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The fast and reliable detection, segmentation and visualization of latent fingerprints are the main tasks in forensics. Currently, conventional fingerprints are searched for, recorded and subsequently analyzed via traditional destructive physical and chemical methods. For firmly defined crime objects and undefined crime scenes, the forensic process is very time-consuming and can take several hours for a single fingerprint. In this context, a laser-based measurement technique that records complete latent fingerprints under fifteen seconds in a non-destructive manner was developed that digitizes the fingerprint for postprocessing steps. The optical system is based on confocal measurements in the mid-infrared wavelength range (2 μm–4 μm) to analyze specific chemical substances at crime scenes. The resulting chemical segmentation allows molecule-dependent analysis of latent and visually invisible fingerprints, providing clear conclusions about the perpetrator or the course of the crime. In this study, the application of the developed measurement system (MIR scanner) to capture fingerprints in a molecule-dependent manner within few seconds is demonstrated, compared with reference methods such as FTIR (Fourier transform infrared spectroscopy) imaging, and extended to real crime objects. [ABSTRACT FROM AUTHOR]

Electrochromic visualization of latent fingermarks has already been achieved on conducting surfaces such as stainless steel. However, their enhancement on non-conducting surfaces such as glass via electrochromism has not been reported. Considering the non-conductive nature of substrates, a layer of gold was introduced to the fingermark-bearing surfaces, in which gold was used as the cathodes to assemble electrochromic devices for visualization. The contact between gold nanoparticles of the as-obtained conducting layer in the fingermark region should be affected by the height difference within the fingermark, leading to conductivity differences, which give rise to coloration differences in electrochromic devices. It is demonstrated that 1,1′-dibenzyl-4,4′-bipyridinium dichloride can be used as the electrochromic chromophore for the visualization of latent fingermarks deposited on nonconducting surfaces, and the primary and secondary characteristic information can be obtained. The electrochromic visualization herein solves the problem of electrochromically enhancing latent fingermarks on non-conducting surfaces. [ABSTRACT FROM AUTHOR]

Neuromuscular disorders are a group of conditions that can result in weakness of skeletal muscles. Examples include fatal diseases such as amyotrophic lateral sclerosis and conditions associated with high morbidity such as myopathies (muscle diseases). Many of these disorders are known to have abnormal protein folding and protein aggregates. Thus, easy to apply methods for the detection of such changes may prove useful diagnostic biomarkers. Raman spectroscopy has shown early promise in the detection of muscle pathology in neuromuscular disorders and is well suited to characterising the conformational profiles relating to protein secondary structure. In this work, we assess if Raman spectroscopy can detect differences in protein structure in muscle in the setting of neuromuscular disease. We utilise in vivo Raman spectroscopy measurements from preclinical models of amyotrophic lateral sclerosis and the myopathy Duchenne muscular dystrophy, together with ex vivo measurements of human muscle samples from individuals with and without myopathy. Using quantitative conformation profiling and matrix factorisation we demonstrate that quantitative 'conformational fingerprinting' can be used to identify changes in protein folding in muscle. Notably, myopathic conditions in both preclinical models and human samples manifested a significant reduction in α-helix structures, with concomitant increases in β-sheet and, to a lesser extent, nonregular configurations. Spectral patterns derived through non-negative matrix factorisation were able to identify myopathy with a high accuracy (79% in mouse, 78% in human tissue). This work demonstrates the potential of conformational fingerprinting as an interpretable biomarker for neuromuscular disorders. [ABSTRACT FROM AUTHOR]

Fingerprints have long been the gold standard for personal identification in forensic science. However, realizing the high-resolution enhancement of eccrine LFPs is difficult using the traditional methods and the label-free detection of fingerprint residue information is also challenging. Herein, we propose two enhancement strategies for LFPs on PVDF membrane (LFPs/PVDF) using blue-black ink staining and scanning electrochemical microscopy (SECM). The blue-black ink staining method was used for the first time to develop three types (sebaceous, natural and eccrine) of LFPs/PVDF based on the difference in wettability between the fingerprint residues and PVDF membrane. The enhanced fingerprints clearly displayed levels 1–3 features with high contrast and low background interference. Furthermore, we achieved chemical imaging of the LFP/PVDF samples, where their possible visualization mechanisms were ascribed to the electrochemical reactivity of squalene and difference in wettability between the LFP and PVDF membrane, which was first proposed and investigated by SECM imaging and water contact angle (WCA) measurements, respectively. Significantly, SECM imaging not only provided fingerprint patterns without any labelling but also revealed the spatial distribution information of squalene in LFPs simultaneously. In addition, it was also demonstrated that LFPs deposited on various surfaces were first successfully transferred to the PVDF membrane, and then further developed with both methods, making them general for personal identity-related applications. Taken together, the blue-black ink staining method can easily and quickly obtain level 3 features of LFPs/PVDF and the SECM approach can non-invasively image the topography and chemical information of LFPs/PVDF, and thus they can be potentially selected according to various requirements in forensic scenarios. [ABSTRACT FROM AUTHOR]

Administration of cytotoxic agents like doxorubicin (DOX) is restrained by the effects on different non-targeted/non-cancerous tissues, which instigates the development of nano-enabled drug delivery systems, among others. In this study, imaging mass spectrometry (IMS) was selected to examine the effects of DOX nanoformulations on non-targeted tissues. Chemical alterations induced by liposomal (LPS) and poly (lactic-co-glycolic acid) (PLG) nanoformulations were assessed against the ones induced by the conventional (CNV) formulation. Kidney cryosections of the treated and control Wistar rats were used as a model of the non-targeted tissue and analyzed by MALDI TOF IMS in the 200–1000 Da m/z range. Principal component analysis (PCA) and Volcano plots of the average mass spectra demonstrated a large overlap between treatments. However, the Venn diagram of significant m/z values revealed a nanoformulation-specific fingerprint consisting of 59 m/z values, which set them apart from the CNV formulation characterized by the fingerprint of 22 significant m/z values. Fingerprint m/z values that were putatively annotated by metabolome database search were linked to apoptosis, cell migration and proliferation. In CNV and PLG cases, false discovery rate adjusted ANOVA showed no differences in the spatial distribution of fingerprint m/z values between the histological substructures like glomeruli and convoluted tubules indicating their tissue-nonselective effect. LPS caused the least significant changes in m/z values and some of the LPS-specific fingerprint m/z values were primarily distributed in the glomeruli. The IMS based procedure successfully differentiated the effects of DOX formulations on the model non-targeted tissue, thus indicating the importance of IMS in effective drug development. [ABSTRACT FROM AUTHOR]

Degradation of fingermark residue has a major impact on the successful forensic detection of latent fingermarks. The time course of degradation has been previously explored with bulk chemical analyses, but little is known about chemical alterations within specific regions of the fingermark, which is difficult to study with bulk measurement. Here we report the use of synchrotron-sourced attenuated total reflection-Fourier transform infrared (ATR-FTIR) microspectroscopy to provide spatio-temporal resolution of chemical changes within fingermark droplets, as a function of time since deposition, under ambient temperature conditions. Eccrine and sebaceous material within natural fingermark droplets were imaged on the micron scales at hourly intervals from the time of deposition until the first 7–13 hours after deposition, revealing that substantial dehydration occurred within the first 8 hours. Changes to lipid material were more varied, with samples exhibiting an increase or decrease in lipid concentration due to the degradation and redistribution of this material. Across 12 donors, it was noticeable that the initial chemical composition and morphology of the droplet varied greatly, which appeared to influence the rate of change of the droplet over time. Further, this study attempted to quantify the total water content within fingermark samples. The wide-spread nature and strength of the absorption of Terahertz/Far-infrared (THz/Far-IR) radiation by water vapour molecules were exploited for this purpose, using THz/Far-IR gas-phase spectroscopy. Upon heating, water confined in natural fingermarks was evaporated and expanded in a vacuum chamber equipped with multipass optics. The amount of water vapour was then quantified by high-spectral resolution analysis, and fingermarks were observed to lose approximately 14–20 μg of water. The combination of both ATR-FTIR and Far-IR gas-phase techniques highlight important implications for experimental design in fingermark research, and operational practices used by law enforcement agencies. [ABSTRACT FROM AUTHOR]

With growing environmental concern and supply chain uncertainty, now is a fitting time to re-evaluate solvent-free methodologies in forensic chemistry processes. Here, this paper reviews solvent-free approaches for fingermark visualisation, including chemical fuming and vapour phase treatments, dry-transfer treatments, application of heat, and thermal paper specific treatments. After providing historical context, three objectives have been emphasised: identify feasible scenarios for implementing solvent-free methods; showcase the effectiveness of solvent-free methods relative to their nearest solution-based equivalent; and estimate the technological readiness level of each method discussed. Having reviewed the literature, dry-transfer methods of developing latent fingermarks on paper were found to be the most promising and feasible solvent-free approaches for near-term implementation. Such methods make use of standard materials and equipment commonly found in forensic laboratories, are effective at fingermark visualisation, and mitigate most of the pressing issues pertaining to environmental concern and solvent scarcity. [ABSTRACT FROM AUTHOR]

Minimising background fluorescence can enhance the visible details of treated fingerprints. Here, a 4-tpt fingerprint powder exhibiting long-lived phosphorescence is applied to this end. The powder was found to suppress background fluorescence, including on challenging surfaces, when using standard forensic equipment and eschewing specialized or bespoke imaging techniques. [ABSTRACT FROM AUTHOR]

Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free techniques being leveraged for digital histopathology. Modern histopathologic identification of ovarian cancer involves tissue staining followed by morphological pattern recognition. This process is time-consuming and subjective and requires extensive expertise. This paper presents the first label-free, quantitative, and automated histological recognition of ovarian tissue subtypes using a new MIRSI technique. This optical photothermal infrared (O-PTIR) imaging technique provides a 10× enhancement in spatial resolution relative to prior instruments. It enables sub-cellular spectroscopic investigation of tissue at biochemically important fingerprint wavelengths. We demonstrate that the enhanced resolution of sub-cellular features, combined with spectroscopic information, enables reliable classification of ovarian cell subtypes achieving a classification accuracy of 0.98. Moreover, we present a statistically robust analysis from 78 patient samples with over 60 million data points. We show that sub-cellular resolution from five wavenumbers is sufficient to outperform state-of-the-art diffraction-limited techniques with up to 235 wavenumbers. We also propose two quantitative biomarkers based on the relative quantities of epithelia and stroma that exhibit efficacy in early cancer diagnosis. This paper demonstrates that combining deep learning with intrinsic biochemical MIRSI measurements enables quantitative evaluation of cancerous tissue, improving the rigor and reproducibility of histopathology. [ABSTRACT FROM AUTHOR]

Raman spectroscopy imaging is a technique that can be adapted for intraoperative tissue characterization to be used for surgical guidance. Here we present a macroscopic line scanning Raman imaging system that has been modified to ensure suitability for intraoperative use. The imaging system has a field of view of 1 × 1 cm2 and acquires Raman fingerprint images of 40 × 42 pixels, typically in less than 5 minutes. The system is mounted on a mobile cart, it is equiped with a passive support arm and possesses a removable and sterilizable probe muzzle. The results of a proof of concept study are presented in porcine adipose and muscle tissue. Supervised machine learning models (support vector machines and random forests) were trained and they were tested on a holdout dataset consisting of 7 Raman images (10 080 spectra) acquired in different animal tissues. This led to a detection accuracy >96% and prediction confidence maps providing a quantitative detection assessment for tissue border visualization. Further testing was accomplished on a dataset acquired with the imaging probe's contact muzzle and tailored classification models showed robust classifications capabilities with specificity, sensitivity and accuracy all surpassing 95% with a support vector machine classifier. Finally, laser safety, biosafety and sterilization of the system was assest. The safety assessment showed that the system's laser can be operated safetly according to the American National Standards Institute's standard for maximum permissible exposures for eyes and skin. It was further shown that during tissue interrogation, the temperature-history in cumulative equivalent minutes at 43 °C (CEM43 °C) never exceeded a safe threshold of 5 min. [ABSTRACT FROM AUTHOR]

An investigation into capillary-scale ion chromatography with suppressed conductivity detection is presented for the identification of low molecular weight anions in samples of limited size. Both particle-packed and polymer monolith capillary ion exchange resins were compared with respect to their chromatographic efficiencies, operating back-pressures and thermal selectivities. Using a multistep hydroxide gradient, it was possible to separate a large selection of inorganic and organic anions in <23 mins using both phases with an injection volume of only 0.4 μL. Method performance was tested with respect to linearity, range, reproducibility and sensitivity and compared to a micro-bore (2 mm) IC method. Limits of mass sensitivity improved by factors up to 1,800-fold using the capillary IC system and lay in the range 0.3-26.2 pg. The finalised analytical method was applied to the determination of both endogenous and exogenous species in sweat and fingermark deposits. It was possible to determine presence of elevated levels of thiocyanate and benzoate in the sweat of three moderate smokers (5-10 cigarettes/day) in comparison to non-smokers. A controlled firing experiment was also conducted to assess the transfer of gunshot residue into fingerprints of a firer. Similarly, identification of direct contact with a black powder substitute is presented via analysis of latent fingermarks. To the best of our knowledge, this represents the first study of sweat and fingerprints using capillary-scale suppressed ion chromatography.

Latent fingermarks are an important form of crime-scene trace evidence and their usefulness may be increased by a greater understanding of the effect of chemical distribution within fingermarks on the sensitivity and robustness of fingermark detection methods. Specifically, the relative abundance and micro-distribution of sebaceous (lipophilic) and eccrine (hydrophilic) material in fingermarks have long been debated in the field, yet direct visualisation of relative abundance and micro-distribution was rarely achieved. Such a visualisation is nonetheless essential to provide explanations for the variation in reproducibility or robustness of latent fingermark detection with existing methods, and to identify new strategies to increase detection capabilities. In this investigation, we have used SR-ATR-FTIR and confocal Raman microscopy to probe the spatial micro-distribution of the sebaceous and eccrine chemical components within latent fingermarks, deposited on non-porous surfaces. It was determined that fingermarks exhibit a complex spatial distribution, influenced by the ratio of lipophilic to aqueous components, and to a first approximation resemble a water-in-oil or oil-in-water emulsion. Detection of a substantial lipid component in “eccrine enriched fingermarks” (wherein hands are washed to remove lipids) is noteworthy, as it provides a potential explanation for several scenarios of unexpected fingermark detection using methods previously thought unsuitable for “eccrine deposits”. Furthermore, the pronounced distribution of lipids observed in natural fingermark deposits was intriguing and agrees with recent discussion in this research field that natural fingermarks contain a much higher lipid content than previously thought. [ABSTRACT FROM AUTHOR]

For over one hundred years, the fingerprint has reigned as one of the most trusted pieces of forensic evidence for suspect identification. In the last few decades, the modernization of chemical analysis technologies led scientists to explore new possibilities to further analyse fingermarks sampled from a crime scene. Indeed, the detection of chemicals a suspect has been in contact with before or during the crime can provide valuable insights into criminal investigations. In this regard, imaging mass spectrometry (IMS) has shown to be a powerful tool for the analysis of fingermarks by combining suspect identification and the detection of numerous endogenous and exogenous compounds. A novel approach developed in our laboratory, silver-assisted laser desorption ionization (AgLDI), was adopted to allow for the chemical analysis of latent fingermarks left on nonconductive surfaces (such as paper, cardboard, plastic and forensic lifting tape) with a time-of-flight mass spectrometer. In this study, we continue to evaluate the potential of AgLDI IMS to provide circumstantial evidence by detecting exogenous substances. We first demonstrate that owner-specific chemical signatures can be recovered from fingermarks based on the presence of several cosmetics and personal care products. We then show the possibility of detecting and imaging fingermarks containing three common illicit drugs, namely tetrahydrocannabinol, cocaine and heroin. Finally, we demonstrate that the methodology also allows us to successfully image bloody fingermarks after appropriate forensic enhancement treatments. Overall, we believe that AgLDI IMS has significant potential that could positively contribute to forensic investigations. [ABSTRACT FROM AUTHOR]

In the study presented here, four examples of crime scene fingermarks analysed by Matrix Assisted Laser Desorption Ionisation Mass Spectrometry Imaging (MALDI MSI), in collaboration with the local Police Force, are reported. These marks are associated to high profile crimes such as drug dealing, murder and harassment. Following the application of forensic enhancement techniques by the CSI or the crime lab, one of the marks could be directly analysed on the surface of deposition and the others were analysed as primary lifts. In one case, no physical or molecular information was obtained whereas in two cases both ridge detail (albeit not useful for identification purposes) and molecular information could be retrieved. In one case, the intelligence gathered around the suspect's state of mind is, to date the most accomplished demonstration of the benefits and the operational feasibility MALDI MS based methods. These four casework examples are to be considered a first insight into the limitations, benefits and feasibility of MALDI MS based methods in the field; due to the extreme variability in the state of the mark, comprehensive evaluation of these aspects can only be undertaken upon the analysis of a large number of crime scene marks. However, this work does represent a significant advancement, compared to previous published work, as it demonstrates operational feasibility, with different levels of success, despite uncontrollable, unknown and unaccountable environmental and donor variability. [ABSTRACT FROM AUTHOR]

This review highlights the considerable advances in the chemical imaging of human fingermarks that provide more chemical information, including numerous endogenous and exogenous constituents. Despite remarkable development in DNA analysis and recognition, human fingermark analysis remains one of the priority approaches available for obtaining reliable forensic evidence. Additional information about the donor can be obtained from the chemical composition of latent fingermarks in addition to the ridge pattern, such as the age, gender, medical history, and possible drug habits. The analytical approaches reviewed here include spectroscopy, mass spectrometry, immuno-labelling and electrochemical methods. Each method has different capabilities with respect to sensitivity, reproducibility, selectivity, reliability and ultimately applicability, either for use in routine forensic practice or in academic research work. The advantages of spectroscopic techniques, including infrared, Raman and micro-X-ray fluorescence spectroscopy, are the capabilities of a rapid and non-destructive imaging of fingermarks by providing spectral information on chemical composition. In addition, mass spectrometry imaging can provide spatially specific information on fingermark chemical composition. Recently, the use of immuno-labelling in latent fingermark detection has attracted significant attention because it can overcome the sensitivity and selectivity problems experienced with other existing methods. The electrochemical method has also been employed to image latent fingermarks by measuring the electric current changes with the spatial chemical composition from the ridges and valleys at high resolution to provide a third level of detail, which is especially useful for multicoloured background surfaces or for surfaces contaminated with blood or other bodily fluids. [ABSTRACT FROM AUTHOR]

Despite the fact that various microorganisms (e.g., bacteria, fungi, viruses, etc.) have been linked with infectious diseases, their crucial role towards sustaining life on Earth is undeniable. The huge biodiversity, combined with the wide range of biochemical capabilities of these organisms, have always been the driving force behind their large number of current, and, as of yet, undiscovered future applications. The presence of such diversity could be said to expedite the need for the development of rapid, accurate and sensitive techniques which allow for the detection, differentiation, identification and classification of such organisms. In this study, we employed Fourier transform infrared (FT-IR), Raman, and surface enhanced Raman scattering (SERS) spectroscopies, as molecular whole-organism fingerprinting techniques, combined with multivariate statistical analysis approaches for the classification of a range of industrial, environmental or clinically relevant bacteria (P. aeruginosa, P. putida, E. coli, E. faecium, S. lividans, B. subtilis, B. cereus) and yeast (S. cerevisiae). Principal components-discriminant function analysis (PC-DFA) scores plots of the spectral data collected from all three techniques allowed for the clear differentiation of all the samples down to sub-species level. The partial least squares-discriminant analysis (PLS-DA) models generated using the SERS spectral data displayed lower accuracy (74.9%) when compared to those obtained from conventional Raman (97.8%) and FT-IR (96.2%) analyses. In addition, whilst background fluorescence was detected in Raman spectra for S. cerevisiae, this fluorescence was quenched when applying SERS to the same species, and conversely SERS appeared to introduce strong fluorescence when analysing P. putida. It is also worth noting that FT-IR analysis provided spectral data of high quality and reproducibility for the whole sample set, suggesting its applicability to a wider range of samples, and perhaps the most suitable for the analysis of mixed cultures in future studies. Furthermore, our results suggest that while each of these spectroscopic approaches may favour different organisms (sample types), when combined, they would provide complementary and more in-depth knowledge (structural and/or metabolic state) of biological systems. To the best of our knowledge, this is the first time that such a comparative and combined spectroscopic study (using FT-IR, Raman and SERS) has been carried out on microbial samples. [ABSTRACT FROM AUTHOR]

Fingerprint analysis is one of the most important methods used for personal identification of evidence found at a crime scene for forensic purposes. Using scanning electrochemical microscopy (SECM) imaging, researchers can visualize the ultrastructure of human fingerprints on wet porous and non-porous surfaces by combining with silver-staining or multi-metal-deposition (MMD) technology. SECM allows investigators to image chemical activities of fingerprint surfaces with an impressively high resolution, such as the third level valuable information for confirming an identification. This methodology takes a significant advantage of the high sensitivity of SECM towards the small variation of electrochemical reaction rates at the substrate surface. In this review, we highlight the recent breakthroughs in ultrasensitive imaging and detection of latent fingerprints with a special focus on a novel application of SECM. We will also discuss our perspectives on future research directions. [ABSTRACT FROM AUTHOR]

Latent fingerprints provide a potential route to the secure, high throughput and non-invasive detection of drugs of abuse. In this study we show for the first time that the excreted metabolites of drugs of abuse can be detected in fingerprints using ambient mass spectrometry. Fingerprints and oral fluid were taken from patients attending a drug and alcohol treatment service. Gas chromatography mass spectrometry (GC-MS) was used to test the oral fluid of patients for the presence of cocaine and benzoylecgonine. The corresponding fingerprints were analysed using Desorption Electrospray Ionization (DESI) which operates under ambient conditions and Ion Mobility Tandem Mass Spectrometry Matrix Assisted Laser Desorption Ionization (MALDI-IMS-MS/MS) and Secondary Ion Mass Spectrometry (SIMS). The detection of cocaine, benzoylecgonine (BZE) and methylecgonine (EME) in latent fingerprints using both DESI and MALDI showed good correlation with oral fluid testing. The sensitivity of SIMS was found to be insufficient for this application. These results provide exciting opportunities for the use of fingerprints as a new sampling medium for secure, non-invasive drug detection. The mass spectrometry techniques used here offer a high level of selectivity and consume only a small area of a single fingerprint, allowing repeat and high throughput analyses of a single sample. [ABSTRACT FROM AUTHOR]

We evaluated the use of the peptide mass fingerprint (PMF) obtained by matrix assisted laser desorption and ionization (MALDI) time-of-flight mass spectrometry (TOF-MS) to track changes in the structure of a protein. The first problem we had to overcome was the inherent complexity of the PMF, which makes it difficult to compare. We dealt with this problem by developing a cluster-based comparison algorithm which takes into account the proportional error made by the mass spectrometer. This procedure involves grouping together similar masses in an intelligent manner, so that we can determine which data correspond to the same peptide (any slight differences can be explained as experimental errors), and which of them are too different and thus more likely to represent different peptides. The proposed algorithm was applied to track changes in a commercially available monoclonal antibody (mAb), namely rituximab (RTX), prepared under the usual hospital conditions and stored refrigerated (4 °C) and frozen (−20 °C) for a long term study. PMFs were obtained periodically over three months. For each checked time, five replicates of the PMFs were obtained in order to evaluate the similarities between them by means of the occurrences of the particular peptides (m/z). After applying the algorithm to the PMF, different approaches were used to analyse the results. Surprisingly, all of them suggested that there were no differences between the two storage conditions tested, i.e. the RTX samples were almost equally well preserved when stored refrigerated at 4 °C or frozen at −20 °C. The cluster-based methodology is new in protein mass spectrometry and could be useful as an easy test for major changes in proteins and biopharmaceutics for diverse applications in industry and other fields, and could provide additional stability data in relation to the practical use of anticancer drugs. [ABSTRACT FROM AUTHOR]

Desorption electro-flow focusing ionization (DEFFI) mass spectrometry was used to image chemical distributions of endogenous, e.g., fatty acids, and trace exogenous compounds, e.g., explosives, narcotics and lotions, in deposited and lifted artificial fingerprints, directly from forensic lift tape. An artificial fingerprint mold and synthetic fingerprint material were incorporated for the controlled deposition of material for technique demonstration and evaluation. [ABSTRACT FROM AUTHOR]

The article focuses on a research which was focused on analyzing the impact of silole compounds on the visualization of the latent fingerprints on wet non-porous surfaces. Topics discussed includes latent fingerprints (LFPs), tetraphenylsiloles, fingerprint detection and also presents various graphs related to the research.

Latent fingermarks are invisible to the naked eye and normally require the application of a chemical developer followed by an optical imaging step in order to visualize the ridge detail. If the finger deposition is poor, or the fingermark is aged, it can sometimes be difficult to produce an image of sufficient quality for identification. In this work, we show for the first time how mass spectrometry imaging (in this case time-of-flight secondary ion mass spectrometry, ToF-SIMS) can be used to enhance the quality of partially recovered fingermarks. We show three examples of how chemical imaging can be used to obtain enhanced images of fingermarks deposited on aluminium foil, glass and the handle of a hand grenade compared with conventional development techniques. [ABSTRACT FROM AUTHOR]

Visualization and detection of latent fingerprints (LFPs) on metal surfaces are of highly practical importance, e.g., in identifying gun cartridges. We report herein the visualization of LFPs on stainless steel surfaces by electrochemiluminescence (ECL). Since organic residues, such as fatty acids, in the fingerprint deposit make the underlying surface electrochemically inert or less active, an ECL reaction occurs only on the metal portions untouched by the fingertip, hence generating a negative image of the fingerprint. The popular ECL reaction solution, consisting of ruthenium(ii) tris(2,2′-bipyridyl) and tri-n-propylamine, was used for this imaging purpose. Factors, including the applied potential and the concentration of ECL luminophore, as well as the stability of ECL negative images, were investigated to achieve a satisfactory visualization enhancement. This imaging approach is simple, rapid, non-invasive, and no pre-treatment either on the background or on the fingerprint itself is needed. It constitutes a powerful tool for visualizing LFPs on metal surfaces. This method was also demonstrated to be suitable for enhancing LFPs collected from various surfaces. [ABSTRACT FROM AUTHOR]

Raman spectroscopy is widely used as a fingerprint technique for molecular identification. However, Raman spectra contain molecular information from multiple components and interferences from noise and instrumentation. Thus, component identification using Raman spectra is still challenging, especially for mixtures. In this study, a novel approach entitled deep learning-based component identification (DeepCID) was proposed to solve this problem. Convolution neural network (CNN) models were established to predict the presence of components in mixtures. Comparative studies showed that DeepCID could learn spectral features and identify components in both simulated and real Raman spectral datasets of mixtures with higher accuracy and significantly lower false positive rates. In addition, DeepCID showed better sensitivity when compared with the logistic regression (LR) with L1-regularization, k-nearest neighbor (kNN), random forest (RF) and back propagation artificial neural network (BP-ANN) models for ternary mixture spectral datasets. In conclusion, DeepCID is a promising method for solving the component identification problem in the Raman spectra of mixtures. [ABSTRACT FROM AUTHOR]

Assessing the capabilities of instrumental techniques aiming at differentiating marine oils is a matter of great importance for both authorities and industries which has been highlighted over 120 years. In this study, different strategies were evaluated by means of principal component analysis (PCA) for their performance in differentiating various marine oils. Triacylglycerols (TAGs) composition and four different profiles including total ion current (TIC) and total mass spectral (TMS) profiles derived from liquid chromatography electrospray single and tandem mass spectrometry (LC-ESI-MS and LC-ESI-MS2) were used as the dataset for PCA study. Among these strategies, the tandem TMS profiles from LC-ESI-MS2experiments as the dataset demonstrated to be the most rapid and convenient approach for the differentiation of various marine and plant oils investigated and for the representation of the characteristics TAG patterns. This novel approach represents an alternative and promising tool for fingerprinting and differentiating marine oils. [ABSTRACT FROM AUTHOR]

This work is concerned with the research and development of methodology for analysis of complex mixtures such as pharmaceutical or food samples, which contain many analytes. Variously treated samples (swill washed, fried and scorched) of the Rhizoma atractylodis macrocephalae(RAM) traditional Chinese medicine (TCM) as well as the common substitute, Rhizoma atractylodis(RA) TCM were chosen as examples for analysis. A combined data matrix of chromatographic 2-D HPLC-DAD-FLD (two-dimensional high performance liquid chromatography with diode array and fluorescence detectors) fingerprint profiles was constructed with the use of the HPLC-DAD and HPLC-FLD individual data matrices; the purpose was to collect maximum information and to interpret this complex data with the use of various chemometrics methods e.g.the rank-ordering multi-criteria decision making (MCDM) PROMETHEE and GAIA, K-nearest neighbours (KNN), partial least squares (PLS), back propagation-artificial neural networks (BP-ANN) methods. The chemometrics analysis demonstrated that the combined 2-D HPLC-DAD-FLD data matrix does indeed provide more information and facilitates better performing classification/prediction models for the analysis of such complex samples as the RAM and RA ones noted above. It is suggested that this fingerprint approach is suitable for analysis of other complex, multi-analyte substances. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease is associated with obesity, diabetes, and metabolic syndrome. The detection of systemic metabolic changes associated with alterations in the liver status during non-alcoholic fatty liver disease could improve patient follow-up. The aim of the present study was to evaluate the potential of mid-infrared fibre evanescent wave spectroscopy as a minimum-invasive method for evaluating the liver status during non-alcoholic fatty liver disease. Seventy-five mice were subjected to a control, high-fat or high-fat–high carbohydrate diets. We analysed the serum biochemical parameters and mRNA levels of hepatic genes by quantitative RT-PCR. Steatosis was quantified by image analysis. The mid-infrared spectra were acquired from serum, and then analysed to develop a predictive model of the steatosis level. Animals subjected to enriched diets were obese. Hepatic steatosis was found in all animals. The relationship between the spectroscopy-predicted and observed levels of steatosis, expressed as percentages of the liver biopsy area, was not linear. A transition around 10% steatosis was observed, leading us to consider two distinct predictive models (＜10% and ＞10%) based on two different sets of discriminative spectral variables. The model performance was evaluated using random cross-validation (10%). The hypothesis that additional metabolic changes occur beyond this transition was supported by the fact that it was associated with increased serum ALT levels, and Col1α1 chain mRNA levels. Our data suggest that mid-infrared spectroscopy combined with statistical analysis allows identifying serum mid-infrared signatures that reflect the liver status during non-alcoholic fatty liver disease. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman spectrocopy (SERS) offers ultrasensitive vibrational fingerprinting at the nanoscale. Its non-destructive nature affords an ideal tool for interrogation of the intracellular environment, detecting the localisation of biomolecules, delivery and monitoring of therapeutics and for characterisation of complex cellular processes at the molecular level. Innovations in nanotechnology have produced a wide selection of novel, purpose-built plasmonic nanostructures capable of high SERS enhancement for intracellular probing while microfluidic technologies are being utilised to reproducibly synthesise nanoparticle (NP) probes at large scale and in high throughput. Sophisticated multivariate analysis techniques unlock the wealth of previously unattainable biomolecular information contained within large and multidimensional SERS datasets. Thus, with suitable combination of experimental techniques and analytics, SERS boasts enormous potential for cell based assays and to expand our understanding of the intracellular environment. In this review we trace the pathway to utilisation of nanomaterials for intracellular SERS. Thus we review and assess nanoparticle synthesis methods, their toxicity and cell interactions before presenting significant developments in intracellular SERS methodologies and how identified challenges can be addressed. [ABSTRACT FROM AUTHOR]

Based on the bianalyte method, time-dependent surface-enhanced Raman spectrosopy (SERS) spectra were applied to observe and study the competitive adsorption of bipyridine isomerides 2,2′-bpy and 4,4′-bpy. These time-dependent SERS spectra offer a significant advantage for observing the continuous SERS spectra of analyte with 2 s resolution, letting one monitor real-time competitive adsorption and corresponding SERS signal intensity for mixed or pure analyte type events under different concentrations. In this study, we report experimental evidence of competitive adsorption of two bipyridine isomerides using SERS mapping and independent spectra in chronological order. On the one hand, the time-dependent SERS spectra of 2,2′-bpy were prior dominated in the early stage either in high concentration or in low concentration. On the other hand, pure type 2,2′-bpy or 4,4′-bpy events only occurred for strong intensity, whereas weak intensity events exhibited more mixed analytes in low concentration, showing a great difference from those at the higher concentration. In addition, we believe that these results and this evidence can motivate the use of time-dependent SERS spectra for distinguishing the fingerprint information of several molecules from similar isomeride molecules in chemical and biological systems. [ABSTRACT FROM AUTHOR]

Human plasma proteins and even structurally similar homologous albumins were fingerprinted and discriminated by a sensor array consisting of a polyion complex library with artificial differentiation constructed by facile tuning of PEGylated polyamine functionalities. [ABSTRACT FROM AUTHOR]

The utilization of the plasmonic response of aptamer–gold nanoparticle conjugates (Apt–AuNPs) to design cross-reactive arrays for fingerprint identification of small molecular targets was demonstrated for the first time. Four aptamers with different structural features previously selected to bind different targets were used in combination with AuNPs by adsorbing the DNA on the AuNPs surface. The optimized response of the Apt–AuNPs to the analytes showed that, depending on the specific aptamer used, target binding by the aptamer could result in an increase or decrease of Apt–AuNPs stability. These Apt–AuNPs showed the ability to recognize different analytes with different affinities, generating fingerprints that allowed unambiguous analyte identification with response times in less than fifteen minutes. Importantly, it was observed that it was not necessary to select an aptamer per analyte of interest to generate differentiable signatures, but a subset of aptamers could be used to identify a larger number of analytes. The data was analyzed using principal component analysis, showing efficient clustering of the different datasets for qualitative and quantitative identification. This work opens the door to using these Apt–AuNPs in point of care diagnostics applications where fast sensors with easy to read outputs are needed. [ABSTRACT FROM AUTHOR]

We describe a novel ‘switch-off’ biosensing strategy for the detection of chymotrypsin based on surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS) spectroscopy. This approach analyzes the fingerprint spectrum of the chymotrypsin-catalyzed substrate. The lowest probed concentration is 0.4 nM for chymotrypsin. [ABSTRACT FROM AUTHOR]

After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable. [ABSTRACT FROM AUTHOR]

Infrared spectroscopy enables the identification of tissue types based on their inherent vibrational fingerprint without staining in a nondestructive way. Here, Fourier transform infrared microscopic images were collected from 22 brain metastasis tissue sections of bladder carcinoma, lung carcinoma, mamma carcinoma, colon carcinoma, prostate carcinoma and renal cell carcinoma. The scope of this study was to distinguish the infrared spectra of carcinoma from normal tissue and necrosis and to use the infrared spectra of carcinoma to determine the primary tumor of brain metastasis. Data processing follows procedures that have previously been developed for the analysis of Raman images of these samples and includes the unmixing algorithm N-FINDR, segmentation by k-means clustering, and classification by support vector machines (SVMs). Upon comparison with the subsequent hematoxylin and eosin stained tissue sections of training specimens, correct classification rates of the first level SVM were 98.8% for brain tissue, 98.4% for necrosis and 94.4% for carcinoma. The primary tumors were correctly predicted with an overall rate of 98.7% for FTIR images of the training dataset by a second level SVM. Finally, the two level discrimination models were applied to four independent specimens for validation. Although the classification rates are slightly reduced compared to the training specimens, the majority of the infrared spectra of the independent specimens were assigned to the correct primary tumor. The results demonstrate the capability of FTIR imaging to complement histopathological tools for brain tissue diagnosis. [ABSTRACT FROM AUTHOR]

Magnetic particles functionalised with anti-cotinine antibody have been used to image latent fingermarks through the detection of the cotinine antigen in the sweat deposited within the fingerprints of smokers. The antibody–magnetic particle conjugates are readily applied to latent fingerprints while excess reagents are removed through the use of a magnetic wand. The results have shown that drug metabolites, such as cotinine, can be detected and used to image the fingermark to establish the identity of an individual within 15 minutes. [ABSTRACT FROM AUTHOR]

Microbiological safety plays a very significant part in the quality control of milk and dairy products worldwide. Current methods used in the detection and enumeration of spoilage bacteria in pasteurized milk in the dairy industry, although accurate and sensitive, are time-consuming. FT-IR spectroscopy is a metabolic fingerprinting technique that can potentially be used to deliver results with the same accuracy and sensitivity, within minutes after minimal sample preparation. We tested this hypothesis using attenuated total reflectance (ATR), and high throughput (HT) FT-IR techniques. Three main types of pasteurized milk – whole, semi-skimmed and skimmed – were used and milk was allowed to spoil naturally by incubation at 15 °C. Samples for FT-IR were obtained at frequent, fixed time intervals and pH and total viable counts were also recorded. Multivariate statistical methods, including principal components-discriminant function analysis and partial least squares regression (PLSR), were then used to investigate the relationship between metabolic fingerprints and the total viable counts. FT-IR ATR data for all milks showed reasonable results for bacterial loads above 105cfu ml−1. By contrast, FT-IR HT provided more accurate results for lower viable bacterial counts down to 103cfu ml−1for whole milk and, 4 × 102cfu ml−1for semi-skimmed and skimmed milk. Using FT-IR with PLSR we were able to acquire a metabolic fingerprint rapidly and quantify the microbial load of milk samples accurately, with very little sample preparation. We believe that metabolic fingerprinting using FT-IR has very good potential for future use in the dairy industry as a rapid method of detection and enumeration. [ABSTRACT FROM AUTHOR]

A proteomics profile analysis was performed on a human hepatocyte carcinoma cell line (HepaRG) by using the FD-LC-MS/MS method. One hundred and fifty-eight proteins were newly identified for the first time of which 10 were found to be specific to human hepatocytes. These proteins are a "proteomics fingerprint" that can be used to characterize HepaRG cells. [ABSTRACT FROM AUTHOR]

Fingermarks have long been recognized as one of the most reliable and valuable evidence for personal identification. In practice, fingerprint analysis primarily concentrates on latent fingerprint visualization. However, fingerprint visualization techniques do not always enable individualization when fingermarks collected in crime scenes are fragmentary, ambiguous, or deformed. Age determination techniques based on physical and chemical composition changes in fingerprints over time have attracted researchers' attention in recent years. Nevertheless, the components of fingerprints are liable to factors including donor features, deposition conditions, substrate properties, environmental conditions and revealing methods. All the influences mainly contribute to unreliable outcomes of age estimation. Recent developments in fingermark age determination have moved forward to more precise approaches. The advanced methods can be classified into two categories including techniques based on the modifications of physical characteristics and chemical composition characteristics. Herein, the review includes the five types of variables that influence the aging process. The methodologies are subsequently highlighted along with their advantages and disadvantages. Furthermore, photography, optical, microscopy and electrochemical methods, and vibrational spectroscopy and mass spectrometry (MS) techniques are summarized in detail, with an emphasis on their utilization. [ABSTRACT FROM AUTHOR]

Fingerprint analysis is one of the most important methods used for personal identification of evidence found at a crime scene for forensic purposes. Using scanning electrochemical microscopy (SECM) imaging, researchers can visualize the ultrastructure of human fingerprints on wet porous and non-porous surfaces by combining with silver-staining or multi-metal-deposition (MMD) technology. SECM allows investigators to image chemical activities of fingerprint surfaces with an impressively high resolution, such as the third level valuable information for confirming an identification. This methodology takes a significant advantage of the high sensitivity of SECM towards the small variation of electrochemical reaction rates at the substrate surface. In this review, we highlight the recent breakthroughs in ultrasensitive imaging and detection of latent fingerprints with a special focus on a novel application of SECM. We will also discuss our perspectives on future research directions.