Age Estimation Of Bloodstains Research Articles

Estimation of Time-Since-Deposition of bloodstains on different surfaces using ATR-FTIR Spectroscopy and Chemometrics.

Blood is commonly discovered at crime scenes in various forms, including stains, dried residue, pools, and fingerprints on assorted surfaces. Estimating the age of bloodstains is a crucial aspect of reconstructing crime scenes. This research aimed to investigate how the nature of different surfaces affects the estimation of bloodstain age, utilizing a reliable and non-destructive approach. The study employed ATR-FTIR spectroscopy in conjunction with Chemometric techniques such as PCA (Principal Component Analysis) and OPLSR (Orthogonal Signal Correction Partial Least Square Regression Analysis) to analyze spectral data and develop regression models for estimating bloodstain age on cement, metal, and wooden surfaces for up to eleven days. The chemometric models for bloodstains on all three substrates demonstrated strong performance, with predictive Root Mean Square Error (RMSE) values ranging from 1.1 to 1.43 and R2 values from 0.84 to 0.89. Notably, the model developed for metal surfaces was found to be the most accurate with minimal prediction error. The findings of the study showed that the porosity of the substrates upon which bloodstains were found had a discernible influence on the age-related transformations observed in bloodstains; the majority of which occured within the spectral range of 2800cm- 1 to 3500cm- 1.

Establishment of a random forest regression model to estimate the age of bloodstains based on temporal colorimetric analysis

Bloodstain age estimation is important in forensic science. Although several studies have used spectroscopy to estimate bloodstain ages, this method has not yet been practically applied due to the need for expensive equipment and low reproducibility. Thus, we aimed to develop a bloodstain age estimation model that can be easily performed using a spectrophotometric colorimeter. First, bloodstains were prepared by placing blood obtained from five healthy volunteers on a plastic plate. The bloodstains were kept on conditions with various brightness and temperatures. Then, each bloodstain was dissolved in saline every 24 h to a final concentration of 1%, measured with a spectrophotometric colorimeter, and subjected to machine learning to generate a random forest regression (RFR) model, and finally, the prediction accuracy of the bloodstain age was verified. We also elucidated the mechanism of the color changes utilizing aminoguanidine, which is an inhibitor of Maillard reaction. Finally, we measured the time-dependent color changes of the blood fluids obtained from healthy volunteers and examined if the method could be potentially applied to estimate postmortem interval (PMI). Our results showed that the RFR model estimated the bloodstain age with no substantial assessment, and it was applicable to bloodstains, regardless of the brightness or temperature. The color changes were affected by the addition of aminoguanidine. Furthermore, the method could be applied to blood fluids, suggesting its potential usefulness for PMI estimation. Considering its feasibility, the present method could potentially be introduced to practical forensic sciences in the near future.

Development of a novel forensic age estimation strategy for aged blood samples by combining piRNA and miRNA markers.

In forensic investigations, age estimation is vital for determining whether a suspect is under or over the legally defined adult age. With breakthroughs in RNA sequencing technology, small noncoding RNAs have provided new ways to solve problems related to the age estimation of trace or aged samples, owing to their small molecular weight and better stability. In our previous study, we had applied miRNAs for the age estimation of bloodstains; however, further improvement of the existing model is needed. PIWI-interacting RNAs (PiRNAs), which are 24-32 nt noncoding small RNA molecules involved in the PIWI-piRNA pathway, play an important role in the aging process. In this study, we explored the possibility of simultaneously analyzing piRNAs and miRNAs for better age estimation purpose. Through massively parallel sequencing, five age-related piRNAs were identified in blood samples that had been stored for eight years. Further real-time PCR analysis revealed that two piRNAs (piR-000753 and piR-020548) showed relatively higher efficiency in age estimation. Additionally, two age-related miRNAs (miR-324-3p and miR-330-5p) were used to build the estimation model. Among all algorithms tested, gradient boosting showed the lowest mean absolute error (MAE) and root mean square error (RMSE) values (3.171 and 4.403years, respectively) for the validation dataset (n = 110). The errors of the model were less than 5years and 10years for 81.82% and 96.36% of the samples, respectively. The results suggest that the combined use of piRNA and miRNA markers may increase the accuracy of age estimation, and our new model has great potential for application in forensic casework.

Neural network based hyperspectral imaging for substrate independent bloodstain age estimation

Being able to determine the age of a bloodstain can be a key element in a crime scene investigation. Many techniques exploit reflectance spectroscopy because it is very versatile and can be used in the field with ease. However, there are no methods for estimating bloodstain age with adequate uncertainty, and the problem of substrate influence is not yet fully resolved. We develop a hyperspectral imaging based technique for the substrate-independent age estimation of a bloodstain. Once the hyperspectral image is acquired, a neural network model recognizes the pixels belonging to the bloodstain. The reflectance spectra belonging to the bloodstain are then processed by an artificial intelligence model that removes the effect of the substrate on the bloodstain and then estimates its age. The method is trained on bloodstains deposited on 9 different substrates over a time period of 0–385 h obtaining an absolute mean error of 6.9 h over the period considered. Within two days of age, the method achieves a mean absolute error of 1.1 h. The method is finally tested on a new material (i.e., red cardboard) never used to test or validate the neural network models. Also in this case the bloodstain age is identified with the same accuracy.

Age estimation of bloodstains based on convolutional neural network algorithm and hyperspectral imaging technology.

The most common trace of evidence at a crime scene is blood. In judicial scientific proof, it is regarded as one of the most important material types of evidence. In this study, the spectral data of the bloodstain samples with different time were collected via a hyperspectral imaging system with a spectral range of 400-1000 nm and spectral sampling interval of 5 nm. The training model of blood aging was built using the Convolutional Neural Network (CNN) algorithm and the above hyperspectral spectral data. It was also compared with the traditional partial least squares (PLS) and extreme learning machine (ELM) models. The experimental results showed that the performance of CNN model was the best, with a determination coefficient (R2) of 0.987, which is higher compared to that of the PLS model (R2 = 0.883) and ELM model (R2 = 0.936). Besides, the root mean square error of prediction (RMSEP) of the CNN model was 6.949 hours, smaller than the PLS model (RMSEP = 18.752 hours) and the ELM model (RMSEP = 13.717 hours). The mean absolute percentage error (MAPE) of the prediction set was 0.49% when using the CNN algorithm, which was also the minimum of the three algorithms, and it represented that the prediction results were the best. The experimental data showed that the method proposed in this study could accurately estimate the age of bloodstains, providing a new technology reference for bloodstain detection.

Discovery and validation of metabolite markers in bloodstains for bloodstain age estimation.

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

Age estimation of bloodstains based on Raman spectroscopy and chemometrics

The accurate estimation of the bloodstain age, which is one of the important biological evidence of crime scene, can provide a lot of information related to crime. How to extract the information quickly and accurately from bloodstains without damage has been a focused problem. In this study, a bloodstains age estimation method based on Raman spectroscopy and chemometrics was developed. As many as 11 simulated environments based on different temperature and humidity were constructed in the method, and bloodstains of three species including human were studied. The influence of environmental factors such as temperature and humidity on the variation of Raman spectral peaks during the aging process of bloodstains was analyzed using the e-index fitting. When the humidity was kept constant, the increase of temperature generally promoted the changes of the spectral peaks. When the temperature was kept constant, the increase of humidity generally slowed the changes of spectral peaks. These works provide data support for the further development of Raman spectroscopy for bloodstain age estimation and could accelerate its application in actual scenes.

The estimation of bloodstain age utilizing circRNAs and mRNAs biomarkers

Determining the time since deposition (TsD) of bloodstains can provide forensic investigators with additional clues, as it can corroborate eyewitness accounts, limit the number of suspects, and help confirm alibis. Bloodstains are the most common bodily fluid stains at crime scenes. In this study, we examined the relative expression levels (REs) of circRNAs and mRNAs data in bloodstains over ten time points by Real-time quantitative polymerase chain reaction (qPCR), to determine the utility of the relative expression levels of RNA markers for TsD estimation. Forensic samples more than just appear in indoor settings, we also evaluated the use of RNA degradation rate to indicate the age of bloodstains in different environments including indoor and outdoor conditions. The expression levels of six blood-specific mRNA markers (GYPA, CD93, ALAS2, SPTB, HBB, HBA), three highly expressed circRNAs in human peripheral blood (hsa_circ_0001445, hsa_circ_0000972, hsa_circ_0000095) and three reference genes (18 S, ACTB and U6) were analyzed across numerous ageing time points. Analysis of the degradation rates of individual RNAs under indoor and outdoor conditions showed that they exhibited a unique degradation profile during the four-month storage interval, with both circRNAs and mRNAs linearly showing continuous degradation, while U6 is more stable than other reference gene markers. In the current study, we firstly used circRNAs as additional novel biomarkers for bloodstain age estimation, and at the same time proved that different environments had a significant impact on the REs of certain blood biomarkers, and sex differences did not affect the age estimation of bloodstains. The REs of the selected RNA molecules in this study showed a non-linear relationship with bloodstain age and the mathematical formula for estimating the bloodstain age based on the relative expression levels of hsa_circ_0001445, ALAS2 and HBB can be used to estimate the TsD of bloodstains from the REs of bloodstains of unknown age, which represent a potentially effective approach to looking for time-dependent changes and TsD estimation.

Short and Long Time Bloodstains Age Determination by Colorimetric Analysis: A Pilot Study.

Bloodstains found at crime scenes represent a crucial source of information for investigative purposes. However, in forensic practice, no technique is currently used to estimate the time from deposition of bloodstains. This preliminary study focuses on the age estimation of bloodstains by exploiting the color variations over time due to the oxidation of the blood. For this purpose, we used a colorimetric methodology in order to easily obtain objective, univocal and reproducible results. We developed two bloodstain age prediction algorithms: a short-term and a long-term useful model for the first 24h and 60 days, respectively. Both models showed high levels of classification accuracy, particularly for the long-term model. Although a small-scale study, these results improve the potential application of colorimetric analysis in the time-line reconstruction of violent criminal events.

Analysis of the influence of EDTA-treated reference samples on forensic bloodstain age estimation

The age estimation of blood traces provides important leads for the chronological assessment of criminal events and their reconstruction. To determine bloodstain age, experimental comparative data from a laboratory environment are used. Under these conditions the utilization of anticoagulants such as EDTA helps to suppress the blood clotting mechanism to allow the examination over a longer time period. This unnatural prevention of blood coagulation is highly questionable when estimating bloodstain age, since the blood’s physical and chemical properties are altered. For this reason, the authors determined actual influence of EDTA on blood spectra over time in order to formulate a statement as to whether this effect can be measured. Human and porcine blood samples were aged under controlled conditions. The resulting UV/VIS spectra were separated into their individual components using signal separation techniques, allowing the changes in the ratios of the individual hemoglobin derivatives to be observed over time. The results show a significant influence of EDTA on the conversion of oxyhemoglobin to methemoglobin and a minor influence on the conversion of methemoglobin to hemichrome within the relevant time range of 5–100 h. The use of EDTA thus slows down the aging process of blood spots. To illustrate the great influence of EDTA, spectra of untreated pig blood samples were included as comparison data. These show that the difference between EDTA-treated and untreated blood samples is as great as the difference between human blood and pig blood. As a consequence of our findings experimental comparative data for the age estimation of bloodstains should never result from EDTA-treated blood.

Dual-DMD hyperspectral spatial frequency domain imaging (SFDI) using dispersed broadband illumination with a demonstration of blood stain spectral monitoring.

Spatial frequency domain imaging (SFDI) is a widefield diffuse optical measurement technique capable of generating 2D maps of sub-surface absorption and scattering in biological tissue. We developed a new hyperspectral SFDI instrument capable of collecting images at wavelengths from the visible to the near infrared. The system utilizes a custom-built monochromator with a digital micromirror device (DMD) that can dynamically select illumination wavelength bands from a broadband quartz tungsten halogen lamp, and a second DMD to provide spatially modulated sample illumination. The system is capable of imaging 10 wavelength bands in approximately 25 seconds. The spectral resolution can be varied from 12 to 30 nm by tuning the input slit width and the output DMD column width. We compared the optical property extraction accuracy between the new device and a commercial SFDI system and found an average error of 23% in absorption and 6% in scattering. The system was highly stable, with less than 5% variation in absorption and less than 0.2% variation in scattering across all wavelengths over two hours. The system was used to monitor hyperspectral changes in the optical absorption and reduced scattering spectra of blood exposed to air over 24 hours. This served as a general demonstration of the utility of this system, and points to a potential application for blood stain age estimation. We noted significant changes in both absorption and reduced scattering spectra over multiple discrete stages of aging. To our knowledge, these are the first measurement of changes in scattering of blood stains. This hyperspectral SFDI system holds promise for a multitude of applications in quantitative tissue and diffuse sample imaging.

Bloodstain age estimation through infrared spectroscopy and Chemometric models

The chemical profiling of bloodstains is essential to link the suspect with the crime. The current study proposed a proof-of-concept methodology for the investigation of bloodstains by utilizing advanced ATR-FTIR spectroscopy coupled with new generation chemometric methods. Current study providesencouraging datato allow discrimination between human and animal blood though with small sample size. In this study, different models for the age estimation of human bloodstains are developed from the trained data sets of 1–175 days old bloodstains. The models such as curve estimation (CE), multiple linear regression (MLR), and partial least squares regressions (PLSR) are developed to determine the best prediction model for aged human bloodstains. The obtained results on the dating of bloodstains are very encouraging and also tested for unknown samples. The maximum dating errors are observed in the curve estimation models whereas, the other models MLR, PLSR show excellent age estimation of unknown bloodstains. These models represent an error of ~3 ± 1 days and ~4 ± 1 days in actual and estimated date, respectively, which is lowest ever reported so far. The present methodology is expected to provide a valuable insight into forensic society and hence, to the law enforcement community. The present methodology can further be explored for an ideal model by including all other external variables/factors and for more longer aging time.

Development of Integrated Device of Trace Bloodstains Imaging and Age Analysis.

Objective To develop a device of trace bloodstains imaging and age analysis, so as to provide a non-destructive, simple and objective method for age estimation of bloodstains at the crime scene. Methods Based on the principle of digital imaging and color pattern analysis, the mobile terminal of the device was used to collect images of bloodstains of different ages. The time-dependent pattern of 6 parameters （R, G, B, C, Y, M） reflecting the changes of color of images of different ages was obtained by computer image analysis. A multiparameter comprehensive inference equation of bloodstains age was established and embedded into the device software to realize the intelligent inference of the bloodstains age. Then the capability and reliability of the device was verified. Results This integrated device of bloodstains imaging and age analysis could quickly collect bloodstains at the crime scene and automatically analyze and infer the age of bloodstains combined with related intelligence software. In the blind test, the detection accuracy of this device was 95% in both natural light airtight group and dark airtight group, and 80% in the natural light ventilation group. Conclusion The integrated device of trace bloodstains imaging and age analysis can be used in a simple manner, which provides a new objective method for bloodstains age estimation.

Highly sensitive and accurate estimation of bloodstain age using smartphone

The estimation of bloodstain age is an important factor in forensic analysis. Previously, we have reported a smartphone-based colorimetric system for age estimation of bloodstain, in which Whole blood and EDTA whole blood were dropped on 4 different materials (700 μL) and captured using a smartphone for 72 h. In order to enhance sensitivity and accuracy of the previous system, the current work is dedicated towards the application of pattern recognition and classification of bloodstain images based on a smartphone. Three detection methods (blood pool, crack ratio, and colorimetric analysis) in terms of 6 steps of drying process of the bloodstain (coagulation, gelation, edge desiccation, center desiccation, crack propagation, and final desiccation) were applied to estimate age of the bloodstain accurately. Three parameters from the bloodstain images were then classified as comparing to those of stored reference images with similar trends in database. The bloodstain age was successfully determined by 9 h, 18 h, and 48 h with respect to the three detection methods mentioned above, respectively. The differences in bloodstain images were clearly distinguished every hour by using smartphone-based pattern recognition analysis. Therefore, our system is expected to shed a light on the field of forensic science by estimating bloodstain age in real time.

SjTREC quantification using SYBR quantitative PCR for age estimation of bloodstains in a Japanese population.

Individual age is a phenotypic trait that provides useful information in forensic investigations. Levels of signal joint T-cell receptor rearrangement excision circle (sjTREC) in human peripheral blood are known to decline with increasing age. The advantages of sjTREC quantification are the simple procedures and highly accurate age estimation results. Whereas TaqMan quantification PCR (qPCR) is widely used for sjTREC quantification, SYBR qPCR assay is not routinely used for evaluating ethnic data. Therefore, we focused on the advantages of the SYBR qPCR assay, which is cheaper and simpler to set up than the TaqMan probe assay. In this study, we developed a SYBR qPCR assay for sjTREC quantification from bloodstains from a Japanese population and evaluated the strength of correlation between sjTREC levels and actual age. The results were obtained from 194 individuals ranging from 18 to 81 years old, and showed a negative correlation between sjTREC level and individual age (r = -0.786). The equation for age estimation was Age = -6.27 dCt (CtTBP - CtsjTREC) - 25.841 with standard error ±8.0 years. Furthermore, this formula for the SYBR assay can be applied to not only fresh bloodstains, but also whole blood and bloodstains up to 1 month old. These results indicate that SYBR qPCR is an effective method for age estimation from bloodstains, and its practicality and affordability make it an attractive sjTREC quantification technique.

Estimation of the age of human bloodstains under the simulated indoor and outdoor crime scene conditions by ATR-FTIR spectroscopy

Estimation of the age of human bloodstains is of great importance in forensic practices, but it is a challenging task because of the lack of a well-accepted, reliable, and established method. Here, the attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique combined with advanced chemometric methods was utilized to determine the age of indoor and outdoor bloodstains up to 107 days. The bloodstain storage conditions mimicked crime scene scenarios as closely as possible. Two partial least squares regression models—indoor and outdoor models with 7–85 days—exhibited good performance for external validation, with low values of predictive root mean squared error (5.83 and 4.77) and high R2 values (0.94 and 0.96) and residual predictive deviation (4.08 and 5.14), respectively. Two partial least squares–discriminant analysis classification models were built and demonstrated excellent distinction between fresh (age ≤1 d) and older (age >1 d) bloodstains, which is highly valuable for forensic investigations. These findings demonstrate that ATR-FTIR spectroscopy coupled with advanced chemometric methods can be employed as a rapid and non-destructive tool for age estimation of bloodstains in real-world forensic investigation.

Quantification of RNA degradation of blood-specific markers to indicate the age of bloodstains

Determining the time since deposition of a biological stain can provide essential information to a police investigation; indicating either when a crime occurred, or whether the biological evidence was deposited at the time of a known crime event. Bloodstains are one of the most important biological evidence types to forensic investigators. This research has used reverse transcription quantitative PCR to examine the relative expression ratio (RER) between different types of blood-specific markers, with the aim of developing a method to estimate the age of bloodstains. Targets included three mRNA markers (HBA, PBGD, HBB) and two microRNA markers (miR16, miR451), along with three reference genes (18S rRNA, ACTB mRNA, U6 snRNA). Blood samples from 10 individuals were deposited onto cotton swabs and stored at room temperature to simulate natural ageing. When samples reached a series of desired age points, total RNA was extracted. Analysis of the degradation rate of individual RNAs showed they exhibited unique degradation profiles during the nine-month storage interval, where miRNAs and U6 were shown to be more stable than other markers. The RERs show a non-linear relationship with bloodstain age, and were shown to be useful for bloodstain age estimation.

Towards substrate-independent age estimation of blood stains based on dimensionality reduction and k-nearest neighbor classification of absorbance spectroscopic data

The age determination of blood traces provides important hints for the chronological assessment of criminal events and their reconstruction. Current methods are often expensive, involve significant experimental complexity and often fail to perform when being applied to aged blood samples taken from different substrates. In this work an absorption spectroscopy-based blood stain age estimation method is presented, which utilizes 400–640nm absorption spectra in computation. Spectral data from 72 differently aged pig blood stains (2h to three weeks) dried on three different substrate surfaces (cotton, polyester and glass) were acquired and the turnover-time correlations were utilized to develop a straightforward age estimation scheme. More precisely, data processing includes data dimensionality reduction, upon which classic k-nearest neighbor classifiers are employed. This strategy shows good agreement between observed and predicted blood stain age (r>0.9) in cross-validation. The presented estimation strategy utilizes spectral data from dissolved blood samples to bypass spectral artifacts which are well known to interfere with other spectral methods such as reflection spectroscopy. Results indicate that age estimations can be drawn from such absorbance spectroscopic data independent from substrate the blood dried on. Since data in this study was acquired under laboratory conditions, future work has to consider perturbing environmental conditions in order to assess real-life applicability.

Age estimation of bloodstains using smartphones and digital image analysis

Recent studies on bloodstains have focused on determining the time since deposition of bloodstains, which can provide useful temporal information to forensic investigations. This study is the first to use smartphone cameras in combination with a truly low-cost illumination system as a tool to estimate the age of bloodstains. Bloodstains were deposited on various substrates and photographed with a smartphone camera. Three smartphones (Samsung Galaxy S Plus, Apple iPhone 4, and Apple iPad 2) were compared. The environmental effects – temperature, humidity, light exposure, and anticoagulant – on the bloodstain age estimation process were explored. The color values from the digital images were extracted and correlated with time since deposition. Magenta had the highest correlation (R2=0.966) and was used in subsequent experiments. The Samsung Galaxy S Plus was the most suitable smartphone as its magenta decreased exponentially with increasing time and had highest repeatability (low variation within and between pictures). The quantifiable color change observed is consistent with well-established hemoglobin denaturation process. Using a statistical classification technique called Random Forests™, we could predict bloodstain age accurately up to 42 days with an error rate of 12%. Additionally, the age of forty blind stains were all correctly predicted, and 83% of mock casework samples were correctly classified. No within- and between-person variations were observed (p>0.05), while smartphone camera, temperature, humidity, and substrate color influenced the age determination process in different ways. Our technique provides a cheap, rapid, easy-to-use, and truly portable alternative to more complicated analysis using specialized equipment, e.g. spectroscopy and HPLC. No training is necessary with our method, and we envision a smartphone application that could take user inputs of environmental factors and provide an accurate estimate of bloodstain age.

Hyperspectral imaging for the age estimation of blood stains at the crime scene

The age estimation of blood stains can provide important information on the temporal aspects of a crime. As previously shown, visible spectroscopy of blood stains can successfully be used for their age estimation. In the present study we evaluated the feasibility to use hyperspectral imaging for this purpose. Visible reflectance spectra of blood stains were recorded using a pushbroom hyperspectral imaging system. From these spectra, the relative amounts of oxyhemoglobin, methemoglobin and hemichrome within the blood stains were derived. By comparison of the hemoglobin derivative fractions with a reference dataset, the age of blood stains up to 200 days old was estimated. The absolute error of the age estimation task increased with age, with a median relative error of 13.4% of the actual age. To test the practical applicability of this method, a simulated crime scene was analyzed, in which blood stains of several ages were deposited. Hyperspectral imaging combined with the proposed analysis provided insight in the absolute age of the blood stains. Additionally, the blood stains were clustered based on their hemoglobin derivative fractions, without the use of a reference dataset. Results demonstrated that the order of formation of blood stains can be determined, even under unknown environmental circumstances, when no proficient reference dataset is available. These findings are an important step toward the practical implementation of blood stain age estimation in forensic casework.