Forensics Research Articles

Innovative approaches in complex data forensics: error rate assessment and its impact on cybersecurity

In the realm of cybersecurity, the integrity of forensic investigations is paramount, especially as the volume and complexity of data continue to escalate. This paper explores innovative approaches to complex data forensics, focusing on the methodologies used to assess error rates in data retrieval and analysis. High error rates in forensic processes can compromise the reliability of findings, leading to erroneous conclusions that may impact security measures and legal proceedings. This research examines various techniques for error rate assessment, including statistical methods and data validation protocols, which serve to quantify the accuracy of forensic analysis. Furthermore, the paper discusses the profound implications that high error rates can have on the integrity of forensic findings, emphasizing the need for meticulous attention to detail in data handling and processing. To counter these challenges, we present strategies aimed at enhancing data reliability, such as implementing rigorous quality assurance processes, leveraging machine learning algorithms for anomaly detection, and utilizing advanced encryption methods to protect data integrity throughout the forensic lifecycle. By addressing the critical role of error rate assessment in data forensics, this research contributes to the broader discourse on cybersecurity and underscores the necessity of adopting robust methodologies to ensure accurate and reliable forensic outcomes in an increasingly complex digital landscape.

Building the Foundation: Towards a Theoretical Framework for Forensic Accounting

This study proposed a forensic accounting theory after examining how the impact of certain variables and their interplay on forensic accounting practices can contribute to developing integrated and robust fraud prevention strategies, enhance organizational accountability, and strengthen the overall integrity of financial and internal control systems. In literature, most studies on forensic accounting and fraud prevention have primarily focused on broader aspects such as governance, ethics, and accountability and are largely predicated on theories such as fraud diamond theory and agency theory that seek to understand the causes of fraud, highlighting the importance of forensic accounting in fraud prevention and detection, without suggesting practical forensic accounting frameworks. Also, the forensic accounting theory developed by Peterson Ozil in 2020 examines how the investigator’s attitude or mindset at the time of decision-making influences the outcomes of a forensic investigation. While these studies provide valuable insights into the overall context of fraud prevention, there is a scarcity of research on the specific forensic accounting processes that should be implemented to enhance the effectiveness of fraud prevention measures. This is the significant difference between the current study and previous studies. Therefore, the proposed Vutumu Forensic Accounting Theory serves as the guiding philosophy that underpins the integrated approach of combining control system reliance, litigation support, whistleblower hotlines, sustainable governance systems, ethical philosophy, digital fraud review frequencies, accounting record to reporting quality, and the frequency of system reviews, thereby enabling organizations to establish a proactive framework that addresses various dimensions of fraud prevention and detection. The implementation of the theory emerges as a formidable and comprehensive anti-fraud strategy, seamlessly integrating multiple elements to create a robust defense against fraudulent activities, safeguarding financial integrity, ethical conduct, and accountability within organizations. Furthermore, it is the researcher’s desire that this study serve as a foundation for further research and practical implementation of forensic accounting frameworks in strengthening the ability to detect and prevent fraud.

Defining clavicle growth in infancy using chest radiographs.

Despite the critical role of the clavicle in understanding growth and development in early childhood, there remains a notable paucity of comprehensive studies investigating clavicle growth patterns during this crucial period. This hinders our ability to establish normative growth parameters during these early life stages. Our study sought to measure clavicle dimensions and subsequently construct growth curves spanning from preterm infants to toddlers up to the age of 6 years by measuring routine chest radiographs. Differences between both sides of the body and between the sexes should be analysed. This aimed to provide a nuanced understanding of clavicle growth dynamics and offering a foundation for the establishment of normative values in this understudied context. In this retrospective study, children aged 23 weeks of gestation to 6 years who underwent a chest radiography between January 2010 and June 2020 were enrolled. A total of 5.311 potential radiographs was screened. Clavicle length and width were measured in all radiographs using the Centricity™ Universal Viewer. Statistical analysis was performed using SPSS®. 1.340 images met the quality criteria to be included in our study. The growth curves of clavicle lengths and widths showed a steadily increasing trend with age. Inclusion of premature infants in the age group of one month resulted in a decrease in this age group. Significant differences between both sides of the body and between the sexes could be shown. Measurements of clavicle length and width, derived from routine chest radiographs, are highly accurate. This accuracy underscores the potential for utilizing thoracic radiographs as a reliable tool for assessing clavicle growth in clinical settings or even forensic analysts. The establishment of reference values derived from our measurements provides a basis for normative growth parameters.

On Accountability: Genetic Tools for Justice and Injustice in Criminal Proceedings

Analysis of DNA found at crime scenes has made headlines when used to solve serial killer cold cases. The DNA Identification Act of 1994 approved the Combined DNA Index System (CODIS), a database that stores profiles of 20 genetic markers for forensic investigations. The CODIS markers were specifically chosen because they were thought to be unlinkable to personally identifiable individual traits. However, advances in genetics research have expanded the traits associated with CODIS markers and increased the tools and applications of forensic genetics, thus further increasing the information investigators could gain from a suspected person’s CODIS profile. This is also true regarding private companies, who may analyze genetic information beyond that included in a CODIS profile. These scientific developments may lead to infringements on genetic privacy rights. Additionally, in 2013, the US Supreme Court held in Maryland v King that people who have been arrested, even if they are acquitted or never indicted, can be added to CODIS databases. Due to racial biases in policing and arrests, this has led to inequity in who is represented in CODIS databases, specifically an over-representation of Black individuals’ genetic profiles. Therefore, the use of genetic tools in criminal proceedings, including but not only from CODIS databases, pose risks to privacy and also serve as a seemingly race-neutral tool that, in practice, promotes racial inequity. We suggest implementation of state-specific research and oversight boards with three charges focused on CODIS and investigations using genetic tools employed by private companies: (1) study uses of genetic tools in criminal investigations; (2) study the impact of genetic tools in criminal proceedings and interface with stakeholders and the general public; and (3) use knowledge from (1) and (2) to inform policy recommendations, for which we make several initial suggestions. These boards will provide accountability to increase accuracy, privacy, and equity when using genetic tools in criminal proceedings.

Mass spectrometry-based proteomics for source-level attribution after DNA extraction

Biological traces recovered from crime scenes serve as vital evidence in forensic investigations. While DNA evidence is frequently used to address the sub-source level of the hierarchy of propositions, the biological source of the DNA can be highly probative at the source level. Current body fluid detection methods pose certain limitations, such as reports of false positive results from some of the presumptive and/or confirmatory tests in current use. These tests are also individual tests for the detection of one body fluid, meaning that if the sample is suspected to be a mixture of multiple body fluids, then different tests would need to be conducted to confirm the body fluid(s) present, which may exhaust small amounts of available biological trace. Proteomics applications for the identification of body fluids have been previously explored, and potential biomarkers indicative of body fluids discovered from liquid-chromatography tandem mass spectrometry (LC-MS/MS) methods have been reported. This work focuses on developing a mass spectrometry-based proteomics approach for the identification of body fluids by targeting discriminating peptide biomarkers from the non-DNA component left over after DNA extraction of samples. The non-DNA component is typically a waste product but with unappreciated evidential value. Our methodology for the purification of proteins from the post-DNA extraction waste includes an acetone precipitation and single-pot solid-phase-enhanced sample preparation (SP3) technique, microwave-assisted trypsin digestion, and LC-MS/MS analysis of the resultant peptides. Preliminary results from this proof-of-concept study include a list of potentially discriminating proteins and peptides for blood, saliva, and semen developed from the analysis of post-DNA extraction waste. Our method allows for multiple analytes to be targeted simultaneously from a DNA profiling waste stream and we anticipate that it could eventually be incorporated into standard forensic laboratory workflows.

Non-target screening analysis of hazardous noxious substances using gas chromatography-quadrupole time-of-flight mass spectrometry

The forensic investigation of hazardous noxious substances (HNS) is paramount for an effective response to chemical spill emergencies and other accidents. Analyzing unknown emergency samples poses a challenge due to the limited availability of background information, making the selection of appropriate sample preparation and analytical methodologies difficult. The utilization of high-resolution mass spectrometers (HRMS) in screening both target and non-target substances proves instrumental in revealing hazardous substances that may be overlooked alongside the intended analytes. In this study, a gas chromatography-quadruple time-of-flight mass spectrometer (GC-QTOF-MS) was employed to identify numerous organic compounds in an indoor dust sample. The compounds detected encompassed normal alkanes, fatty acids (saturated and unsaturated), alcohols, phenols, sterols, drugs, polycyclic aromatic hydrocarbons (PAHs), pesticides, flame retardants (such as polybrominated biphenyl ethers, PBDEs), plasticizers (such as phthalates and phosphates), among others. Notably, concentrations of n-alkanes, fatty acids, and phthalates were relatively high, while PAHs and pesticides were present at trace levels. The application of GC-QTOF-MS provides a swift and confirmative approach for analyzing target, suspect, and non-target compounds in both routine and emergency scenarios. This methodology proves invaluable in enhancing our capability to comprehensively assess and address chemical incidents, ensuring a more thorough and accurate response.

Forensic and ecological significance of necrophagous insects: Insights from animal carcasses, human cadavers, and myiasis patients

Necrophagous insects, including flies and beetles, play pivotal roles in decomposition, ecology, and forensics. Their diversity and activities vary across environments, necessitating comprehensive studies for understanding and management. The aim of the study is to investigate insect infestation on animal carcasses, human cadavers, and myiasis patients to enhance ecological, forensic, and medical entomological understanding, aiding in ecosystem management, forensic investigations, and disease control.Various species of flies and beetles were found associated with animal carcasses, human cadavers, and myiasis patients, as indicated by the comprehensive study. On animal carcasses, notable fly species included Chrysomya rufifacies (Macquart, 1842), Chrysomya megacephala (Fabricius, 1794), Lucilia cuprina (Wiedemann, 1830), and Sarcophaga sp., while beetles such as Dermestes maculatus (De Geer, 1774), Necrobia rufipes (Fabricius, 1781), Saprinus quadrigatattus (Fabricius, 1798), Saprinus splendens (Paykull, 1811), Saprinus optabilis (Marseul, 1855), Saprinus chalcites (Iliger, 1807), and Omorgus sp. (Erichson, 1847) were also observed. Similarly, human cadavers exhibited a presence of flies like Chrysomya albiceps (Wiedemann, 1819), Chrysomya rufifacies (Macquart, 1842), Chrysomya megacephala (Fabricius, 1794), and Sarcophaga dux (Thomson, 1869). In cases of myiasis patients, flies including Chrysomya megacephala, Cochliomyia hominivorax (Coquerel, 1858), and Chrysomya bezziana (Villeneuve, 1914) were identified.These findings underscore the diverse range of insect species involved in carcass decomposition, forensic investigations, and medical entomology, illustrating their crucial roles in ecological processes, forensic assessments, and disease management.

From forensic chemistry: an educational experience

Abstract The study of forensic chemical analysis not only aids justice in the investigation of accidental or criminal events but also trains chemistry students in analysing hypothetical scenes, such as the design of scientific experiments, and alerting them to potential dangers. In this way, it contributes to generating awareness about safety and security, ethics, and the professional responsibilities of chemists. These, although ambitious, are some of the objectives that have led to the development of this course on Chemical Analysis in Forensic Investigation, whose thematic units and teaching details are developed. This work presents a detailed programme for the Forensic Chemistry course offered at the Faculty of Exact and Natural Sciences at the University of Buenos Aires. It includes examples of activities and bibliography, allowing it to be used as a template for similar courses or to adapt some of the thematic units to other chemistry courses. The suggested bibliography supports the education of both students and educators in the field of forensic chemistry. The incorporation of topics such as fires, explosives, chemical warfare agents (CWA), and environmental crimes aims to develop professional profiles for a new generation of chemists more committed to the societal impact of their work.

Animal family discrimination from hair using ATR-FTIR and machine learning methods for applications in illegal wildlife trafficking.

Wildlife forensics plays a pivotal role in the combating illegal trafficking, supporting biodiversity conservation, and aiding in the identification of animals in wildlife. Animal hair, often found in trafficking crimes, serves as vital biological evidence that can provide significant information for animal identification. This study proposes a novel method integrating machine learning classifiers with Fourier transform infrared (FTIR) spectroscopy in attenuated total reflectance (ATR) mode to enhance the effectiveness of animal identification in wildlife forensic casework. Additionally, compound microscopy has also been utilized as a preliminary tool to perform morphological analysis of hair samples from four animal families, including Bovidae, Cervidae, Elephantidae, and Felidae. Further, chemical profiling through spectral data revealed significant overlapping peaks between family Bovidae and Cervidae. The classification experiment provides the random forest (RF) classifier as the most effective for family discrimination model. This research offers valuable insights for wildlife forensics by improving the identification accuracy of unknown hair samples, thus enhancing the overall effectiveness in forensic investigations.

Genetic variability and discriminatory power of RM Y-STRs in gilgit men: a population study

AbstractShort Tandem Repeats (STRs) found on the Y chromosome have multiple applications, such as in forensic investigations, male identification for legal reasons, as well as population genetics. However, commercially accessible Y-STR tests are limited in their capability to distinguish closely linked male individuals in forensic genetics. Recent studies have revealed that Rapidly Mutating Y-STRs (RM Y-STRs) offer significantly greater haplotype diversity around the worldwide populations associated to conventional Y-STRs, though some RM Y-STR loci are not contained, current commercial kits. The objective of this research is to create a database of RM Y-STR haplotype frequencies for the Gilgit population in Pakistan and evaluate the effectiveness of these genetic markers in distinguishing individuals with genetic variations. The research involved examining several RM Y-STRs in 56 unrelated Gilgit men. The statistical analysis determined that the majority of the loci-maintained haplotype values, as specific varied in certain cases. The results presented that the RM Y-STRs were very effective in distinguishing genetic changes among the Gilgit population, through a GD value of 0 for DYD403S1 and GD values greater than 0.7 for all other loci, with maximum value of 0.9920 for the RM Y-STR DYS612.

AIE Active Imidazole-Stilbene Conjugated Fluorescent Probes: Illuminating Latent Fingerprints and Advancing Anticounterfeiting Technologies.

Aggregation-induced emission luminogens (AIEgens) are widely used in the realm of latent fingerprint visualization owing to their luminosity and resistance to photobleaching. However, challenges such as significant background interference and limited resolution hinder their rapid advancement. Consequently, there is a pressing need to improve the detailed visualization of latent fingerprint (LFP) imaging, particularly for analyzing level 3 details. To address this, we have designed donor-acceptor (D-A) type AIEgens named MMIMV, DMIMV, and TMIMV. These compounds exhibit robust emissions ranging from 481 to 552 nm and signify positive fluorosolvatochromism. When applied as powder dusting, these derivatives enable the fluorescence imaging of LFPs on various material substrates. The analysis of these imaged LFPs yields intricate details regarding fingerprint ridge patterns. Our results underscore the potential of highly emissive AIEgens MMIMV, DMIMV, and TMIMV as promising candidates for fingerprint visualization, thus offering significant implications for forensic investigations. Furthermore, these derivatives serve as effective fluorescent security inks for writing and drawing, presenting a novel avenue for robust anticounterfeiting applications.

Inadequate Postmortem Reports: Investigating the Underlying Factors

Postmortem reports play a vital role in forensic pathology, providing essential information about the causes of death needed for legal investigations. However, several factors undermine the quality of these reports, threatening their reliability and compromising the integrity of the judicial system. This study explores the key issues contributing to inadequate postmortem reports, such as the absence of standardized protocols, lack of adequate training for forensic staff, communication breakdowns, external pressures on forensic teams, overwhelmed laboratories with insufficient infrastructure, personnel, and equipment, and challenges in implementing new technologies. By examining these elements, the research seeks to identify opportunities for improvement to enhance the quality and accuracy of autopsies. An integrated approach is crucial for establishing standardized practices, upgrading facilities and equipment, increasing staffing and laboratory numbers, improving training for forensic professionals, and promoting better communication among all stakeholders in forensic investigations. The findings emphasize the need to address these systemic issues to produce more reliable postmortem reports, which are essential for delivering accurate forensic insights and ensuring just legal outcomes.

Enhancing forensic blood detection using hyperspectral imaging and advanced preprocessing techniques

Bloodstains are pivotal in forensic investigations as they can provide crucial DNA information about individuals involved in a crime. Traditional methods for bloodstain detection, including chemical tests and forensic lights, have limitations such as non-specificity to human blood and susceptibility to false positives. In forensic blood detection, molecular spectroscopy is crucial for identifying the unique spectral fingerprints of blood, which arise from its molecular composition. Hyperspectral imaging (HSI) leverages this principle by capturing a wide spectrum of light for each pixel in an image, allowing for the detailed analysis of various substances. HSI has emerged as a promising alternative, offering non-contact, rapid, and cost-effective detection of bloodstains by analyzing the visible and near-infrared electromagnetic spectrum. This study explores the application of HSI for blood detection, addressing challenges such as spectral mixing, time-related changes in bloodstain spectra, and data complexity. The study introduces a novel framework to optimize HSI data, enhancing the accuracy and efficiency of bloodstain classification, called the Fast Extraction (FE) framework. It includes two stages. The main method in the first one is the Enhancing Transformation Reduction (ETR) method to reduce the dimension and complexity of the HSI. The second stage contains a compatible classification model to enhance feature extraction and classification. Our approach is validated using the HyperBlood datasets and many evaluation methods, demonstrating superior performance compared to state-of-the-art deep learning models. It provides high accuracy (97%–100 %) for all HSIs, overcoming various difficulties and blood collection times.

Neural radiance fields as a complementary method to photogrammetry for forensic 3D documentation: Initial comparative insights

ObjectivesPhotogrammetry is widely used in forensic practice to create 3D models of crime scenes, bodies, living individuals, and objects. However, it has limitations in accurately capturing transparent, reflective, and low-texture surfaces, which can hinder forensic investigations. Neural Radiance Fields (NeRFs), a recently developed method, offer a potential solution by creating more accurate and detailed 3D models in these challenging contexts. This study aims to evaluate whether NeRFs can serve as effective alternatives to structure-from-motion (SfM) photogrammetry for recording forensic autopsies. Materials and MethodsPhotogrammetric scans were performed on a variety of forensic subjects, including a cadaver with skin discoloration and epidermal exfoliation, a metal trashcan, a vehicle, and a mock crime scene. The scans were processed using traditional photogrammetry software (Meshroom) and compared with NeRF-based visualizations generate using instant neural graphics primitives. ResultsNeRF-based models provided more lifelike and detailed visualizations than photogrammetry, particularly when documenting transparent, reflective, or featureless surfaces. NeRF demonstrated superior capability in capturing complex details that photogrammetry struggled with. ConclusionNeRF technology shows considerable promise for improving the documentation of forensic autopsies, offering enhanced visual fidelity for challenging surfaces such as transparent or reflective materials. While the method presents challenges related to editing, software compatibility, and high computational demands, its potential benefits in forensic investigations are evident and merit further exploration.

Validation of morphological ear classification devised by principal component analysis using three-dimensional images for human identification.

This study attempts to classify ear morphology for human identification in forensic investigations by distinguishing between the upper auricle and lobule areas. A three-dimensional homologous model of the ear was created using 414 ear images of males aged 17-93 years reconstructed from computed tomography scans of forensic autopsy cases. Morphological changes were visualized using principal component analysis and areas of significant individual differences within the entire ear were identified. The classification criterion images for the upper auricle (ten images) and lobule (12 images) were developed by combining multiple principal component values: components 1-5 for the upper auricle and 1-6 for the lobule. Three-dimensional ear images of the upper auricle and lobule areas from 414 subjects were categorized using a measurement method based on the minimum distance between 5,507 corresponding points. The results indicate the applicability of the criterion images for the morphological classification of ears in this study.

Morphometric analysis of the hard palate in sex estimation among koreans using three-dimensional computed tomography

Accurate sex estimation is crucial for comprehensive analysis of the biological profiles of unidentified human skeletal remains. However, there is a notable lack of research specifically addressing the morphometrics of the hard palate. Therefore, this study aimed to derive discriminant equations using the hard palate and assess their applicability for sexing partial skeletal remains in a contemporary Korean population. Statistical analyses were performed for 24 measurements derived from three-dimensional models of the hard palate, generated using computed tomography scans of 301 individuals (156 males, 145 females). Descriptive statistics revealed significant sexual dimorphism in the mean comparison of hard palate sizes between Korean males and females, with males exhibiting larger palates across all measurements (p < 0.05). Discriminant function score equations were generated to aid in sex determination. Univariate analysis yielded an accuracy range of 57.8–75.1%, whereas the stepwise method achieved an accuracy of 80.7% with five selected variables: IF-PNS, GFL-GFR, IF-GFR, Pr-EcL, and Pr-EnR. The results of this metric analysis demonstrate the usefulness of the hard palate for sex estimation in the contemporary Korean population. These findings have potential implications for forensic investigations, archeological studies, and population-specific anatomical research.

DNA methylation at AHRR as a master predictor of smoke exposure and a biomarker for sleep and exercise

BackgroundDNA methylation profiling may provide a more accurate measure of the smoking status than self-report and may be useful in guiding clinical interventions and forensic investigations. In the current study, blood DNA methylation profiles of nearly 800 Polish individuals were assayed using Illuminia EPIC and the inference of smoking from epigenetic data was explored. In addition, we focused on the role of the AHRR gene as a top marker for smoking and investigated its responsiveness to other lifestyle behaviors.ResultsWe found > 450 significant CpGs associated with cigarette consumption, and overrepresented in various biological functions including cell communication, response to stress, blood vessel development, cell death, and atherosclerosis. The model consisting of cg05575921 in AHRR (p = 4.5 × 10–32) and three additional CpGs (cg09594361, cg21322436 in CNTNAP2 and cg09842685) was able to predict smoking status with a high accuracy of AUC = 0.8 in the test set. Importantly, a gradual increase in the probability of smoking was observed, starting from occasional smokers to regular heavy smokers. Furthermore, former smokers displayed the intermediate DNA methylation profiles compared to current and never smokers, and thus our results indicate the potential reversibility of DNA methylation after smoking cessation. The AHRR played a key role in a predictive analysis, explaining 21.5% of the variation in smoking. In addition, the AHRR methylation was analyzed for association with other modifiable lifestyle factors, and showed significance for sleep and physical activity. We also showed that the epigenetic score for smoking was significantly correlated with most of the epigenetic clocks tested, except for two first-generation clocks.ConclusionsOur study suggests that a more rapid return to never-smoker methylation levels after smoking cessation may be achievable in people who change their lifestyle in terms of physical activity and sleep duration. As cigarette smoking has been implicated in the literature as a leading cause of epigenetic aging and AHRR appears to be modifiable by multiple exogenous factors, it emerges as a promising target for intervention and investment.

The impact of burnt carcass on the occurrence probability of Chrysomya albiceps and Lucilia ochricornis (Diptera: Calliphoridae) in southern Rio Grande do Sul, Brazil

We evaluated the impact of burnt carcasses on the probability of finding Chrysomya albiceps (Wiedemann, 1819) and Lucilia ochricornis (Wiedemann, 1830) (Diptera: Calliphoridae), and the time it took for them to arrive at the experimental carcasss. These species are biological indicators of the postmortem interval (PMI) in forensic scenarios. Using stillborn pig carcasses, this study analysed how different degrees of burning affect the level of attraction and colonisation by these species. Experimental models were subjected to level 2 (CG2) and 4 (CG4) burning according to the Crow-Glassman (CG) scale, ranging from fresh to skeletonization. Generalised Linear Models (GLM) with a Binomial distribution were used to evaluate the influence of decomposition time and experimental treatment on the probability of occurrence of each species. Additionally, survival analyses with the Weibull distribution were used to investigate how long it takes until the arrival of the first fly species in each experimental group. The results indicate that burning affects the probability of occurrence and colonisation time of the studied fly species. Although both species were affected by high degrees of burning, Lucilia ochricornis was more heavily affected than Chrysomya albiceps. This pattern was reflected in the time it took for the first occurrence of each fly species. In both cases, it took longer for flies to arrive at carcasses that had been more severely burnt. In the case of C. albiceps, the longest mean time until a fly was detected (Weibull, α = 79.9 h) happened in the CG4 group, followed by the CG2 group (α = 65.6 h) and the control group (α = 51.5 h). In contrast, for L. ochricornis, the longest mean first occurrence time (α = 85.4 h) was in CG2 group, followed by the Control (α = 49.1 h) and CG4 (α = 54.4 h) groups. This study emphasises the importance of considering whether or not a carcass was burnt and its degree of burning in forensic investigations, given that this variable can influence the accuracy of PMI estimation in crime scenes.

Forensic Investigation of a Cracked Highway Embankment Pavement in Louisiana: A Case Study

Forensic Investigation of a Cracked Highway Embankment Pavement in Louisiana: A Case Study

Portable Miniature Mass Spectrometry for Enhanced On-Site Detection of Analytes in Complex Samples by Integrating Solid-Phase Microextraction and Nano-Electrospray Ionization.

On-site mass spectrometry (MS) analysis plays a crucial role in timely understanding chemical compositions of field samples but presents a challenge to miniaturization, portability, and sensitivity. In this work, a portable MS approach was developed by integrating biocompatible solid-phase microextraction (SPME) and a nano-electrospray ionization (nESI) emitter into a kit to couple miniature MS (mMS). The SPME fiber was used for on-site extractive sampling of analytes from complex liquid samples and living organisms and was then inserted into an nESI emitter for on-site MS analysis via the facile kit. The limit of detection was found to be at the pg/mL level for various compounds tested. Acceptable relative standard deviation (RSD) values (5.5-7.6%, n = 6) were obtained for direct measurement of analytes in complex matrixes; acceptable linear responses (0.1-50 ng/mL) and matrix effects (76.0-82.6%) were also found. Enhanced detection of compounds of interest in various real samples, such as food samples, human fluids, environmental water, and living organisms, was unambiguously demonstrated. Our experimental data showed that SPME-nESI-mMS is a promising tool for on-site analysis of various complex samples in significant applications including but not limited to food safety, environmental monitoring, forensic investigation, and bioanalysis.