Unbalanced Mixtures Research Articles

Developmental Validation of a DIP-InDel/DIP-STR System for the Detection of Unbalanced DNA Mixtures.

Extracting "masked" minor donor information from an unbalanced DNA mixture stain is important for the identification of the person of interest. In recent years, a series of compound markers genotyped based on allele-specific amplifications have been proposed to detect minor contributors of mixed stains. In this study, we selected out 18 DIP-InDel markers from previous literatures and established a multiplex system encompassing 18 DIP-InDel markers and 6 DIP-STR markers in two separate reactions. The allele frequencies were estimated based on 200 samples, and 23 of the 24 DIP-linked length polymorphic markers had a relatively high probability of informative markers (I value >0.267), which indicated their potential usefulness in the Chinese Han population. Moreover, the multiplex was highly sensitive (requiring >0.025ng) and specific to human DNA. This system is capable of detecting the minor contributor comprising 1% in unbalanced mixtures of two individuals. The capacity of profiling cell-free DNA was also analyzed in few cases. At least one paternal allele could be detected in maternal plasma samples with gestation periods ranging from 27 to 40 weeks. To conclude, the DIP-linked length polymorphic markers may serve as a convenient method for detecting the presence of a minor donor in unbalanced mixtures and show promise for noninvasive prenatal diagnosis.

Discovery unbalanced DNA mixtures and evaluation mixing ratio via a droplet digital PCR method.

Small amounts of DNA from a perpetrator collected during crime-scene investigations can be masked by large amounts of DNA from the victim. These samples can provide important information for the perpetrator's conviction. Short tandem repeat (STR) detection system is not sensitive enough to detect trace amounts of minor components in unbalanced mixed DNA. We developed a system using droplet digital polymerase chain reaction (ddPCR) capable of discovering trace components and accurately determining the ratio of mixed DNA in extremely unbalanced mixtures. The non-recombining regions of the X chromosome and Y chromosome were quantified in the DNA of male and female mixtures using duplex ddPCR. Absolute quantification of low-abundance portions of trace samples and unbalanced mixtures was done using different mixing ratios. The ddPCR system could be used to detect low-abundance samples with < 5 copies of DNA components in an extremely unbalanced mixture at a mixing ratio of 10000:1. The high sensitivity and specificity of the system could identify the mixing ratio of mixed DNA accurately. A ddPCR system was developed for evaluation of mixed samples of male DNA and female DNA. Our system could detect DNA quantities as low as 5 copies in extremely unbalanced mixed samples with good specificity and applicability. This method could assist forensic investigators in avoiding the omission of important physical evidence, and evaluating the ratio of mixed male/female trace samples.

Development and validation of a new multiplex panel using SNaPshot-based DIP-TriSNP markers for forensic DNA mixtures.

Short tandem repeat analysis is challenging when dealing with unbalanced mixtures in forensic cases due to the presence of stutter peaks and large amplicons. In this research, we propose a novel genetic marker called DIP-TriSNP, which combines deletion/insertion polymorphism (DIP) with tri-allelic single nucleotide polymorphism in less than 230bp length of human genome. Based on multiplex PCR and SNaPShot, a panel, including 14 autosomal DIP-TriSNPs and one Y chromosomal DIP-SNP, had been developed and applied to genotyping 102 unrelated Han Chinese individuals in Sichuan of China and simulated a mixture study. The panel sensitivity can reach as low as 0.1ng DNA template, and the minor contributor of DNA can be detected with the highest ratio of 19:1, as indicated by the obtained results. In the Sichuan Han population, the cumulative probability of informative genotypes reached 0.997092, with a combined power of discrimination of 0.999999998801. The panel was estimated to detect more than two alleles in at least one locus in 99.69% of mixtures of the Sichuan Han population. In conclusion, DIP-TriSNPs have shown promising as an innovative DNA marker for identifying the minor contributor in unbalanced DNA mixtures, offering advantages such as short amplifications, increased polymorphism, and heightened sensitivity.

Laminar Flame Speed, Ignition Delay Time, and CO Laser Absorption Measurements of a Gasoline-like Blend of Pentene Isomers.

The combustion properties of a gasoline-like blend of pentene isomers were determined using multiple types of experimental measurements. The representative mixture (Mix A) is composed of 5.7% 1-pentene (1-C5H10), 39.4% 2-pentene (2-C5H10), 12.5% 2-methyl-1-butene (2M1B), and 42.4% 2-methyl-2-butene (2M2B) (% mol). Laminar flame speeds were measured at equivalence ratios of 0.7-1.5 in a constant-volume combustion chamber, and ignition delay times (including both OH* and CH* diagnostics) as well as CO time-history profiles were performed in shock tubes, in highly diluted mixtures (0.995 He/Ar), at a stoichiometric condition for temperatures ranging from 1350 to 1750 K, and at near-atmospheric pressure. Two additional unbalanced mixtures removing either 2M2B (Mix B) or 2-C5H10 (Mix C) were studied in a shock tube to collect CO time histories, representing the most stringent validation constraints, as these two pentenes constitute the biggest proportions in Mix A and exhibit opposite behaviors in terms of reactivity due to their chemical structure differences. Numerical predictions using a recent validated chemical kinetics mechanism encompassing all pentene isomers from Grégoire et al. ( Fuel2022, 323, 124223) are presented. The use of a complex blend of four pentene isomers in the present paper provided a capstone test of the current mechanism's ability to model pentene-isomer combustion chemistry, with very good results that reflect positively on the current state of the art in pentene isomer kinetics modeling.

Investigation into the effect of mixtures comprising related people on non-donor likelihood ratios, and potential practises to mitigate providing misleading opinions

The interpretation of mixtures containing related individuals can be difficult due to allele sharing between the contributors. Challenges include the assignment of the number of contributors (NoC) to the mixture with the under assignment of NoC resulting in false exclusions of true donors. Non-donating relatives of the true contributors to mixtures of close relatives can result in likelihood ratios supporting their adventitious inclusion within the mixture. We examine the effect of non-donor likelihood ratios on mixtures of first order relatives. Mixtures of full siblings and parent-child were created by mixing the DNA from known family members in vitro, or by in silico simulation. Mixtures were interpreted using the probabilistic genotyping software STRmix™ and likelihood ratios were assigned for the true donors and non-donors who were either further relatives of the true donors or unrelated to the true donors. The two donor balanced mixtures deconvoluted straightforwardly when analysed as NoC = 2 giving approximately the experimental design 1:1 ratio. When analysed as NoC = 3 a very large number of non-donor genotypes produced LRs close to 1 including many instances of adventitious support. The in vitro three donor balanced mixtures proved difficult to assign as NoC = 3 by a blind examination of the profile. It is likely that many of these would be misassigned as NoC = 2. The analysis of the in vitro and in silico mixtures assuming NoC = 3 with no use of a conditioning profile or with the use of a conditioning profile but without informed priors on the mixture proportions (Mx priors) was ineffective. If the profile can be assigned as NoC = 3 then assignment of the Mx priors is straightforward. This analysis gave no false exclusions. Adventitious support did happen for relatives with high allele sharing. Adventitious support was not observed for any unrelated non-donors. The analysis of the three-person mixtures as NoC = 2 produced many false exclusions and fewer instances of adventitious support. The three donor unbalanced mixtures could all be assigned as NoC= 3. Analysis without Mx priors produced an alternate genotype explanation.

A novel set of short microhaplotypes based on non-binary SNPs for forensic challenging samples.

Short tandem repeats (STRs) are the most widely used genetic markers in forensic application, but they are not ideal genetic markers for the analysis of forensic challenging samples such as highly degraded or unbalanced mixed samples because of their relatively large amplicons and stutter peaks. In this study, we developed a set of short microhaplotypes based on non-binary SNPs with molecular extent sizes no longer than 60 bases and genotyped 100 unrelated individuals from northern Han groups. Our results showed this panel has similar discrimination power to STR kits, as the combined random match probability (CMP) reached 1.396 × 10-22 and mean effective number of alleles (Ae) was 3.59. The cumulative probability of exclusion for duos (CPE-duos) was 0.999919 and the cumulative probability of exclusion for trios (CPE-trios) was 0.9999999987, suggesting this panel could be applied for forensic personal identification and parentage testing independently. Population differentiation in 26 populations from the 1000 Genomes Project indicated this panel could distinguish populations from Africa, East Asia, South Asia, America, and Europe. These microhaplotypes based on non-binary SNPs have short amplicons, good discrimination power, no stutter artifacts, and have great potential in detection of highly degraded and unbalanced mixtures for personal identification, paternity testing, and ancestry inference.

Miscibility Regimes in a 23Na–39K Quantum Mixture

The effects of miscibility in interacting two-component classical fluids are relevant in a broad range of daily applications. When considering quantum systems, two-component Bose–Einstein condensates provide a well-controlled platform where the miscible–immiscible phase transition can be completely characterized. In homogeneous systems, this phase transition is governed only by the competition between intra- and inter-species interactions. However, in more conventional experiments dealing with trapped gases, the pressure of the confinement increases the role of the kinetic energy and makes the system more miscible. In the most general case, the miscibility phase diagram of unbalanced mixtures of different atomic species is strongly modified by the atom number ratio and the different gravitational sags. Here, we numerically investigate the ground-state of a 23Na–39K quantum mixture for different interaction strengths and atom number ratios considering realistic experimental parameters. Defining the spatial overlap between the resulting atomic clouds, we construct the phase diagram of the miscibility transition which could be directly measured in real experiments.

Bimodality of Plasma Glucose Distributions in Whites: A Bootstrap Approach to Testing Mixture Models

The null distribution of the likelihood ratio test (LRT) of a onecomponent normal model versus two-component normal mixture model is unknown. In this paper, we take a bootstrap approach to the likelihood ratio test for testing bimodality of plasma glucose concentrations from Rancho Bernardo Diabetes Study. The small p-values from this approach support the hypothesis that a bimodal normal mixture model fits the data significantly better than a unimodal normal model. The size and power of the bootstrap based LRT are evaluated through simulations. The results suggest that a sample size of close to 500 would be necessary in order to attain a power of 90% for detecting the unbalanced mixtures with means and variances similar to those in the Rancho Bernardo data. Besides sample size, the power also depends on the two means and variances of the two components in the data.

Electrostatic separation of HIPS/ABS and HIPS/ABS-PC plastic mixtures from IT equipment using fluidized bed tribocharging

The paper presents an experimental study of the triboelectrostatic separation feasibility of two plastic mixtures, high-impact polystyrene (HIPS)/acrylonitrile butadiene styrene (ABS) and high-impact polystyrene (HIPS)/acrylonitrile butadiene styrene-polycarbonate (ABS-PC). To mirror real-world material recovery situations, the mixtures of 1-2 mm granular samples were sourced from Information Technology (IT) waste. In addition to balanced composition mixtures of 50% component A and 50% component B, heavily unbalanced compositions such as 10% A/90% B and 90% A/10% B were used in this study. The laboratory set-up consists in a free fall electrostatic separator equipped with a fluidized bed tribocharging device, characterized by interchangeable tribocharging chambers. Preliminary tests established the optimal material for the tribocharging chamber and the duration of the charging process. Samples of granular mixture were tribocharged, then introduced into the free-fall electrostatic separator. The analysis of the seven collecting boxes contents shows a recovery rate of approximately 90% and a purity of about 99% for both components. These results demonstrate the feasibility and the high efficiency of the triboelectrostatic separation of balanced and as well as heavily unbalanced composition mixtures of HIPS/ABS and HIPS/ABS-PC, using the fluidized bed for the tribocharging device.

Simulation-derived best practices for clustering clinical data

IntroductionClustering analyses in clinical contexts hold promise to improve the understanding of patient phenotype and disease course in chronic and acute clinical medicine. However, work remains to ensure that solutions are rigorous, valid, and reproducible. In this paper, we evaluate best practices for dissimilarity matrix calculation and clustering on mixed-type, clinical data. MethodsWe simulate clinical data to represent problems in clinical trials, cohort studies, and EHR data, including single-type datasets (binary, continuous, categorical) and 4 data mixtures. We test 5 single distance metrics (Jaccard, Hamming, Gower, Manhattan, Euclidean) and 3 mixed distance metrics (DAISY, Supersom, and Mercator) with 3 clustering algorithms (hierarchical (HC), k-medoids, self-organizing maps (SOM)). We quantitatively and visually validate by Adjusted Rand Index (ARI) and silhouette width (SW). We applied our best methods to two real-world data sets: (1) 21 features collected on 247 patients with chronic lymphocytic leukemia, and (2) 40 features collected on 6000 patients admitted to an intensive care unit. ResultsHC outperformed k-medoids and SOM by ARI across data types. DAISY produced the highest mean ARI for mixed data types for all mixtures except unbalanced mixtures dominated by continuous data. Compared to other methods, DAISY with HC uncovered superior, separable clusters in both real-world data sets. DiscussionSelecting an appropriate mixed-type metric allows the investigator to obtain optimal separation of patient clusters and get maximum use of their data. Superior metrics for mixed-type data handle multiple data types using multiple, type-focused distances. Better subclassification of disease opens avenues for targeted treatments, precision medicine, clinical decision support, and improved patient outcomes.

DIP-microhaplotypes: new markers for detection of unbalanced DNA mixtures.

The identification of a suspect in a degraded and unbalanced DNA mixture has been a challenge for the standard short tandem repeat polymorphisms (STR) typing. Several methods have been introduced to solve this problem, such as DIP-STR, DIP-SNP, and SNP-STR markers. In this study, we proposed DIP-microhaplotype (deletion/insertion linked a chain of SNPs) as a kind of new genetic marker to type the unbalanced and degraded DNA mixture. We established the detection method with ten DIP-microhaplotype markers including 26 SNPs using allele-specific multiplex PCR followed by SNaPshot assay. This novel compound marker allows us to detect the minor DNA with a sensitivity of 1:100 to 1:1000 in a DNA mixture of any gender. Most of the DIP-microhaplotype markers had a relatively high probability of informative alleles with an average informative value (I value) of 0.308. In all, we proposed DIP-microhaplotype as a novel type of DNA marker for the detection of minor contributor from unbalanced DNA mixtures. Due to their inherent shorter length, higher polymorphism, and sensitivity, DIP-microhaplotypes are promising markers for the examination of the degraded and unbalanced mixtures in forensic stains or clinical chimeras.

Nitrogen concentration in the upper leaves of the canopy is a reliable indicator of plant N nutrition in both pure and mixed grassland swards

AbstractEffective indicators of plant nitrogen (N) nutrition are needed to improve N management in grasslands. This is particularly the case for mixtures that rely on N fixation by legumes as a major N input, because no reference tool such as the nitrogen nutrition index (NNI) exists under these conditions. The aims of this study were to test the reliability of a plant‐based index, the N concentration of upper leaves in the canopy (Nup), as a possible alternative for NNI in both pure and mixed grasslands. Data were gathered from four experiments covering a range of pure and mixed grasslands under different N fertilization levels. A cross‐validation of Nup predictions against NNI in pure stands, and against two NNI‐derived indices in mixtures, was performed. The Nup values appeared to be linearly related to NNI in pure stands of both grasses and legumes. The relationship was identical for the two groups of species and explained up to 86% of NNI variability. In mixtures, Nup also displayed a linear relationship with the two other tested indices, explaining 65% and 78% of variability. The conclusions of the three indices diverged with respect to strongly unbalanced mixtures, where the assumptions regarding the computation of NNI‐derived indices were not met. Excluding these situations, the overall relationship between Nup and NNI proved to be identical for mixtures and pure stands. The results suggest that Nup is a valid criterion for plant N nutrition which applies to a broad range of grassland species and to mixture conditions.

Toluene and methylethylketone: effect of combined exposure on their metabolism in rat

1. Multiple exposures are ubiquitous in industrial environments. In this article, we highlight the risks faced by workers and complete the data available on the metabolic impact of a common mixture: toluene (TOL) and methylethylketone (MEK).2. Rats were exposed by inhalation under controlled conditions either to each solvent individually, or to mixtures of the two. How the interaction between the two solvents affected their fate in the blood and brain, their main relevant urinary metabolites (o-cresol, benzylmercapturic acid for TOL and 2,3-butanediols for MEK) and their hepatic metabolism were investigated.3. Although the cytochrome P450 concentration was unchanged, and the activities of CYP1A2 and CYP2E1 isoforms were not additively or synergistically induced by co-exposure, TOL metabolism was inhibited by the presence of MEK (and vice versa). Depending on the relative proportions of each compound in the mixture, this sometimes resulted in a large increase in blood and brain concentrations. Apart from extreme cases (unbalanced mixtures), the amount of o-cresol and benzylmercapturic acid (and to a lesser extent 2,3-butanediols) excreted were proportional to the blood solvent concentrations.4. In a co-exposure context, ortho-cresol and benzylmercapturic acid can be used as urinary biomarkers in biomonitoring for employees to relatively accurately assess TOL exposure.

An investigation of a set of DIP-STR markers to detect unbalanced DNA mixtures among the southwest Chinese Han population

The resolution of DNA mixtures is still a difficult problem that is worthy of further study. A common method applied for analysing mixtures is the use of autosomal STR markers as well as related calculation software based on genotypes; however, these markers have a limitation in detecting minor DNA in unbalanced mixtures if major DNA constitutes over 95% of the stain. Novel biomarkers, such as Y-STR, DIP-STR and SNP-STR, have been shown to perform well in distinguishing DNA donors in this type of mixture. DIP-STR can successfully target minor DNA in 1000-fold background DNA using two separate allele-specific primers. However, whether this method can successfully detect minor DNA primarily depends on the distribution of the DIPs in a population. Until now, only Swiss population data have been reported; therefore in this study, we selected 10 DIP-STR markers that performed well in the Swiss population and investigated whether these markers were also useful among the southwest Chinese Han population. The allele frequencies were estimated based on 152 samples, and six of the ten DIP-STR makers had a relatively high probability of informative markers (I value), which indicated their potential usefulness in the southwest Chinese Han population. A comparative study of DIP-STR markers and autosomal STR markers demonstrated that DIP-STR markers detected minor DNA at a ratio of 1:1000, while autosomal STR markers often failed to genotype minor DNA because of strong background noises caused by large amount of major DNA. However, the discrimination power was not high enough using these six DIPs alone. Therefore, we suggest that development of a panel with more loci is imperative and that a panel combined with DIP-STR and SNP-STR markers may be a possible way to achieve better discrimination power.

Evaluating 130 microhaplotypes across a global set of 83 populations

Today the primary DNA markers used in forensics are short tandem repeat (STR) polymorphisms (STRPs), initially selected because they are highly polymorphic. However, the increasingly common need to deal with samples with a mixture of DNA from two or more individuals sometimes is complicated by the inherent stutter involved with PCR amplification, especially in strongly unbalanced mixtures when the minor component coincides with the stutter range of the major component. Also, the STRPs in use provide little evidence of ancestry of a single source sample beyond broad “continental” resolution. Methodologies for analyzing DNA have become much more powerful in recent years. Massively parallel sequencing (MPS) is a new method being considered for routine use in forensics. Primarily to aid in mixture deconvolution and avoid the issue of stutter, we have begun to investigate a new type of forensic marker, microhaplotype loci, that will provide useful information on mixtures of DNA and on ancestry when typed using massively parallel sequencing (MPS). We have identified 130 loci and estimated their haplotype (allele) frequencies in 83 different population samples. Many of these loci are shown to be highly informative for individual identification and for mixture identification and deconvolution.

YfilerⓇ Plus population samples and dilution series: stutters, analytic thresholds, and drop-out probabilities.

The Yfiler Ⓡ Plus Amplification Kit amplifies 27 Y chromosomal small tandem repeat (STR) markers. The kit has five-fluorescent dye chemistry and the improved PCR buffer system of modern STR kits. We validated the kit for accredited investigations of crime scene samples by a thorough study of kit dynamics and performance. We determined dye-dependent analytical thresholds by receiver operating characteristics (ROC) and made a customised artefact filter that includes theoretical known artefacts by use of previously analysed population samples. Dilution series of known male DNA and a selection of crime scene samples were analysed with the customised thresholds and artefact filters. The Yfiler Ⓡ Plus Amplification Kit was sensitive giving full profiles down to 70 pg of male DNA. The balances between the fluorescent dyes as well as between loci were very good. The kit was able to produce full Y-STR profiles from crime scene samples containing small amounts of male DNA and large amounts of female DNA (although unspecific reactions were evident for very unbalanced mixtures). A decrease in the drop-out rate was found for both the dilution series and population samples, as well as a small increase in the drop-in rate for population samples, using the customised threshold and artefact filters compared to company-provided thresholds and artefact filters. The additional drop-ins were all of a nature that would be detected by inspection of the results. For the crime scene samples, large amounts of female DNA complicated the analysis by causing drop-ins of characteristic female DNA artefacts. Even though the customised analytical threshold in combination with the custom-made artefact filters gave more alleles, crime scene samples still needed special attention from the forensic geneticist.

Sensitive DIP-STR markers for the analysis of unbalanced mixtures from “touch” DNA samples

Casework samples collected for forensic DNA analysis can produce genomic mixtures in which the DNA of the alleged offender is masked by high quantities of DNA coming from the victim. DIP-STRs are novel genetic markers specifically developed to enable the target analysis of a DNA of interest in the presence of exceeding quantities of a second DNA (up to 1000-fold). The genotyping system, which is based on allele-specific amplifications of haplotypes formed by a deletion/insertion polymorphism (DIP) and a short tandem repeat (STR), combines the capacity of targeting the DNA of an individual with a strong identification power. Finally, DIP-STRs are autosomal markers therefore they can be applied to any combination of major and minor DNA.In this study we aimed to assess the ability of DIP-STRs to detect the minor contributor on challenging “touch” DNA samples simulated with representative crime-associated substrates and to compare their performance to commonly used male-specific markers (Y-STRs). As part of a comprehensive study on the relative DNA contribution of two persons handling the same object, we selected 71 unbalanced contact traces of which 14 comprised a male minor DNA contributor mixed to a female major DNA contributor. Using a set of six DIP-STRs, one to four markers were found to be informative for the minor DNA detection across traces. When compared to Y-STRs (14 traces), the DIP-STRs showed similar sensitivity in detecting the minor DNA across substrate materials with a similar occurrence of allele drop-out. Conversely, because of the sex combination of the two users of the object, 57 remaining traces could only be investigated by DIP-STRs. Of these, 30 minor DNA contributors could be detected by all informative markers while 12 traces showed events of allele drop-out. Finally, 15 traces showed no amplification of the minor DNA. These last 15 samples were mostly characterized by a combination of short handling time of the object, low DNA recovery and/or one single informative DIP-STR.In conclusion, the DIP-STRs represent alternative markers to help solving unbalanced two-source DNA mixtures, and also those produced from contact stains. These markers, in addition to a novel set of 10 DIP-STRs specifically developed according to forensic technical standards, will offer a valuable tool complementary to Y-STR markers.

FDSTools: A software package for analysis of massively parallel sequencing data with the ability to recognise and correct STR stutter and other PCR or sequencing noise

Massively parallel sequencing (MPS) is on the advent of a broad scale application in forensic research and casework. The improved capabilities to analyse evidentiary traces representing unbalanced mixtures is often mentioned as one of the major advantages of this technique. However, most of the available software packages that analyse forensic short tandem repeat (STR) sequencing data are not well suited for high throughput analysis of such mixed traces. The largest challenge is the presence of stutter artefacts in STR amplifications, which are not readily discerned from minor contributions. FDSTools is an open-source software solution developed for this purpose. The level of stutter formation is influenced by various aspects of the sequence, such as the length of the longest uninterrupted stretch occurring in an STR. When MPS is used, STRs are evaluated as sequence variants that each have particular stutter characteristics which can be precisely determined. FDSTools uses a database of reference samples to determine stutter and other systemic PCR or sequencing artefacts for each individual allele. In addition, stutter models are created for each repeating element in order to predict stutter artefacts for alleles that are not included in the reference set. This information is subsequently used to recognise and compensate for the noise in a sequence profile. The result is a better representation of the true composition of a sample. Using Promega Powerseq™ Auto System data from 450 reference samples and 31 two-person mixtures, we show that the FDSTools correction module decreases stutter ratios above 20% to below 3%. Consequently, much lower levels of contributions in the mixed traces are detected. FDSTools contains modules to visualise the data in an interactive format allowing users to filter data with their own preferred thresholds.

Advancing forensic RNA typing: On non-target secretions, a nasal mucosa marker, a differential co-extraction protocol and the sensitivity of DNA and RNA profiling

The forensic identification of human body fluids and tissues by means of messenger RNA (mRNA) profiling is a long studied methodology that is increasingly applied to casework samples. Previously, we have described an mRNA multiplex system that targets blood, saliva, semen, menstrual secretion, vaginal mucosa and skin (Lindenbergh et al. and van den Berge et al.) [1–2]. In this study we consider various topics to improve this mRNA profiling system or its use and adapt the method accordingly. Bodily secretions that may be encountered at a crime scene whilst not targeted by the multiplex—id est nasal mucosa, sweat, tears, faeces and urine-were examined for false positive signals. The results prompted us to identify a nasal mucosa marker that allows the discrimination of nasal mucosa from saliva or vaginal mucosa and nosebleed blood from peripheral blood. An updated version of the multiplex was prepared to which the nasal mucosa marker was added and in which markers for semen, vaginal mucosa and blood were replaced. Lactobacillus markers were regarded unsuitable as replacement for vaginal mucosa mRNA markers because of background signals on penile swabs that appeared devoid of female DNA. Furthermore, we provide approaches to deal with highly unbalanced mixtures. First, a differential extraction protocol was incorporated into a co-extraction protocol to allow DNA and RNA analysis of separated non-sperm and sperm fractions. In a second approach, besides the standard multiplex, a customized multiplex is used which excludes markers for prevailing cell types. This allows the use of lower cDNA inputs for the prevailing cell types and higher inputs for cell types that appear masked. Additionally, we assessed the relation between the percentage of alleles or markers detected in DNA or RNA profiles when decreasing sample amounts are analysed. While blood, saliva, semen and menstrual secretion show the trend that DNA profiling is more sensitive than RNA profiling, the reverse is seen for skin and variable results occur for vaginal and nasal mucosa. Lastly, we show that replicates are useful for interpretation of RNA data, as variations can be found even for true technical replicates. Increased numbers of replicates (over four) do, however, not cancel out the impact of this variation on data interpretation. Overall, the results of this study further forensic RNA profiling.

Robust estimation of unbalanced mixture models on samples with outliers.

Mixture models are often used to compactly represent samples from heterogeneous sources. However, in real world, the samples generally contain an unknown fraction of outliers and the sources generate different or unbalanced numbers of observations. Such unbalanced and contaminated samples may, for instance, be obtained by high density data sensors such as imaging devices. Estimation of unbalanced mixture models from samples with outliers requires robust estimation methods. In this paper, we propose a novel robust mixture estimator incorporating trimming of the outliers based on component-wise confidence level ordering of observations. The proposed method is validated and compared to the state-of-the-art FAST-TLE method on two data sets, one consisting of synthetic samples with a varying fraction of outliers and a varying balance between mixture weights, while the other data set contained structural magnetic resonance images of the brain with tumors of varying volumes. The results on both data sets clearly indicate that the proposed method is capable to robustly estimate unbalanced mixtures over a broad range of outlier fractions. As such, it is applicable to real-world samples, in which the outlier fraction cannot be estimated in advance.