Forensic analysis of fibres by vibrational spectroscopy

Fibres are extremely common. They can originate directly from human and animal hair, and also from textiles in the form of clothing, upholstery and carpets. Hair and textile fibres are relatively easily shed and transferred, which means that it is highly likely that fibres will be found at crime scenes. If such fibres are carefully characterised they can be of immense value in the forensic environment. Vibrational spectroscopy is one of the most important methods for the characterisation of natural and synthetic fibres. The vibrational spectrum, whether mid-IR or Raman, can be considered to be a fingerprint of the molecular structure of the fibre and as such has a very high information content.

Non-destructive evaluation of articular cartilage defects using near-infrared (NIR) spectroscopy in osteoarthritic rat models and its direct relation to Mankin Score

Objective The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. Method Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACLT); and (iii) intra-articular injection of mono-ido-acetete (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made nearinfrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wavenumber range 4 000 – 12 500 cm−1. Following spectral data acquisition, the specimens were fixed and Safranin–O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankinscores of the samples tested. Results Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrate that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankinscore (R2 = 88.85%). Conclusion We conclude that NIR is a viable tool for evaluating articularcartilage health and physical properties such as change in thickness with degeneration.

Application of near infrared (NIR) spectroscopy for determining the thickness of articular cartilage

The determination of the characteristics of articular cartilage such as thickness, stiffness and swelling, especially in the form that can facilitate real-time decisions and diagnostics is still a matter for research and development. This paper correlates near infrared spectroscopy with mechanically measured cartilage thickness to establish a fast, non-destructive, repeatable and precise protocol for determining this tissue property. Statistical correlation was conducted between the thickness of bovine cartilage specimens (n = 97) and regions of their near infrared spectra. Nine regions were established along the full absorption spectrum of each sample and were correlated with the thickness using partial least squares (PLS) regression multivariate analysis. The coefficient of determination (R2) varied between 53 and 93%, with the most predictive region (R2 = 93.1%, p < 0.0001) for cartilage thickness lying in the region (wavenumber) 5350–8850 cm−1. Our results demonstrate that the thickness of articular cartilage can be measured spectroscopically using NIR light. This protocol is potentially beneficial to clinical practice and surgical procedures in the treatment of joint disease such as osteoarthritis.

Characterisation of Ni carbonate-bearing minerals by UV-Vis-NIR spectroscopy

Four nickel carbonate-bearing minerals from Australia have been investigated to study the effect of Ni for Mg substitution. The spectra of nullaginite, zaratite, widgiemoolthalite and takovite show three main features in the range of 26,720–25,855 cm−1 (ν1-band), 15,230–14,740 cm−1 (ν2-band) and 9,200–9,145 cm−1 (ν3-band) which are characteristic of divalent nickel in six-fold coordination. The Crystal Field Stabilization Energy (CFSE) of Ni2+ in the four carbonates is calculated from the observed 3A2g(3F) → 3T2g(3F) transition. CFSE is dependent on mineralogy, crystallinity and chemical composition (Al/Mg-content). The splitting of the ν1- and ν3-bands and non-Gaussian shape of ν3-band in the minerals are the effects of Ni-site distortion from regular octahedral. The effect of structural cation substitutions (Mg2+, Ni2+, Fe2+ and trivalent cations, Al3+, Fe3+) in the carbonate minerals is noticed on band shifts. Thus, electronic bands in the UV–Vis–NIR spectra and the overtones and combination bands of OH and carbonate ion in NIR show shifts to higher wavenumbers, particularly for widgiemoolthalite and takovite.

Spatial mapping of proteoglycan content in articular cartilage using near-infrared (NIR) spectroscopy

Diagnosis of articular cartilage pathology in the early disease stages using current clinical diagnostic imaging modalities is challenging, particularly because there is often no visible change in the tissue surface and matrix content, such as proteoglycans (PG). In this study, we propose the use of near infrared (NIR) spectroscopy to spatially map PG content in articular cartilage. The relationship between NIR spectra and reference data (PG content) obtained from histology of normal and artificially induced PG-depleted cartilage samples was investigated using principal component (PC) and partial least squares (PLS) regression analyses. Significant correlation was obtained between both data (R2 = 91.40%, p<0.0001). The resulting correlation was used to predict PG content from spectra acquired from whole joint sample, this was then employed to spatially map this component of cartilage across the intact sample. We conclude that NIR spectroscopy is a feasible tool for evaluating cartilage contents and mapping their distribution across mammalian joint

Organo-LDH synthesized via tricalcium aluminate hydration in the present of Na-dodecylbenzenesulfate aqueous solution and subsequent investigated by near-infrared and mid-infrared

Na-dodecylbenzenesulfate (SDBS), a natural anionic surfactant, has been successfully intercalated into a Ca based LDH host structure during tricalcium aluminate hydration in the presence of SDBS aqueous solution (CaAl-SDBS-LDH). The resulting product was characterized by powder X-ray diffraction (XRD), mid-infrared (MIR) spectroscopy combined with near-infrared (NIR) spectroscopy technique, thermal analysis (TG–DTA) and scan electron microscopy (SEM). The XRD results revealed that the interlayer distance of resultant product was expanded to 30.46 Å. MIR combined with NIR spectra offered an effective method to illustrate this intercalation. The NIR spectra (6000–5500 cm−1) displayed prominent bands to expound SDBS intercalated into hydration product of C3A. And the bands around 8300 cm−1 were assigned to the second overtone of the first fundamental of CH stretching vibrations of SDBS. In addition, thermal analysis showed that the dehydration and dehydroxylation took place at ca. 220 °C and 348 °C, respectively. The SEM results appeared approximately hexagonal platy crystallites morphology for CaAl-SDBS-LDH, with particle size smaller and thinner.

A forensic investigation of single human hair fibres using FTIR-ATR spectroscopy and chemometrics

Human hair fibres are ubiquitous in nature and are found frequently at crime scenes often as a result of exchange between the perpetrator, victim and/or the surroundings according to Locard's Principle. Therefore, hair fibre evidence can provide important information for crime investigation. For human hair evidence, the current forensic methods of analysis rely on comparisons of either hair morphology by microscopic examination or nuclear and mitochondrial DNA analyses. Unfortunately in some instances the utilisation of microscopy and DNA analyses are difficult and often not feasible. This dissertation is arguably the first comprehensive investigation aimed to compare, classify and identify the single human scalp hair fibres with the aid of FTIR-ATR spectroscopy in a forensic context. Spectra were collected from the hair of 66 subjects of Asian, Caucasian and African (i.e. African-type). The fibres ranged from untreated to variously mildly and heavily cosmetically treated hairs. The collected spectra reflected the physical and chemical nature of a hair from the near-surface particularly, the cuticle layer. In total, 550 spectra were acquired and processed to construct a relatively large database. To assist with the interpretation of the complex spectra from various types of human hair, Derivative Spectroscopy and Chemometric methods such as Principal Component Analysis (PCA), Fuzzy Clustering (FC) and Multi-Criteria Decision Making (MCDM) program; Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Geometrical Analysis for Interactive Aid (GAIA); were utilised. FTIR-ATR spectroscopy had two important advantages over to previous methods: (i) sample throughput and spectral collection were significantly improved (no physical flattening or microscope manipulations), and (ii) given the recent advances in FTIR-ATR instrument portability, there is real potential to transfer this work.s findings seamlessly to on-field applications. The "raw" spectra, spectral subtractions and second derivative spectra were compared to demonstrate the subtle differences in human hair. SEM images were used as corroborative evidence to demonstrate the surface topography of hair. It indicated that the condition of the cuticle surface could be of three types: untreated, mildly treated and treated hair. Extensive studies of potential spectral band regions responsible for matching and discrimination of various types of hair samples suggested the 1690-1500 cm^-1 IR spectral region was to be preferred in comparison with the commonly used 1750-800 cm^-1. The principal reason was the presence of the highly variable spectral profiles of cystine oxidation products (1200-1000 cm^-1), which contributed significantly to spectral scatter and hence, poor hair sample matching. In the preferred 1690-1500 cm^-1 region, conformational changes in the keratin protein attributed to the α-helical to β-sheet transitions in the Amide I and Amide II vibrations and played a significant role in matching and discrimination of the spectra and hence, the hair fibre samples. For gender comparison, the Amide II band is significant for differentiation. The results illustrated that the male hair spectra exhibit a more intense β-sheet vibration in the Amide II band at approximately 1511 cm^-1 whilst the female hair spectra displayed more intense α-helical vibration at 1520-1515cm^-1. In terms of chemical composition, female hair spectra exhibit greater intensity of the amino acid tryptophan (1554 cm^-1), aspartic and glutamic acid (1577 cm^-1). It was also observed that for the separation of samples based on racial differences, untreated Caucasian hair was discriminated from Asian hair as a result of having higher levels of the amino acid cystine and cysteic acid. However, when mildly or chemically treated, Asian and Caucasian hair fibres are similar, whereas African-type hair fibres are different. In terms of the investigation's novel contribution to the field of forensic science, it has allowed for the development of a novel, multifaceted, methodical protocol where previously none had existed. The protocol is a systematic method to rapidly investigate unknown or questioned single human hair FTIR-ATR spectra from different genders and racial origin, including fibres of different cosmetic treatments. Unknown or questioned spectra are first separated on the basis of chemical treatment i.e. untreated, mildly treated or chemically treated, genders, and racial origin i.e. Asian, Caucasian and African-type. The methodology has the potential to complement the current forensic analysis methods of fibre evidence (i.e. Microscopy and DNA), providing information on the morphological, genetic and structural levels.

Near-infrared spectroscopic studies of human scalp hair in a forensic context

Human hair is a relatively inert biopolymer and can survive through natural disasters. It is also found as trace evidence at crime scenes. Previous studies by FTIRMicrospectroscopy and – Attenuated Total Reflectance (ATR) successfully showed that hairs can be matched and discriminated on the basis of gender, race and hair treatment, when interpreted by chemometrics. However, these spectroscopic techniques are difficult to operate at- or on-field. On the other hand, some near infrared spectroscopic (NIRS) instruments equipped with an optical probe, are portable and thus, facilitate the on- or at –field measurements for potential application directly at a crime or disaster scene. This thesis is focused on bulk hair samples, which are free of their roots, and thus, independent of potential DNA contribution for identification. It explores the building of a profile of an individual with the use of the NIRS technique on the basis of information on gender, race and treated hair, i.e. variables which can match and discriminate individuals. The complex spectra collected may be compared and interpreted with the use of chemometrics. These methods can then be used as protocol for further investigations. Water is a common substance present at forensic scenes e.g. at home in a bath, in the swimming pool; it is also common outdoors in the sea, river, dam, puddles and especially during DVI incidents at the seashore after a tsunami. For this reason, the matching and discrimination of bulk hair samples after the water immersion treatment was also explored. Through this research, it was found that Near Infrared Spectroscopy, with the use of an optical probe, has successfully matched and discriminated bulk hair samples to build a profile for the possible application to a crime or disaster scene. Through the interpretation of Chemometrics, such characteristics included Gender and Race. A novel approach was to measure the spectra not only in the usual NIR range (4000 – 7500 cm-1) but also in the Visible NIR (7500 – 12800 cm-1). This proved to be particularly useful in exploring the discrimination of differently coloured hair, e.g. naturally coloured, bleached or dyed. The NIR region is sensitive to molecular vibrations of the hair fibre structure as well as that of the dyes and damage from bleaching. But the Visible NIR region preferentially responds to the natural colourants, the melanin, which involves electronic transitions. This approach was shown to provide improved discrimination between dyed and untreated hair. This thesis is an extensive study of the application of NIRS with the aid of chemometrics, for matching and discrimination of bulk human scalp hair. The work not only indicates the strong potential of this technique in this field but also breaks new ground with the exploration of the use of the NIR and Visible NIR ranges for spectral sampling. It also develops methods for measuring spectra from hair which has been immersed in different water media (sea, river and dam)

Characterisation of soils with the use of instrumental techniques : a multivariate forensic study

The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.

Non-invasive, quantitative analysis of drug mixtures in containers using spatially offset Raman spectroscopy (SORS) and multivariate statistical analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for non-invasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform non-invasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.