Unveiling Morphine: A Rapid and Selective Fluorescence Sensor for Forensic and Medical Analysis.

Opioid use, particularly morphine, is linked to CNS-related disorders, comorbidities, and premature death. Morphine, a widely abused opioid, poses a significant global health threat and serves as a key metabolite in various opioids. Here, we present a turn-off fluorescent sensor capable of detecting morphine with exceptional sensitivity and speed in various samples. The fluorescent sensor was developed through the dimerization process of 7-methoxy-1-tetralone and subsequent demethylation to produce the final product. Despite morphine possessing inherent fluorophoric properties and emitting light in an approximately similar wavelength as the sensor's fluorescent blue light, the introduction of the target molecule (morphine) in the presence of the sensor caused a reduction in the sensor's fluorescence intensity, which is attributable to the formation of the sensor-morphine complex. By utilizing this fluorescence quenching sensor, the chemo-selective detection of morphine becomes highly feasible, encompassing a linear range from 0.008 to 40 ppm with an impressive limit of detection of 8 ppb. Consequently, this molecular probe demonstrates a successful application in determining trace amounts of morphine within urine, yielding satisfactory analytical results. The study also explores the effect of several variables on the sensor's response and optimizes the detection of morphine in urine using a response surface methodology with a central composite design.

Assessment of Blood and Semen Detection and DNA Collection from Swabs up to Three Months after Deposition on Five Different Cloth Materials.

Body fluid identification plays a crucial role in criminal investigations. Because of their presence in many cases, blood and semen are the most relevant body fluids in forensic sciences. Based on antigen-antibody reactions binding unique proteins for each body fluid, serological assays represent one of the most rapid and highly specific tests for blood and semen. Currently, few studies have assessed the factors affecting body fluid identification by applying these assays. This work aimed to study the effect of different fabrics from clothes and time since deposition on identification through immunochromatographic tests for blood and semen, DNA isolation, and STR profiling from these samples. Body fluids were deposited on black- and white-dyed denim and cotton fabrics, and on leather. Afterward, blood and semen were sampled at 1 day, 30 days, and 90 days after deposition and identified by using the SERATEC® HemDirect Hemoglobin Test and the PSA Semiquant and SERATEC® BLOOD CS and SEMEN CS tests, respectively. Laboratory and crime scene tests presented similar performances for the detection of blood and semen stains on every tested fabric. No differences were found on band intensities between timepoints for all fabrics. It was possible to recover and identify blood and semen samples up to three months after deposition and to obtain full STR profiles from all the tested fabrics. Both body fluid STR profiles showed differences in their quality between 1 and 90 days after deposition for all fabrics except for black cotton for semen samples. Future research will expand the results, assessing body fluid identification on other substrates and under different environmental conditions.

Body fluid contamination in the context of an adverse analytical finding in doping: About a case involving ostarine.

Ostarine, also known as MK-2866 or enobosarm, is a selective androgen receptor modulator (SARM). It has anabolic properties and as such is widely used in doping, accounting in 2021 for 25 % of the adverse analytical findings (AAF) among the class S1.2 "Other anabolic agents" of products banned by the World Anti-Doping Agency, to which it belongs. But in some cases, it can be responsible for an AAF following contamination. We report the case of an athlete who contaminated herself by exchanging body fluids while kissing her boyfriend, who took 25 mg per day of MK-2866 for 9 days prior to the athlete's AAF (urinary concentration evaluated at 13 ng/mL) without her knowledge. Both subjects came to our lab for hair testing. The athlete's hair was black and slightly frizzy. Six segments of 2 cm then 7 × 3 cm (33 cm) were analysed and showed increasing concentrations, from 2 pg/mg on the first segment to 17.8 pg/mg on the last segment. The boyfriend's hair, light-brown, analyzed on 4 × 2 cm, also showed increasing values, from 65 to 143 pg/mg. These gradients of concentration in the hair's athlete and in her boyfriend were compatible with external contamination of the hair, confirmed by analysis of washing baths, pillowcases (150 pg on each), and the athlete's hairbrush (250 pg). Fingernails were also contaminated, with 21 pg/mg in the athlete and 1041 pg/mg in the boyfriend, with highly contaminated washing baths, and toenails were less contaminated, with 2 pg/mg in the athlete and 17.3 pg/mg in the boyfriend. Urine samples taken 35 days after the start of MK-2866 treatment showed a value of 3690 ng/mL in the boyfriend and 5.7 ng/mL in the athlete. After 6 days off, these concentrations were 3.3 ng/mL and 0.1 ng/mL, respectively. A controlled transfer study was carried out 12 days after discontinuation (urine concentrations returned to negative level). After administration of 17 mg (the 25 mg/mL vial having been controlled at 17 mg/mL), urine samples were taken from the boyfriend and the athlete (n = 10 for each) for more than 25 h after they had been living normally with each other (regular kissing in particular). The boyfriend's urine concentrations ranged from 681 ng/mL to 12822 ng/mL (Tmax = 8:30 hrs), and the athlete's from 0.3 ng/mL to 13 ng/mL with Tmax = 8:30 hrs, i.e. at 22:30 hrs, which corresponded exactly to the time of collection of the urine that showed AAF, with a similar concentration. The dose ingested by the athlete was estimated at 15 µg. These results demonstrate the transfer of ostarine via body fluids between two subjects, with a high risk of AAF in one athlete, as observed in our case.

Mass spectrometry-based proteomic analysis of biological stains identifies body fluids specific markers.

The identification of biological stains and their tissue resource is an important part of forensic research. Current methods suffer from several limitations including poor sensitivity and specificity, trace samples, and sample destruction. In this study, we profiled the proteomes of menstrual blood, peripheral blood, saliva, semen, and vaginal fluid with mass spectrometry technology. Tissue-enhanced and tissue-specific proteins of each group have been proposed as potential biomarkers. These candidate proteins were further annotated and screened through the combination with the Human Protein Atlas database. Our data not only validates the protein biomarkers reported in previous studies but also identifies novel candidate biomarkers for human body fluids. These candidates lay the foundation for the development of rapid and specific forensic examination methods.

A portable EIS-based biosensor for the detection of microcystin-LR residues in environmental water bodies and simulated body fluids.

Due to the eutrophication of water bodies around the world, there is a drastic increase in harmful cyanobacterial blooms leading to contamination of water bodies with cyanotoxins. Chronic exposure to cyanotoxins such as microcystin leads to oxidative stress, inflammation, and liver damage, and potentially to liver cancer. We developed a novel and easy-to-use electrochemical impedance spectroscopy-based immunosensor by fabricating stencil-printed conductive carbon-based interdigitated microelectrodes and immobilising them with cysteamine-capped gold nanoparticles embedded in polyaniline. It has been also coupled with a custom handheld device enabling regular on-site assessment, especially in resource-constrained situations encountered in developing countries. The sensor is able to detect microcystin-LR up to 0.1 µg L-1, having a linear response between 0.1 and 100 µg L-1 in lake and river water and in serum and urine samples. In addition to being inexpensive, easy to fabricate, and sensitive, it also has very good selectivity.

Metabolic insights at the finish line: deciphering physiological changes in ultramarathon runners through breath VOC analysis.

Exhaustive exercise can induce unique physiological responses in the lungs and other parts of the human body. The volatile organic compounds (VOCs) in exhaled breath are ideal for studying the effects of exhaustive exercise on the lungs due to the proximity of the breath matrix to the respiratory tract. As breath VOCs can originate from the bloodstream, changes in abundance should also indicate broader physiological effects of exhaustive exercise on the body. Currently, there is limited published data on the effects of exhaustive exercise on breath VOCs. Breath has great potential for biomarker analysis as it can be collected non-invasively, and capture real-time metabolic changes to better understand the effects of exhaustive exercise. In this study, we collected breath samples from a small group of elite runners participating in the 2019 Ultra-Trail du Mont Blanc ultra-marathon. The final analysis included matched paired samples collected before and after the race from 24 subjects. All 48 samples were analyzed using the Breath Biopsy Platform with GC-Orbitrap™ via thermal desorption gas chromatography-mass spectrometry. The Wilcoxon signed-rank test was used to determine whether VOC abundances differed between pre- and post-race breath samples (adjustedP-value < .05). We identified a total of 793 VOCs in the breath samples of elite runners. Of these, 63 showed significant differences between pre- and post-race samples after correction for multiple testing (12 decreased, 51 increased). The specific VOCs identified suggest the involvement of fatty acid oxidation, inflammation, and possible altered gut microbiome activity in response to exhaustive exercise. This study demonstrates significant changes in VOC abundance resulting from exhaustive exercise. Further investigation of VOC changes along with other physiological measurements can help improve our understanding of the effect of exhaustive exercise on the body and subsequent differences in VOCs in exhaled breath.

Automated 2D peak detection in gas chromatography-ion mobility spectrometry through persistent homology.

BACKGROUND: Gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful analytical technique which has gained widespread use in a variety of fields. Detecting peaks in GC-IMS data is essential for chemical identification. Topological data analysis (TDA) has the ability to record alterations in topology throughout the entire spectrum of GC-IMS data and retain this data in diagrams known as persistence diagrams. To put it differently, TDA naturally identifies characteristics such as mountains, volcanoes, and their higher-dimensional equivalents within the original data and measures their significance. RESULTS: In the present contribution, a novel approach based on persistent homology (a flagship technique of TDA) is suggested for automatic 2D peak detection in GC-IMS. For this purpose, two different GC-IMS data examples (urine and olive oil) are used to show the performance of the proposed method. The outputs of the algorithm are GC-IMS chromatogram with detected peaks, persistence plot showing the importance (intensity) of the detected peaks and a table with retention times (RT), drift times (DT), and persistence scores of detected peaks. The RT and DT can be used for identification of the peaks and persistence scores for quantitation. Additionally, watershed segmentation is applied to the GC-IMS images to index individual peaks and segment overlapping compounds allowing for a more accurate identification and quantification of individual peaks. SIGNIFICANCE: Inspection of the results for GC-IMS datasets showed the accurate and reliable performance of the proposed strategy based on persistent homology for automatic 2D GC-IMS peak detection for qualitative and quantitative analysis. In addition, this approach can be easily extended to other types of hyphenated chromatographic and/or spectroscopic data.

The optimization and comparison of two high-throughput faecal headspace sampling platforms: the microchamber/thermal extractor and hi-capacity sorptive extraction probes (HiSorb).

Disease detection and monitoring using volatile organic compounds (VOCs) is becoming increasingly popular. For a variety of (gastrointestinal) diseases the microbiome should be considered. As its output is to large extent volatile, faecal volatilomics carries great potential. One technical limitation is that current faecal headspace analysis requires specialized instrumentation which is costly and typically does not work in harmony with thermal desorption units often utilized in e.g. exhaled breath studies. This lack of harmonization hinders uptake of such analyses by the Volatilomics community. Therefore, this study optimized and compared two recently harmonized faecal headspace sampling platforms:High-capacity Sorptive extraction (HiSorb) probesand theMicrochamber thermal extractor (Microchamber). Statistical design of experiment was applied to find optimal sampling conditions by maximizing reproducibility, the number of VOCs detected, and between subject variation. To foster general applicability those factors were defined using semi-targeted as well as untargeted metabolic profiles. HiSorb probes were found to result in a faster sampling procedure, higher number of detected VOCs, and higher stability. The headspace collection using the Microchamber resulted in a lower number of detected VOCs, longer sampling times and decreased stability despite a smaller number of interfering VOCs and no background signals. Based on the observed profiles, recommendations are provided on pre-processing and study design when using either one of both platforms. Both can be used to perform faecal headspace collection, but altogether HiSorb is recommended.

Combining Thermal Desorption with Selected Ion Flow Tube Mass Spectrometry for Analyses of Breath Volatile Organic Compounds.

An instrument integrating thermal desorption (TD) to selected ion flow tube mass spectrometry (SIFT-MS) is presented, and its application to analyze volatile organic compounds (VOCs) in human breath is demonstrated for the first time. The rationale behind this development is the need to analyze breath samples in large-scale multicenter clinical projects involving thousands of patients recruited in different hospitals. Following adapted guidelines for validating analytical techniques, we developed and validated a targeted analytical method for 21 compounds of diverse chemical class, chosen for their clinical and biological relevance. Validation has been carried out by two independent laboratories, using calibration standards and real breath samples from healthy volunteers. The merging of SIFT-MS and TD integrates the rapid analytical capabilities of SIFT-MS with the capacity to collect breath samples across multiple hospitals. Thanks to these features, the novel instrument has the potential to be easily employed in clinical practice.

Predicting nitrogen excretion of cattle kept under tropical and subtropical conditions using semimechanistic models.

The present study aims at evaluating whether current semimechanistic models developed for temperate cattle systems can be adopted for cattle under (sub-) tropical husbandry systems to adequately (accurately and precisely) predict total nitrogen (TN), urine nitrogen (UN), faecal nitrogen (FN) excretion and its partition into different FN fractions. Selected models were built based on the feeding recommendations for ruminants of the British (Model A), German (Model G) and French (INRA; Model I) system. Model evaluation was conducted using eight nitrogen balance studies performed in El Salvador, Kenya and Peru (n = 392 individual observations including lactating cows, heifers and steers). Concordance correlation coefficient, root mean square errors (RMSE), and mean biases were estimated to evaluate the models' adequacy in predicting nitrogen excretion. Input variables causing greatest variation in nitrogen excretion prediction were identified by a sensitivity analysis and adjusted. Model G was able to adequately (i.e., RMSE of <25% of observed mean, systematic error of <5% of the mean square error) predict TN excretion through a compensation between overestimation of UN excretion and underestimation of FN excretion. None of the models were able to adequately predict UN, FN, and different FN fractions. Model I adequately predicted FN (RMSE = 18%) when duodenal microbial crude protein flow was increased, and the intercept used to predict FN excretion was reduced from 4.30 to 3.82 g of nitrogen per kilogram of dry matter intake. These adjustments, however, were not sufficient to predict adequately UN excretion (RMSE = 38%), individual FN fractions (RMSE > 56%), and TN (RMSE = 22%) excretion, by Model I.

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.

Simple and rapid detection of three amatoxins and three phallotoxins in human body fluids by UPLC-MS-MS and its application in 15 poisoning cases.

Amatoxins and phallotoxins are toxic cyclopeptides found in the genus Amanita and are among the predominant causes of foodborne sickness and poisoning-related fatalities in China. This study introduces and validates a simple, rapid and cost-effective ultra-performance liquid chromatography-mass spectrometry method for the simultaneous determination and quantification of α-amanitin, ß-amanitin, γ-amanitin, phallisacin, phallacidin and phalloidin in human blood and urine. Quick therapeutic decision-making is supported by a 9 min chromatographic separation performed on a Waters Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 µm) using a gradient of high-performance liquid chromatography (HPLC)-grade water and methanol:0.005% formic acid. The analyte limit of quantification was 1-3 ng/mL in blood and 0.5-2 ng/mL in urine. Calibrations curves, prepared by spiking drug-free blood and urine, demonstrated acceptable linearity with mean correlation coefficients (r) greater than 0.99 for all phallotoxins and amatoxins. Acceptable intraday and interday precision (relative standard deviation <15%) and accuracy (bias, -4.8% to 13.0% for blood and-9.0% to 14.7% for urine) were achieved. The validated method was successfully applied to analyze 9 blood samples and 2 urine samples testing positive for amatoxins and/or phallotoxins. Amatoxins and/or phallotoxins were identified in each whole blood sample at a range of 1.12-5.63 ng/mL and in two urine samples from 1.01-9.27 ng/mL. The method has the benefits of simple sample preparation (protein precipitation) and wide analyte coverage, making it suitable for emergency quantitative surveillance toxicological analysis in clinics and forensic poisoning practice.

Does Aggregation of Therapeutic IgGs in PBS Offer a True Picture of What Happens in Models Derived from Human Body Fluids?

Therapeutic proteins such as monoclonal antibodies (mAb) are known to form aggregates due to various factors. Phosphate buffered saline (PBS), human serum, and human serum filtrate (HSF) are some of the models used to analyze mAb stability in physiologically relevant in-vitro conditions. In this study, aggregation of mAb in PBS and models derived from body fluids seeded with mAb samples subjected to various stresses were compared. Samples containing mAb subjected to pH, temperature, UV light, stirring, and interfacial agitation stress were seeded into different models for 2 case studies. In the first case study, %HMW (high molecular weight species) of mAb in PBS and HSF were compared using size exclusion chromatography. It was found that change in %HMW was higher in PBS compared to HSF. For example, PBS containing mAb that was subjected to UV light stress showed change in HMW by >10 % over 72 h, but the change was <5 % in HSF. In second case study, aggregates particles of FITC tagged mAb were monitored in PBS and serum using fluorescence microscope image processing. It was found that PBS and serum containing mAb subjected to stirring and interfacial agitation resulted in aggregates of >2 µm size, and average size and percentage number of particles having >10 µm size was higher in serum compared to PBS at all analysis time point. Overall, it was found that aggregation of mAb in PBS was different from that in human body fluids. Second case study also showed the importance of advanced strategies for further characterization of mAb in serum.

Predicting methane emissions of individual grazing dairy cows from spectral analyses of their milk samples.

Data on the enteric methane emissions of individual cows are useful not just in assisting management decisions and calculating herd inventories but also as inputs for animal genetic evaluations. Data generation for many animal characteristics, including enteric methane emissions, can be expensive and time consuming, so being able to extract as much information as possible from available samples or data sources is worthy of investigation. The objective of the present study was to attempt to predict individual cow methane emissions from the information contained within milk samples, specifically the spectrum of light transmittance across different wavelengths of the mid-infrared (MIR) region of the electromagnetic spectrum. A total of 93,888 individual spot measures of methane (i.e., individual samples of an animal's breath when using the GreenFeed technology) from 384 lactations on 277 grazing dairy cows were collapsed into weekly averages expressed as grams per day; each weekly average coincided with a MIR spectral analysis of a morning or evening individual cow milk sample. Associations between the spectra and enteric methane measures were performed separately using partial least squares regression or neural networks with different tuning parameters evaluated. Several alternative definitions of the enteric methane phenotype (i.e., average enteric methane in the 6 d preceding or 6 d following taking the milk sample or the average of the 6 d before and after the milk sample, all of which also included the enteric methane emitted on the day of milk sampling), the candidate model features (e.g., milk yield, milk composition, and milk MIR) as well as validation strategy (i.e., cross-validation or leave-one-experimental treatment-out) were evaluated. Irrespective of the validation method, the prediction accuracy was best when the average of the milk MIR from the morning and evening milk sample was used and the prediction model was developed using neural networks; concurrently including milk yield and days in milk in the prediction model generated superior predictions relative to just the spectral information alone. Furthermore, prediction accuracy was best when the enteric methane phenotype was the average of at least 20 methane spot measures across a 6-d period flanking each side of the milk sample with associated spectral data. Based on the strategy that achieved the best accuracy of prediction, the correlation between the actual and predicted daily methane emissions when based on 4-fold cross-validation varied per validation stratum from 0.68 to 0.75; the corresponding range when validated on each of the 8 different experimental treatments focusing on alternative pasture grazing systems represented in the dataset varied from 0.55 to 0.71. The root mean square error of prediction across the 4-folds of cross-validation was 37.46 g/d, whereas the root mean square error averaged across all folds of leave-one-treatment-out was 37.50 g/d. Results suggest that even with the likely measurement errors contained within the MIR spectrum and gold standard enteric methane phenotype, enteric methane can be reasonably well predicted from the infrared spectrum of milk samples. What is yet to be established, however, is whether (a) genetic variation exists in this predicted enteric methane phenotype and (b) selection on estimates of genetic merit for this phenotype translate to actual phenotypic differences in enteric methane emissions.

Sample Matrices for Mass Spectrometry-Based Adherence Monitoring: A Systematic Critical Review.

BACKGROUND: Analytical monitoring of adherence using mass spectrometry (MS) plays an important role in clinical toxicology. Unambiguous detection of drugs (of abuse) and/or their metabolites in body fluids is needed to monitor intake of medication as prescribed or to monitor abstinence as a follow-up to detoxification procedures. This study focused on the advantages and disadvantages of different sample matrices used for MS-based adherence monitoring. METHODS: Relevant articles were identified through a literature search in the PubMed database. English articles published between January 01, 2017, and December 31, 2022, were selected using the keywords "adherence assess*" or "adherence monit*" or "compliance assess*" or "compliance monit*" in combination with "mass spectrom*" in the title or abstract. RESULTS: A total of 51 articles were identified, 37 of which were within the scope of this study. MS-based monitoring was shown to improve patient adherence to prescribed drugs. However, MS analysis may not be able to assess whether treatment was rigorously followed beyond the last few days before the sampling event, except when hair is the sample matrix. For medication adherence monitoring, blood-based analyses may be preferred because reference plasma concentrations are usually available, whereas for abstinence control, urine and hair samples have the advantage of extended detection windows compared with blood. Alternative sample matrices, such as dried blood samples, oral fluid, and exhaled breath, are suitable for at-home sampling; however, little information is available regarding the pharmacokinetics and reference ranges of drug (of abuse) concentrations. CONCLUSIONS: Each sample matrix has strengths and weaknesses, and no single sample matrix can be considered the gold standard for monitoring adherence. It is important to have sufficient information regarding the pharmacokinetics of target substances to select a sample matrix in accordance with the desired purpose.

A combined molecular approach utilizing microbial DNA and microRNAs in a qPCR multiplex for the classification of five forensically relevant body fluids.

Body fluid identification is an essential step in the forensic biology workflow that can assist DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the specificity that molecular techniques can achieve; therefore, molecular methods, including microRNA (miRNA) and microbial signature characterization, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase the discrimination efficiency of multiple body fluids from a single assay. While microbial signatures have been successful in identifying fluids with high bacterial abundances, microRNAs have shown promise in fluids with low microbial abundance (blood and semen). This project synergized the benefits of microRNAs and microbial DNA to identify multiple body fluids using DNA extracts. A reverse transcription (RT)-qPCR duplex targeting miR-891a and let-7g was validated, and miR-891a differential expression was significantly different between blood and semen. The miRNA duplex was incorporated into a previously reported qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius to presumptively identify vaginal/menstrual secretions, feces, and saliva, respectively. The combined classification regression tree model resulted in the presumptive classification of five body fluids with 94.6% overall accuracy, now including blood and semen identification. These results provide proof of concept that microRNAs and microbial DNA can classify multiple body fluids simultaneously at the quantification step of the current forensic DNA workflow.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

How the physicochemical substrate properties can influence the deposition of blood and seminal deposits.

A comprehensive investigation into the impact of the physical and chemical variables of a substrate on the deposition was conducted to aid in the estimation of the subsequent transfer probabilities of blood and semen. The study focussed on surface roughness, topography, surface free energy (SFE), wettability, and the capacity for protein adsorption. Conjointly, evaluations of the physical and chemical characteristics of blood and seminal deposits were conducted, to assess the fluid dynamics of these non-Newtonian fluids and their adhesion potential to aluminium and polypropylene. A linear range of surface roughness parameters (0.5 - 3.5 µm) were assessed for their impact on the deposit deposition spread and adhesion height, to gather insight into the change in fluid dynamics of non-Newtonian fluids. Blood has shown to produce a uniform adhesion coverage on aluminium across all roughness categories while blood deposited on polypropylene exhibited a strong hydrophobic response from a surface roughness of 2.0 µm and beyond. Interestingly, the deposition height of blood resulted in near identical values, whether deposited onto the hydrophobic polypropylene or the hydrophilic aluminium substrate, illustrating the potential influence of a heightened fibrinogen adsorption effect. Semen deposited on aluminium resulted in concentrated localised deposition regions after reaching a surface roughness of 2.0 µm, highlighting the development of crystal formations afforded by the sodium ion concentration in the seminal fluid. The semen deposited on polypropylene conformed to the substrate contours producing a deposition film that was smoother than the substrate itself, underlining the effects of thixotropic fluid dynamics. Variables identified here establish the complexity observed for non-Newtonian fluids, and the effect protein adsorption may have on the deposition behaviour of blood and seminal deposits and inform questions in relation to the adhesion strength of said deposits and their ability to dislodge (becoming detached upon the application of an external force) from the substrate surface during a potential transfer event.

Electro-oxidation and UV irradiation coupled method for in-site removing pollutants from human body fluids in swimming pool.

A comprehensive study was conducted to investigate how ultraviolet (UV) irradiation combined with electrochemistry (EC) can efficiently remove human body fluids (HBFs) related pollutants, such as urea/creatinine/hippuric acid, from swimming pool water (SPW). In comparison with the chlorination, UV, EC, and UV/chlorine treatments, the EC/UV treatment exhibited the highest removal rates for these typical pollutants (TPs) from HBFs in synthetic SPW. Specifically, increasing the operating current of the EC/UV process from 20 to 60 mA, as well as NaCl content from 0.5 to 3.0 g/L, improved urea and creatinine degradation while having no influence on hippuric acid. In contrast, EC/UV process was resilient to changes in water parameters (pH, HCO3-, and actual water matrix). Urea removal was primarily attributable to reactive chlorine species (RCS), whereas creatinine and hippuric acid removal were primarily related to hydroxyl radical, UV photolysis, and RCS. In addition, the EC/UV procedure can lessen the propensity for creatinine and hippuric acid to generate disinfection by-products. We can therefore draw the conclusion that the EC/UV process is a green and efficient in-situ technology for removing HBFs related TPs from SPW with the benefits of needless chlorine-based chemical additive, easy operation, continuous disinfection efficiency, and fewer byproducts production.

Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood.

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.