Rapid and nondestructive analysis of lipstick on different substrates using ATR-FTIR spectroscopy and chemometrics.

Lipstick can be an important piece of evidence in crimes like murders, rapes, and suicides. Due to its prevalence, it can be an important corroborative evidence in crime reconstruction. The analysis of such evidence can provide an evidentiary link between the suspect, the victim, object, or the crime scene. We report the use of nondestructive ATR-FTIR spectroscopy combined with chemometrics for the classification of 10 brands of lipsticks with nine samples each. Chemometric method of partial least square-discriminant analysis (PLS-DA) has been employed to interpret the data and classify the samples into their respective classes. The PLS-DA model provides an AUC figure above 0.99 in all brands except one; for which it is slightly less at 0.94. We have also tested the traces of these lipstick samples on different substrates treating them as unknowns in the already trained PLS-DA model. 100% of the samples on nine substrates viz. a cotton, nylon, plastic, dry tissue, denim (blue jeans), wet tissue, nitrile gloves, white paper, and polyester were correctly attributed to their source brand. In conclusion, the results suggest that ATR-FTIR combined with the chemometrics is a rapid, nondestructive, and accurate method for the discrimination and source attribution of lipstick. This study has potential for use in actual forensic casework conditions.

Preliminary forensic assessment of the visualised fingerprints on nonporous substrates immersed in water using the green and optimised novel nanobio-based reagent.

The discovery of forensic evidence (e.g. weapons) during forensic underwater investigations has seen an increasing trend. To date, small particle reagent (SPR) has been one of the routinely used methods for visualising fingerprints on wet, non-porous substrates. However, the long term use of SPR is detrimental to humans and environment due to the use of toxic chemicals. Although previously we have successfully developed and optimised a greener nanobio-based reagent (NBR), its suitable practical use in a more realistic scene (e.g. outdoor pond) was not evaluated. Therefore, this present research is aimed at (1) investigating the performance of NBR against the benchmark SPR in visualising fingerprints immersed in a natural outdoor pond and (2) evaluating the greenness of NBR against the analytical Eco-Scale. Results showed that the performance of the optimised NBR was mostly comparable (University of Canberra (UC) comparative scale: 0) with SPR at visualising fingerprints on three different non-porous substrates immersed in a natural outdoor pond. Observably, the NBR had higher preference towards aged fingerprints (up to 4 weeks of immersion). In addition, its greenness assessment revealed 76 points, indicating 'excellent green analysis'. The findings gathered here further supported the practical use of the NBR in forensic investigations.

On the discrimination between facial creams of different brands using Raman Spectroscopy and partial least squares discriminant analysis for forensic application.

Determining the origin of cosmetic traces is an important aspect of forensic investigations, that helps linking a suspect to a crime. Such type of evidence can help further narrow down the undergoing investigations. This paper reports the first use of Raman Spectroscopy (RS) coupled with the exploratory principal component analysis (PCA) and supervised partial least squares-discriminant analysis (PLS-DA) in facial creams. 40 facial cream samples of 8 different brands were studied in this work. Preliminary assessments through visual inspection of their Raman spectra revealed the presence of oxides, titanium dioxide, castor seed oil, and beeswax. Also, the peaks of alkyne groups were indicative of the presence of talc or mica compounds. The exploratory PCA correctly segregated the samples into 8 clusters and the supervised PLS-DA model correctly classified them into 8 classes. Further evaluation of the performance of the trained PLS-DA model resulted in perfect classification shown by the receiver operating characteristic (ROC) curves. The PLS-DA model also resulted in 100% accuracy of correctly assigning the brand on the face wipes on each of the five substrates viz. cotton, dry and wet tissue paper, nylon substrate, and polyester. This validation was done treating these samples as unknowns. The study has a potential for use under actual forensic casework conditions.

Box-Behnken design optimisation of a green novel nanobio-based reagent for rapid visualisation of latent fingerprints on wet, non-porous substrates.

OBJECTIVE: Optimisation of the green novel nanobio-based reagent (NBR) for rapid visualisation of groomed fingerprints on wet non-porous substrates using response surface methodology and assessment of its stability and sensitivity were attempted for forensic applications. RESULTS: Scanning electron microscopy images demonstrated successful attachments of NBR onto the constituents of fingerprints on the substrates. The highest average quality of visualised fingerprints was attained at the optimum condition (100 mg of CRL; 75 mg of acid-functionalised multi-walled carbon nanotubes; 5 h of immobilisation). The NBR produced comparable average quality of fingerprints with the commercially available small particle reagent, even after 4 weeks of storage (without any preservatives) in both chilled and sultry conditions. The NBR was sensitive enough to visualise the increasingly weaker fingerprints, particularly on glass slides. CONCLUSION: The optimised novel NBR could be the relatively greener option for visualising latent fingerprints on wet, non-porous substrates for forensic applications.

Detection of microplastics in human colectomy specimens.

BACKGROUND AND AIM: While dietary exposure to microplastics is increasingly recognized, it is unknown if ingested plastics remain within the digestive tract. We aimed to examine human colectomy specimens for microplastics and to report the characteristics as well as polymer composition of the particles. METHODS: Colectomy samples were obtained from 11 adults (mean age 45.7, six males) who were residents of Northeastern Peninsular Malaysia. Microplastics were identified following chemical digestion of specimens and subsequent filtration. The samples were then examined for characteristics (abundance, length, shape, and color) and composition of three common polymer types using stereo- and Fourier Transform InfraRed (FTIR) microscopes. RESULTS: Microplastics were detected in all 11 specimens with an average of 331 particles/individual specimen or 28.1 ± 15.4 particles/g tissue. Filaments or fibers accounted for 96.1% of particles, and 73.1% of all filaments were transparent. Out of 40 random filaments from 10 specimens (one had indeterminate spectra patterns), 90% were polycarbonate, 50% were polyamide, and 40% were polypropylene. CONCLUSION: Our study suggests that microplastics are ubiquitously present in the human colon.

Population data of 21 autosomal STR loci in Malaysian populations for human identification.

The use of 21 autosomal STR loci for human identification has been gaining popularity throughout the world. It has been indicated that the forensic statistical parameters for supporting the use of 21 STR loci varied among different populations. Hitherto, such data for the diverse Malaysian populations remain unreported, rendering doubts in the court of law about its real ability for human identification in Malaysian population. Using the GlobalFiler™ Express PCR Amplification Kit, complete DNA profiles of 21 STR loci from buccal swabs of convicted Malaysian criminal (n = 570; 190 each for Malays, Chinese, and Indians) (by the year 2016-2017) were analyzed for their allele frequencies, exact test of Hardy-Weinberg equilibrium, observed and expected heterozygosity, power of discrimination, power of exclusion, match probability, and polymorphism information content. Most of the loci were found to be in the Hardy-Weinberg equilibrium after the Bonferroni correction. Being the most informative locus, SE33 demonstrated the highest power of discrimination and power of exclusion, indicating its usefulness to discriminate individuals. In contrast, TPOX had the lowest power of discrimination and power of exclusion, as well as being the less informative genetic locus for all Malaysian population studied here. The probabilities that two individuals would share the same DNA profiles among the Malaysian Malays, Chinese, and Indians, as well as in general Malaysian population, were 1.3713 × 10-25, 2.8822 × 10-25, 7.5668 × 10-26, and 1.0385 × 10-26, respectively. The results obtained here were found comparable with similar studies reported in other populations. Hence, its robustness for forensic human identification among the Malaysian populations is, therefore, statistically supported.

Source Determination of Red Gel Pen Inks using Raman Spectroscopy and Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy combined with Pearson's Product Moment Correlation Coefficients and Principal Component Analysis.

The potential combination of two nondestructive techniques, that is, Raman spectroscopy (RS) and attenuated total reflectance-fourier transform infrared (ATR-FTIR) spectroscopy with Pearson's product moment correlation (PPMC) coefficient (r) and principal component analysis (PCA) to determine the actual source of red gel pen ink used to write a simulated threatening note, was examined. Eighteen (18) red gel pens purchased from Japan and Malaysia from November to December 2014 where one of the pens was used to write a simulated threatening note were analyzed using RS and ATR-FTIR spectroscopy, respectively. The spectra of all the red gel pen inks including the ink deposited on the simulated threatening note gathered from the RS and ATR-FTIR analyses were subjected to PPMC coefficient (r) calculation and principal component analysis (PCA). The coefficients r = 0.9985 and r = 0.9912 for pairwise combination of RS and ATR-FTIR spectra respectively and similarities in terms of PC1 and PC2 scores of one of the inks to the ink deposited on the simulated threatening note substantiated the feasibility of combining RS and ATR-FTIR spectroscopy with PPMC coefficient (r) and PCA for successful source determination of red gel pen inks. The development of pigment spectral library had allowed the ink deposited on the threatening note to be identified as XSL Poppy Red (CI Pigment Red 112).

Estimation of stature from hand and handprint measurements in Iban population in Sarawak, Malaysia and its applications in forensic investigation.

Handprints and dismembered hands are commonly found during crime scene investigations and disaster victim identifications, respectively. It has been indicated that the accuracy of handprint and hand measurements for estimating stature maybe population specific. Since Iban is the largest ethnic population in Sarawak, Malaysia and because the application of anthropometry of hand and handprint within this population as well as other populations within the Southeast Asian countries remain unreported, this present study that investigated the reliability and accuracy of these two anthropometric aspects acquires forensic significance. Upon measuring the height, 21 measurements were recorded on each hand and the corresponding handprint of 50 male and 52 female consented adult Iban subjects. Using univariate statistics as well as simple and multiple regression analyses, interpretation of the measurements examined here was attempted. Results revealed that lengths of hand and handprint are the more reliable traits for estimating stature in both the male and female Iban subjects (p < 0.05) with correlation strength ranging from 0.60 to 0.76. Comparable to the established skeletal standards for hand, the stature prediction accuracy using hand and handprint measurements investigated in this research ranged between 4.29 and 5.78 cm. Hence, this research provided the first forensic standard for estimation of stature among the Iban population in Sarawak that may prove useful for crime scene investigations and disaster victim identifications in Malaysia.

Provenance Establishment of Stingless Bee Honey Using Multi-element Analysis in Combination with Chemometrics Techniques.

As consumption of stingless bee honey has been gaining popularity in many countries including Malaysia, ability to identify accurately its geographical origin proves pertinent for investigating fraudulent activities for consumer protection. Because a chemical signature can be location-specific, multi-element distribution patterns may prove useful for provenancing such product. Using the inductively coupled-plasma optical emission spectrometer as well as principal component analysis (PCA) and linear discriminant analysis (LDA), the distributions of multi-elements in stingless bee honey collected at four different geographical locations (North, West, East, and South) in Johor, Malaysia, were investigated. While cross-validation using PCA demonstrated 87.0% correct classification rate, the same was improved (96.2%) with the use of LDA, indicating that discrimination was possible for the different geographical regions. Therefore, utilization of multi-element analysis coupled with chemometrics techniques for assigning the provenance of stingless bee honeys for forensic applications is supported.

Classification and source determination of medium petroleum distillates by chemometric and artificial neural networks: a self organizing feature approach.

Three different medium petroleum distillate (MPD) products (white spirit, paint brush cleaner, and lamp oil) were purchased from commercial stores in Glasgow, Scotland. Samples of 10, 25, 50, 75, 90, and 95% evaporated product were prepared, resulting in 56 samples in total which were analyzed using gas chromatography-mass spectrometry. Data sets from the chromatographic patterns were examined and preprocessed for unsupervised multivariate analyses using principal component analysis (PCA), hierarchical cluster analysis (HCA), and a self organizing feature map (SOFM) artificial neural network. It was revealed that data sets comprised of higher boiling point hydrocarbon compounds provided a good means for the classification of the samples and successfully linked highly weathered samples back to their unevaporated counterpart in every case. The classification abilities of SOFM were further tested and validated for their predictive abilities where one set of weather data in each case was withdrawn from the sample set and used as a test set of the retrained network. This revealed SOFM to be an outstanding mechanism for sample discrimination and linkage over the more conventional PCA and HCA methods often suggested for such data analysis. SOFM also has the advantage of providing additional information through the evaluation of component planes facilitating the investigation of underlying variables that account for the classification.

Application of unsupervised chemometric analysis and self-organizing feature map (SOFM) for the classification of lighter fuels.

A variety of lighter fuel samples from different manufacturers (both unevaporated and evaporated) were analyzed using conventional gas chromatography-mass spectrometry (GC-MS) analysis. In total 51 characteristic peaks were selected as variables and subjected to data preprocessing prior to subsequent analysis using unsupervised chemometric analysis (PCA and HCA) and a SOFM artificial neural network. The results obtained revealed that SOFM acted as a powerful means of evaluating and linking degraded ignitable liquid sample data to their parent unevaporated liquids.