SPECIAL ISSUE PAPER

E. A. Preoteasa Æ Rodica Georgescu Æ C. CiorteaDaniela Fluerasu Æ Livia Harangus Æ Andreea Iordan

Feride Severcan Æ Handan Boyar Æ Elena Preoteasa

I. Piticu Æ D. Pantelica Æ Vl Gheordunescu

Standardless PIXE analysis of thick biomineral structures

Received: 10 December 2003 / Revised: 6 April 2004 / Accepted: 20 April 2004 / Published online: 4 June 2004

� Springer-Verlag 2004

Abstract The particle-induced X-ray emission (PIXE) ofthick biomineral targets provides pertinent surfaceanalysis, but if good reference materials are missing thencomplementary approaches are required to handle thematrix effects. This is illustrated by our results fromqualitative and semiquantitative analysis of biomaterialsand calcified tissues in which PIXE usually detected upto 20 elements with Z > 14 per sample, many at tracelevels. Relative concentrations allow the classificationof dental composites according to the mean Z and bymultivariate statistics. In femur bones from streptozo-tocin-induced diabetic rats, trace element changesshowed high individual variability but correlated to eachother, and multivariate statistics improved discrimina-tion of abnormal pathology. Changes on the in vitrodemineralization of dental enamel suggested that a dis-solution of Ca compounds in the outermost layer resultsin the uncovering of deeper layers containing highertrace element levels. Thus, in spite of significant limita-tions, standardless PIXE analysis of thick biomineralsamples together with proper additional procedures canprovide relevant information in biomedical research.

Keywords PIXE Æ Trace elements ÆBiomaterials Æ Dental enamel Æ Bone Æ Multivariatestatistics

Abbreviations AAS: Atomic absorption spectrometry ÆERDA: Elastic recoil detection analysis Æ ESR: Electronspin resonance Æ FDA: Factorial discriminantanalysis Æ FTIR spectroscopy: Fourier transform infra-red spectroscopy Æ HP Ge detector: Hyperpure Gedetector Æ ICP-AES: Inductively coupled plasma atomicemission spectrometry Æ NAA: Neutron activationanalysis Æ NRA: Nuclear reaction analysis Æ PCA:Principal component analysis Æ PIXE: Particle-inducedX-ray emission Æ PIGE: Particle-induced c-rayemission Æ RBS: Rutherford backscatteringspectroscopy Æ SRIXE: Synchrotron radiation-inducedX-ray emission

Introduction

Particle-induced X-ray emission (PIXE) is a robustmethod that integrates both spectrochemical and ionbeam features. Energy-dispersive detection PIXE classi-fies as a notably sensitive, multielemental, convenientlyspecific, and relatively nondestructive instrumental tech-nique, able to analyze a thin layer at the specimen’s surfaceand to cover a high dynamic range of values in its spectra[1–4]. Like other nuclear andatomic analyticalmethods, itcan give relevant information on major to trace elementsin biomedical applications [5, 6]. This is particularly truein the study of solid and heterogeneous specimens, such asteeth, bones, and biomaterials, as PIXE is ideally suitedfor the thin-layer analysis of their surface and in assessingthe changes of the latter. Biomineral structures of thiskind [7–9] have in common inorganic (dominant) andorganic parts, and all show composite-like structures,with nanometric to micrometric mineral particlesembedded in protein or synthetic polymer matrixes. Atthe same time, the mineralized tissues undergo changes innormal or pathologic decalcification and (re)calcification

E. A. Preoteasa (&) Æ R. Georgescu Æ C. CiorteaD. Fluerasu Æ L. Harangus Æ A. IordanI. Piticu Æ D. PantelicaHoria Hulubei National Institute for Physics and NuclearEngineering, P.O. Box MG-6, Magurele,76900 Bucharest, RomaniaTel.: +40-21-4042300Fax: +40-21-4321701E-mail: eugpre@ifin.nipne.ro, eugen_preoteasa@yahoo.com

F. Severcan Æ H. BoyarDepartment of Biology, Faculty of Science,Middle East Technical University,06531 Ankara, Turkey

E. PreoteasaHelident Dental Surgery Ltd., 10 M. Eminescu,2150 Campina, Romania

V. GheordunescuInstitute of Biochemistry, 296 Spl. Independentei,77700 Bucharest, Romania

Anal Bioanal Chem (2004) 379: 825–841DOI 10.1007/s00216-004-2656-4

processes, while composite biomaterials are submitted tochemical and mechanical degradation during their dentaland medical use.

The preparation of biomineral systems for PIXE inthe form of thick samples is remarkably simple, pre-serves the natural state of the specimens, and accountsbest for the surface when different from the bulk. Thisapproach is most convenient when qualitative PIXEanalysis is consistent by itself owing to the method’ssensitivity for trace elements. In fact, fast trace elementdetection at the surface of biomineral structures bythick-target PIXE analysis may be useful in finding outmany pertinent characteristics of the specimens. Thus,trace elements help us to understand the influence ofbiologically relevant processes, pathology, medicaltreatment, and of preparation techniques in many fieldsof life sciences [5, 6, 10, 11], including in calcified tissuesresearch. Also, they may be valuable fingerprints in theidentification of biomaterials and in checking theirpurity and in following element transfer at the interfacewith the tissues. Usually we detected up to 18 or moreelements with Z > 14 per biomineral sample, many ofwhich were at trace levels (e.g., in dental composites andemamel and in bones from diabetic rats showing oste-oporosis).

However, a more consistent PIXE approach of thick-target mineralized tissues and biomaterials resides in the(semi)quantitative evaluation of changes and differencesat their surface. It has been remarked that the realpotential of PIXE emerges of with biomineral systems[12], but quantitative thick-target PIXE analysis raisesserious issues, especially when appropriate referencematerials are missing and physical calculations arerequired [1–4, 12–17]. It faces difficulties due to matrixeffects, meaning that absolute element concentrationanalysis needs corrections dependent in turn on theunknown concentrations. Therefore, PIXE analysis of athick target surface is neither a common problem nor aminor digression from the thin target case where matrixeffects are neglected [12]. Yet, during recent years a largebody of PIXE studies on thick targets has providedhighly relevant information in a diversity of biologicalapplications [18–24]. To evaluate element concentrationsfrom the peak areas, procedures are needed to establishthe X-ray yield function converting the latter to theformer. If reference materials with similar compositionand structure are lacking, one is compelled to resort toalternative approaches, such as corroborative evidencefrom other ion beam analysis methods with lower matrixeffects. But these procedures can be more or less inac-curate and a combination of more than one with PIXEmay be the best choice. Still accurate absolute concen-trations are hard to get in a standardless PIXE analysis[25, 26] and, without the use of advanced computerprograms based on developments in thick-target analysis[27–30], frequently one is limited to relative concentra-tions. These are relevant in practice and can be obtainedfor thick targets by various experimental and theoreticalstratagems related to the abovementioned approaches.

Thick-target PIXE (and micro-PIXE) has beenwidely utilized for the investigation of biologically andmedically relevant structures containing inorganic com-ponents, both of natural and artificial origin. Studies ofdental biomaterials, enamel, and bones illustrate thisimage. Thus, in the analysis of dentistry materials and oftheir interactions with the oral environment, PIXE hasbeen applied to follow the release of metals fromamalgam fillings [31, 32] and titanium dental implantsinto the hard tissues [18, 19], and we have further usedPIXE along with elastic recoil detection analysis(ERDA) and X-ray fluorescence (XRF) for the charac-terization of dental composites [33–35]. In other appli-cations on human enamel, PIXE helped correlate thetrace elements with the caries score, age, and gender ofsubjects [36, 37], evidence concentration changes of traceelements in decayed teeth [38], demonstrate distributionchanges after CO2-laser irradiation [39], and identify anancient tooth inlay [40]. In bone research, PIXE wasemployed to evaluate trace element levels in bones fromcontemporary man [41] and from ancient humans [41,22], to evidence calcium changes in chronic renal failure(including hemodialyzed patients) and in osteomalacia[42], to estimate the effects of estrogen preventivetreatments in rats with osteoporosis [20], and to assessforensic cases [21]. Another calcified tissue biologicallyrelated to bone is cartilage, and its changes in arthrosiswere examined with PIXE [43]. In addition, new appli-cations may emerge in the field of biomineral structures(e.g., for the recently engineered bone and cartilagesubstitutes [44]). But also, significant questions remainto be answered by PIXE on most systems of interest toour group. In particular, dental composites develop at ahigh rate [45] and their analysis by this method is a newapplication that may be a useful prerequisite to subse-quently approach their long-term alteration and possiblerole in the formation of secondary caries around dentalfillings [46]. Moreover, the incipient demineralization ofdental enamel leading to caries formation in theaggressive milieu of the oral cavity [47, 48] has not beenstudied so far by PIXE. Likewise, application of thistechnique to the characterization of bones from animalssuffering from osteoporosis as a complication in exper-imentally induced diabetes may help our understandingof the changes affecting the metabolism of Ca, P, andtrace elements in this disease and may be correlated toalterations shown recently in bone by FTIR [49].

Here, the above-discussed ideas are illustrated basedon recent and preliminary results that we obtained fromstandardless thick-specimen PIXE measurements ondental composites, enamel, animal and human bones,and a regenerative biomaterial. The results point to twomain concepts, emerging partly as well from previousreports from our group [33–35, 50–52]: (a) that a numberof approaches and approximations currently at handenhance the potential of PIXE in the thick-target studyof biomineral systems, and (b) that both the corre-sponding qualitative and semiquantitative analysis mayyield medically and biologically relevant insight into

826

these systems and their changes. The present paper isbased on two recent conference communications [53,54].

Experimental

Materials and target preparation

Thick dental composite samples with a flat surface wereprepared by polymerization of ten types of commercialWestern materials (labeled I–X, of which four were intwo color shades noted a and bto give a total of 14specimens, as described before [33, 34]) and of threeRomanian products (labeled 106, 109, and 121 [34, 35]).Teethwith carious lesions were extracted from adults andchildren, and external surfaces of clinically soundenamel were studied by PIXE in the intact tooth or insectioned blocks. All teeth were washed with deionizedwater and some were also incubated in concentrated(33 %) hydrogen peroxide (Merck) to remove theorganic component from the surface. Demineralizationof enamel was done by incubation for approximately3 days in 20 mL of 0.09 M lactic acid solution atpH 4.45 (initial value) with stirring [55]. Femur bonesfrom Wistar rats both normal and those made diabeticby injecting 50 mg kg�1i.p.streptozotocin dissolved incitrate buffer were cleaned of the soft tissues and storedcold [49]. Fragments of human tibia bones from diabeticpatients undergoing surgery were cleaned of soft tissueand washed. After deionized water washing, teeth,dental enamel blocks, and bone fragments were dried fora few hours at 60�C. A Romanian regenerative bioma-terial prepared as a sponge of collagen impregnatedmainly with hydroxyapatite was studied as provided bythe producer (Poneti Ltd., Bucharest).

PIXE measurements

For the PIXE measurements, all thick targets were fixedon aluminum diaphragms. For complementary analysesof solution samples such as the enamel demineralizingsolutions, the specimens were prepared as thin layers byair drying on thin Mylar substrates. To avoid back-ground build up from ejected electrons accelerated backto the target, electrical charging of the insulating com-posites, teeth, and bones was prevented by coveringthem with a thin carbon film (5–10 lg cm�2) by carbondeposit. PIXE measurements were performed with3-MeV protons from a tandem Van deGraaff acceleratoras described before [33–35]. In most measurements ofthick targets and in all cases for the thin-layer specimens,the proton beam hit the target at 45� with respect to thesurface normal. In angular dependence studies of thicktargets, the angle was varied between 10 and 80�. TheX-rays emerging from the target were collected with aCanberrahyperpure (HP) Ge detector with an energyresolution of 180 eV at 5.9 keV and placed perpendic-

ularly to the beam. Occasionally we also tested a Si(Li)detector. The X-rays passed through the Be windows ofthe scattering chamber (0.25-mm thick) and detector(76-lm thick) and a 1.5-cm air gap. For each sample, afirst spectrum was collected without additional absorberfor the light element analysis, and a second one with anAlabsorber foil (30- or 50-lm thick) to improve heavierelements’ detection limits by reducing the counting ratedue to major light components (especially Ca). Beamcurrent integration was used for normalization. Tomeasure the beam current entering the scatteringchamber and hitting the insulating target, the chamberitself was insulated from the rest of the system, and thecollected charge was measured using an Ortec model 439current digitizer. No electron suppression was used.Although our method does not give an accurate mea-surement, it may serve for normalizing the spectra. Thespectroscopic chain consisted of detector preamplifier, aTennelec amplifier, a Canberra analog-to-digital con-verter, and a Canberra S100 counting system connectedto a computer. The spectra were processed by back-ground subtraction and least-squares fit of lines withGaussians.

PIXE detection limits

Orientatively, the empirical detection limits were evalu-ated from PIXE spectra obtained for some actual spec-imens. The detection limits were established by imposingthat the minimum detectable number of pulses in thepeak, Np, must satisfy the relationship Np ‡ 3NB

1/2,where NB is the number of pulses in the backgroundunder the peak in an interval having the width equal tothe FWHM (full width at half maximum) of the peakcorresponding to the considered Ka or La line [1]. Withthe present experimental conditions, we provisionallyevaluated detection limits in some thick targets: in dentalenamel these reached their best of 0.5–0.6 lg g�1for Fe,Zn, and Pb, rising slightly for Mn to approximately0.85 lg g�1 and up to approximately 5.5 lg g�1 for Sr.The detection limit declined to 64 l g g�1 for Ca and toapproximately 5 % (w/w) for P due to absorbtion in theBe windows of the specimen chamber and detector andto reduced detector sensitivity at low energies. For thecalcified tissues, the effect of a 30-lm Alabsorber con-sisted in a 2–20 times improvement of the detection limitfor the elements from Ca on. The detection limits werecomparatively higher (i.e., sensitivity lower) in the caseof dental composite IV.a. The best detection limit ofapproximately 5 lg g�1 was for Zr and the worse wasfor Ca (approximately 67 lg g�1). The detection limitswere influenced by carbon covering and by the Alab-sorber mostly for the lower- and higher-energy X-rays(e.g., Ca Ka and Ba Ka). Carbon covering improved thedetection limit by values between about 90 % for Ca Ka

and approximately 20 % for Ba La/Yb La. For higher Zelements (Ba La energy and above), the spectrumrecorded with 30-lm Al foil showed detection limits

827

better by approximately 85 % for Zr Ka and by about35 % for Ba La.

Other measurements

Other measurements were made by using ERDA, atomicabsorption spectrometry (AAS), solution pH and con-ductivity determinations, and Fourier transform infra-red (FTIR) spectroscopy.

ERDA is an ion beam analysis method which, insteadof protons, employs a beam of heavy accelerated ions tocommunicate energy and impulse to the nuclides in theanalyzed target and to eject them outside where they aresorted by energy/nature and counted by a specialdetection system [56, 57]. This technique allows themultielemental analysis of light- and medium-mass ele-ments at the surface of the specimen and the determi-nation of their depth profile. ERDA measurements wereperformed on dental composites with Cu ions [33] andon bone samples with I ions [58, 59] using a compactDE(gas)–E(solid) telescope detector. In both cases, theangles of incidence and exit were 75� relative to thesample normal.

AAS spectrometric analysis of Fe, Cu, and Zn in theteeth demineralizing solution was performed with aVarianGTA 97 spectrometer using an acetylene flame.

Solution pH determinations with automatic temper-ature compensation were performed with a digitalOrion Model 290 A+ instrument. For each measure-ment 20–40 successively displayed pH and temperaturepairs of values were read until a stationary regime wasreached, and temperature corrections were made.Conductance of solutions were measured with aRomanian instrument, after a 10-min equilibration ofthe liquid with the cell.

For FTIR spectroscopy, Wistar rat bones were milledand prepared in KBr pellets, and spectra recorded from4,000 to 400 cm�1. Interferograms were averaged for400 scans at 4-cm�1 resolution, and the mineral/organicratio was calculated from integrated areas of amide Iand m1, m3 phosphate stretching bands [49].

Statistical analysis

For the biomineral samples (bones and enamel)descriptive statistics of the data [60, 61] (e.g., means,standard deviations, etc.) were calculated. For compar-ison of the mean values the Student t-test was used, andthe differences between means were considered signifi-cant when they exceeded a confidence interval of 95 %(p < 0.05). Because the populations included so far inthe study were too small, we did not perform explorativestatistical procedures and non-parametric approaches toeliminate outliers and to test normality of distributions[62]. Procedures for multivariate statistical analysis ofdata [63, 64] were applied, which included principalcomponent analysis (PCA) for the classification of

dental composites and factor discriminant analysis(FDA) for discriminating the normal and osteoporoticpopulations. Calculations were done with the multivar-iate statistical program package STATITCF (ITCF-France).

Results and discussions

Qualitative analysis

Overview

Surface analysis of mineral elements from tooth enameland bone tissue on the one hand and from dental com-posites and newly developed biomaterials on the othermay play a central role in understanding pathologicaltransformations and interface processes of interest forrestorative dentistry and regenerative medicine. There-fore, the results of a comparative study on such speci-mens has a relevance of its own. All studied biomineralsystems have a complex elemental composition of themineral part; contain major and/or minor elements fromthe second main group (Ca, Sr or Ba); can undergo tovarious degrees de- and remineralization in the biologi-cal environment; have a granular structure on a micro-metric-to-nanometric scale; and have dielectricproperties. However, the PIXE spectra were highly di-verse for the dental composites (Fig. 1) and relativelysimilar for the calcified tissues and the regenerativebiomaterial (Fig. 2), respectively. In the former, up to 26elements were detected (Si, Cl, K, Ca, Ti, V, Cr, Mn, Fe,Ni, Cu, Zn, Sr, Y, Zr, Ba, Yb, Hf, and possibly traceelements like Ga, Nb, Ag, Nd, Ho, Hg, Au, Pb) and themajor elements could differ from one biomaterial toanother, while in the latter only 18 were observed (P, S,Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, Y,Zr), among which Ca always gave the most intensespectrum because all clarified biostructures containedhydroxyapatite (calcium phosphate hydroxide) as themain mineral component (Table 1).

Although owing to its better low-energy sensitivitythe Si(Li) detector could offer some advantages for thelow-Z trace elements, its use offered little benefit for Ca-rich specimens such as bones and dental enamel, becausethe Ca Ka–Si Ka escape line overlapped the P Ka lineand thus obstructed the detection of this biologicallyimportant element. Therefore, almost all results wereobtained by measurements performed with the HP Gedetector.

Qualitative composition of dental composites

The qualitative composition of dental composites variedgreatly [33–35] (Fig. 1, Table 1). PIXE detected Ca as amajor element only in dental composites III, V, and 121;other main elements included Si, Cl (in I), Ti (in I andIII), Cu (in I and II), Fe (in III), Sr (in VII, 106 and 109),Zr (in VI and 106), Ba (in IV, VIII, IX, X and 109), and

828

Yb (in IVand V). The same high diversity was shown bythe minor and trace elements (cf. Table 1). Some dom-inant ‘exotic’ elements (like Zr, Yb, Hf) might contributeto adverse effects in occupational exposure and dentaluse of composites [65, 66]. Of the trace elements, somecould not be detected due to spectral overlap (e.g., Ti, Fein IV) or sensitivity (Se in IV), while other (Sr, Y, Pb inV) were mainly impurities not known to the producer[67], which might influence the materials’ properties.Thus, in the long list of detected trace elements (K, Ca,Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Sr, Y, Zr, Nb, Ag,Cd, Ba, Nd, Ho, Yb, Au, and Pb), practically all ana-lyzed dental composites, both Western and Romanian,contained some impurities which supposedly came fromthe raw materials used for their preparation [33–35].

Qualitative composition of calcified structures

In contrast to dental composites, all the clarified bio-mineral structures showed only a limited variability(Fig. 2, Table 1) as they were dominated by Ca. Theother major element, P, visible in most specimens, dis-played only a very weak line in one spectra due toreduced low-energy detector sensitivity and for absorb-tion in the windows. Differences in minor and traceelements were specific to each sample. The light minorelements gave faint signals if any: S was not detected insome specimens of dental enamel, Cl was observedoccasionally in Wistar rat femur and in enamel (notdemonstrated in the spectrum shown in Fig. 2), and Kwas clearly seen only in rat bone. Zn, a medium-Z ele-ment with borderline levels between trace and minor,was seen very well in all.

Among trace elements, Fe was present in loweramounts in dental enamel than in bones; however, in thelatter it could also come partly from blood retained in thepores and not just from the bone tissue itself. The heaviertrace elements could be seen better in the spectra recordedwith the Al foil absorber (not shown in Fig. 2). In thespectra accumulated without additional absorber fromthese Ca-rich specimens, the pile-up effects could not becompletely excluded even with reasonably low countrates, and the pile-up line of Ca Ka + Ca Ka interferedwith Ni Ka and thus obscured when present; the formerline togetherwith theCaKa + CaKbpile-upare shown inthe rat femur spectrum this trace element of Fig. 2, wherethey were more intense. All calcified tissues containedtraces of Cu, Sr, and Pb. (The weak signal attributable tothe overlapping PbLa and AsKa lines has been assignedentirely to Pb, although the occurrence of As in thespecimens could not be excluded in principle. At the sametime, the concentrations of these two toxic ele-ments—admitting that both were present—were too lowto distinguish between by making use of the correspond-ing b lines, resolved by almost 1 keV. However, PIXEdetected Pb in teeth at concentrations of 2–21 lg g�1, i.e.,above our detection limit, but failed to evidenceAs [31, 37,38, 68]. To our knowledge, the teeth of the fur seal fromJapan are the only such biological material showing boththese elements in detectable amounts [69].) Other traceelements were related to the nature of tissue, species, anddisease. Traces of Ti/Ba, V, Mn, Co, Ni, Br, Rb, and Zr,and possiblyCr, Se, andYwere seen in dental enamel, andonly a few appeared in bones; e.g., rat femur showedCr inaddition, and occasionally Cd. Levels of Cu, Br, and Pbwere higher in bones than in enamel, and the highest levels

Fig. 1 Thick-target PIXEspectra of Western (I,V,VI,VII ) and Romanian (106,121) dental composites selectedto illustrate the diversity in theelemental composition of theanalyzed restorativebiomaterials. 3-MeV protonsand 30-lm Alabsorber foil wereused during the accumulationof the presented spectra. Thelinear plots in the main framesevidence the major and minorelements; insets show enlargedzones of the spectra insemilogarithmic plots tovisualize the most importanttrace elements. Note that theRomanian composites 106 and121 can serve as referencematerials for the similarWestern products V and VII

829

of Sr and Pb levels were found in tibia from diabetichumans. Note that while Pb and Cd are toxic, otherdivalent trace and minor metals like Mn, Fe, Cu, Zn, andSr could play a role both normal and related to osteopo-rosis. Also Cr, usually a trivalent metal, and the divalentNi may be involved in the experimental diabetes animalmodel of osteoporosis. Surface preparation may alsoinfluence PIXE observation of trace elements; they wereseen best in dental enamel and worst in the human tibia,probably due to the incomplete removal of organic tissuefrom the human bones’ surface.

Some of the many trace elements evidenced in thedental enamel by various methods (second column ofTable 1, e.g., ref. [38] for PIXE results) could not bedetected in our PIXE analysis, but other methods cannotsee so many of them just at the dental surface. Consid-ering the effects induced by demineralization on enameltrace elements, we noted that the relative intensities ofCr, Mn, Fe, Cu, Zn, Rb, Sr, and Pb (and in some casesof Ti, V, Ni, and Zr) changed, most of them apparentlyincreasing with respect to Ca (see Sect. ‘‘PIXE evidenceof dental enamel demineralization’’).

Fig. 2 Thick-target PIXEspectra from surface layersof calcified tissues (dentalenamelblock from a humantooth crown, cervical areaof a Wistar rat femur withstreptozotocin-induceddiabetes, cervical area of humantibia prelevated surgically froma diabetic patient) and from aregenerative biomaterial(a collagen sponge impregnatedwith hydroxyapatite).The spectra presented assemilogarithmic plots wererecorded without additionalabsorber. In the insetsthe low-energy regions of the spectrawere enlarged to show thedetected low-Z elements

830

However, the regenerative biomaterial, which is typ-ical for the biotechnological approaches used in arecently developed branch of medicine [44], evidencedmany differences to the calcified tissues. Besides Ca,which showed the usual high intensity, P has beenobserved by a lines signal comparable to the noise andthus its detection as a major element in the regenerativebiomaterial was uncertain; however, we observed a verystrong signal of Cl, an element which was almostunnoticed in the natural calcified tissues, except in theWistar rat femur. Minor elements were represented byFe and Zn, and possibly by S which was hardly visible(although its detection can be improved with minorchanges in the experimental setup, e.g., by introducingthe detector directly in the specimen chamber). Unex-pectedly, a pregnant spectrum of Zr was detected. Traceelements included Ti/Ba, Cu, Br, Rb, Sr, and Pb, andpossibly Ni, and were surprisingly similar to those foundin biogenic calcified tissues. Thus, the main particularityof the regenerative biomaterial consisted in the relativelyhigh levels of Cl and Zr, and the unusually low apparentlevel of P. Although impurities from collagen could benot excluded, this suggests more probably that themineral phase of the biomaterial consisted not only ofhydroxyapatite but also of another mineral componentnot disclosed by the producer, or that the hydroxyapa-tite used was of different origin to that found in thebones and dental enamel.

Relative concentrations

Towards quantitative analysis

To evaluate element concentrations from the peakareas of the thick-target PIXE spectra, a procedure isneeded to establish the X-ray yield function to con-vert the latter to the former. Such procedures mayinclude: (1) use of reference materials with similarcompositions and structures, (2) ‘prime principles’calculations of X-ray yields, (3) use of publishedconcentrations determined by various methods for amaterial sufficiently similar to the investigated sam-ple(s), (4) PIXE measurements in experimental con-ditions which minimize the matrix effects, e.g., atconvenient orientations of the sample with respect tothe beam and detector, (5) measurements for some ofthe elements by other nuclear methods with lowermatrix effects. In general, we did not dispose ofproper reference materials, and we were compelled toresort to such alternative procedures. Any of themcan be more or less inaccurate and a combinationmay be the best choice; however, accurate absoluteconcentrations can still be hard to attain in this wayand one should limit attention to relative concentra-tions. This means that irrespective of the procedureused for finding the X-ray yield curve, the elementalconcentrations were obtained by reference to a singleelement in the same spectrum, on which we managedT

able

1ElementsdetectedbyPIX

Equalitativeanalysisandnominalorknownconstituents

indentalcomposites,anim

alandhumanbones,humandentalenamel,andaregenerative

biomaterial

Biomineralsystem

Mineralnominalcompositionorknownelem

entsa,b,c

Detectedelem

entsf

Major

Minor

Trace

FourteenWestern

and

threeRomanian

dentalcomposites

B,O,F,Na,Al,Si,Ca,Ti,Fe,

Se,

Sr,Zr,Ba,Yb

Ca,Si,Cl,Ti,Cu,Fe,

Sr,Zr,Ba,Yb

K,Ca,Ti,V,Cr,Mn,Fe,

Ni,Cu,Zn,Sr,Zr,Nb,Cd

Ca,Ti,V,Cr,Mn,Fe,

Co,Ni,Cu,Zn,Ga,Sr,Y,

Zr,Nb,Ag,Ba,Nd,Ho,

Yb,Hf,Au,Pb

Humandentalenamel

Hd,Li,B,Cd,O

d,F,Al,Si,P,S,Na,Mg,Cl,K,Ca,

Ti,V,Cr,Mn,Fe,

Co,Ni,Cu,Zn,Se,

Br,Rb,Sr,Zr,

Pd,Ag,Cd,Sn,Sb,Ba,Pt,Au,Hg,Pb

P,Ca

Zn;possibly

S,Cl

Ti/Ba,V,Mn,Fe,

Ni,Cu,

Br,Rb,Sr,Zr,Pb,

occasionallyCr,Y

Wistarratfemur

(norm

alanddiabetic)

Hd,Cd,O

d,F,Na,Mg,P,Cl,K,Ca,Fe,

Zn,Br,Sr,Ba,Pb

P,Ca

S,Cl,K,Zn

Fe,

Cu,Sr,Cr,Mn,Ni,Br,

Rb,Pb,occasionally

Cd,Y,Zr

Diabetic

humantibia

Hd,Li,Cd,O

d,F,Na,Mg,Si,P,Cl,K,Ca,Fe,

Zn,Br,Sr,Ba,Pb

P,Ca

S,Zn

Fe,

Cu,Sr,Pb,occasionally

Br,Rb,Y,Zr

Regenerativebiomateriale

Hd,Cd,O

d,Si,P,Cain

hydroxyapatite

Cl,Ca

Fe,

Zn,Zr,possibly

P,S

Ti/Ba,Mn,Ni,Cu,Br,Pb,

occasionallyV,Rb

aSpecified

bytheproducer/knownfrom

published

data

bMinorandtrace

elem

ents

from

thenominalcompositionsare

written

initalics

cAllspecim

enscontained

H,C,N,andO

inthesoft(organic)phase

ofthebiomineralsystem

inthefollowingproportionsofthedry

substance

(w/w

):dentalcompositesapproxim

ately

25%

(mixture

ofacrylicanduretanicpolymers);bones,raw

bonetissueapproxim

ately

46–47%

(about20%

proteinspredominantlyascollagen,about26–27%

lipids);dentalenamel

approxim

ately

2%

(citricacid,keratins,solubleandinsolublecollagen,other

solubilizableproteinsandpeptides);regenerativebiomaterialapproxim

ately

50%

(collagen).Accordingto

theirorganicfractional

content,thematerialsrankin

thefollowingorder:regenerativebiomaterial>

bones

>dentalcomposites>

dentalenamel

dMineralO

indentalcomposites:in

silicatesandoxides.MineralH,C,andO

inenamel,bones,andcalcified

biomaterial:in

hydroxyapatite

andCaCO

3derivatives

eRegenerativebiomaterial:collagen

+hydroxyapatite

+other

(unidentified)mineral

f Majorelem

ents,above>5%;minorelem

ents,0.5–5%

range;

trace

elem

ents,below

0.5%

831

to get some concentration information by independentprocedures or sources [25–27].

X-ray yields calculations

Although in principle one can convert thick-target PIXEpeak areas to absolute concentrations by X-ray yieldscalculations, we applied this approach only heuristically,for the estimation of relative concentrations in dentalcomposites. This is because of the difficulties of suchcalculations [12–17] for most biomineral sam-ples—complex, heterogeneous, granular, and dielectricthick targets—and especially for dental composites dueto their high diversity. Namely: (a) targets are ‘infinitelythick’ and matrix effects corrections are important; (b) atleast for the major elements, these corrections depend onthe concentrations, unknown in most cases; c) accuracyof corrections depend on the granularity of the materi-als, which can be accounted for by ingenious models [16,70]; (d) sample inhomogeneity and its variations areimportant sources of imprecision [71]; (e) the specimenscontain low-Z constituents not seen by PIXE (however,one commonly used scheme for bypassing this drawbackof biological samples is to measure the concentrations oflight elements by other methods, usually by Rutherfordbackscattering spectroscopy, or RBS [18, 20, 23, 24, 72];instead, we applied ERDA for some of the analyzedsamples—see Sect. ‘‘Linking PIXE to other nuclearanalysis methods’’); and (f) the accuracy of absoluteconcentrations by X-ray yields calculations is limited to5–15 % relative in thick biological samples and even tohigher values (e.g., 30 %) for some elements due, amongother things, to imprecision in available atomic data,surface roughness, and sample inhomogeneity [1–4, 12–17]. (One should note, however, that many correctionscan now be obtained routinely with the use of programsdeveloped for the analysis of thick targets [28–30],including for standardless analysis [27], so that for majorelements accuracy can be better than 3 % [73] and aslow as 1.6 % in long-term runs on standard materials[74].)

In the model used, for a flux F of incident protonshitting the target at an angle h with the normal to thetarget surface (h=45� in most of our experiments), theyield of primary XI (I = a, b) rays reaching the detector(positioned at 90� to the proton beam and subtending asmall solid angle) from the element k present with a massconcentration ck, produced in a volume element ofthicknessds at the depth s behind the surface, is welldescribed by the following integral over the targetthickness:

I ðprimÞXi;k¼ U

ckNA

Akxk

CXi

CX

� �kðef Þk

ZdsrkðsÞe�lks= tan h ð1Þ

In the above relationship, Ak is the atomic mass ofthe element k, NA is the Avogadro number, rk(s) is theionization cross-section, which is variable with the depths due to energy loss, which in turn is dependent on the

concentrations of all elements in the target; xk is thefluorescent yield; ðCXi=CX Þkis the partial radiativewidth, i.e., the fraction from the total (X-ray plus Augerelectron) decay rate represented by the analyzed X-rayline (usually Ka or La) of the element k; lk is theabsorption coefficient of the primary X-rays of elementk, which also depends on the concentrations of all ele-ments in the specimen; (�f)k is a factor denoting thedetector efficiency (�k) times the correction for attenua-tion (fk) in the windows, air and aluminum foil (ifpresent). The model approximates the target as perfectlyhomogeneous and flat; composite targets were approxi-mately flat but heterogeneous. Equation 1 accounts for(1) the decreasing energy of the projectile entering thethick target and (2) the attenuation of the X-rays leavingthe specimen in the direction of the detector; at the sametime it neglects the secondary fluorescence of X-rays.Calculations for a matrix with a few major elementsallow evaluations of minor and trace elements, becausethe matrix effects depend to a first order mainly on themean Z and less on the detailed composition. Thedatabase used in our calculations includes the protonenergy loss from semiempirical relationships reported byAndersen and Ziegler [75], the ECPSSR model ioniza-tion cross-sections tabulated by Cohen and Harrigan[77], the fluorescence yields of Krause [78], the partialradiative widths from Salem et al. [79], and the photo-effect and total mass attenuation coefficients fromVeigele [80].

We numerically integrated Eq. 1 over the targetthickness to calculate the X-ray yield curve for K-serieslines from a hypothetical thick matrix containing O(31 %), Si (18 %), Ca (12 %), and Fe (39 %) (in atomicpercentages), and with a mean Z (or <Z>) of 17.54. Adeeply asymmetric bell-shaped curve was obtained forZ = 15–40, and this X-ray yield versus Z curve wasused to estimate relative concentrations of PIXE-de-tected elements in all dental composites. This obviouslyis a rough approximation, because the very diversematrixes of the composites (Fig. 1) drastically limits thevalidity of translating the conversion function from oneto another. Note that such a procedure, intended to limitthe number of calculations, should not be necessary anylonger as soon as one can make use of an advancedprogram for thick target corrections (which in somecases also include the correction for secondary fluores-cence X-rays) [27–30]: this would make it possible tocalculate corrections for each measurement and even usean iterative procedure with multiple calculations permeasurement [24, 73]. Nevertheless, our actual proce-dure gives some insight. Thus, for the 14 Westerncomposites, taking into account the relative concentra-tions of the PIXE-detected elements and assuming lightelement content similar to that detected by ERDA incomposite IV.a ([33, 34]; see Sect. ‘‘Linking PIXE toother nuclear analysis methods’’), <Z> was foundbetween 11.6 and 15.5. These values are not too far fromthe hypothetical matrix <Z>, suggesting that theevaluated relative concentrations are approximately

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valid, and more accurate for the composites with heaviermatrix IVand VIII–X. Moreover, according to <Z>,the relative concentrations estimated as described abovecould serve to obtain more accurate values of their ownby calculating more than one X-ray yield curve for the14 composites—but how many?

Classification of dental composites

To answer this question we tested two different classifi-cation procedures of the composites based on the ana-lyzed relative concentrations [50]. In the first one,according to the calculated mean Z, the 14 Westerncomposites could be classified into several related con-figurations (formed from five to seven groups) accordingto the difference between successive <Z> valuesdefined as significant. In the second case, we appliedprincipal component analysis (PCA), a multivariatestatistics technique [63, 64], both to the relative con-centrations and to their logarithms. In this way, thecomposites could be classified in nine, eight, seven, or six

groups, according to the incidence frequency of clustersin the ten planes defined by the five principal compo-nents. For illustration, the planes shown in Fig. 3 sug-gest classifications of the biomaterials in six and sevengroups, respectively. These slightly different classifica-tions are not completely unequivocal because no quan-titative method has been used for the segmentation ofpartially overlapping clusters; also, the relative concen-trations (or their logarithms) used in the PCA calcula-tion were affected by unknown systematic errors due tothe evaluation method described in the previous section.However, our preliminary study shows that a six groupclassification compatible with the results calculated bothwith relative concentrations and with their logarithmscan be obtained. Moreover, with minor modifications,the five groups classification based on <Z> couldmerge into the six to seven group ones that were ob-tained by PCA. Thus, the two completely differentprocedures may converge by classifying for instance thecomposites in the following seven groups: (Ia, Ib), (II,III), (IVa, IVb), (V), (VIa, VIb), (VII) and (VIIIa, VIIIb,IX, X), which appear to represent a reasonable com-promise close to the minimal number of clusters con-sistent with both methods. In this way, the relativeconcentrations from thick-target PIXE together with thetwo classification procedures simplify further quantita-tive analysis, i.e., by grouping 14 of dental composites inonly seven distinct classes and, therefore, by reducing toits half the number of necessary distinct yield curves.Further work is necessary, however, to exploit more thequantitative side of the PCA classification procedure.Below some hints are given in order to obtain thesecurves without denovo calculations using Eq. 1.

We note that although the classification proceduredeveloped for the dental composites with the purpose oflimiting the number of calculations may lose part of itsrelevance—given that, as mentioned earlier (Sect.‘‘X-ray yields calculations’’), the yield curves can be

Fig. 3 Two-dimensional plots showing projections of all dataobtained by PCA from the logarithms of relative concentrationsestimated by PIXE into the space of the first two (left) and next two(right) principal components: Left The plane PC1·PC2 accountsfor 68.0% of the variation in the data and is consistent to thefollowing classification in six clusters: (Ia, Ib), (II, III), (IVa, IVb,V ), (VIa, VIb), (VII ), (VIIIa, VIIIb, IX, X ). PC1 accounts mainlyfor the concentration logarithms of Cr, Ti, Fe, Ni, Mn,... and PC2for Hf, V, Sr, Zr, Ba,... . Right The plane PC3·PC4 accounts for21.4% of the variation in the data and is consistent to the followingclassification in seven clusters: (Ia, Ib), (II, III), (IVa, IVb), (V ),(VIa, VIb), (VII), (VIIIa, VIIIb, IX, X). PC3 accounts mainly forthe concentration logarithms of Yb, Ca, Hf, V,..., and PC3 for Cd,Mn, K, Cl, Ca,... Note that the result of clusters (IVa, IVb) and (V )merging together to form a common cluster (as in plane PC1·PC2)or not (as in plane PC3·PC 4) depends on the projection direction.Although further advances in this PCA application seem necessaryto solve such issues, generally the classifications from differentplanes converge for the 14 dental composites

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computed with an advanced PIXE program for thick-target corrections [27–30]—the same multivariate sta-tistics approach may be very useful for the more generalanalytical aim of classifying a set of related but diversebiological specimens. At this point, it may be worthmentioning that we were, for example, confronted withsuch a situation in the case of blood serum trace ele-ments in hemopathies when comparing patients withdifferent but related disorders and/or with a polymor-phic disease [81]. As a result of applying PCA to theserum concentrations measured by thin-layer PIXE andneutron activation analysis (NAA), we could define anorder relationship similar to those assessed from theclinical diagnosis and from biochemical parameters ofblood (E.A. Preoteasa and R. Georgescu, unpublishedresults).

‘Approximate’ reference materials

Romanian dental composites 106 and 121 were similarto the Western composites VII and V, respectively [53,54] (Fig. 1). Nominal concentrations were known in106 for Sr and Zr and in 121 for Ca and Yb, so thesematerials could serve as approximate standards for VIIand V. However, uncertainties for the nominal con-centrations (which may arise from diverse sources suchas weighing, impurities in the raw materials, impurifi-cation and substance loss during high-temperatureprocessing of glass and ceramics, polymerization, localmacroscopic heterogeneity, etc.) were not communi-cated by the producer. Under the reserve of unknownuncertainties, these composites could also be used togive an idea on the accuracy of estimations based onyield calculations with Eq. 1. In fact in 106 the ratioSr:Zr compared well for the evaluated and nominalconcentrations [34]. On the other hand the ratio Ca:Ybin 121 was not so close to its nominal value; however,it could give some insight for the L-series X-ray yieldsof heavier elements. Similarly, we used dental enamelas an approximate reference material to evaluate rel-ative concentrations in bones.

Empirical construction of X-ray yield curvefor calcified tissues

By using data on the composition of dental enamel, weconstructed an X-ray yield curve with the same asym-metric bell shape but with different maximum position,width, and other characteristics as ‘compared to thehypothetical matrix’ one. We assumed that this corre-sponded to the hydroxyapatite from dental enamel,Ca10�x(PO4)6(OH)2�xHxÆ2.5x H2O with x=0.5, andhaving <Z>=10.66. Besides the hydration waterwhich may be partly lost during drying of teeth, notethat this formula, which describes better the P/Ca ratioin enamel, is different to that of the pure hydroxyapatite,Ca10� x(PO4)6(OH)2; additional hints on the main ele-mental components of dental enamel may be found

elsewhere [31]. Our procedure involved some incertitudeconnected to the enamel’s clinical condition, as Ni, Cu,and Zn concentrations for example may be up toapproximately 100 times higher in decayed rather thanhealthy enamel [38]. The use of a unique X-ray yieldcurve for the spectra of all calcified structures is obvi-ously approximate (see Fig. 2). Due to the differencesamong them (e.g., see footnote c of Table 1 for varia-tions in their organic part; also, they differ in density,structure, granularity, surface shape and smoothness,and conductivity), a rigorous treatment should be nee-ded to separate X-ray yield curves for each calcifiedmaterial. However, the unique curve approximation ismore adequate here than for dental composites. Com-paring the two curves, i.e. for the hypothetical matrixwith <Z> = 17.54 and for the ‘enamel hydroxyapa-tite’ matrix with <Z> = 10.66, empirical relationshipswere established for constructing families of X-ray yieldcurves for various matrixes characterized by a givenmean value <Z>. According to the <Z> = 11.6–15.5 values evaluated for the dental composites, theirimproved X-ray yield curves should fall approximatelybetween the two previous curves.

Angular dependence of X-ray yields

If the angle between the normal to the target and thebeam is increased above 45�, the depth of the analyzedlayer decreases and, therefore, the matrix effects de-crease towards zero when the angle approaches 90�. Thisis suggested by the factor exp(�ls/tan h) in Eq. 1[12].Dental composites favor such measurements becausethey are easily prepared with a macroscopically flatsurface. Measurements of the Romanian composite 106suggest that in our familiar 45� geometry the matrixeffects would reduce the intensity of Ca Ka line to about70 % of its value in their absence (by extrapolation tothe beam quasiparallel to the target surface,i.e.,h = 90�). This corresponds to about 1.53 % per 1�tilt of the target, rather close to a reference value of1.72 % [12]; the difference could be due to the granu-larity of the biomaterial. Such developments carried outnow in our group could evaluate the contribution ofmatrix effects for various dental materials without priorknowledge on their compositions. This approach is notequally simple for native bones and enamel, whosecurved natural surfaces do not allow a good orientationcontrol. Enamel from teeth with the surface curved to acertain degree evidenced so far a more reduced angulardependence, probably due to angle change compensa-tion between adjacent areas.

Linking PIXE to other nuclear analysis methods

Low-Z elements that are not observed by PIXE can bedetected by other ion beam analysis techniques. For thispurpose, in studies of thick biological samples, RBS iscommonly used [18, 20, 23, 24]; some of the light ele-

834

ments (Li to F) can also be detected in such systems bynuclear reaction analysis (NRA) [31, 38, 39, 82–84], andin particular by particle-induced c-ray emission (PIGE)[84–87]. (Physical overviews of these methods are givenelsewhere (e.g., in refs. [72, 88, 89]), and their biomedicalapplications are reviewed in ref. [6]) The advantage ofRBS, NRA, and PIGE is that their measurements can beperformed simultaneously with the PIXE measurements.Less frequently, the detection of light elements is per-formed by ERDA measurements [90] which, in contrastto the above methods, cannot be carried out at the sametime with PIXE. But the advantage of ERDA resides inits capability of easily detecting all the low-Z elements,hydrogen included—an element that cannot be detectedby RBS and that is hard to detect by PIGE and NRA;observation of elements lighter than carbon would be forinstance hardly possible with RBS. Both for its principleand for its experimental setup, ERDA differs in manyregards with respect to PIXE (e.g., use of heavy accel-erated ions and of a compact gas–solid telescope detec-tor [57], different geometry corresponding to incidentand emergent beams far from surface normal [56–58]).Also, while in PIXE cross-sections strongly depend onZ, the cross-section for producing recoils and thus thesensitivity of ERDA is almost constant for Z = 3–20[58].

Dental composites By using ERDA with Cu ion pro-jectiles we determined relative concentrations of ele-ments from H to Si in the dental composite IV.a(imparted earlier [33] as relative atomic proportions).Combining relative concentrations from PIXE andERDA measurements, tentative absolute concentrationscompatible with the results of both methods were esti-mated for the complete elemental composition of inmaterial IV.a (except for a few trace elements). The massconcentrations (relative values as input data and abso-lute values as outputs) are given in Table 2. Because noelement was measured by both methods, the followingapproximate assumptions were made in our calculation:

(1) absence of any significant element between Si (theheaviest element detected by ERDA) and Ca (thelightest element detected by PIXE); (2) a ratio of 79 %/21 % (w/w) for the inorganic/organic parts of thecomposite, as given by the producer [91]; (3) a F/Ybratio set to 0.672 (w/w). The last conjecture was to someextent arbitrary, as this ratio should only exceed a valueof 0.329 characteristic to YbF3—one of the two fluoride-containing compounds present in the composite beside afluorosilicate glass which embodies an unknown amountof F. Hence, a linear equation system was obtained,which was solved to a first approximation only for themajor elements and then for the minor elements in-cluded in the calculation. Accordingly, the tentativepercentage concentrations of H, B, C, N, O (total, or-ganic and inorganic), F, Na, Al, Si, Ca, Zr, Ba, and Ybin biomaterial IV.a were obtained (Table 2). We notethat although the estimated concentrations were sepa-rately compatible with the ratios between elementsfound by the two methods, their accuracy could not beevaluated due to the critical dependence of the ratiobetween elements measured by ERDA (H to Si) and byPIXE (Ca to Pb), respectively, on the arbitrarily as-sumed Yb/F ratio. The PIXE spectra also evidencedtraces of Sr and Pb, probably in the range of 10 lg g�1,which were not knowingly added by the producer andwere most likely impurities coming with the raw mate-rials [67], as already mentioned (Sect. ‘‘Qualitativecomposition of dental composites’’). In addition, thebiomaterial contained trace elements that we did notpositively detect in the present analysis, i.e., Fe and Tifrom the TiO2 and Fe2O3 pigments, and Se as animpurity accompanying the camphorquinone light-cur-ing catalyst added in the organic part [67]. However, onecan expect that an improved fit of the PIXE spectrashould identify Fe and Ti by their Ka lines overlappingwith the intense Ba La and Yb L1 lines, also a mea-surement with a windowless detector installed directly inthe scattering chamber may possibly detect the traces ofSe in the IVa dental composite.

Table 2 The mass concentration ratios of elements detected by ERDA and PIXE in the dental composite IVa, and an estimate of absolutemass concentrations of all elements detected in the biomaterial consistent with the data from both methods

Method and parameter Detected elementsa

H B C N O F Na Al Si Ca Zr Ba Yb

ERDA, element/Cb 0.08 0.11 1 0.04 2.3 0.36 0.01 0.25 1.25 – – – –PIXE, element/Cac – – – – – – – – – 1.00 0.36 4.8 10.0ERDA+PIXE, absolute concentration,% (w/w)d

1.4 1.8 16.1 0.7 37.5 5.7 0.2 4.1 18.8 0.9 0.3 4.2 8.5

aIn addition, the PIXE analysis detected traces of Sr and Pb notknown to the producer; the material also contained traces of Ti, Fe,and SebThe measurement incertitudes for the relative concentrations ofelements determined by ERDA were evaluated to at least ±(5–10)% relativecFor the elements analyzed by PIXE, the incertitudes of the relativeconcentrations due solely to the measurement counting errors were

of ±(0.9–1.2)% relative for Ca, Ba, and Yb and of ±3% for Zr.However, errors due to other factors (e.g., beam current integra-tion, line and background fit in the spectrum analysis, inaccuracyof matrix effect corrections) could be appreciably more importantdAn estimation of overall errors of the calculated concentrations isnot possible without further independent information concerningthe F/Yb ratio, in addition to the specification of a minimum 0.329value (we arbitrarily set this ratio to 0.672)

835

Normal and osteoporosis-affected bones For calcifiedtissues, ERDA can be relevant for the low-Z branch ofthe PIXE yield curve where a few elements may bedetected by both methods. Thus, ERDA with I ionprojectiles found a P/Ca molar ratio of 0.62±0.03 innormal human femur [58, 59], which compares very wellwith our PIXE estimation of 0.71±0.12 for this ratio innormal Wistar rat femur. Also, in human osteoporoticfemur a P/Ca ratio of 0.52±0.01 was found by ERDA,while in rat femur affected by diabetes-associated oste-oporosis we found a ratio of 0.63±0.40 by PIXE. Theerrors associated with the P/Ca values given above havedifferent meanings, which explains why the relativeerrors were apparently lower in the ERDA rather thanPIXE data. For ERDA, they represent the measurementincertitudes (because only a very small number of bio-logical cases were included in the cited study [58], whosemain concern was the feasibility of the method); forPIXE, they are the standard deviation of the mean in thebiological populations. The difference between theresults of the two methods in each couple is neitherstatistically significant nor biologically relevant. Bothfor normal and osteoporotic bones, the P/Ca molar ratiofound by ERDA in single cases of human femur falls inthe range of individual values found by PIXE in ratfemur (0.54–0.79 and 0.09–1.20, respectively). It resultstherefore that individual variability is sufficient from thebiological point of view to explain the differences, andthat the difference between the two species is probablynot involved. In fact such differences between mammalsare minimal. For instance, the mineral ash content ofcompact bones is 58 % for humans and 60 % for rats,and the spin concentration of stable paramagnetic cen-ters measured by electron spin resonance (ESR) incompact bone has exactly the same value in the twospecies [92]. On the other hand, although the ERDAresults are not sufficient to give an answer, the numerical

difference between methods raise the question of exper-imental inaccuracy, i.e., the slightly higher valuesobtained by PIXE may indeed be due to an overesti-mation of P in the rat femur associated to the use ofhuman enamel yield curve used for bones, as alreadydiscussed (Sect. ‘‘PIXE and FTIR analysis of normaland streptozotocin-induced diabetic rat bones’’).Comparison of ERDA and PIXE Due to its sensitivityfor light elements, ERDA detected Li, N, and Mg inbones in addition to P and Ca measured by PIXE. Inparticular, it succeeded to evidence a substantial increaseof Li/Ca and Mg/Ca in the osteoporotic human bone[58, 59]. On the whole, however, the sensitivity of ourERDA measurements was not noticable superior toabout 0.2%, the lowest estimated concentration for anelement detected by this method (Table 2). Such avalue underlines the much better sensitivity of PIXE,illustrated by detection limits down to approximately0.5–0.6 lg g�1 for Fe and Zn in calcified tissues and ofapproximately 5 lg g�1 for Zr in composite IVa,respectively (see Sect. ‘‘PIXE detection limits’’). How-ever, the uncertainity of concentration measurements bythe two methods may be comparable, because in PIXEthe advantage of low statistical counting errors (ca. 1 %relative) was lost by inaccuracy of corrections for thematrix effects (ca. 18 % in the case of rat bones, see nextsection).

PIXE and FTIR analysis of normaland streptozotocin-induced diabetic rat bones

Osteoporosis, a syndrome of various ethiologies char-acterized by low bone density [93], occurs frequently as acomplication of Type 1 or insulin-dependent diabetesmellitus. In this disease, FTIR studies evidenced changesin the mineral/protein ratio and in the relative carbonate

Table 3 The P/Ca molar ratio measured by PIXE in femur bone from normal and streptozotocin-induced diabetic Wistar rats ascompared to reference values in biological and inorganic materials

Sample or reference material P/Ca molar ratio References

Corrected experimentalvaluesa

Normal control rat bonesb 0.58±0.10 –Diabetic rat bonesb 0.52±0.33 –Lowest value in the diabetic populationc 0.074±0.008 –Highest value in the diabetic populationc 0.986±0.003 –

Reference biologicalvalues

Compact bone, human 0.59 [98]Healthy dental enamel 0.62 [97]Dental enamel hydroxyapatite,Ca10�x(PO4)6(OH)2�xHxÆ2.5xH2O(x=0.5) ” Ca9.5(PO4)6(OH)1.5H0.5Æ1.25H2O

0.63 [97]

Reference values inmodel compounds

Calcium carbonate CaCO3 0.00 [100]Pure hydroxyapatite Ca10(PO4)6(OH)2 0.60 [92, 100]Calcium phosphate Ca3(PO4)2 0.67 [92, 100]Octocalcic phosphate Ca8H2(PO4)Æ6H2O 0.75 [92]Acid calcium phosphate CaHPO4Æ2H2O 1.00 [92]Calcium pyrophosphate Ca2P2O7 1.00 [100]Calcium trimetaphosphate Ca3(P3O9)2 2.00 [100]

aP/Ca values determined from the PIXE analysis of bones reducedby 18% in order to account for a probable inaccuracy in the X-rayyield curve used

bMean ± SD of the P/Ca values in the biological populationcP/Ca value estimated from the spectrum of single sam-ple ± counting statistics incertitude

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content of bone [49]. PIXE has been applied before inthe study of osteoporosis, including in an affected boneamputated from a diabetic man [41] and the preventiveestrogen effects in a rat model of osteoporosis [20]. Othermethods, like NAA [94, 95] and inductively coupledplasma atomic emissions spectrometry (ICP-AES) [96],have been applied also, but the mechanism of the im-plied alteration in the Ca, P, and trace element metab-olism in osteoporosis is not yet completely understood.In our study, we examined the P/Ca ratio at the cervicalsurface of femur bones from normal and streptozotocin-induced diabetic Wistar rats, a widely used animalmodel for the complications of Type 1 diabetes mellitus.

P/Ca ratio In healthy rat femur, a P/Ca molar ratio of0.71±0.12 was estimated by PIXE in agreement with themean value of 0.59 found biochemically for the molarratio in normal compact human bone [97, 98] and withthe molar ratio of 0.65±0.38 evaluated by neutron

activation analysis (NAA) in the human bone IAEAstandard material [99]. For the diabetic rat femur, wecould compare our value with another PIXE study ontibia bone from a diabetic human undergoing surgery.These authors analyzed a single bone and found a ratiobetween P and Ca X-ray counts of 0.0055±0.0005 [41],which compares reasonably with our counts ratio on thediabetic rats femur bones of 0.0070±0.0052 (corre-sponding to the molar ratio of 0.63±0.40 mentionedbefore). We note, however, that both for normal anddiabetic bones our P/Ca molar ratio was slightly higherthan other communicated values. Thus, with respect tothe quoted studies including ERDA, this ratio for nor-mal bone was in the mean 18±8 % higher, which sug-gests a reasonable accuracy in our evaluation of theP/Ca molar ratio. The slight systematic deviation pre-sumed for P/Ca might be due to the use of a humandental enamel X-ray yield curve, probably leading tosome overestimation of P in the rat bones. Accordingly,a correction in the enamel yield curve is needed for theP/Ca ratio in rat bones. With this assumption, correctedvalues of the P/Ca ratio in rat femur can be considered,namely 0.58±0.10 in normal bone and 0.52±0.33 in thediabetic one (Table 3).

The mean P/Ca ratio did not change significantly inthe diabetes-induced osteoporotic bones with respect tonormal, in agreement with other studies. Thus, no con-centration change was evidenced for P and Ca in calfbones by chemical analysis [101] and for Ca in rabbitbones by NAA [95]. This may suggest that in the meanthe proportion of hydroxyapatite and carbonate doesnot change significantly in osteoporosis. However, theindividual P/Ca ratio values were more grouped fornormal rat femur and more scattered in the diabetic rats.The higher dispersion of P/Ca in the osteoporotic bonesseems to be biologically relevant, if the minimum andmaximum values of the corrected P/Ca in the studiedpopulation of diabetic rats are not rejected as outsiders.The minimum value as low as 0.07, suggests an alteredcomposition of bone with a very low content ofhydroxyapatite (P/Ca is 0.60 in pure hydroxyapataite)and, probably, with an unusually high content of cal-cium carbonate, as in CaCO3the P/Ca ratio equals 0 (seeTable 3). At the other end, the maximum value of 0.99suggest the almost complete absence of carbonate in amixture of hydroxyapatite with a high proportion ofcalcium acid phosphate, as in this particular specimen itis much higher than in hydroxyapatite, higher than inoctocalcic phosphate (0.75) and very close to calciumacid phosphate (1.00) [92, 97, 98, 100].

FTIR results FTIR results obtained on bones from ratsundergoing identical treatment and regimen revealed thatdiabetes caused a slight increase in relative mineral/pro-tein matrix (PO4

3�/Amide I) ratio and a relative carbon-ate content decrease in the femur and tibia [49].Within thedispersion of data, they are consistent with the status of Pand Ca found by PIXE in the majority of pathological

Fig. 4 Thick-target PIXE spectra of normal and in vitro demin-eralized dental enamel. For demineralization, blocks of enamel cutfrom extracted teeth were incubated in lactic acid solution for3 days with stirring. 3-MeV protons and 30-lm Al absorber foilwere used during the accumulation of the shown spectra.Apparently, the relative intensities of the trace elements (Fe, Cu,Zn, Pb, Sr) are increasing following the incipient in vitrodemineralization. The effect evidences changes occurring in theouter surface layer (of the order of 10 lm) of the enamel

837

cases and they also seem to support directly the second‘‘extreme’’ form of osteoporosis (very high P/Ca) sug-gested by the PIXE data. On the other hand, in the case ofthe first ‘‘extreme’’ form of osteoporosis (low P/Ca) itwould be hard to say so far whether the opposite trendevidenced by the PIXE and FTIR results reveals a diver-gence or not, because the two methods measure differentparameters. However, on the whole the two methodsconverge complementarily in understanding relevantminerality alterations of bones affected by diabetes.

Trace elements At the cervical surface of rat bones, thePIXE spectra (Fig. 2) found higher than normal molarratios of K, Mn, Zn, and Sr with respect to Ca inthe diabetes-associated osteoporotic femur, while Casignificantly decreased, indicating a slower-than-Cadecrease or a slight increase of the former elements [51].At the same time, the Ni/Ca molar ratio decreased in thediabetic osteoporosis. Note that excepting K, all theabove elements are divalent cation-forming metalswhich may show chemical properties similar to Ca. Theratios to Ca of Fe and Cu, two other metals which formdivalent cations, did not change significantly in diabetes,but unexpectedly, Fe/Ca and Cu/Ca were the only ratiosto show only positive correlations with the ratios of allother trace elements to Ca. The above results suggestthat the mentioned divalent metals before might playsome role, either direct or mediated, in the diabeticosteoporosis. For instance Ni is an insulin activationcofactor [10, 11], and Cu is necessary for the copper-dependent lysylaminooxidase which is involved in thesynthesis of the collagen forming the organic matrix ofbone [102, 103]. Also, one can expect Zn to be involvedin the pathological mechanisms; studies by histochemi-cal methods and by synchrotron radiation-inducedemission of X-ray (SRIXE) microscopy of normal and invitrodemineralized bone showed that Zn is distributed inthree distinct pools which include the alkaline phos-phatase [104], an enzyme essential to the mineralmetabolism of the bone. Other trace elements like Cr,Br, Rb, Y, Zr, and Pb also show trends of change in thediabetic rat bones. Of the trace elements investigated inosteoporosis by other authors, some—like Cu [94], Crand Zn [96, 105]—evidenced changes in bone, while Mnand Sr did not show any modification [95].

Factorial discriminant analysis Both the P/Ca and thetrace element results were confronted with a high disper-sion of data due to a high biological variability, which formany elements made it difficult to differentiate betweenthe normal and the diabetic groups. However, a multi-variate statistics procedure [63, 64], factorial discriminantanalysis (FDA), that we applied earlier for hair traceelements changes evidenced by NAA in diabetes [106],showed that the distance index between diabetic andnormal bones increased considerably when consideringsimultaneously themolar ratios toCa of three or five traceelements insteadof just one significantly changing element

(Mn). Thus, FDA emphasized the relevance of the mul-tielemental character of PIXE analysis and, implicitly,showed that the relative changes of bone trace elements indiabetic osteoporosis were correlated.

PIXE evidence of dental enamel demineralization

In the oral environment, dental enamel undergoesdemineralization leading to caries formation, and incu-bation of enamel in solution of organic acids provides asimplified in vitro model of this process in its incipientphase. Microradiographic studies showed that underthese conditions mineral substance is removed from adeep layer located at several tens of lm below the surfaceof enamel [46–48]. Much less attention was paid to thechanges that may occur in the surface layer. BecausePIXE explores in enamel only a thin layer near the sur-face [31, 70], it appears well suited to follow the effects ofin vitro incipient demineralization at the natural surfacelayer of the hard dental tissue. As we already noted [54],in spite of the wide use of the method for the study ofdental enamel in various normal and pathological con-ditions [31, 32, 36–40, 69, 70, 84, 85], this phenomenonhas not been investigated before by PIXE.

After incubation of dental enamel blocks in lacticacid solution (initial pH 4.45), the PIXE spectra of theenamel surface layer evidenced an apparent increase ofthe Fe/Ca, Cu/Ca, Zn/Ca, Sr/Ca, and Pb/Ca intensityratios (Fig. 4). The apparent increases of Fe, Cu, Zn, Sr,and Pb with respect to Ca showed that changes tookplace in the outer superficial layer of enamel within adepth of the order of ten lm from the surface [31, 70].At the same time thin-target PIXE of the solution evi-denced only increases of P, Ca, and Zn, with the increaseof Zn in solution supported also by AAS data. Con-comitantly, the pH of the lactic acid solution increasedto 4.89 and its conductivity by 11%, which is consistentwith dissociation of ions from the enamel. No hypoth-esis of selective dissolution from the surface layer (of Caalone, or of P, Ca and Zn) could explain consistently allthese facts. Rather, the apparent increase in the enamelX-ray spectra of the trace elements with respect to Ca isdue probably to the depth profiles of the respective traceelements. Those elements are more concentrated in alayer starting below 5–7 lm from the surface andshowing maxima around a depth of approximately30 lm in the healthy tissue, while the outer layer con-tains mainly P and Ca, as evidenced by micro-PIXE intooth sectioned normally to the surface [39]. The in-crease of the relative intensities of Fe, Cu, Zn, Sr, and Pbsignals seems to be due most probably to an unmaskingeffect produced by the demineralization, by the removalof P and Ca from the outer superficial layer of enamel.A loss of Ca in a higher proportion than the loss of thetrace elements could also contribute to some extent tothe observed effects. Note that trace elements like Znand Fe are involved in the structure and function ofenzymes regulating the enamel maturation [107–109],

838

including the alkaline phosphatase [110] mentionedabove for a similar role in bone. Thus, PIXE showedthat the incipient demineralization of enamel does notreduce to the loss of mineral substance at depths ofseveral tens of lm below the surface of enamel, but in-cludes also modifications in an outer surface layer with athickness of the order of 10 lm, suggesting that theprocess depends on the complex microscopic morphol-ogy of enamel and on the depth profiles of elements (andpossibly, on their chemical forms).

Conclusions

Thick-target PIXE analysis of biomineral systems bringstogether many advantages and is unique among multi-elemental analysis methods by providing sensitive traceanalysis exclusively in a thin layer at the sample surface.Although matrix effects in thick targets raise consider-able difficulties concerning the determination of absoluteconcentrations—and without proper reference materialsthe method faces many limitations—our approach pro-vides the prerequisites to overcome these limitations.A large body of stratagems makes possible the evalua-tion of the elements’ relative concentrations, whosevariations allow relevant insight into biomedical struc-tures and processes. To this purpose, the concertedcontrol of a great number of very diverse preparative,experimental, and computational parameters is required,and very different concepts and approaches should beapplied, ranking from atomic physics to biology and tomultivariate statistics. This approach proved valid in ourstudies of dental composites and calcified tissues andbiomaterials, and allows further advances in the thick-target PIXE analysis of these biomineral structures.

Acknowledgements We are indebted to a number of people forcooperation and assistance in preparing, providing, and character-izing the samples, and for valuable suggestions and discussions, inparticular to Dr. Maria Moldovan (RalucaRipan Institute ofChemistry, Cluj-Napoca, Romania) for the Romanian dental com-posites, and Prof. C. Ionescu Tirgoviste and Dr. Daniela Gutu(Nicolae Paulescu Institute of Diabetes and Metabolic Diseases,Bucharest) for the human femur samples. Also we thank Dr. Mari-ana Anghel (Institute for Water Quality Control, Bucharest) for herexpert help with the AAS analysis. E.A.P. warmly acknowledges thehighly valuable suggestions and discussions he benefitted from Prof.S. Gomez (Department of Pathological Anatomy, Faculty ofMedicine, University of Cadiz, Spain). Last but not least, a specialmention is due to Prof. M. Petrascu (Institute for Physics andNuclear Engineering, Bucharest) for pertinent advice and strongencouragement in preparing the manuscript. Part of this study hasbeen performed in the frame of research project 76/2001 of theCERES national program (Institute of Atomic Physics, Bucharest)and has been sponsored by theRomanianMinistry of Education andResearch.

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