False Inclusions Research Articles

Title-plus-abstract versus title-only first-level screening approach: a case study using a systematic review of dietary patterns and sarcopenia risk to compare screening performance

BackgroundConducting a systematic review is a time- and resource-intensive multi-step process. Enhancing efficiency without sacrificing accuracy and rigor during the screening phase of a systematic review is of interest among the scientific community.MethodsThis case study compares the screening performance of a title-only (Ti/O) screening approach to the more conventional title-plus-abstract (Ti + Ab) screening approach. Both Ti/O and Ti + Ab screening approaches were performed simultaneously during first-level screening of a systematic review investigating the relationship between dietary patterns and risk factors and incidence of sarcopenia. The qualitative and quantitative performance of each screening approach was compared against the final results of studies included in the systematic review, published elsewhere, which used the standard Ti + Ab approach. A statistical analysis was conducted, and contingency tables were used to compare each screening approach in terms of false inclusions and false exclusions and subsequent sensitivity, specificity, accuracy, and positive predictive power.ResultsThirty-eight citations were included in the final analysis, published elsewhere. The current case study found that the Ti/O first-level screening approach correctly identified 22 citations and falsely excluded 16 citations, most often due to titles lacking a clear indicator of study design or outcomes relevant to the systematic review eligibility criteria. The Ti + Ab approach correctly identified 36 citations and falsely excluded 2 citations due to limited population and intervention descriptions in the abstract. Our analysis revealed that the performance of the Ti + Ab first-level screening was statistically different compared to the average performance of both approaches (Chi-squared: 5.21, p value 0.0225) while the Ti/O approach was not (chi-squared: 2.92, p value 0.0874). The predictive power of the first-level screening was 14.3% and 25.5% for the Ti/O and Ti + Ab approaches, respectively. In terms of sensitivity, 57.9% of studies were correctly identified at the first-level screening stage using the Ti/O approach versus 94.7% by the Ti + Ab approach.ConclusionsIn the current case study comparing two screening approaches, the Ti + Ab screening approach captured more relevant studies compared to the Ti/O approach by including a higher number of accurately eligible citations. Ti/O screening may increase the likelihood of missing evidence leading to evidence selection bias.Systematic review registrationPROSPERO Protocol Number: CRD42020172655.

Unbiased choice of global clustering parameters for single-molecule localization microscopy

Single-molecule localization microscopy resolves objects below the diffraction limit of light via sparse, stochastic detection of target molecules. Single molecules appear as clustered detection events after image reconstruction. However, identification of clusters of localizations is often complicated by the spatial proximity of target molecules and by background noise. Clustering results of existing algorithms often depend on user-generated training data or user-selected parameters, which can lead to unintentional clustering errors. Here we suggest an unbiased algorithm (FINDER) based on adaptive global parameter selection and demonstrate that the algorithm is robust to noise inclusion and target molecule density. We benchmarked FINDER against the most common density based clustering algorithms in test scenarios based on experimental datasets. We show that FINDER can keep the number of false positive inclusions low while also maintaining a low number of false negative detections in densely populated regions.

Probabilistic Genotyping of Single Cell Replicates from Mixtures Involving First-Degree Relatives Prevents the False Inclusions of Non-Donor Relatives.

Analysis of complex DNA mixtures comprised of related individuals requires a great degree of care due to the increased risk of falsely including non-donor first-degree relatives. Although alternative likelihood ratio (LR) propositions that may aid in the analysis of these difficult cases can be employed, the prior information required for their use is not always known, nor do these alternative propositions always prevent false inclusions. For example, with a father/mother/child mixture, conditioning the mixture on the presence of one of the parents is recommended. However, the definitive presence of the parent(s) is not always known and an assumption of their presence in the mixture may not be objectively justifiable. Additionally, the high level of allele sharing seen with familial mixtures leads to an increased risk of underestimating the number of contributors (NOC) to a mixture. Therefore, fully resolving and identifying each of the individuals present in familial mixtures and excluding related non-donors is an important goal of the mixture deconvolution process and can be of great investigative value. Here, firstly, we further investigated and confirmed the problems encountered with standard bulk analysis of familial mixtures and demonstrated the ability of single cell analysis to fully distinguish first-degree relatives (FDR). Then, separation of each of the individual donors via single cell analysis was carried out by a combination of direct single cell subsampling (DSCS), enhanced DNA typing, and probabilistic genotyping, and applied to three complex familial 4-person mixtures resulting in a probative gain of LR for all donors and an accurate determination of the NOC. Significantly, non-donor first-degree relatives that were falsely included (LRs > 102–108) by a standard bulk sampling and analysis approach were no longer falsely included using DSCS.

Evaluation of the performance of modern X-ray fluorescence spectrometry systems for the forensic analysis of glass

Micro X-ray Fluorescence Spectrometry (µXRF) is a well-established technique for the elemental analysis of glass in forensic casework. The standard test method for the forensic analysis of glass using µXRF (ASTM E2926) provides recommendations for the number of replicate measurements that should be collected to characterize a known source and the criteria for the comparison between the known and questioned samples. However, these recommendations were based on interlaboratory data collected using µXRF instrumentation equipped with traditional lithium-doped silicon (SiLi) detectors. This interlaboratory study aimed to evaluate the performance of modern µXRF systems equipped with silicon drift detectors (SDDs) for the forensic comparison of glass. While the SDD-µXRF instruments resulted in improved precision and detection limits (1.4 µg·g−1–1386 µg·g−1) and excellent discrimination (>99 %) of different-source samples, the false exclusion rates for same-source samples were relatively high (>20 %). Two methods were evaluated to reduce the high false exclusion rates: increasing the number of fragments collected for the known source and modifying the recommended comparison criteria. To reduce the false exclusion rate to 5 % or less, a minimum of five known fragments were needed. Alternatively, modifying the recommended comparison criterion reduced the false exclusion rate from 23 % to 2 %, while maintaining low false inclusions (<1%). The findings in this study demonstrate the improved sensitivity and precision observed in glass measurements acquired with µXRF-SDD systems. However, these systems may require adjustments to sampling and the comparison criteria to minimize potential error rates in the forensic comparison of glass fragments.

The impact of motherless paternity testing in a South African population.

Paternity investigations play an important role in determining biological relatedness, and in South Africa, the outcome of these investigations impacts medical, judicial and home affairs decisions. Short Tandem Repeat (STR) analysis is utilised to perform paternity and kinship analysis, due to the polymorphic nature of STR loci. The cost associated with paternity testing is high, and there is a demand for motherless testing. This study aims to determine what the impact of motherless testing would have been by evaluating 6182 paternity trio cases. The AmpFLSTR™ Identifiler™ PCR Amplification kit was used to profile each of the trio cases. A scenario was created where the mother was eliminated from the test results to determine if the paternity outcome would change. Putative fathers were excluded in 27% of all cases, and in 2.5% of those cases, putative fathers would have been falsely included, had the mother not been tested. These false inclusions are attributed to coincidental STR loci that are shared between the mother and the putative father. The addition of loci to the STR profiling kit may resolve the issue; however, comparable STR data with more loci will have to be evaluated to ensure it overcomes the issue of coincidentally shared loci between unrelated individuals. We would recommend that within our setup and within similar setups, the mother always be included for testing, except in extreme scenarios such as death. False inclusion of putative fathers could have serious legal implications for testing laboratories.

Noninvasive prenatal paternity determination using microhaplotypes: a pilot study

BackgroundThe use of noninvasive techniques to determine paternity prenatally is increasing because it reduces the risks associated with invasive procedures. Current methods, based on SNPs, use the analysis of at least 148 markers, on average.MethodsTo reduce the number of regions, we used microhaplotypes, which are chromosomal segments smaller than 200 bp containing two or more SNPs. Our method employs massively parallel sequencing and analysis of microhaplotypes as genetic markers. We tested 20 microhaplotypes and ascertained that 19 obey Hardy–Weinberg equilibrium and are independent, and data from the 1000 Genomes Project were used for population frequency and simulations.ResultsWe performed simulations of true and false paternity, using the 1000 Genomes Project data, to confirm if the microhaplotypes could be used as genetic markers. We observed that at least 13 microhaplotypes should be used to decrease the chances of false positives. Then, we applied the method in 31 trios, and it was able to correctly assign the fatherhood in cases where the alleged father was the real father, excluding the inconclusive results. We also cross evaluated the mother-plasma duos with the alleged fathers for false inclusions within our data, and we observed that the use of at least 15 microhaplotypes in real data also decreases the false inclusions.ConclusionsIn this work, we demonstrated that microhaplotypes can be used to determine prenatal paternity by using only 15 regions and with admixtures of DNA.

Assessing false paternity risk in simulated motherless cases from more than 20 000 real exclusion trios.

When the mother's DNA profile is not available for paternity testing, there is a smaller probability that a locus will exclude an alleged father. This study aims to evaluate the risk of potential false paternity inclusions in motherless cases. More than 20 000 duos were generated by removing the maternal genotypes from exclusion trios. After recalculating paternity in these duos, any found inclusions would be false. The use of an appropriate number of loci, mutation model, and mutation rates to analyze motherless paternity cases was robust against false inclusions. A single potential false inclusion was observed in a case wherein kinship plays a role. This result highlights the importance of testing the mother when available and of obtaining information on family circumstances for the proper handling of cases involving related individuals. The guidelines we used here were sufficient to avoid false inclusions in a data set of more than 20 000 motherless cases.

Dimensionality reduction of multielement glass evidence to calculate likelihood ratios

AbstractDimensionality reduction of multivariate elemental concentrations of glass is reported for computing likelihood ratios (LRs). The LRs calculated using principal component analysis (PCA) and a post hoc calibration steps result in very low (&lt;1%) false inclusions when comparing glass samples known to originate from different sources and very low (&lt;1%) false exclusions when comparing glass samples known to originate from the same source. The LRs calculated using the novel PCA approach are compared with previously reported LRs calculated using a more computationally intensive Multivariate Kernel (MVK) model followed by a calibration step using a Pool Adjacent Violators (PAV) algorithm. In both cases, the calibrated LRs limited the magnitude of the misleading evidence, providing only weak to moderate support for the incorrect hypotheses. Most of the different pairs that were found to be falsely included were explained by chemical relatedness (same manufacturer of the glass sources in very close time interval between manufacture). The computation of LRs using dimensionality reduction of elemental concentrations using PCA may transfer to other multivariate data‐generating evidence types.

An inter-laboratory evaluation of LA-ICP-MS analysis of glass and the use of a database for the interpretation of glass evidence

Ten laboratories conducting forensic glass analysis participated in three inter-laboratory exercises to evaluate the use of a standard method (ASTM 2927-16e1) for the analysis and comparison of glass evidence using LA-ICP-MS. This study was designed to evaluate the rate of misleading evidence (ROME) when blind glass samples were distributed to the participants and asked to compare the glass samples (K vs. Q) and report their findings as they would in a case. Three different databases were used as background populations to calculate likelihood ratios (LRs) and frequency of elemental profile. The first database was composed of 420 vehicle windshield samples and the analytical data and application of this database is reported here, for the first time. The second database was provided by the BKA laboratory in Germany representing 385 casework samples including an assortment of float glass, container glass, and specialty glasses. The third background database was a combination of both databases. In the first inter-laboratory exercise, the likelihood ratio (LR) calculations result in 34/36 (94.4%) correct associations and no false inclusions for all labs. LRs in the second and third inter-laboratory exercises result in all participating laboratories correctly associating glass samples originating from the same source (57 comparisons) and all laboratories correctly discriminating glass samples from different sources (167 comparisons). The random match probability of glass samples known to originate from different glass sources was found to be ∼0.1% and in agreement with previously reported values by other researchers.

Search for More Effective Microsatellite Markers for Forensics With Next-Generation Sequencing.

Published by the Combined DNA Index System (CODIS) program of the Federal Bureau of Investigation (FBI) in 1997, the 13 core short tandem repeat (STR) loci are widely adopted as genetic markers in forensic applications, e.g., identity testing and paternity testing. However, these loci may be biased and suffer from reduced sensitivities toward specific population groups. In addition, the rapid growth of entries in forensic databases raises the chance of random hits, which can cause false recognitions of criminal suspects. A solution to these problems is to introduce more effective STR markers. The availability of whole genome sequencing enables us to identify more reliable STRmarkers for forensic applicationscomputationally. In this paper, we proposed an algorithm to identify STR markers with high discriminative abilities from the next-generation sequencing data. Our algorithm could select a customized set of loci for a given population with pre-specified discriminative thresholds. We have applied the method to 320 Chinese individuals from the 1000 Genomes Project and obtained various numbers of loci, which were able to statistically identify an individualworldwide and had higher combined powers of discrimination and combined probabilities of exclusion than the existing CODIS 13 loci. For identity testing, themean frequencyofDNAprofile (FDP) with the selected 11 STRs was smaller than that with CODIS 13 STRs by student's t-test. With more loci, much smaller FDPs were obtained. The databasematching probabilities for selected loci were also lower than that for CODIS 13 STRs in a database with 10 billion entries. Moreover, the selected loci were able to provide considerably low chance of random profile matches so that statistically no false positives could occur. The selected loci also reduced the risk of random allele matches when doing the familial search, with lower random allele matching probabilities. In addition, the selected STRs were statistically better than CODIS STRs for paternity testing in our simulated data, with lower probabilities of false inclusions and exclusions.

Effect of Motherless Paternity Cases on the Interpretation of Parent age Investigations in a Population with Recurrent Inbreeding Practices

Currently, parentage testing relies mainly on the study of Short Tandem Repeats (STRs) DNA profiles. Parentage cases could be DUO (motherless/fatherless cases) or TRIO (where both parents' and child's DNA profiles are available). The absence of the DNA profile of one of the parents in DUO parentage testing increases the testing uncertainties. The Lebanese population is known to have a high rate of endogamous and consanguineous marriages, which challenges the power of discrimination of the DNA profiles among different individuals. The present study aimed at evaluating the effect of motherless paternity cases on the interpretation of parentage investigations in the Lebanese population with recurrent inbreeding practices. 64 real DUO parentage exclusions and 15 real TRIO parentage exclusion cases were re-evaluated by assessing the possibility of false inclusions when decreasing DNA profile sizes or when simulating DUO cases from TRIO ones. One case showed false positivity with 6 mismatches in its TRIO state, but only one mismatch in its DUO scenario. The probability of parentage (POP) obtained for this case after omitting the mismatch (a frequent inappropriate malpractice in some local laboratories) was 99.9%. This simulated DUO case was cleared as an exclusion when tested using DNA profile sizes of 24 STR markers. None of the other cases showed false positive results.

Demonstration of false inclusion risks of duo parentage analyses in the Turkish population in light of parentage acceptance criteria

In routine parentage tests, trio analyses (father-mother-child) are preferred. Under certain circumstances, laboratories may have to perform duo analysis (without mother/father). However, duo analyses increase the risk of false inclusions. This paper aimed to evaluate the false inclusion risks of duo analyses in the Turkish population from the point of forensic applications and the Turkish judicial system. Children from 400 previously analysed cases were compared separately with fathers and mothers of other cases by using a computer programme. From the total 345,006 comparisons, in 16 comparisons, no Short Tandem Repeat (STR) mismatch was observed at 15 STR loci between the child and an unrelated parent. In other words, duo tests provided a coincidental second mother or father to 16 children. In almost all of these cases, the probabilities of paternity estimation values are greater than Turkish Judicial System’s parentage acceptance limit, which is 99.73%. According to results, we suggested that trio cases should be performed as much as possible and the parentage acceptance limit, which is 99.73%, should be re-evaluated by a law maker’s commission to prevent false inclusion parentage cases in Turkey.

Per Aspera ad Astra: Through Complex Population Modeling to Predictive Theory.

Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam's razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam's razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.

A simple unconstrained semi-continuous model for calculating likelihood ratios for complex DNA mixtures

Methods for calculating likelihood ratios to provide weight for complex DNA mixtures have been developed, but factors including the complexity of the equations and assumptions about the possible number of contributors to a profile have prevented some laboratories from embracing these methods. By producing and studying complex DNA mixture profiles and approaching interpretation using a minimal number of assumptions, we have developed a semi-continuous method for calculating likelihood ratios. The unconstrained likelihood ratio (UCLR) model for providing statistical weight to inclusions is simple and can be performed without making assumptions about the number of contributors. Additionally, we are able to establish and test the limits of the model, providing greater assurance that false inclusions will not occur by chance.

How many markers are enough? Factors influencing parentage testing in different livestock populations.

Reliability of parentage test panels is usually based on its power to exclude wrong parentage assignments based on allele frequencies. We evaluated the rates of false exclusions and inclusions in parentage assignments, and how these results are affected by allele frequencies, panel sizes and the number of allowed mismatches. We also evaluated the reliability of parentage testing by comparing populations with distinct genetic backgrounds using pure and composite families of cattle and sheep. Allowing for 1% genotype mismatches in true parent-offspring relations provided the best compromise between false-positive and false-negative assignments. Pure breeds needed at least 200-210 single-nucleotide polymorphism (SNP) markers to correctly assign relations, but between 700 and 890 markers to avoid assigning incorrect relationships. Composite breeds needed between 220 (sheep) and 500 (cattle) markers for correct assignment; 680 (cattle) to 4400 (sheep) SNPs were needed to eliminate false-positive assignments. Allowing 0% genotype mismatches decreased false-positive but increased false-negative assignments, whilst a higher threshold of 2% showed the opposite effects. Panels with high minor allele frequencies (0.35-0.45) provided the best chance for correct parentage resolutions requiring fewer markers. Further, we propose that a dynamic threshold would allow adapting to population specific error rates. A comparison to the performance of the official International Society for Animal Genetics SNP panel for cattle and a recently published SNP panel for sheep showed that randomly selected markers performed only slightly worse for the applied parentage test based on opposing homozygotes. This suggests that even with carefully selected panels, only marginal assignment improvements are obtainable for a particular number of SNPs. The main point for improvement is the number of markers used. We recommend using at least 200 SNP markers for parentage testing if the aim is to reduce false-negative results. To fully exclude false positives at least 700 markers are required.

Validation of the danish national diabetes register.

The Danish National Diabetes Register (NDR) was established in 2006 and builds on data from Danish health registers. We validated the content of NDR, using full information from the Danish National Patient Register and data from the literature. Our study indicates that the completeness in NDR is ≥95% concerning ascertainment from data sources specific for diabetes, ie, prescriptions with antidiabetic drugs and diagnoses of diabetes in the National Patient Register. Since the NDR algorithm ignores diabetes-related hospital contacts terminated before 1990, the establishment of the date of inclusion is systematically delayed for ≥10% of the registrants in general and for ≥30% of the inclusions before 1997 in particular. This bias is enhanced for ascertainment by chiropody services and by frequent measurements of blood glucose because the date of reimbursement of services, rather than the date of encounter, has been taken as the date of inclusion in NDR. We also find that some 20% of the registrations in NDR may represent false positive inclusions of persons with frequent measurements of blood glucose without having diabetes. We conclude that NDR is a novel initiative to support research in the epidemiological and public health aspects of diabetes in Denmark, but we also present a list of recommended changes for improving validity, by reducing the impact of current sources of bias and misclassifications.

Decision analysis for the genotype designation in low-template-DNA profiles

What genotype should the scientist specify for conducting a database search to try to find the source of a low-template-DNA (lt-DNA) trace? When the scientist answers this question, he or she makes a decision. Here, we approach this decision problem from a normative point of view by defining a decision-theoretic framework for answering this question for one locus. This framework combines the probability distribution describing the uncertainty over the trace's donor's possible genotypes with a loss function describing the scientist's preferences concerning false exclusions and false inclusions that may result from the database search. According to this approach, the scientist should choose the genotype designation that minimizes the expected loss. To illustrate the results produced by this approach, we apply it to two hypothetical cases: (1) the case of observing one peak for allele xi on a single electropherogram, and (2) the case of observing one peak for allele xi on one replicate, and a pair of peaks for alleles xi and xj, i ≠ j, on a second replicate. Given that the probabilities of allele drop-out are defined as functions of the observed peak heights, the threshold values marking the turning points when the scientist should switch from one designation to another are derived in terms of the observed peak heights. For each case, sensitivity analyses show the impact of the model's parameters on these threshold values. The results support the conclusion that the procedure should not focus on a single threshold value for making this decision for all alleles, all loci and in all laboratories.

Non-CODIS DNA markers could be more effective than CODISbased STRs in problematic biological relationship cases

Short tandem repeat (STR) markers are used worldwide for forensic and paternity identification purposes. It has been proven that a commercial STR kit joined with supplemental STR loci will strengthen the power of resolving complex paternity cases. In the past years, we encountered two rare and difficult family relationship cases; CODIS-based commercial kits were initially used, but failed. We thus employed additional non-CODIS loci and finally resolved the cases. A total of 40 STRs, 13 CODIS and 27 non-CODIS, were profiled using an ABI 3130 Genetic Analyzer. In the two cases, the exclusionary events and percentage obtained from the non-CODIS markers were 9 (33%, out of 27 in case 1) and 18 (also 33%, out of 54 in case 2). Statistical results revealed that the non-CODIS STRs were significantly informative than the CODIS in identifying problematic kinship cases, and that the high case-resolving capability of the non-CODIS was irrelevant to repeat motif composition of STRs. Four index measures, heterozygosity rate, power of exclusion, power of discrimination, and polymorphism information content, were evaluated for the usefulness of both categories, also implying that the non-CODIS seemed to be more available than the CODIS. Our findings are in concordance with a previous research that the 13 core CODIS STRs are not sufficient to definitively differentiate between pairs of close relatives and may lead to false inclusions. The result, an indispensable system of the non- CODIS, could provide a reference for resolving similar complex relationship cases.

The low-template-DNA (stochastic) threshold—Its determination relative to risk analysis for national DNA databases

Although the low-template or stochastic threshold is in widespread use and is typically set to 150–200 rfu peak height, there has been no consideration on its determination and meaning. In this paper we propose a definition that is based upon the specific risk of wrongful designation of a heterozygous genotype as a homozygote which could lead to a false exclusion. Conversely, it is possible that a homozygote { a, a} could be designated as { a, F} where ‘ F’ is a ‘wild card’, and this could lead to increased risk of false inclusion. To determine these risk levels, we analysed an experimental dataset that exhibited extreme drop-out using logistic regression. The derived probabilities are employed in a graphical model to determine the relative risks of wrongful designations that may cause false inclusions and exclusions. The methods described in this paper provide a preliminary solution of risk evaluation for any DNA process that employs a stochastic threshold.

A comparison of laser ablation inductively coupled plasma mass spectrometry, micro X-ray fluorescence spectroscopy, and laser induced breakdown spectroscopy for the discrimination of automotive glass

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), micro X-ray fluorescence spectroscopy (μXRF), and laser induced breakdown spectroscopy (LIBS) are compared in terms of discrimination power for a glass sample set consisting of 41 fragments. Excellent discrimination results (> 99% discrimination) were obtained for each of the methods. In addition, all three analytical methods produced very similar discrimination results in terms of the number of pairs found to be indistinguishable. The small number of indistinguishable pairs that were identified all originated from the same vehicle. The results also show a strong correlation between the data generated from the use of µXRF and LA-ICP-MS, when comparing µXRF strontium intensities to LA-ICP-MS strontium concentrations. A 266 nm laser was utilized for all LIBS analyses, which provided excellent precision (< 10% RSD for all elements and < 10% RSD for all ratios, N = 5). The paper also presents a thorough data analysis review for forensic glass examinations by LIBS and suggests several element ratios that provide accurate discrimination results related to the LIBS system used for this study. Different combinations of 10 ratios were used for discrimination, all of which assisted with eliminating Type I errors (false exclusions) and reducing Type II errors (false inclusions). The results demonstrate that the LIBS experimental setup described, when combined with a comprehensive data analysis protocol, provides comparable discrimination when compared to LA-ICP-MS and μXRF for the application of forensic glass examinations. Given the many advantages that LIBS offers, most notably reduced complexity and reduced cost of the instrumentation, LIBS is a viable alternative to LA-ICP-MS and μXRF for use in the forensic laboratory.