GC-MS analysis of cuticular lipids in recent and older scavenger insect puparia. An approach to estimate the postmortem interval (PMI)

Advances and Current Status in the Use of Cuticular Hydrocarbons for Forensic Entomology Applications

Cuticular hydrocarbons (CHCs) are long-chain lipids found on the exoskeletons of insects, serving primarily as a protective barrier against water loss and environmental factors. In the last few decades, the qualitative and quantitative analysis of CHCs, particularly in blow flies, has emerged as a valuable tool in forensic entomology, offering promising potential for species identification and age estimation of forensically important insects. This review examines the current application of CHC analysis in forensic investigations and highlights the significant advancements in the field over the past few years. Studies have demonstrated that CHC profiles vary with insect development, and while intra-species variability exists due to factors such as age, sex, geographical location, and environmental conditions, these variations can be harnessed to refine post-mortem interval (PMI) estimations and improve the accuracy of forensic entomological evidence. Notably, CHC analysis can also aid in distinguishing between multiple generations of insects on a body, providing insights into post-mortem body movement and aiding in the interpretation of PMI in complex cases. Furthermore, recent studies have investigated the variability and degradation of CHCs over time, revealing how environmental factors-such as temperature, humidity, UV light exposure, and toxicological substances-affect CHC composition, providing valuable insights for forensic investigations. Despite the promise of CHC profiling, several challenges remain, and this review also aims to highlight future research directions to enhance the reliability of this technique in forensic casework.

Variations in cuticular hydrocarbons of Calliphora vicina (Diptera: Calliphoridae) empty puparia: Insights for estimating late postmortem intervals

Necrophagous flies, particularly blowflies, serve as vital indicators in forensic entomology and ecological studies, contributing to minimum postmortem interval estimations and environmental monitoring. The study investigates variations in the predominant cuticular hydrocarbons (CHCs) viz. n-C25, n-C27, n-C28, and n-C29 of empty puparia of Calliphora vicina Robineau-Desvoidy, 1830, (Diptera: Calliphoridae) across diverse environmental conditions, including burial, above-ground and indoor settings, over 90 days. Notable trends include a significant decrease in n-C25 concentrations in buried and above-ground conditions over time, while n-C27 concentrations decline in buried and above-ground conditions but remain stable indoors. Burial conditions show significant declines in n-C27 and n-C29 concentrations over time, indicating environmental influences. Conversely, above-ground conditions exhibit uniform declines in all hydrocarbons. Indoor conditions remain relatively stable, with weak correlations between weathering time and CHC concentrations. Additionally, machine learning techniques, specifically Extreme Gradient Boosting (XGBoost), are employed for age estimation of empty puparia, yielding accurate predictions across different outdoor and indoor conditions. These findings highlight the subtle responses of CHC profiles to environmental stimuli, underscoring the importance of considering environmental factors in forensic entomology and ecological research. The study advances the understanding of insect remnant degradation processes and their forensic implications. Furthermore, integrating machine learning with entomological expertise offers standardized methodologies for age determination, enhancing the reliability of entomological evidence in legal contexts and paving the way for future research and development.

Evaluation of Volatile Organic Compounds from Spotted Lanternfly (Lycorma delicatula) Eggs Using Headspace Odor Sampling Methods

The spotted lanternfly (SLF) is an invasive species native to China. It was first discovered in the United States in Pennsylvania in 2014. It is known to cause great economic damage by destroying various crops, specifically grape vines, and therefore, several efforts have been made to control and mitigate its spread from the Northeast. Canine detection is a useful detection tool; however, it is crucial to understand the volatile organic compounds emitting by this pest to better direct canine training paradigms to prevent false alerts and to understand potential volatile markers of importance indicative of this species. The purpose of this study is to address the gap in research regarding the volatile organic compound (VOC) profile of SLF to better inform pest control mitigation strategies. Instrumental analysis was performed utilizing SPME-GC/MS on cold-killed SLF eggs, dried crickets, and tree bark. Differences in detected VOCs within each sample set depicted distinctive odor profiles for each matrix tested. Storage of these samples also depicted VOC accumulation variation as a function of time, thereby providing implications for long-term storage and sample handling for these types of training aids in canine applications.

Combining spectrum and machine learning algorithms to predict the weathering time of empty puparia of Sarcophaga peregrine (Diptera: Sarcophagidae)

The weathering time of empty puparia could be important in predicting the minimum postmortem interval (PMImin). As corpse decomposition progresses to the skeletal stage, empty puparia often remain the sole evidence of fly activity at the scene. In this study, we used empty puparia of Sarcophaga peregrina (Diptera: Sarcophagidae) collected at ten different time points between January 2019 and February 2023 as our samples. Initially, we used the scanning electron microscope (SEM) to observe the surface of the empty puparia, but it was challenging to identify significant markers to estimate weathering time. We then utilized attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to detect the puparia spectrogram. Absorption peaks were observed at 1064 cm-1, 1236 cm-1, 1381 cm-1, 1538 cm-1, 1636 cm-1, 2852 cm-1, 2920 cm-1. Three machine learning models were used to regress the spectral data after dimensionality reduction using principal component analysis (PCA). Among them, eXtreme Gradient Boosting regression (XGBR) showed the best performance in the wavenumber range of 1800-600 cm-1, with a mean absolute error (MAE) of 1.20. This study highlights the value of refining these techniques for forensic applications involving entomological specimens and underscores the considerable potential of combining FTIR and machine learning in forensic practice.

Analysis and comparison of machine learning methods for species identification utilizing ATR-FTIR spectroscopy

Accurate identification of insect species holds paramount significance in diverse fields as it facilitates a comprehensive understanding of their ecological habits, distribution range, and impact on both the environment and humans. While morphological characteristics have traditionally been employed for species identification, the utilization of empty pupariums for this purpose remains relatively limited. In this study, ATR-FTIR was employed to acquire spectral information from empty pupariums of five fly species, subjecting the data to spectral pre-processing to obtain average spectra for preliminary analysis. Subsequently, PCA and OPLS-DA were utilized for clustering and classification. Notably, two wavebands (3000-2800 cm-1 and 1800-1300 cm-1) were found to be significant in distinguishing A. grahami. Further, we established three machine learning models, including SVM, KNN, and RF, to analyze spectra from different waveband groups. The biological fingerprint region (1800-1300 cm-1) demonstrated a substantial advantage in identifying empty puparium species. Remarkably, the SVM model exhibited an impressive accuracy of 100 % in identifying all five fly species. This study represents the first instance of employing infrared spectroscopy and machine learning methods for identifying insect species using empty pupariums, providing a robust research foundation for future investigations in this area.

A global perspective of forensic entomology case reports from 1935 to 2022

Forensic entomology case reports are the product of rapid development in the field, the widespread acceptance of the science and the application of forensic entomological knowledge. In this study, we retrospectively summarized information derived from 307 forensic entomology case reports from 1935 to 2022 from a global perspective. Our checklist of relevant information included insect species, specific indoor or outdoor preferences, preferred temperatures, and stages of body decomposition. Finally, a concept and calculation method for postmortem interval (PMI) estimation accuracy was proposed. There were 232 cases using insect developmental data and 28 cases using succession patterns to estimate PMI. A total of 146 species of insects were involved in the cases, of which 62.3% were Diptera and 37.7% were Coleoptera. Postmortem intervals were estimated from eggs in 4 cases, larvae in 180 cases, pupae in 45 cases, and puparia in 38 cases. The majority of cases were from June to October, and the average number of species mentioned in the cases was more at 15-30 °C. Considering the standardization of application, in the majority of cases, insect evidence was collected by other personnel and sent to forensic entomologists, there was a delay in the sampling, and the scene or meteorological data were directly used without correcting. Our data shows that there are still many shortcomings in the universality and standardization of forensic entomology in its practical application.

Cuticular hydrocarbons as weathering biomarkers of empty puparia of the forensically important blowfly Calliphora vicina Robineau-Desvoidy, 1830 (Diptera: Calliphoridae) in soil v/s under room conditions

Forensic entomology uses the age of insects, such as blow flies, to determine a minimum post-mortem interval (PMImin). Recent research has focused on using the analysis of specific cuticular hydrocarbons (CHCs) in adult insects and their empty puparia to estimate their age, as it has been shown that their profile changes are consistent with age. The current work is based on the weathering of five CHCs from empty puparia of Calliphora vicina that were stored in soil (field/outdoor) and non-soil (room/indoor conditions) based pupariation media for a total of six months. The experiment was conducted in a controlled environment chamber at a constant temperature of 25 ± 2 °C under constant darkness. Gas chromatography-mass spectrometry (GC-MS) was used to analyze the cuticular hydrocarbons after they were extracted in n-Hexane. n-Pentacosane, n-Hexacosane, n-Heptacosane, n-Octacosane, and n-Nonacosane were the five CHCs investigated. Results showed that CHCs weathered more quickly in the soil than in the non-soil environment. It was also found that the abundance of Heptacosane increased in the samples during the fifth month when stored in a non-soil medium, while the abundances of all five CHCs were not detected after eight weeks onwards in soil pupation medium.

Predicting the Weathering Time by the Empty Puparium of Sarcophaga peregrina (Diptera: Sarcophagidae) with the ANN Models

Empty puparium are frequently collected at crime scenes and may provide valuable evidence in cases with a long postmortem interval (PMI). Here, we collected the puparium of Sarcophaga peregrina (Diptera: Sarcophagidae) (Robineau-Desvoidy, 1830) for 120 days at three temperatures (10 °C, 25 °C, and 40 °C) with the aim to estimate the weathering time of empty puparium. The CHC profiles were analyzed by gas chromatography-mass spectrometry (GC-MS). The partial least squares (PLS), support vector regression (SVR), and artificial neural network (ANN) models were used to estimate the weathering time. This identified 49 CHCs with a carbon chain length between 10 and 33 in empty puparium. The three models demonstrate that the variation tendency of hydrocarbon could be used to estimate the weathering time, while the ANN models show the best predictive ability among these three models. This work indicated that puparial hydrocarbon weathering has certain regularity with weathering time and can gain insight into estimating PMI in forensic investigations.

A Study of Cuticular Hydrocarbons of All Life Stages in Sarcophaga peregrina (Diptera: Sarcophagidae)

Sarcophaga peregrina (Robineau-Desvoidy, 1830), a synanthropic flesh fly species found in different parts of the world, is of medical and forensic importance. Traditional methods of inferring developmental age rely on the life stage of insects and morphological changes. However, once the larvae reach the pupal and adult stage, morphological changes would become barely visible, so that the classic method would be invalid. Here, we studied the cuticular hydrocarbon profile of S. peregrina of the whole life cycle from larval stage to adult stage by GC-MS. Sixty-three compounds with carbon chain length ranging from 8 to 36 were detected, which could be categorized into four classes: n-alkanes, branched alkanes, alkenes, and unknowns. As developmental increased, branched alkanes dominant, and the content of high-molecular-weight hydrocarbons is variable, especially for 2-methyl C19, DiMethyl C21, docosane (C22), and tricosane (C23). This study shows that the composition of CHC could be used to determine the developmental age of S. peregrina and aid in postmortem interval estimations in forensic science.

Post-Mortem Interval Estimation Based on Insect Evidence: Current Challenges

During death investigations insects are used mostly to estimate the post-mortem interval (PMI). These estimates are only as good as they are close to the true PMI. Therefore, the major challenge for forensic entomology is to reduce the estimation inaccuracy. Here, I review literature in this field to identify research areas that may contribute to the increase in the accuracy of PMI estimation. I conclude that research on the development and succession of carrion insects, thermogenesis in aggregations of their larvae and error rates of the PMI estimation protocols should be prioritized. Challenges of educational and promotional nature are discussed as well, particularly in relation to the collection of insect evidence.

The optimal post-eclosion interval while estimating the post-mortem interval based on an empty puparium

The puparium is the hardened exoskeleton of the last larval instar of a fly, inside which a prepupa, a pupa and a pharate adult fly successively develop. Empty puparia are frequently collected at death scenes, especially in cases with a long post mortem interval (PMI). Although we are not able to estimate the interval between the eclosion of an adult fly and the collection of an empty puparium (i.e. the post-eclosion interval (PEI)), empty puparia may still provide valuable evidence about the minimum PMI. However, because of the unknown PEI, it is impossible to determine the time when the fly emerged, and thus when the retrospective calculation of the minimum PMI should start. In this study, the estimation of PMI (or minimum PMI) for empty puparia of Protophormia terraenovae Rob.-Desv. (Calliphoridae) and Stearibia nigriceps Meig. (Piophilidae) was simulated, to gain insight into the changes in estimates, when different PEIs and different temperature conditions were assumed. The simulations showed that the PEI (in a range of 0–90 days) had no effect on the PMI (or minimum PMI) when the puparium was collected in winter or early spring (December–April). In late spring, summer, or autumn (May–November) the PMI (or minimum PMI) increased with the PEI. The increase in PMI was large in the summer months, and surprisingly small in the autumn months, frequently smaller than the PEI used in the estimation. The shortest PMI was always obtained with a PEI of 0, indicating that the true minimum PMI is always estimated using a PEI of 0. When the puparium was collected during spring, simulations indicated that oviposition had occurred in the previous year, while in summer the previous-year oviposition has been indicated by the simulations only when longer PEIs had been assumed. These findings should guide estimation of the PMI (or minimum PMI) based on an empty puparium.

Eye-background contrast as a quantitative marker for pupal age in a forensically important carrion beetle Necrodes littoralis L. (Silphidae)

Insect pupae sampled at a death scene may be used to estimate the post-mortem interval. The pupal age is however difficult to estimate, as there are no good quantitative markers for the age of a pupa. We present a novel method for pupal age estimation based on the quantification of contrast in intensity between the eyes of a pupa and the middle grey photography card as a standard background. The intensity is measured on a standardized scale from 0 (perfect black) to 255 (perfect white) using computer graphical software and pictures of the eye and the background taken with a stereomicroscope. Eye-background contrast is calculated by subtracting the average intensity of the eye from the average intensity of the background. The method was developed and validated using pupae of Necrodes littoralis (Linnaeus, 1758) (Coleoptera: Silphidae), one of the most abundant beetle species on human cadavers in Central Europe. To develop the model, pupae were reared in 17, 20 and 23 °C, with a total of 120 specimens. The method was validated by three raters, using in total 182 pupae reared in 15, 17, 20, 23 and 25 °C. We found a gradual increase in eye-background contrast with pupal age. Changes followed generalized logistic function, with almost perfect fit of the model. Using our method pupal age was estimated with the average error of 8.1 accumulated degree-days (ADD). The largest error was 27.8 ADD and 95% of age estimates had errors smaller than 20 ADD. While using the method, different raters attained similar accuracy. In conclusion, we have demonstrated that eye-background contrast is a good quantitative marker for the age of N. littoralis pupae. Contrast measurements gave accurate estimates for pupal age. Our method is thus proven to be a candidate for a reliable approach to age insect pupae in forensic entomology.

New method for estimating the post-mortem interval using the chemical composition of different generations of empty puparia: Indoor cases

Most flies of forensic importance are in two superfamilies, the Muscoidea and the Oestroidea, with similar life stages including the puparium. Upon completion of metamorphosis the adult fly emerges from the puparium, leaving behind an exuvia that is of potential significance in forensic investigation. The empty puparium is a durable piece of entomological evidence lasting several years. Through the study of chemical compounds, specifically the hydrocarbons of these puparia, it is possible to identify the species, in addition to how long they have been exposed to weathering and for this reason, these parameters can assist forensic entomologists in estimating long-term postmortem interval (minPMI). In corpses that take a relatively longer time to decompose, insects may use the same corpses for several oviposition cycles. Therefore, the aim of this study was to develop a new method to determine the PMI based on chemical compounds of the puparia from different oviposition cycles of the fly Chrysomya megacephala. The chemical composition of 50 puparia from different cycles of oviposition were evaluated by Gas Chromatography–Mass Spectrometry (GC-MS). In total, 60 compounds were identified ranging from C₁₈ to C₃₄, 38 of those were common to all generations. Our results demonstrate that chemical profiles can be used to differentiate puparia collected from successive cycles, and therefore valuable in the estimation of minPMI.

The potential use of cuticular hydrocarbons and multivariate analysis to age empty puparial cases of Calliphora vicina and Lucilia sericata

Cuticular hydrocarbons (CHC) have been successfully used in the field of forensic entomology for identifying and ageing forensically important blowfly species, primarily in the larval stages. However in older scenes where all other entomological evidence is no longer present, Calliphoridae puparial cases can often be all that remains and therefore being able to establish the age could give an indication of the PMI. This paper examined the CHCs present in the lipid wax layer of insects, to determine the age of the cases over a period of nine months. The two forensically important species examined were Calliphora vicina and Lucilia sericata. The hydrocarbons were chemically extracted and analysed using Gas Chromatography – Mass Spectrometry. Statistical analysis was then applied in the form of non-metric multidimensional scaling analysis (NMDS), permutational multivariate analysis of variance (PERMANOVA) and random forest models. This study was successful in determining age differences within the empty cases, which to date, has not been establish by any other technique.

Predictable weathering of puparial hydrocarbons of necrophagous flies for determining the postmortem interval: a field experiment using Chrysomya rufifacies

Preadult development of necrophagous flies is commonly recognized as an accurate method for estimating the minimum postmortem interval (PMImin). However, once the PMImin exceeds the duration of preadult development, the method is less accurate. Recently, fly puparial hydrocarbons were found to significantly change with weathering time in the field, indicating their potential use for PMImin estimates. However, additional studies are required to demonstrate how the weathering varies among species. In this study, the puparia of Chrysomya rufifacies were placed in the field to experience natural weathering to characterize hydrocarbon composition change over time. We found that weathering of the puparial hydrocarbons was regular and highly predictable in the field. For most of the hydrocarbons, the abundance decreased significantly and could be modeled using a modified exponent function. In addition, the weathering rate was significantly correlated with the hydrocarbon classes. The weathering rate of 2-methyl alkanes was significantly lower than that of alkenes and internal methyl alkanes, and alkenes were higher than the other two classes. For mono-methyl alkanes, the rate was significantly and positively associated with carbon chain length and branch position. These results indicate that puparial hydrocarbon weathering is highly predictable and can be used for estimating long-term PMImin.

Research progress in the estimation of the postmortem interval by Chinese forensic scholars

The determination of time since death or the postmortem interval (PMI) is one of the most important and frequently asked questions in forensic medicine. Medicolegal scholars and forensic pathologists around the world have studied the estimation of PMI extensively in the past, and many novel methods and advanced technologies have now been applied in the field. For several centuries, Chinese forensic examiners have also worked on the estimation of the PMI, and there are a large number of excellent studies published in Chinese rather than in English, and these are not easily accessible or known internationally. Therefore we have conducted a review of relevant studies published by Chinese forensic scholars in the last few decades. The scope of this review is to provide a concise summary of the current progress in the estimation of PMI by Chinese forensic researchers using molecular biology, spectroscopic technology, entomological methods, energy changes, thanatochemistry and other methods.

The experimental design of postmortem studies: the effect size and statistical power

Purpose

The aim is of this study was to show the poor statistical power of postmortem studies. Further, this study aimed to find an estimate of the effect size for postmortem studies in order to show the importance of this parameter. This can be an aid in performing power analysis to determine a minimal sample size.

Methods

GPower was used to perform calculations on sample size, effect size, and statistical power. The minimal significance (α) and statistical power (1 − β) were set at 0.05 and 0.80 respectively. Calculations were performed for two groups (Student’s t-distribution) and multiple groups (one-way ANOVA; F-distribution).

Results

In this study, an average effect size of 0.46 was found (n = 22; SD = 0.30). Using this value to calculate the statistical power of another group of postmortem studies (n = 5) revealed that the average statistical power of these studies was poor (1 − β < 0.80).

Conclusion

The probability of a type-II error in postmortem studies is considerable. In order to enhance statistical power of postmortem studies, power analysis should be performed in which the effect size found in this study can be used as a guideline.