Discriminant analysis of Raman spectra for body fluid identification for forensic purposes

A review on forensic analysis of bio fluids (blood, semen, vaginal fluid, menstrual blood, urine, saliva): Spectroscopic and non-spectroscopic technique

The accurate detection, identification, and analysis of biofluids at crime scenes play a critical role in forensic investigations. Various biofluids, such as blood, semen, vaginal fluid, menstrual blood, urine, and saliva, can be crucial evidence. In a murder case involving a knife attack, for instance, bloodstains from both the victim and perpetrator might be present. Sexual assault cases often involve the analysis of semen and vaginal secretions. Biofluid analysis employs a two-tiered approach: presumptive tests for initial identification and confirmatory tests for definitive analysis. This review article focuses on six key biofluids and their forensic significance. In this review, we comprehensively explore the relevant analytical techniques, including non-spectroscopic methods like immunoassays, spot tests, and cytokine profiling, alongside spectroscopic techniques such as Infrared (IR) spectroscopy, Mass Spectrometry (MS), and Raman Spectroscopy (RS).

AI-driven feature selection and epigenetic pattern analysis: A screening strategy of CpGs validated by pyrosequencing for body fluid identification

Identification of body fluid stain at crime scene is one of the important tasks of forensic evidence analysis. Currently, body fluid-specific CpGs detected by DNA methylation microarray screening, have been widely studied for forensic body fluid identification. However, some CpGs have limited ability to distinguish certain body fluid types. The ongoing need is to discover novel methylation markers and fully validate them to enhance their evidentiary strength in complex forensic scenarios. This research gathered forensic-related DNA methylation microarrays data from the Gene Expression Omnibus (GEO) database. A novel screening strategy for marker selection was developed, combining feature selection algorithms (elastic net, information gain ratio, feature importance based on Random Forest, and mutual information coefficient) with epigenetic pattern analysis, to identify CpG markers for body fluid identification. The selected CpGs were validated through pyrosequencing on peripheral blood, saliva, semen, vaginal secretions, and menstrual blood samples, and machine learning classification models were constructed based on the sequencing results. Pyrosequencing results revealed 14 CpGs with high specificity in five types of body fluid samples. A machine learning classification model, developed based on the pyrosequencing results, could effectively distinguish five types of body fluid samples, achieving 100 % accuracy on the test set. Utilizing six CpG markers, it was also feasible to attain ideal efficacy in identifying body fluid stains. Our research proposes a systematic and scientific strategy for screening body fluid-specific CpGs, contributing new insights and methods to forensic body fluid identification.

Identification of semen traces at a crime scene through Raman spectroscopy and machine learning

Biological fluid stains can be instrumental in solving crimes. Identification of semen can help reconstruct events in sexual assault cases and identify suspects via DNA profiling. Current methods for semen identification suffer from limitations, including destruction of the sample and potential false positives. One of the main unsolved issues is the elimination of underlying substrate interference. In this paper, chemometric approaches were developed to isolate and identify a biofluid stain on interfering substrates using Raman spectroscopy. The first approach, called Multivariate Curve Resolution with the Addition Method, combines the standard addition method with multivariate curve resolution. The second one uses a criterion based on reducing the spectrum complexity when a spectral component is removed from a Raman spectrum of a multi-component sample entirely. The results demonstrate the superiority of the first approach relative to the second for both small volume fraction of the fluid stain compared to the substrate and random noise.

Applications of Raman spectroscopy in the analysis of biological evidence

During the past few decades, Raman spectroscopy has progressed and captivated added attention in the field of science. However, the application of Raman spectroscopy is not limited to the field of forensic science and analytical chemistry; it is one of the emerging spectroscopic techniques, utilized in the field of forensic science which in turn could be a supporting tool in the law and justice system. The advantage of Raman spectroscopy over the other conventional techniques is that it is rapid, reliable, and non-destructive in nature with minimal or no sample preparation. The quantitative and qualitative analysis of evidence from biological and non-biological origins could easily be performed by using Raman spectroscopy. The forensic domain is highly complex with multidisciplinary branches, and therefore a plethora of techniques are utilized for the detection, identification, and differentiation of innumerable pieces of evidence for the purpose of law and justice. Herein, a systematic review is carried out on the application of Raman spectroscopy in the realm of forensic biology and serology considering its usefulness in practical perspectives. This review paper highlights the significance of modern techniques, including micro-Raman spectroscopy, confocal Raman spectroscopy, surface-enhanced Raman spectroscopy, and paper-based surface-enhanced Raman spectroscopy, in the field of Raman spectroscopy. These techniques have demonstrated notable advancements in terms of their applications and capabilities. Furthermore, to comprehensively capture the progress in the development of Raman spectroscopy, all the published papers which could be retrieved from the available databases from the year 2007 to 2022 were incorporated.

Spectral effects and enhancement quantification in healthy human saliva with surface-enhanced Raman spectroscopy using silver nanopillar substrates

OBJECTIVES

Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva.

METHODS

Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR).

RESULTS

SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered.

CONCLUSIONS

Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids.

Machine Learning for Prediction, Classification, and Identification of Immobilized Enzymes for Biocatalysis

BACKGROUND

Enzyme immobilization is a beneficial component involved in biocatalytic strategies. Understanding and evaluating the enzyme immobilization system plays an important role in the successful development and implementation of the biocatalysis route. Ensuring the implementation of a successful enzyme immobilization process is vital for realizing a highly functioning and well suited biocatalytic process within pharmaceutical development.

AIM

To develop a method which can accurately and objectively identify and classify differences within enzyme immobilization systems, sample preparation methods, and data collection parameters.

METHODS

Raman hyperspectral imaging was used to obtain a total of eight spectral data sets from enzyme immobilization samples. Partial least squares discriminant analysis (PLS-DA) was used to classify and identify the samples based on their differences.

RESULTS

Several two-class, four-class, and eight-class PLS-DA models were built to classify the different sample data sets. All models reached between 92-100% accuracy after cross-validation and external validation, illustrating great success of the models for identifying differences between the samples.

CONCLUSION

Raman hyperspectral imaging with machine learning can be used to investigate, interpret, and classify different data collection parameters, sample preparation methods, and enzyme immobilization supports, providing crucial insight into enzyme immobilization process development.

Ultra-sensitive, rapid detection of dried bloodstains by surface enhanced Raman scattering on Ag substrates

A simple water extraction and transfer procedure is found to result in reproducible and highly sensitive 785 nm excited SERS spectra of 24 h dried bloodstains on Ag nanoparticle substrates. This protocol allows confirmatory detection and identification of dried stains of blood that have been diluted by up to 10⁵ in water on Ag substrates. While previous SERS results demonstrated similar performance on Au substrates when a 50% acetic acid extraction and transfer procedure was used, the water/Ag methodology avoids any potential DNA damage when the sample size is extremely small (≤∼1 μL) due to low pH exposure. The water only procedure is not effective on Au SERS substrates. This metal substrate difference results from the efficient red blood cell lysis and hemoglobin denaturation effects of the Ag nanoparticle surfaces as compare to that of Au nanoparticles. Consequently, the 50% acetic acid exposure is required for the acquisition of 785 nm SERS spectra of dried bloodstains on Au substrates.

Specific fluorescent signatures for body fluid identification using fluorescence spectroscopy

Non-invasive, rapid, on-site detection and identification of body fluids is highly desired in forensic investigations. The use of fluorescence-based methods for body fluid identification, have so far remain relatively unexplored. As such, the fluorescent properties of semen, serum, urine, saliva and fingermarks over time were investigated, by means of fluorescence spectroscopy, to identify specific fluorescent signatures for body fluid identification. The samples were excited at 81 different excitation wavelengths ranging from 200 to 600 nm and for each excitation wavelength the emission was recorded between 220 and 700 nm. Subsequently, the total emitted fluorescence intensities of specific fluorescent signatures in the UV-visible range were summed and principal component analysis was performed to cluster the body fluids. Three combinations of four principal components allowed specific clustering of the body fluids, except for fingermarks. Blind testing showed that 71.4% of the unknown samples could be correctly identified. This pilot study shows that the fluorescent behavior of ageing body fluids can be used as a new non-invasive tool for body fluid identification, which can improve the current guidelines for the detection of body fluids in forensic practice and provide the robustness of methods that rely on fluorescence.

Comparative Study of Sample Carriers for the Identification of Volatile Compounds in Biological Fluids Using Raman Spectroscopy

Vibrational spectroscopic techniques and especially Raman spectroscopy are gaining ground in substituting the officially established chromatographic methods in the identification of ethanol and other volatile substances in body fluids, such as blood, urine, saliva, semen, and vaginal fluids. Although a couple of different carriers and substrates have been employed for the biochemical analysis of these samples, most of them are suffering from important weaknesses as far as the analysis of volatile compounds is concerned. For this reason, in this study three carriers are proposed, and the respective sample preparation methods are described for the determination of ethanol in human urine samples. More specifically, a droplet of the sample on a highly reflective carrier of gold layer, a commercially available cuvette with a mirror to enhance backscattered radiation sealed with a lid, and a home designed microscope slide with a cavity coated with gold layer and covered with transparent cling film have been evaluated. Among the three proposed carriers, the last one achieved a quick, simple, and inexpensive identification of ethanol, which was used as a case study for the volatile compound, in the biological samples. The limit of detection (LoD) was found to be 1.00 μL/mL, while at the same time evaporation of ethanol was prevented.

Dose-Response Relationship and Threshold Drug Dosage Identification for a Novel Hybrid Mechanical-Thrombolytic System with an Ultra-Low Dose Patch

Introduction

Ischemic stroke treatment has advanced in the last two decades and intravenous thrombolysis is now considered the standard of care for selected patients. Recanalization can also be achieved by mechanical endovascular treatment for patients with large vessel occlusions. Complicating treatment-related symptomatic intracerebral hemorrhage and prolonged needle-to-recanalization times have been identified as major determinants of poor three-month functional outcomes. A hybrid mechanical-thrombolytic system with a patch imbued with an ultra-low dose of thrombolytic agents loaded onto a stent-retriever has been developed.

Methods

In this study, the in situ dose-response relationship of the thrombolytic patch imbued with up to 1000 IU of urokinase plasminogen activator (uPA) was quantified using Raman spectroscopy.

Results

Thrombi of up to 400 μm thickness dissolved within 15 min when patches imbued with < 1% of the conventional thrombolysis therapy dosage were applied. The results demonstrated that low-dose thrombolytic patches can dissolve normal clots compressed in the blood vessel in a short time. 500 IU is the threshold uPA dosage in the thrombolytic patch that most effectively dissolves the clots.

Conclusion

This study suggests that a novel endovascular stent-retriever loaded with an ultra-low drug dose fibrinolytic patch may be a suitable treatment for patients who are ineligible for conventional thrombolytic therapy.

Recent advances of vibrational spectroscopy and chemometrics for forensic biological analysis

Biological materials found at a crime scene are crucially important evidence for forensic investigation because they provide contextual information about a crime and can be linked to the donor-individuals through combination with DNA analysis. Applications of vibrational spectroscopy to forensic biological analysis have been emerging because of its advantageous characteristics such as the non-destructivity, rapid measurement, and quantitative evaluation, compared to most current methods based on histological observation or biochemical techniques. This review presents an overview of recent developments in vibrational spectroscopy for forensic biological analysis. We also emphasize chemometric techniques, which can elicit reliable and advanced analytical outputs from highly complex spectral data from forensic biological materials. The analytical subjects addressed herein include body fluids, hair, soft tissue, bones, and bioagents. Promising applications for various analytical purposes in forensic biology are presented. Simultaneously, future avenues of study requiring further investigation are discussed.

Spectroscopic molecular-fingerprint profiling of saliva

Saliva analysis has been gaining interest as a potential non-invasive source of disease indicative biomarkers due to being a complex biofluid correlating with blood-based constituents on a molecular level. For saliva to cement its usage for analytical applications, it is paramount to gain underpinning molecular knowledge and establish a 'baseline' of the salivary composition in healthy individuals as well as characterize how these factors are impacting its performance as potential analytical biofluid. Here, we have systematically studied the molecular spectral fingerprint of saliva, including the changes associated with gender, age, and time. Via hybrid artificial neural network algorithms and Raman spectroscopy, we have developed a non-destructive molecular profiling approach enabling the assessment of salivary spectral changes yielding the determination of gender and age of the biofluid source. Our classification algorithm successfully identified the gender and age from saliva with high classification accuracy. Discernible spectral molecular 'barcodes' were subsequently constructed for each class and found to primarily stem from amino acid, protein, and lipid changes in saliva. This unique combination of Raman spectroscopy and advanced machine learning techniques lays the platform for a variety of applications in forensics and biosensing.

Surface enhanced Raman scattering specificity for detection and identification of dried bloodstains

Surface enhanced Raman spectroscopy (SERS) provides highly specific vibrational signatures identifying dried blood for a variety of forensic applications. SERS spectra on Au nanoparticle substrates excited at 785 nm are found to identify dried stains of human and nonhuman blood from seven animals, and distinguish stains due to menstrual and peripheral blood. In addition, the unique SERS bloodstain spectrum is distinct from the SERS spectra of thirty red-brown stains of potential household substances that could be visually mistaken for bloodstains and from food stains that have been shown to give positive results with presumptive colorimetric blood tests. Finally, a SERS swab procedure has been developed and demonstrates that the substrates that a blood sample dried on does not offer any Raman or fluorescence interference for the SERS identification of dried blood. Such bloodstains on porous and nonporous materials are all identical and exclusively due to the heme moiety of hemoglobin. Optimized selection of the extraction solvent is found to control the chemical composition of molecular components appearing in the SERS spectrum of complex, multicomponent biological mixtures, such as body fluids.

Comparative Analysis of Machine Learning Algorithms on Surface Enhanced Raman Spectra of Clinical Staphylococcus Species

Raman spectroscopy (RS) is a widely used analytical technique based on the detection of molecular vibrations in a defined system, which generates Raman spectra that contain unique and highly resolved fingerprints of the system. However, the low intensity of normal Raman scattering effect greatly hinders its application. Recently, the newly emerged surface enhanced Raman spectroscopy (SERS) technique overcomes the problem by mixing metal nanoparticles such as gold and silver with samples, which greatly enhances signal intensity of Raman effects by orders of magnitudes when compared with regular RS. In clinical and research laboratories, SERS provides a great potential for fast, sensitive, label-free, and non-destructive microbial detection and identification with the assistance of appropriate machine learning (ML) algorithms. However, choosing an appropriate algorithm for a specific group of bacterial species remains challenging, because with the large volumes of data generated during SERS analysis not all algorithms could achieve a relatively high accuracy. In this study, we compared three unsupervised machine learning methods and 10 supervised machine learning methods, respectively, on 2,752 SERS spectra from 117 Staphylococcus strains belonging to nine clinically important Staphylococcus species in order to test the capacity of different machine learning methods for bacterial rapid differentiation and accurate prediction. According to the results, density-based spatial clustering of applications with noise (DBSCAN) showed the best clustering capacity (Rand index 0.9733) while convolutional neural network (CNN) topped all other supervised machine learning methods as the best model for predicting Staphylococcus species via SERS spectra (ACC 98.21%, AUC 99.93%). Taken together, this study shows that machine learning methods are capable of distinguishing closely related Staphylococcus species and therefore have great application potentials for bacterial pathogen diagnosis in clinical settings.

Rapid and noninvasive diagnosis of oral and oropharyngeal cancer based on micro-Raman and FT-IR spectra of saliva

Fast, sensitive, and noninvasive techniques are needed for better health care management, particularly when traditional biopsies could be replaced with appropriate analyses of body fluids, such as saliva. Here is presented a proof-of-concept study, which aims to test a recently developed saliva samples preparation method, for oral and oropharyngeal cancer diagnosis, using micro-Raman and Fourier transform infrared (FT-IR) spectroscopic techniques. The detected biomarker bands and the cancer classification rates are compared and discussed. Saliva samples were collected from healthy donors and pathologically confirmed oral and oropharyngeal cancer patients. Principal components analysis (PCA) and principal components analysis-linear discriminant analysis (PCA-LDA) chemometric methods were applied to build discrimination models for the test and control groups. Based on the differences between salivary spectra of healthy and cancer patients, several biomarker bands were identified. Noteworthy, a significant vibrational biomarker band at 2064 cm^-1, assigned to thiocyanate, was observed in both the FT-IR and Raman data-set. Other cancer characteristic Raman bands were 754 cm^-1 (tryptophan), 530 and 927 cm^-1 (lysozyme), 1001 cm^-1 (phenylalanine), while the FT-IR biomarker band was located at 1075 cm^-1 (phosphodiester bonds stretching in DNA, RNA). The oral and oropharyngeal cancer was classified with an accuracy of 90% based on the micro-Raman data and 82% based on the FT-IR data set, respectively. The study showed that oral and oropharyngeal cancer can be differentiated from control saliva samples based on their respective micro-Raman and FT-IR spectral signatures, due to the biomolecular modifications induced by the disease.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Surface enhanced Raman scattering for robust, sensitive detection and confirmatory identification of dried bloodstains

785 nm SERS spectra provide rapid, sensitive confirmatory identification of dried bloodstains due to a ferric, high spin heme moiety.

Towards normalization selection of Raman data in the context of protein glycation: application of validity indices to PCA processed spectra

Vibrational data of biological samples require appropriate pre-processing for ensuring relevant interpretation. Here, mathematical criteria (validity indices) are used to select how to normalize Raman data collected in the protein glycation context.

Phenotype Profiling for Forensic Purposes: Determining Donor Sex Based on Fourier Transform Infrared Spectroscopy of Urine Traces

Forensic science is an important field of analytical chemistry where vibrational spectroscopy, in particular Fourier transform infrared spectroscopy and Raman spectroscopy, present advantages as they have a nondestructive nature, high selectivity, and no need for sample preparation. Herein, we demonstrate a method for determination of donor sex, based on attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy of dry urine traces. Trace body fluid evidence is of special importance to the modern criminal investigation as a source of individualizing DNA evidence. However, individual identification of a urine donor is generally difficult because of the small amount of DNA. Therefore, the development of an innovative method to provide phenotype information about the urine donor-including sex-is highly desirable. In this study, we developed a multivariate discriminant model for the ATR FT-IR spectra of dry urine to identify the donor sex. Rigorous selection of significant wavenumbers on the spectrum using a genetic algorithm enabled superb discrimination performance for the model and conclusively indicated a chemical origin for donor sex differences, which was supported by physiological knowledge. Although further investigations need to be conducted, this proof-of-concept study demonstrates the great potential of the developed methodology for phenotype profiling based on the analysis of urine traces.

Fourier based partial least squares algorithm: new insight into influence of spectral shift in "frequency domain"

Developments in analytical chemistry technology, especially the combination between the partial least squares and spectroscopy, have contributed significantly to predicting the chemical concentrations and discriminating similar chemical analytes. However, spectral shift is an unwanted but inevitable factor for the spectroscopic analyzer, especially in practical application, which decreases the method's accuracy and stability. To remove the term of spectral shift completely and increase the robustness of spectroscopic analysis method, Fourier transform based partial least squares method was proposed. The approach used Fourier transform first to transform the spectral shift in the "time domain" to the phase term in the "frequency domain." The module of the Fourier transformed spectra was then calculated. As a result, the phase term was removed (the module of the phase term is 1), which means the spectral shift term was removed completely. Finally, the spectra modules were used to build the model and validate. The approach's advantages are: (i) that the approach provides a new insight to treat the spectral shift in spectroscopic analyzer; (ii) that the model is insensitive to spectral shift; (iii) that the approach makes partial least squares combined with spectroscopy more suitable for practical application, rather than lab experiment, because spectral shift is permitted, which means the decreased requirements of measure environment. As an example, blood species discrimination, using Raman spectroscopy, was used in order to demonstrate this approach's effectiveness.

Sample Treatment for Tissue Proteomics in Cancer, Toxicology, and Forensics

Since the birth of proteomics science in the 1990, the number of applications and of sample preparation methods has grown exponentially, making a huge contribution to the knowledge in life science disciplines. Continuous improvements in the sample treatment strategies unlock and reveal the fine details of disease mechanisms, drug potency, and toxicity as well as enable new disciplines to be investigated such as forensic science.This chapter will cover the most recent developments in sample preparation strategies for tissue proteomics in three areas, namely, cancer, toxicology, and forensics, thus also demonstrating breath of application within the domain of health and well-being, pharmaceuticals, and secure societies.In particular, in the area of cancer (human tumor biomarkers), the most efficient and multi-informative proteomic strategies will be covered in relation to the subsequent application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and liquid extraction surface analysis (LESA), due to their ability to provide molecular localization of tumor biomarkers albeit with different spatial resolution.With respect to toxicology, methodologies applied in toxicoproteomics will be illustrated with examples from its use in two important areas: the study of drug-induced liver injury (DILI) and studies of effects of chemical and environmental insults on skin, i.e., the effects of irritants, sensitizers, and ionizing radiation. Within this chapter, mainly tissue proteomics sample preparation methods for LC-MS/MS analysis will be discussed as (i) the use of LC-MS/MS is majorly represented in the research efforts of the bioanalytical community in this area and (ii) LC-MS/MS still is the gold standard for quantification studies.Finally, the use of proteomics will also be discussed in forensic science with respect to the information that can be recovered from blood and fingerprint evidence which are commonly encountered at the scene of the crime. The application of proteomic strategies for the analysis of blood and fingerprints is novel and proteomic preparation methods will be reported in relation to the subsequent use of mass spectrometry without any hyphenation. While generally yielding more information, hyphenated methods are often more laborious and time-consuming; since forensic investigations need quick turnaround, without compromising validity of the information, the prospect to develop methods for the application of quick forensic mass spectrometry techniques such as MALDI-MS (in imaging or profiling mode) is of great interest.

Development and clinical assessment of new objective adherence markers for four microbicide delivery systems used in HIV prevention studies

Background

Adherence is critical for successful topical, vaginally delivered anti-retroviral (ARV)-based HIV pre-exposure prophylaxis (PrEP). Quantitating systemic or tissue ARV levels through LC–MS/MS is currently viewed as the most reliable measure of adherence. However, for placebo-controlled trials, this is a high cost analysis that measures adherence only in the drug treatment group. A desirable marker of adherence is one that is measured in both placebo and drug treatment groups using a simple on-site clinical laboratory test, which allows necessary interventions for supporting participant adherence. Our objective was to develop adherence markers for four vaginal placebo products currently used as microbicide delivery systems: gel, film, insert, and intravaginal ring. Excipient and spectroscopy-based approaches were used for preclinical development of the placebo markers and subsequently validated by the CONRAD 135 study. The study collected vaginal swabs collected each day for 1 week post vaginal application of gel, film, or insert in the clinic with or without sex. Intravaginal rings were collected after 1 day, 7, and 30 days of use.

Results

Placebo gel, film, and insert in vaginal swabs were successfully detected by specific excipient colorimetric or probe-based assays for hydroxyethylcellulose, glycerin, and sorbitol respectively, as well as spectroscopy-based prediction models. The range of detection for gel, film, and insert in swabs collected up to 16 h post vaginal application was 70-100% of the total swabs per time point, with some markers showing potential for longer duration. Decreasing residual glycerin levels and increasing bioanalyte penetration of vaginally used intravaginal rings showed significant changes between 1 and 30 days of use.

Conclusions

We demonstrated clinical proof-of-concept that adherence markers for placebo product can be measured using simple, lower cost approaches. Measuring adherence in both placebo and drug arms of a HIV PrEP study would better inform future trial designs.

Electronic supplementary material

The online version of this article (10.1186/s40169-018-0213-6) contains supplementary material, which is available to authorized users.

Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis

Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.

Determination of Ethanol in Blood Samples Using Partial Least Square Regression Applied to Surface Enhanced Raman Spectroscopy

Alcohol consumption triggers toxic effect to organs and tissues in the human body. The risks are essentially thought to be related to ethanol content in alcoholic beverages. The identification of ethanol in blood samples requires rapid, minimal sample handling, and non-destructive analysis, such as Raman Spectroscopy. This study aims to apply Raman Spectroscopy for identification of ethanol in blood samples. Silver nanoparticles were synthesized to obtain Surface Enhanced Raman Spectroscopy (SERS) spectra of blood samples. The SERS spectra were used for Partial Least Square (PLS) for determining ethanol quantitatively. To apply PLS method, 920~820 cm-1 band interval was chosen and the spectral changes of the observed concentrations statistically associated with each other. The blood samples were examined according to this model and the quantity of ethanol was determined as that: first a calibration method was established. A strong relationship was observed between known concentration values and the values obtained by PLS method (R2 = 1). Second instead of then, quantities of ethanol in 40 blood samples were predicted according to the calibration method. Quantitative analysis of the ethanol in the blood was done by analyzing the data obtained by Raman spectroscopy and the PLS method.

Biofluid spectroscopic disease diagnostics: A review on the processes and spectral impact of drying

The complex patterns observed from evaporated liquid drops have been examined extensively over the last 20 years. Complete understanding of drop deposition is vital in many medical processes, and one which is essential to the translation of biofluid spectroscopic disease diagnostics. The promising use of spectroscopy in disease diagnosis has been hindered by the complicated patterns left by dried biological fluids which may inhibit the clinical translation of this technology. Coffee-ring formation, cracking and gelation patterns have all been observed in biofluid drops, and with surface homogeneity being a key element to many spectroscopic techniques, experimental issues have been found to arise. A better understanding of the fundamental processes involved in a drying droplet could allow efficient progression in this research field, and ultimately benefit the population with the development of a reliable cancer diagnostic.

Spectral Mining for Discriminating Blood Origins in the Presence of Substrate Interference via Attenuated Total Reflection Fourier Transform Infrared Spectroscopy: Postmortem or Antemortem Blood?

Often in criminal investigations, discrimination of types of body fluid evidence is crucially important to ascertain how a crime was committed. Compared to current methods using biochemical techniques, vibrational spectroscopic approaches can provide versatile applicability to identify various body fluid types without sample invasion. However, their applicability is limited to pure body fluid samples because important signals from body fluids incorporated in a substrate are affected strongly by interference from substrate signals. Herein, we describe a novel approach to recover body fluid signals that are embedded in strong substrate interferences using attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and an innovative multivariate spectral processing. This technique supported detection of covert features of body fluid signals, and then identified origins of body fluid stains on substrates. We discriminated between ATR FT-IR spectra of postmortem blood (PB) and those of antemortem blood (AB) by creating a multivariate statistics model. From ATR FT-IR spectra of PB and AB stains on interfering substrates (polyester, cotton, and denim), blood-originated signals were extracted by a weighted linear regression approach we developed originally using principal components of both blood and substrate spectra. The blood-originated signals were finally classified by the discriminant model, demonstrating high discriminant accuracy. The present method can identify body fluid evidence independently of the substrate type, which is expected to promote the application of vibrational spectroscopic techniques in forensic body fluid analysis.

Characterization of postmortem biochemical changes in rabbit plasma using ATR-FTIR combined with chemometrics: A preliminary study

Postmortem interval (PMI) determination is one of the most challenging tasks in forensic medicine due to a lack of accurate and reliable methods. It is especially difficult for late PMI determination. Although many attempts with various types of body fluids based on chemical methods have been made to solve this problem, few investigations are focused on blood samples. In this study, we employed an attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique coupled with principle component analysis (PCA) to monitor biochemical changes in rabbit plasma with increasing PMI. Partial least square (PLS) model was used based on the spectral data for PMI prediction in an independent sample set. Our results revealed that postmortem chemical changes in compositions of the plasma were time-dependent, and various components including proteins, lipids and nucleic acids contributed to the discrimination of the samples at different time points. A satisfactory prediction within 48h postmortem was performed by the combined PLS model with a good fitting between actual and predicted PMI of 0.984 and with an error of ±1.92h. In consideration of the simplicity and portability of ATR-FTIR, our preliminary study provides an experimental and theoretical basis for application of this technique in forensic practice.

Snapshot depth sensitive Raman spectroscopy in layered tissues

Depth sensitive Raman spectroscopy has been shown effective in the detection of depth dependent Raman spectra in layered tissues. However, the current techniques for depth sensitive Raman measurements based on fiber-optic probes suffer from poor depth resolution and significant variation in probe-sample contact. In contrast, those lens based techniques either require the change in objective-sample distance or suffer from slow spectral acquisition. We report a snapshot depth-sensitive Raman technique based on an axicon lens and a ring-to-line fiber assembly to simultaneously acquire Raman signals emitted from five different depths in the non-contact manner without moving any component. A numerical tool was developed to simulate ray tracing and optimize the snapshot depth sensitive setup to achieve the tradeoff between signal collection efficiency and depth resolution for Raman measurements in the skin. Moreover, the snapshot system was demonstrated to be able to acquire depth sensitive Raman spectra from not only transparent and turbid skin phantoms but also from ex vivo pork tissues and in vivo human thumbnails when the excitation laser power was limited to the maximum permissible exposure for human skin. The results suggest the great potential of snapshot depth sensitive Raman spectroscopy in the characterization of the skin and other layered tissues in the clinical setting or other similar applications such as quality monitoring of tablets and capsules in pharmaceutical industry requiring the rapid measurement of depth dependent Raman spectra.

Analysis of human bodily fluids on superabsorbent pads by ATR-FTIR

Superabsorbent pads are composed of different layers with different grades of absorbent capacity, being the lower one the most absorbent layer. Due to their complexity, the analysis of bodily fluids on superabsorbent pads is certainly difficult. In this study, semen, vaginal fluid and urine stains placed on superabsorbent pads including sanitary napkins, panty-liners and diapers were non-destructively detected by Attenuated Total Reflectance (ATR) Fourier Transform Infrared spectroscopy (FTIR). In spite of the higher absorbent capacity of the lower layers, this technique was able to detect the three fluids on the upper layer of all pads, showing that bodily fluids are distributed within all layers. Additionally, mixtures of these bodily fluids prepared on superabsorbent pads and cotton were studied, since real forensic investigations involving sexual abuse cases usually deal with mixtures of these fluids. Due to their IR marked protein region (1800-1480cm^-1), semen and vaginal fluid were easily distinguished from urine. However, since semen and vaginal fluid have both a high protein composition, that region of their IR signatures were quite similar, except for slight visual differences, that should be further analysed. Therefore, we propose ATR-FTIR as a suitable, presumptive, non-destructive and rapid approach to detect stains of human bodily fluids on the upper layer of superabsorbent pads from sexual crimes.

The effect of mark enhancement techniques on the subsequent detection of saliva

There appears to be a limited but growing body of research on the sequential analysis/treatment of multiple types of evidence. The development of an integrated forensic approach is necessary to maximise evidence recovery and to ensure that a particular treatment is not detrimental to other types of evidence. This study aims to assess the effect of latent and blood mark enhancement techniques (e.g. fluorescence, ninhydrin, acid violet 17, black iron-oxide powder suspension) on the subsequent detection of saliva. Saliva detection was performed by means of a presumptive test (Phadebas®) in addition to analysis by a rapid stain identification (RSID) kit test and confirmatory DNA testing. Additional variables included a saliva depletion series and a number of different substrates with varying porosities as well as different ageing periods. Examination and photography under white light and fluorescence was carried out prior to and after chemical enhancement. All enhancement techniques (except Bluestar® Forensic Magnum luminol) employed in this study resulted in an improved visualisation of the saliva stains, although the inherent fluorescence of saliva was sometimes blocked after chemical treatment. The use of protein stains was, in general, detrimental to the detection of saliva. Positive results were less pronounced after the use of black iron-oxide powder suspension, cyanoacrylate fuming followed by BY40 and ninhydrin when compared to the respective positive controls. The application of Bluestar® Forensic Magnum luminol and black magnetic powder proved to be the least detrimental, with no significant difference between the test results and the positive controls. The use of non-destructive fluorescence examination provided good visualisation; however, only the first few marks in the depletion were observed. Of the samples selected for DNA analysis only depletion 1 samples contained sufficient DNA quantity for further processing using standard methodology. The 28-day delay between sample deposition and collection resulted in a 5-fold reduction in the amount of useable DNA. When sufficient DNA quantities were recovered, enhancement techniques did not have a detrimental effect on the ability to generate DNA profiles. This study aims to contribute to a strategy for maximising evidence recovery and efficiency for the detection of latent marks and saliva. The results demonstrate that most of the enhancement techniques employed in this study were not detrimental to the subsequent detection of saliva by means of presumptive, confirmative and DNA tests.

In vitro examination of the pressure effect on clot dissolution with thrombolytic patch

Bio-kinetic thrombus dissolution model has been developed to describe the thrombus dissolution behavior during endoluminal thrombolytic patch treatment to recanalize blocked vessel in ischemic strokes. The initial model ignored the effect of pulsatile pressure in the lumen. However, pulsatile pressure in the lumen may affect molecule diffusion and bio-chemical reaction rate and accelerate clot dissolution. The effect of pressure on the dissolution rate was examined in this study. The dissolution behaviors of 100-400 μm thick blood clot specimens subject to diastolic, systolic, and pulsatile pressure were characterized using Raman spectroscopy. The results showed that dissolution time was reduced by less than 2 mins and is negligible in comparison with total treatment time. The effect of pressure may be ignored and the developed bio-kinetic model may be used in surgical applications of endoluminal thrombolytic patch to estimate treatment time in ischemic stroke.

Vibrational Spectroscopy in Body Fluids Analysis

Vibrational spectroscopy offers a unique opportunity to investigate the composition of unknown substances on a molecular basis. The spectroscopy of molecular vibrations using mid-infrared or Raman techniques has been applied to samples of body fluids. This review presents some applications related to body fluids published in the period 2005-2015.

Race Differentiation by Raman Spectroscopy of a Bloodstain for Forensic Purposes

Bearing in mind forensic purposes, a nondestructive and rapid method was developed for race differentiation of peripheral blood donors. Blood is an extremely valuable form of evidence in forensic investigations so proper analysis is critical. Because potentially miniscule amounts of blood traces can be found at a crime scene, having a method that is nondestructive, and provides a substantial amount of information about the sample, is ideal. In this study Raman spectroscopy was applied with advanced statistical analysis to discriminate between Caucasian (CA) and African American (AA) donors based on dried peripheral blood traces. Spectra were collected from 20 donors varying in gender and age. Support vector machines-discriminant analysis (SVM-DA) was used for differentiation of the two races. An outer loop subject-wise cross-validation (CV) method evaluated the performance of the SVM classifier for each individual donor from the training data set. The performance of SVM-DA, evaluated by the area under the curve (AUC) metric, showed 83% probability of correct classification for both races, and a specificity and sensitivity of 80%. This preliminary study shows promise for distinguishing between different races of human blood. The method has great potential for real crime scene investigation, providing rapid and reliable results, with no sample preparation, destruction, or consumption.