Application of Fourier transform infrared spectroscopy with chemometrics on postmortem interval estimation based on pericardial fluids

Multi-omics integration strategy in the post-mortem interval of forensic science

Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts, are fundamentally based on assessments of variability among diverse molecular markers (including proteins and metabolites), their correlations, and their temporal changes in post-mortem organisms. Nevertheless, the present approach to estimating the PMI is not comprehensive and exhibits poor performance. We developed an innovative approach that integrates multi-omics and artificial intelligence, using multimolecular, multimarker, and multidimensional information to accurately describe the intricate biological processes that occur after death, ultimately enabling inference of the PMI. Called the multi-omics stacking model (MOSM), it combines metabolomics, protein microarray electrophoresis, and fourier transform-infrared spectroscopy data. It shows improved prediction accuracy of the PMI, which is urgently needed in the forensic field. It achieved an accuracy of 0.93, generalized area under the receiver operating characteristic curve of 0.98, and minimum mean absolute error of 0.07. The MOSM integration framework not only considers multiple markers but also incorporates machine-learning models with distinct algorithmic principles. The diversity of biological mechanisms and algorithmic models further ensures the generalizability and robustness of PMI estimation.

Estimation of time since deposition of semen stain on different fabric types using ATR-FTIR spectroscopy and chemometrics

Various body fluids such as blood, semen, vaginal secretions, and saliva are frequently encountered at crime scene. In cases of sexual assault, semen stains are one of the most reliable evidence of biological origin. In this study, our objective was to develop a method for estimating the time since deposition of semen stains on five different fabric types using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy, with a focus on a time frame of up to 8 weeks. Semen samples from six different volunteers were dripped onto five distinct fabric materials, and ATR-FTIR measurements were obtained at 17 different time points. Principal component analysis (PCA) and partial least squares (PLS) methods were employed to differentiate semen stains on various fabric samples and estimate the age of semen stains. Models constructed using PCA and PLSR achieved high R2 values and low root-mean-square error (RMSE). While the performance varies depending on fabric types, it was observed that age estimation of semen stains can be made within following intervals: 0.39-0.76 days for 0-7 day range, 2.59-3.38 days for the 1-8 week range, and 3.98-8.1 days for the 0-56 day range. This study demonstrates the effectiveness of using ATR-FTIR spectroscopy in combination with chemometrics to estimate the age of human semen stains on various fabric types based on time-dependent spectral changes.

Metabolomics investigation of post-mortem human pericardial fluid

INTRODUCTION

Due to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors' knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or post-mortem interval based on pericardial fluids has still rarely been attempted.

OBJECTIVES

We applied a metabolomic approach based on 1H nuclear magnetic resonance spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for post-mortem interval estimation.

METHODS

Pericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 h after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of 1H nuclear magnetic resonance and multivariate statistical data analysis.

RESULTS

The pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33-34 h depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 h, the prediction power of the model was significantly improved with an error of 13-15 h depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.

CONCLUSION

The present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.

A Dual-Purpose Ce(III)-Organic Framework with Amine Groups and Open Metal Sites: Third-Order Nonlinear Optical Activity and Catalytic CO2 Fixation

The present work focuses on the synthesis and properties of a novel multifunctional cerium(III) MOF, [Ce2(data)3(DMF)4]·DMF (data2-: 2,5-diaminoterephthalate), abbreviated as NH2-Ce-MUM-2. Its crystal structure reveals an intricate 3D 4,5-connected framework with a xah topology. This MOF features unique properties, such as open metal sites, presence of free amino groups, and high stability. Two main applications of NH2-Ce-MUM-2 were investigated: (i) as a heterogeneous catalyst in the CO2 fixation into cyclic carbonates and (ii) as a material with third-order nonlinear optical activity. As a model reaction, the cycloaddition of CO2 to propylene oxide to give the corresponding cyclic carbonate was explored under mild conditions, at the atmospheric pressure of carbon dioxide and in the absence of cocatalyst and added solvent. Various reaction parameters were investigated toward optimization and exploration of substrate scope, revealing up to 99% product yields of cyclic carbonate products. Besides, the structure of NH2-Ce-MUM-2 is highly stable, permitting its recyclability and reusability in further catalytic experiments. The significant contributions of free amino groups and open metal sites within this catalyst were particularly considered when proposing a potential mechanism for the reaction. Z-Scan measurements were used to evaluate the nonlinear optical (NLO) properties of NH2-Ce-MUM-2 at various laser intensities. A high two-photon absorption (TPA) under greater incident intensities shows that NH2-Ce-MUM-2 might be applicable in optical switching devices. Besides, the self-focusing effects of NH2-Ce-MUM-2 under various incident intensities were highlighted by the nonlinear index of refraction (n2). By reporting the synthesis and characterization of a novel MOF, along with its highly promising catalytic and NLO behavior, the current study introduces an additional example of multifunctional material into a growing family of metal-organic frameworks.

Estimation of Late Postmortem Interval: Where Do We Stand? A Literature Review

Estimating time since death can be challenging for forensic experts, and is one of the most challenging activities concerning the forensic world. Various methods have been assessed to calculate the postmortem interval on dead bodies in different stages of decomposition and are currently widely used. Nowadays, the only well-recognized dating technique is carbon-14 radioisotope measurement, whereas other methods have been tested throughout the years involving different disciplines with different and sometimes not univocal results. Today, there is no precise and secure method to precisely determine time since death, and late postmortem interval estimation remains one of the most debated topics in forensic pathology. Many proposed methods have shown promising results, and it is desirable that with further studies some of them might become acknowledged techniques to resolve such a difficult and important challenge. The present review aims at presenting studies about the different techniques that have been tested in order to find a valuable method for estimating time since death for skeletal remains. By providing a comprehensive overview, the purpose of this work is to offer readers new perspectives on postmortem interval estimation and to improve current practice in the management of skeletal remains and decomposed bodies.

Overcoming obstacles: Analysis of blood and semen stains washed with different chemicals with ATR-FTIR

INTRODUCTION

Blood and semen stains are the most common biological stains encountered at crime scenes. The washing of biological stains is a common application that perpetrators use to spoil the crime scene. With a structured experiment approach, this study aims to investigate the effects of washing with various chemicals on the ATR-FTIR detection of blood and semen stains on cotton.

MATERIALS AND METHODS

On cotton pieces, a total of 78 blood and 78 semen stains were applied, and each group of six stains was immersed or mechanically cleaned in water, 40% methanol, 5% sodium hypochlorite solution, 5% hypochlorous acid solution, 5 g/L soap dissolved pure water, and 5 g/L dishwashing detergent dissolved water. ATR-FTIR spectra gathered from all stains and analyzed with chemometric tools.

RESULTS AND DISCUSSION

According to performance parameters of developed models, PLS-DA is a powerful tool for discrimination of washing chemical for both washed blood and semen stains. Results from this study show that FTIR is promising for use in detecting blood and semen stains that have become invisible to the naked eye due to washing of the findings.

CONCLUSION

Our approach allows blood and semen to be detected on cotton pieces using FTIR combined with chemometrics, even though it is not visible to the naked eye. Washing chemicals also can be distinguished via FTIR spectra of stains.

Pupal Age Estimation of Sarcophaga peregrina (Diptera: Sarcophagidae) at Different Constant Temperatures Utilizing ATR-FTIR Spectroscopy and Cuticular Hydrocarbons

Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is a forensically important flesh fly that has potential value in estimating the PMImin. The precise pupal age estimation has great implications for PMImin estimation. During larval development, the age determination is straightforward by the morphological changes and variation of length and weight, however, the pupal age estimation is more difficult due to anatomical and morphological changes not being visible. Thus, it is necessary to find new techniques and methods that can be implemented by standard experiments for accurate pupal age estimation. In this study, we first investigated the potential of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and cuticular hydrocarbons (CHCs) for the age estimations of S. peregrina pupae at different constant temperatures (20 °C, 25 °C, and 30 °C). The orthogonal projections latent structure discrimination analysis (OPLS-DA) classification model was used to distinguish the pupae samples of different developmental ages. Then, a multivariate statistical regression model, partial least squares (PLS), was established with the spectroscopic and hydrocarbon data for pupal age estimations. We identified 37 CHCs with a carbon chain length between 11 and 35 in the pupae of S. peregrina. The results of the OPLS-DA model show a significant separation between different developmental ages of pupae (R2X > 0.928, R2Y > 0.899, Q2 > 0.863). The PLS model had a satisfactory prediction with a good fit between the actual and predicted ages of the pupae (R2 > 0.927, RMSECV < 1.268). The results demonstrate that the variation tendencies of spectroscopy and hydrocarbons were time-dependent, and ATR-FTIR and CHCs may be optimal for the age estimations of pupae of forensically important flies with implications for PMImin estimation in forensic practice.

Predicting the Postmortem Interval Based on Gravesoil Microbiome Data and a Random Forest Model

The estimation of a postmortem interval (PMI) is particularly important for forensic investigations. The aim of this study was to assess the succession of bacterial communities associated with the decomposition of mouse cadavers and determine the most important biomarker taxa for estimating PMIs. High-throughput sequencing was used to investigate the bacterial communities of gravesoil samples with different PMIs, and a random forest model was used to identify biomarker taxa. Redundancy analysis was used to determine the significance of environmental factors that were related to bacterial communities. Our data showed that the relative abundance of Proteobacteria, Bacteroidetes and Firmicutes showed an increasing trend during decomposition, but that of Acidobacteria, Actinobacteria and Chloroflexi decreased. At the genus level, Pseudomonas was the most abundant bacterial group, showing a trend similar to that of Proteobacteria. Soil temperature, total nitrogen, NH₄⁺-N and NO₃^--N levels were significantly related to the relative abundance of bacterial communities. Random forest models could predict PMIs with a mean absolute error of 1.27 days within 36 days of decomposition and identified 18 important biomarker taxa, such as Sphingobacterium, Solirubrobacter and Pseudomonas. Our results highlighted that microbiome data combined with machine learning algorithms could provide accurate models for predicting PMIs in forensic science and provide a better understanding of decomposition processes.

Attenuated total reflection-Fourier transform infrared spectroscopy: a universal analytical technique with promising applications in forensic analyses

Contemporary criminal investigations are based on the statements made by the victim and the eyewitnesses. They also rely on the physical evidences found in the crime scene. These evidences, and more particularly biological ones, have a great judicial value in the courtroom. They are usually used to revoke the suspect’s allegations and confirm or refute the statements made by the victim and the witnesses. Stains of body fluids are biological evidences highly sought by forensic investigators. In many criminal cases, the success of the investigation relies on the correct identification and classification of these stains. Therefore, the adoption of reliable and accurate forensic analytical methods seems to be of vital importance to attain this objective. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) is a modern and universal analytical technique capable of fingerprint recognition of the analyte using minimal amount of the test sample. The current systematic review aims to through light on the fundamentals of this technique and to illustrate its wide range of applications in forensic investigations. ATR-FTIR is a nondestructive technique which has demonstrated an exceptional efficiency in detecting, identifying and discriminating between stains of various types of body fluids usually encountered in crime scenes. The ATR-FTIR spectral data generated from bloodstains can be used to deduce a wealth of information related to the donor species, age, gender, and race. These data can also be exploited to discriminate between stains of different types of bloods including menstrual and peripheral bloods. In addition, ATR-FTIR has a great utility in the postmortem investigations. More particularly, in estimating the postmortem interval and diagnosing death caused by extreme weather conditions. It is also useful in diagnosing some ambiguous death causes such as fatal anaphylactic shock and diabetic ketoacidosis.

FT-IR Method Limitations for β-Glucan Analysis

β-glucans are known as biological response modifiers. However, different sources can result in structural differences and as a result differences in their biological activity. The hot water extraction method allows to obtain, high molecular weight β-glucans without altering their structure by using strong chemicals, such as alkalis or acids. Analysis of β-glucans by FT-IR and NMR spectroscopy in solid state is superior to analysis in solution as it allows researchers to study the preserved structure of the extracted polysaccharides. FT-IR spectroscopy was used in this study to make side-by-side comparison analysis of hot water extracted β-glucans from different yeast sources. NMR spectroscopy was used to confirm findings made by FT-IR spectroscopy. Extracted β-glucans exhibit characteristic structure of β-1,3/1,6-linked glucans with noticeable levels of proteins, possibly in a form of oligopeptides, chitin and other impurities. β-glucans obtained from C. guilliermondii, P. pastoris and S. pastorianus exhibited higher protein content. Differences in mannan, chitin and α-glucan content were also observed; however, the species-specific structure of obtained β-glucans could not be confirmed without additional studies. Structural analysis of high molecular weight β-glucans in solid state by FT-IR spectroscopy is difficult or limited due to band intensity changes and overlapping originating from different molecules.

Sustainable approaches for removal of cephalexin antibiotic from non-clinical environments: A critical review

In this article, the removal of cephalexin (CFX) antibiotic from non-clinical environment is reviewed. Adsorption and photocatalytic degradation techniques are widely used to remove CFX from waters and wastewaters, the combination of these methods is becoming more common for CFX removal. The treatment methods of CFX has not been reviewed before, the present article aim is to organize the scattered available information regarding sustainable approaches for CFX removal from non-clinical environment. These include adsorption by nanoparticles, bacterial biomass, biodegradation by bacterial enzymes and the photocatalysis using different catalysts and Photo-Fenton photocatalysis. The metal-organic frameworks (MOFs) appeared to have high potential for CFX degradation. It is evident from the recently papers reviewed that the effective methods could be used in place of commercial activated carbon. The widespread uses of photocatalytic degradation for CFX remediation are strongly recommended due to their engineering applicability, technical feasibility, and high effectiveness. The adsorption capacity of the CFX is ranging from 7 mg CFX g^-1 of activated carbon nanoparticles to 1667 mg CFX g^-1 of Nano-zero-valent iron from Nettle. In contrast, the photo-degradation was 45% using Photo-Fenton while has increased to 100% using heterogeneous photoelectro-Fenton (HPEF) with UVA light using chalcopyrite catalyst.

Efficient removal of diclofenac and cephalexin from aqueous solution using Anthriscus sylvestris-derived activated biochar

The objective of this study was to investigate the adsorption of diclofenac (DF) and cephalexin (CPX) by Anthriscus sylvestris-derived activated biochar. The raw biochar (R-BC) and activated biochar (ACT-B) were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy and elemental analyses techniques to obtain information regarding the morphology, functional groups and elements of the adsorbents. Batch studies were carried out to examine the effect of various operational parameters. The maximum adsorption capacity of ACT-B was 392.94 mg g^-1 for DF and 724.54 mg g^-1 for CPX. The removal of DF and CPX was influenced by temperature and the co-existing ions. The kinetic data fitted well with the pseudo-second-order kinetic model, whereas the isotherm data showed the best correlation with Langmuir isotherm model. Electrostatic adsorption, hydrophobic interaction and π-π bonding play a key role in adsorption of both adsorbates by ACT-B. Additionally, column studies were conducted using ACT-B at different flow rates and different concentrations of DF and CPX to investigate the practical applicability of ACT-B in removal of the target contaminants. Thus, this study provides a feasible approach to synthesize activated biochar that can minimize pharmaceuticals pollution in water bodies.

Predicting postmortem interval based on microbial community sequences and machine learning algorithms

Microbes play an essential role in the decomposition process but were poorly understood in their succession and behaviour. Previous researches have shown that microbes show predictable behaviour that starts at death and changes during the decomposition process. Research of such behaviour enhances the understanding of decomposition and benefits estimating the postmortem interval (PMI) in forensic investigations, which is critical but faces multiple challenges. In this study, we combined microbial community characterization, microbiome sequencing from different organs (i.e. brain, heart and cecum) and machine learning algorithms [random forest (RF), support vector machine (SVM) and artificial neural network (ANN)] to investigate microbial succession pattern during corpse decomposition and estimate PMI in a mouse corpse system. Microbial communities exhibited significant differences between the death point and advanced decay stages. Enterococcus faecalis, Anaerosalibacter bizertensis, Lactobacillus reuteri, and so forth were identified as the most informative species in the decomposition process. Furthermore, the ANN model combined with the postmortem microbial data set from the cecum, which was the best combination among all candidates, yielded a mean absolute error of 1.5 ± 0.8 h within 24-h decomposition and 14.5 ± 4.4 h within 15-day decomposition. This integrated model can serve as a reliable and accurate technology in PMI estimation.

Bulk Nanobubbles or Not Nanobubbles: That is the Question

Bulk nanobubbles are a novel nanoscale bubble system with unusual properties which challenge our understanding of bubble behavior. Because of their extraordinary longevity, their existence is still not widely accepted as they are often attributed to the presence of supramolecular structures or contaminants. Nonetheless, bulk nanobubbles are attracting increasing attention in the literature, but reports generally lack objective evidence that the observed nano-entities are indeed nanobubbles. In this paper, we use various physical and chemical analytical techniques to provide multiple evidence that the nano-entities produced mechanically in pure water by a continuous high-shear rotor-stator device or acoustic cavitation and spontaneously by water-ethanol mixing are indeed gas-filled domains. We estimate that the results presented here combined provide conclusive proof that bulk nanobubbles do exist and they are stable. This paper should help close the debate about the existence of bulk nanobubbles and, hence, enable the scientific community to rather focus on developing the missing fundamental science in this area.

An investigation on annular cartilage samples for post-mortem interval estimation using Fourier transform infrared spectroscopy

Many attempts have been made to estimate the post-mortem interval (PMI) using bioanalytical methods based on multiple biological samples. Cartilage tissues could be used as an alternative for this purpose because their rate of degradation is slower than that of other soft tissue or biofluid samples. In this study, we applied Fourier transform infrared (FTIR) spectroscopy to acquire bioinformation from human annular cartilages within 30 days post-mortem. Principal component analysis (PCA) showed that sex and causes of death have almost no impact on the overall spectral variations caused by post-mortem changes. With pre-processing approaches, several predicted models were established using a conventional machine learning method, known as the partial least square (PLS) regression. The best model achieved a satisfactory prediction with a low error of 1.49 days using the second derivative transform of 3-point smoothing and extended multiplicative scatter correction (EMSC), and the spectral regions from proteins and carbohydrates contributed greatly to the PMI prediction. This study demonstrates the feasibility of cartilage-based FTIR analysis for PMI estimation. Further work will introduce advanced algorithms for more accurate and precise PMI prediction.

Comprehensive quality assessment of Dendrubium officinale using ATR-FTIR spectroscopy combined with random forest and support vector machine regression

Dendrobium officinale, as a tonic herb, has attracted more and more consumers to consume in daily life. In order to protect the wild resource, the herb has made great progress though cultivation in vitro. However, the quality is fluctuated in Chinese herbal medicine market due to influence such as cultivated areas and harvesting period. Therefore, the herbal samples from different cultivated locations were evaluated with high-performance liquid chromatography with diode array detector (HPLC-DAD) in terms of two chemical components, quercetin and erianin. In addition, two markers in leaf and stem also were used for support vector machine regression (SVMR) prediction. Samples from different harvesting periods were also classified using attenuated total reflectance mid-infrared spectroscopy coupled with random forest model. The results indicated that Pu'er and Menghai in Yunnan Province were suitable places for the herb cultivation and the leaf of the herb was also an exploitable resource just in light of the content of two components. What's more, combination of suitable spectra pretreatment and grid search method efficiently improved the prediction performance of the regression model. The results of random forest model indicated that important variables combination between stem and leaf was an effective tool to predict the harvesting time of the herb with 94.44% accuracy in calibration set and 97.92% classification correct rate in validation set. The results of combination were better than the models using individual stem and leaf spectra. In addition, the suitable harvesting time (December) could be classified efficiently. Our study provides a reference for quality control of raw materials from D. officinale herb.

An experimental study on investigating the postmortem interval in dichlorvos poisoned rats by GC/MS-based metabolomics

The estimation of the postmortem interval (PMI) is always a key issue in forensic science. Although many attempts based on metabolomics approaches have been proven to be feasible and accurate for PMI estimation, there have been no reports regarding the determination of the PMI in acute dichlorvos (DDVP) poisoning. In this study, all rats were killed by acute DDVP poisoning at a dose three fold the oral LD₅₀ (240 mg/kg). Gas chromatography-mass spectrometry (GC/MS) was applied to investigate the metabolic profiling of blood samples at various times after death up to 72 h. A total of 39 metabolites were found to be associated with PMI, and the combinations of various numbers of metabolites were used to establish support vector regression (SVR) models to investigate the PMI. The SVR model constructed by 23 metabolites had a minimum mean squared error (MSE) of 5.49 h for the training set. Then, the SVR model was validated by prediction set with an MSE of 10.33 h, suggesting good predictive ability of the model for investigating the PMI. The findings demonstrated the great potential of GC/MS-based metabolomics combined with the SVR model in determining the PMI of DDVP poisoned rats and provided an experimental basis for the application of this approach in investigating the PMI of other toxicants.

Studies on structure property relations of efficient decal substrates for industrial grade membrane electrode assembly development in pemfc

Electrode fabrication and membrane electrode assembly (MEA) processes are critical steps in polymer electrolyte membrane fuel cell (PEMFC) technology. The properties of decal substrate material are important in decal coating technique for efficient transfer of catalyst layer. In the present study, MEAs are fabricated in decal method using 6 different decal substrates among which polypropylene (PP) is found ideal. Morphological, thermal, spectroscopic and sessile drop measurements are conducted for 6 decal substrates to evaluate the thermal and physicochemical properties. Studies indicate PP is thermally stable at hot-press conditions, having optimal hydrophobicity that hinders the coagulation of catalyst ink slurry cast. The pristine PP film has been identified to showcase 100% transfer yield onto the Nafion membrane without contamination and delamination of catalyst layer from membrane. The PP based MEAs are evaluated underconstant current mode in a hydrogen-oxygen fuel cell test fixture. The performance is found to be of 0.6 V at a constant current density of 1.2 A.cm⁻². Besides, the cost of PP-film is only 7.5% of Kapton-film, and hence the current research work enables the high throughput electrode fabrication process for PEMFC commercialization.