealed the suitability of XRF technique for hair trace element analysis.

Fig. 7.

EDX-SEM images showing surface morphology of hair samples (×800) and (×3000). Reproduced from Bolortuya and Zuzaan (2022) with the permission from John Wiley & Sons

Fig. 8.

Comparison spectra of hair single fibers (EDXRF with Mo secondary target). Reproduced from Bolortuya and Zuzaan (2022) with the permission from John Wiley & Sons

In Tables 1, 2, and 3, we have summarized the key summary of elemental studies of hairs and nails using LIBS and XRF techniques. These techniques have great potential for disease diagnosis in humans. The detailed analytical performances of LIBS and XRF techniques for elemental quantifications of calcified tissue samples including nails and hairs and detailed comparison with other existing advance spectroscopic techniques can be found elsewhere (Rawat et al. 2022; Singh et al. 2022b). For elemental imaging, the special resolution of LIBS and XRF techniques has also been summarized by Rawat et al. (2022) and compared with other imaging techniques. This literature review has indicated that the development of highly sensitive LIBS and XRF spectrometers, as well advanced LIBS and XRF techniques will one day dominate for the analysis of bio-compatible samples in various fields such as clinical diagnostics, forensic, and environmental applications.

Table 1.

Summary of the analysis of nails and hairs using LIBS and XRF for disease diagnosis purposes

Diseases	Samples analyzed	Techniques	Key results	References (Authors et al. year)
Breast hyperplasia and cancer	Women hairs	XRF, SRXFA	Se deficiency is more noticeable in patients with breast cancer as compared to breast hyperplasia	(Kolmogorov et al. 2000)
Lung cancer	Fingernails	μ-XRF, μ-XANES	The presence of spots of Fe in higher concentration as compared with other remaining sample	(Katsikini et al. 2010)
Discolored nails	Fingernails	XRF, XAFS	Different chemical species of Zn in black colored nail samples	(Uo et al. 2010)
Onychomycosis	Fingernails	LIBS	Higher concentration of Na and Ca in affected nails	(Hamzaoui et al. 2011)
Osteoporosis	Fingernails	LIBS	Correlations between the levels of Na, Ca, Fe, Mg, and bone mineral density (BMD)	(Bahreini et al. 2012)
Thyroidism	Fingernails	LIBS, DFA	Higher levels of Na and K in nails samples of thyroidism	(Bahreini and Tavassoli 2012)
Diabetes	Fingernails	LIBS	Mg, K, and Si in nails as an indicator of diabetes	(Bahreini et al. 2013)
Leukonychia and melanonychia nails	Fingernails	LIBS	Higher Ca and lower K levels in melanonychia nails	(Harun et al. 2017)
Vitamin D deficiency	Fingernails	LIBS, ICP-AES	Negative correlation between the vitamin D and K	(Almessiere et al. 2018)
Cancer	Fingernails	XRF	Higher level of trace elements Mn, Pb, Zn, Cd, Cr, and Cu in nails of cancer patients	(Al-saedi et al. 2020)
Cancer	Scalp hairs	XRF and signal processing	Significant difference in P, Al, and Si in hairs of healthy and cancer patients	(Birgani et al. 2020)

XRF, X-ray fluorescence; μ-XRF, micro-X-ray fluorescence; SRXFA, synchrotron radiation X-ray fluorescence analysis; μ-XANES, micro-X-ray absorption near edge structure; XAFS, X-ray absorption fine structure analysis; LIBS, laser-induced breakdown spectroscopy; ICP-AES, inductively coupled plasma atomic emission spectroscopy; DFA, deterministic finite automata

Table 2.

Summary of key results of XRF studies carried out on hairs and nails and the detected trace elements

Elements detected	Samples analyzed	Techniques	Key results	References (Authors et al. year)
Hg, Zn, Fe, and Cu	Human hairs	XRF	Trace elemental investigation	(Toribara 1995)
Se and Zn	Hairs	ED-XRF, SRXFA	Significantly drop of Se and Zn in persons with mammary gland oncological disorders	(Kolmogorov et al. 2000)
Fe	Fingernails	XRF	Investigation of Fe spots	(Katsikini et al. 2010)
As	Toenail	XRF	Different species of As	(Pearce et al. 2010)
Zn	Nails	XRF, XAFS	Different chemical species of Zn in black colored nails	(Uo et al. 2010)
Cu, Ni, Mn, Zn, and Fe	Hairs	EDXRF	Higher amount of Zn, Fe, and Cu in hairs of sanitation workers	(Khudzari et al. 2011)
As and Se	Nails	XRF	Calibration approached for elemental quantification in XRF of nail samples	(Gherase and Fleming 2011)
Zn and Mn	Phantom nail	Portable XRF (pXRF)	Elemental concentration of nail samples	(Fleming et al. 2013)
As	Nails, phantom clippings	XRF	Estimation of the elemental concentration of nail samples	(Gherase et al. 2013)
Cr	Nail, phantom nails	pXRF	LoD ~ 1.2 μg/g for Cr in nail sample	(Fleming and Ware 2017)
Hg and Mn	Human toenail	pXRF	LoDs for Mn ~ 3.65 μg/g and for Hg ~ 0.55 μg/g	(Zhang et al. 2018)
Ca, Si, Cu, and K	Hairs	WDXRF, PCA	Varying levels of Ca, Si, Cu, and K	(Santos et al. 2018)
Ni, Zn, As, Pb, and Se	Human toenail	pXRF, ICP-MS	Elemental quantification using XRF and ICP-MS	(Bhatia et al. 2021)

XRF, X-ray fluorescence; EDXRF, energy-dispersive X-ray fluorescence; WDXRF, wavelength-dispersive X-ray fluorescence; SRXFA, synchrotron radiation X-ray fluorescence analysis; XAFS, X-ray absorption fine structure analysis; PCA, principal component analysis; ICP-MS, inductively coupled plasma-mass spectroscopy

Table 3.

Summary of the LIBS studies of human nails and hair samples

Elements detected	Samples analyzed	Techniques	Key results	References (Authors et al. year)
Ca	Hairs	LIBS	Elemental analysis of hairs using LIBS	(Haruna et al. 2000)
Ca	Hairs	LIBS	Variation of Cain hairs with age	(Ohmi et al. 2000)
	Hairs	CF-LIBS	Elemental analysis of hairs using LIBS	(Corsi et al. 2003)
Na, Ca, and K	Nails	LIBS, PCA	Noticeable variations in the levels of Na, Ca, and K in normal and remodeled nails	(Pathak, 2010)
C, Al, Si, and Ti	Nails	LIBS, DFA	Higher levels of C, Al, Si, and Tiin the nail of opium addicted persons	(Shadman et al. 2012)
Pb	Nails	LIBS	LIBS-based detection of Pb in nails	(Ye et al. 2012)
Zn	Nails	LIBS, ICP-MS	Quantification of Zn using LIBS and ICP-MS	(Martinez and Baudelet 2020)
Cu and Zn	Hairs	UAAD-LIBS	LoDs for Cu ~0.3517 μg/g and for Zn ~ 0.0146 μg/g	(Zhang et al. 2020)
Ca, Mg, and Zn	Hairs	LIBS	LoDs for Ca ~ 710 ppm,for Mg ~9.0 ppm and for Zn ~ 27 ppm	(Nakagawa and Matsuura 2021)

LIBS, laser-induced breakdown spectroscopy; CF-LIBS, calibration-free laser-induced breakdown spectroscopy; PCA, principal component analysis; DFA, deterministic finite automata; ICP-MS, inductively coupled plasma-mass spectroscopy; UAAD-LIBS, ultrasound-assisted alkali dissolution-laser-induced breakdown spectroscopy

Conclusion

LIBS and XRF techniques are highly suitable for the elemental analysis and imaging of human hairs and nails. LIBS and XRF are complementary techniques and are competitive to other existing analytical techniques for the analysis of bio-compatible samples like human nails and hairs. We have collected the most prominent references over a 10-year period. Detecting heavy and trace minerals in hairs and nails can reveal the disease status of humans. In the described publications, authors have correlated the levels of elements present in hairs and nails with the disease type and stage. LIBS and XRF have been shown as useful as continuous monitoring analytical tools in medical science to track the elemental status and changes in hairs, nails, and other human biological tissues.

Author contribution

All authors contributed equally.

Declarations

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publish

Yes

Competing interests

The authors declare no competing interests.