Elemental Fingerprints Research Articles

Identifying the Geographical Origin of Tobacco Leaf by Strontium and Lead Isotopic with Mineral Elemental Fingerprint

The primary aim of this paper was to identifying the geographical origin of tobacco leaves based on stable isotopic and mineral elemental fingerprint. We collected eighty-one tobacco leaf samples from Argentina, Brazil, Zimbabwe, the U.S., Zambia, and China. And nine mineral element contents and four strontium and lead isotope ratios of the tobacco leaves were determined by thermal ionization mass spectrometry (TIMS) and inductively coupled plasma mass spectrometry (ICP-MS). After variance and stepwise discriminant analysis, the discriminant functions of the tobacco leaf’s geographical origin were established. The results indicate that: (1) the contents of six mineral elements including Cu, Zn, Cr, Ni, Cd, and Pb, together with four strontium and lead isotope ratios containing 87Sr/86Sr, 208Pb/204Pb, 207Pb/204Pb, and 206Pb/204Pb, were significantly different among six countries. (2) Different countries presented some characteristic mineral elemental and isotopic fingerprint. The even contents of mineral elements from Zambian tobacco leaf were much lower than the other countries, among which four elements consisting of Zn, Cr, As, and Cd were not detected. The three average lead isotope ratios including 208Pb/204Pb, 207Pb/204Pb, and 206Pb/204Pb from Zimbabwe tobacco leaves were far higher than the other countries, and the range of which was unoverlapped. (3) The effective identification of the geographical origin of tobacco leaf was accomplished by Fisher stepwise discriminant analysis and the characteristic tracing elements consisted of Cu, Zn, Cr, Ni, Cd, Pb, 87Sr/86Sr, 207Pb/204Pb, and 206Pb/204Pb. Based on the established discriminant functions, the original and cross-validation accuracy towards different geographical origins of tobacco leaves were 98.8% and 95.1%, respectively. The study shows that the strontium and lead isotopic with mineral elemental fingerprints is a potential effective method to identify the geographical origin of tobacco leaves from different countries.

The Elemental Fingerprints of Different Types of Whisky as Determined by ICP-OES and ICP-MS Techniques in Relation to Their Type, Age, and Origin.

A total of 170 samples of whisky from 11 countries were analysed in terms of their elemental profiles. The levels of 31 elements were determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS): Ag, Al, B, Ba, Be, Bi, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, U, and V, Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) Ca, Fe, K, Mg, P, S, Ti, and Zn and Cold Vapor-Atomic Absorption (CV-AAS): Hg techniques in those alcoholic samples. A comparative analysis of elemental profiles was made on the basis of the content of chosen elements with regard to selected parameters: country of origin, type of whisky (single malt and blended) and age of products. One of the elements which clearly distinguishes single malt and blended types of whisky is copper. Single malt Scotch whisky had a uniform concentration of copper, which is significantly higher for all malt whisky samples when compared with the blended type. Analysis of samples from the USA (n = 26) and Ireland (n = 15) clearly revealed that the objects represented by the same product but originating from independent bottles (e.g., JB, JDG, BUS brands) show common elemental profiles. On the other hand, comparative analysis of Scotch whisky with respect to aging time revealed that the longer the alcohol was aged, (i.e., the longer it stayed in the barrel), the higher the content of Cu and Mn that was recorded.

Application of stable isotopic and mineral elemental fingerprints in identifying the geographical origin of concentrated apple juice in China

Food traceability is an important component of food safety and quality. Currently, there is no authentic established technique to identify the origin of concentrated apple juice (CAJ) in China. In this study, the isotopes of δ13C, δ18O and the contents of 32 elements in CAJ from five production areas (BHB, NWR, SCH, LP and YRAR) were determined. The δ13C, δ18O and 28 elements were significantly different (P < 0.05: post-hoc Duncan’s test) in the five production areas. PCA, PLS-DA and OPLS-DA were employed for regional classification of samples. The results show that ten key variables (Tl, Se, δ18O, B, Mg, Sr, Nd, Mo, As, and Na) are more relevant for discrimination of the samples. These findings contribute to understanding the variations of stable isotopic and element compositions in Chinese CAJ depending on geographic origins and offer valuable insight into the control of fraudulent labeling regarding the geographic origins of CAJ.

High-resolution otolith elemental signatures in eteline snappers from valuable deepwater tropical fisheries.

Marine resources are often shared among countries, with some fish stocks straddling multiple Exclusive Economic Zones, therefore understanding the structure of populations is important for the effective management of fish stocks. Otolith chemical analyses could discriminate among populations based on differences in the chemical composition of otoliths. We used otoliths from two deepwater snappers (flame snapper Etelis coruscans and ruby snapper Etelis boweni) to examine the evidence for population structure across six Pacific Island countries using solution‐based inductively coupled plasma mass spectrometry (ICP‐MS) for otolith core and whole otolith samples and laser ablation ICP‐MS (LA‐ICP‐MS) for core and edge areas of a cross‐sectioned otolith. The inter‐species comparison of these methods is important as the two species are often managed under the same regulations. For both species, the two methods demonstrated separation among the locations sampled with high classification accuracy. Smaller laser ablation spot size gave greater temporal resolution over the life‐history transect. Comparing the early life‐history section of the otoliths (i.e., the core), one interpretation is that young fish experienced more uniform environments in the open ocean as larvae than adults, as the elemental fingerprints had greater overlap among multiple locations. LA‐ICP‐MS methods had some advantages over solution‐based ICP‐MS and generally better discrimination for the trace elements investigated. There were substantial differences between species, but both methods suggested nonmixing populations at the regional scale. Otolith chemistry can be an effective tool in discriminating variation for deepwater marine species in multispecies fisheries, and edge measurements from LA‐ICP‐MS provided the greatest resolution. Although caution should be taken in interpreting the results from relatively small samples sizes, otolith chemical analyses could be useful at these spatial scales to investigate population structure. This information on separate or overlapping populations could be used in future regional fishery management plans.

Stable isotope and trace element analysis for tracing the geographical origin of the Mediterranean mussel (Mytilus galloprovincialis) in food authentication

Determining the geographical origin of seafood is crucial for regulators and fishing industries who seek to prevent commercial fraud, enforce food safety regulations and ensure high standards in sustainable fisheries management. Hence, we have investigated the potential of stable isotope ratio analysis (SIRA) and trace element fingerprinting (TEF), both individually and in combination, to trace the geographical origin of farmed M. galloprovincialis mussels harvested from eight different regions, located in the Mediterranean Sea, the European Atlantic coast and the Chilean Pacific coast. Particularly, carbon and nitrogen isotope ratios of mussel tissue (n = 179) and concentrations of 16 trace elements in shells (n = 100) were measured. Results show that significant differences exist in the chemical signatures of mussels harvested at different locations, and particularly among those belonging to different marine regions. Random forest (RF) classification method based on combined data (n = 64) revealed the best prediction accuracy correctly assigning 97% of individuals to their harvest location. The most relevant elements for provenance discrimination were δ13C, δ15N, Pb, Ba, Mn, and Al. Our results support the possibility for developing a reliable origin assignment tool based on stable isotopes and trace element analyses with global uses in seafood traceability and food safety.

Elemental fingerprints of bivalve shells (Ruditapes decussatus and R. philippinarum) as natural tags to confirm their geographic origin and expose fraudulent trade practices

Bivalves are some of the most valued and consumed seafood species worldwide. However, these organisms can represent a threat to consumers’ health, particularly species harvested from contaminated areas (e.g., historical pollution by heavy or toxins produced by phytoplankton). The elemental composition of bivalve shells generally mirrors the geochemical conditions of the habitat where these organisms have grown. As such, in this study, the geographic origin of two economically important bivalves, the grooved carpet shell ( Ruditapes decussatus ) and Manila clam ( R. philippinarum ), sourced from several locations along the NW, W and SW Iberian coast was confirmed based on the EF of their shells. Overall, random forest analyses of EF (expressed as ratios to Ca) correctly identified the site of harvest of individuals with remarkably high success rate among locations (96.3% for R. decussatus and 98.1% for R. philippinarum ). In general, the most relevant ratios for this discrimination success were the same for both species (i.e., Ba/Ca, Co/Ca, Fe/Ca and Mn/Ca). However, species-specific differences in the EF of shells could also be perceived for specimens of the two bivalve species sampled in the same location. The present findings can allow authorities to expose fraudulent practices associated with the mislabeling of geographic origin of bivalves, namely R. philippinarum , whose harvest in one of the sampled locations (Tagus estuary) is currently forbidden due to public health issues, and develop origin certification for highly valued bivalve species sourced from specific locations (such as R. decussatus from Ria Formosa). • Elemental fingerprints (EF) of bivalve shells ( Ruditapes spp.) differed spatially. • The EF of shells trace the geographic origin of R. decussatus and R. philippinarum . • The EF of shells presented species-specific variations within the same location. • Spatial variations of EF can allow origin certification and expose illegal fishing.

Unravelling the spatial-temporal population structure of Trachurus picturatus across the North-East Atlantic using otolith fingerprinting

The blue jack mackerel Trachurus picturatus is one of the most important pelagic fish captured in the Macaronesian islands of the Azores and Madeira. However, in the last years' landings registered substantial decreases. Fluctuations may be related to oscillations in the cohorts’ recruitment rates, although no information regarding the species movements and connectivity is available. The present study applies laser ablation inductively coupled-plasma mass spectrometry (LA-ICP-MS) to investigate the otolith chemical fingerprints (core and edge) of three cohorts sampled off the Azores, Madeira, Canaries and Peniche (Portuguese coast) in 2013, 2016 and 2019. Otoliths from juveniles (age 0+ and 1+) and adults (age 3+) were examined to infer the scale of geographical variation among fishing grounds and years. Univariate analyses showed significant differences among locations based on Li:Ca, Mg:Ca, Sr:Ca and Ba:Ca concentration ratios. Multi-elemental analyses allocated 70% (2013), 43% (2016) and 43% (2019) of the individuals to their original location based on core elemental fingerprint, and 63% (2013), 75% (2016) and 83% (2019) based on the edge elemental signature. The natal signature suggests that there is some degree of self-recruitment in the fishing grounds and that the subpopulations are connected essentially by dispersal of larvae/juveniles. Furthermore, data suggests that self-recruitment is variable among the cohorts sampled. The discrimination of individuals observed at the time of collection suggests that T. picturatus populations across the north-eastern Atlantic should be regarded as different population units and manage accordingly, as previously observed. Future works should focus on identifying the natal sources of each fishing ground and assess the impact of environmental changes on the distance and direction of larval dispersal.

Geographic origin discrimination of red swamp crayfish Procambarus clarkii from different Chinese regions using mineral element analysis assisted by machine learning techniques

To explore the application prospects of mineral element analysis assisted by machine learning in the geographical origin traceability of red swamp crayfish (Procambarus clarkii) and establish an origin traceability model for it, we used inductively coupled plasma mass spectrometry (ICP-MS) to determine the content of 24 mineral elements, including Cu, Zn, Ga, As, Se, Rb, Sr, and Mo, in red swamp crayfish muscle tissues from Anhui, Hunan, and Hubei provinces of China. The ten characteristic elements, screened by the principal component analysis (PCA), were incorporated into the linear discriminant analysis (LDA) to establish an origin discriminant model of red swamp crayfish. We have verified the feasibility of the mineral element fingerprinting to trace the geographical origin of red swamp crayfish in three regions of China. To improve the discrimination performance, three machine learning classification algorithms, the support vector machine (SVM), the feed-forward neural networks (FNN), and the back-propagation neural network (BPNN), were combined to classify the red swamp crayfish of different origins based on mineral element content. The discriminative accuracy of the training models of both FNN and BPNN reached 100%, and their cross-validation accuracy were 91.88% and 93.13%, respectively, with the area under the receiver operating characteristic (ROC) curve (AUC) values close to 1. Thus, the overall performance of the FNN and BPNN was better than that of SVM. Taken together, our results showed that mineral elements combined with neural networks showed great advantages and potential in geographic origin traceability of red swamp crayfish.

Written in ink: Elemental signatures in octopus ink successfully trace geographical origin

In recent years, validation of seafood authenticity and provenance has attracted the attention of authorities and consumers. Increasing levels of food fraud has raised awareness regarding seafood traceability, especially in highly valuable and highly consumed seafood products, such as the common octopus (Octopus vulgaris). Seafood traceability studies based on trace element fingerprinting generally focus on muscle tissues or carbonate structures whilst the ink fluid has been overlooked. Untargeted multi-element Total Reflection X-ray Fluorescence (TXRF) analysis of O. vulgaris ink successfully discriminated four collection areas [91.2 % and 84.1 % using Variable Importance in Projection Partial Least-Squares Discriminant Analysis (VIP-PLS-DA) and Linear Discriminant Analysis (LDA), respectively] along the mainland Portuguese coast (ca. 900 km coast in the Northeast Atlantic). Arsenic, Pb, Na, Sr and Rb were highlighted as elements with higher contributions for sample discrimination between the four considered capture areas. Regarding food safety, it is important to note that some ink samples Cu, Mn and Pb concentrations exceeded human consumption recommended values. Thus, the results show that untargeted TXRF spectroscopy analysis of O. vulgaris ink is a reliable tool for disentangling the geographical origin of the octopus, as well as to inform about the food safety of octopus ink.

Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food.

Elemental fingerprint coupled with machine learning modelling was proposed for species authentication of the edible animal blood gel (EABG). A total of 25 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectroscopy (AAS) in 150 EABG samples prepared from five species of animals, namely duck, chicken, bovine, pig, and sheep. Extreme learning machine (ELM) models were constructed and optimized. Principal component analysis and Fisher linear discriminant analysis were comparatively utilized for dimension reduction of the crucial input elements selected via stepwise discriminant analysis and one-way ANOVA. The optimal ELM model was obtained with the crucial elements selected by one-way ANOVA from the relative content of the measured elements, which afforded accuracies of 98.0% and 96.0% for the training and test set, respectively. All findings suggest that elemental fingerprint accompanied by ELM have great potential in authenticating the edible animal blood food.

Application of elemental fingerprinting for the authentication of tea: A review

Physicochemical and Phytochemical evaluation of different black tea brandsPradeep Kumar Sharma, Mohammad Ali, Dinesh Kumar Yadav

Keemun black tea: Tracing its narrow-geographic origins using comprehensive elemental fingerprinting and chemometrics

Authentication of food geographic origin improves traceability, quality control, and brand protection. In this study, elemental fingerprints of 27 mineral elements from 104 samples of Keemun black tea from its core (Qimen) and traditional (Dongzhi and Guichi) production regions were analyzed using inductively coupled plasma - mass spectrometry (ICP-MS) coupled with chemometrics to determine the narrow-geographic origin. Variance analysis revealed that Keemun black teas from different regions had their own elemental fingerprints. Although the orthogonal partial least squares-discriminant analysis (OPLS-DA) presented a satisfactory performance, the discrimination of teas based on linear discriminant analysis (LDA) had 100% accuracy and 99% cross-validation, and thus outperformed OPLS-DA. Similarly, support vector machines was able to differentiate 100% of teas from all geographical origins. The results indicate that elemental fingerprints coupled with chemometrics can be used to authenticate the narrow-geographic origins of Keemun black teas. • Keemun black teas from narrow-geographic origins were authenticated. • Chemometrics was used for authentication of narrow-geographic origin. • SVM and LDA were able to differentiate 100% of Keemun black teas. • Rb, Ba, Sr, Cu, Zn, Cd, P, Mn, Mo and Ni were important in the classification.

Elemental fingerprinting of thornback ray (Raja clavata) muscle tissue as a tracer for provenance and food safety assessment

The verification of food authenticity and provenance is a complex task and has raised public concern in recent years due to multiple episodes of food fraud and potential risks to consumers. In this sense, the evaluation of multi-elemental signatures is increasingly applied to confirm and validate the site of origin of animal products. Yet, we lack understanding of its efficacy for mobile organisms such as fish. Using multi-element Total Reflection X-ray Fluorescence (TXRF) analysis of muscle of thornback ray Raja clavata we successfully identified the fishing area of individuals collected in four areas along the Portuguese Atlantic coast (Atlantic Iberian waters, Northeast Atlantic). Overall, As, Fe, Sn, V and Zn presented higher contributions to discrimination (especially Fe and Rb for neighbouring collection areas), whilst the higher concentration elements (Na, K, P, S, Ca, Cl, Br and Sr) had similar concentrations among locations. Rays captured in the two areas with higher urbanization/industrialization presented higher concentration of elements associated with anthropogenic activities (such as As, Zn, Sn and V). In terms of food safety, only 0.9% and 2.8% of the individuals surpassed the recommended thresholds values for human consumption for Hg and Cd respectively. A canonical analysis of principal components resulted in classification accuracy of thornback ray to collection site of 56.7–84.2% (depending on site), with an overall accuracy of 65.1% over c. 500 km of coast in the Northeast Atlantic.

Assessing the variability and discriminatory power of elemental fingerprints in whiteleg shrimp Litopenaeus vannamei from major shrimp production countries

Provenance of seafood items is a concern for consumers and importers alike. Elemental profiling has been put forth as a potential tool to improve seafood traceability. Whiteleg shrimp Litopenaeus vannamei collected from farms in Ecuador, India, Indonesia, Vietnam, and Thailand were classified to country of origin based on element concentrations in muscle tissue. Shrimp were dried, digested, and analyzed via ICP-MS. Out of the 41 elements investigated, 33 are reported as being above detection limits. Twenty-eight elements were statistically different across countries, and of these 28, Ecuador had unique group membership in 7. A random forest classification model utilizing 16 elements had an overall accuracy of 91% of correctly classified samples to country of origin. A canonical discriminant analysis was conducted to understand the variation in the data and identify elements that were important to differentiation in multi-dimension space. Elements identified as important contributors were Al, As, B, Ca, Co, Cs, Sr, and V. This study shows that shrimp from Ecuador tend to be more mineralized than shrimp from Asia, and classification models can discern samples from these countries successfully. This demonstrates the potential of a traceability database for cultured shrimp products from predominant production countries.

Origin verification of Chinese concentrated apple juice using stable isotopic and mineral elemental fingerprints coupled with chemometrics

Verification of the origin of 116 concentrated apple juice (CAJ) samples from three production areas (BHB, SCH and LP) of China was investigated in a trial using stable isotopic (δ13C, δ18O and δD) and the contents of 26 mineral elements. Our aim was to identify and differentiate the geographical origin of these CAJ samples, and more importantly to establish a model that can be used to verify geographical origin of Chinese CAJ samples, as to date there is no such study. Combining with the multivariate statistical analyses including principal component analysis (PCA) and partial least squared-discriminant analysis (PLS-DA), the predictive models were successfully established to discriminate diverse CAJ producing areas with an accuracy rate of 93.2 %. The most important variables to discriminate CAJ of Chinese origin were turned out to be δD, Mg, Tl, δ18O, Mo, Sr, V, As, and δ13C. Therefore, the results of this first exploratory work highlight the possibility of discriminating CAJ of different provenance. This work proposes the use of combined analyses related to stable isotopes and minerals elements as markers for CAJ certification. Our study helps to fill in the gap of origin identification of CAJ in China.

Withdrawal: Chemical characterization of Sicilian dried nopal [Opuntia ficus-indica (L.) Mill.] in relation to the cultivar and pruning season, Giuseppa Di Bella, Giovanna Lo Vecchio, Ambrogina Albergamo, Vincenzo Nava, Giovanni Bartolomeo, Antonio Macrì, Loretta Bacchetta, Vincenzo Lo Turco and Angela Giorgia Potortì.

Sicilian dried nopal (Opuntia ficus-indica L.) was for the first time chemically characterized in relation to the cultivar (i.e., Sanguigna, Surfarina and Muscaredda) and the pruning season (i.e., January-February and June-July 2019). To this purpose, a variety of analytical techniques were employed for elucidating its proximate composition, fatty acid composition, sugars, element fingerprint, and single polyphenols. Sicilian nopal was rich in dietary fiber (44.11-49.55%), inorganic elements -such as Ca (4780.31-5041.47 mg/100g) and K (4899.25-6612.95 mg/100g)- phenolic acids (4.10-5.3 g/Kg) and flavonoids (3.80-4.85 g/Kg), including the characteristic kaempferol-3-O-rutinoside and isorhamnetin-3-O-rutinoside. It was also a good source of carbohydrates, with predominant monosaccharides such as glucose (9.30-12.00 g/100g) and galacturonic acid (6.16-7.90-g/100g) and demonstrated to be low in fat (0.76-2.46%). In particular, its fatty acid composition was characterized by the predominance of short and long chain fatty acids, such as caprylic acid (3.48-7.65%), linoleic (20.81-24.27%) and linolenic acids (11.02-16.83%). Overall, obtained results pointed out that Sicilian dried nopal had a unique (phyto)chemical profile, not comparable to the dried nopal coming from other relevant producer countries (e.g., Mexico and Spain). Its macro- and micronutrients showed to be affected by both cultivar and pruning season, being, however, the influence of the pruning season more pronounced. Such variability should be considered when evaluating the employment of Sicilian nopal in food and nutraceutical areas. This article is protected by copyright. All rights reserved.

Distinguishing Engineered TiO2 Nanomaterials from Natural Ti Nanomaterials in Soil Using spICP-TOFMS and Machine Learning.

Identifying engineered nanomaterials (ENMs) made from earth-abundant elements in soils is difficult because soil also contains natural nanomaterials (NNMs) containing similar elements. Here, machine learning models using elemental fingerprints and mass distributions of three TiO2 ENMs and Ti-based NNMs recovered from three natural soils measured by single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) was used to identify TiO2 ENMs in soil. Synthesized TiO2 ENMs were unassociated with other elements (>98%), while 40% of Ti-based ENM particles recovered from wastewater sludge had distinguishable elemental associations. All Ti-based NNMs extracted from soil had a similar chemical fingerprint despite the soils being from different regions, and >60% of Ti-containing NNMs had no measurable associated elements. A machine learning model best distinguished NNMs and ENMs when differences in Ti-mass distribution existed between them. A trained LR model could classify 100 nm TiO2 ENMs at concentrations of 150 mg kg-1 or greater. The presence of TiO2 ENMs in soil could be confirmed using this approach for most ENM-soil combinations, but the absence of a unique chemical fingerprint in a large fraction of both TiO2 ENMs and Ti-NNMs increases model uncertainty and hinders accurate quantification.

Stable Isotope and Element Profiling for Determining the Agroclimatic Origin of Cow Milk within a Tropical Country.

Information on the geographic origin of milk is important in determining quality attributes and for economic gain through building brand value associated with origin. Stable isotope signatures and trace element concentrations have been increasingly used in authentication of milk, though information on the power of such technology in verifying agroclimatic origin in small continents with diverse climatic, environmental conditions, and animal management practice is scarce. Therefore, the main objective of this study was to investigate the possibility of using a stable isotope composition of C, N, O, and H and element fingerprints to determine the agroclimatic origin of milk produced in different agroclimatic zones of Sri Lanka. Stable isotopes ratios of C, N, H, and O, and elemental fingerprints of milk samples were determined by IRMS and ICP-MS, respectively. Significant variations were observed in stable isotope ratios, especially δ18O and the mean content of Li, Al, Cr, Mn, and Sr in the bulk milk samples obtained from different agroclimatic zones. A linear discriminant analysis differentiated cow milk produced from four agroclimatic zones based on stable isotope ratios, and the inclusion of elemental ratios enhanced the discriminating ability.

Fingerprints of Element Concentrations in Infective Endocarditis Obtained by Mass Spectrometric Imaging and t-Distributed Stochastic Neighbor Embedding.

Staphylococcus aureus-induced infective endocarditis (IE) is a life-threatening disease. Differences in virulence between distinct S. aureus strains, which are partly based on the molecular mechanisms during bacterial adhesion, are not fully understood. Yet, distinct molecular or elemental patterns, occurring during specific steps in the adhesion process, may help to identify novel targets for accelerated diagnosis or improved treatment. Here, we use laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of post-mortem tissue slices of an established mouse model of IE to obtain fingerprints of element distributions in infected aortic valve tissue. Three S. aureus strains with different virulence due to deficiency in distinct adhesion molecules (fibronectin-binding protein A and staphylococcal protein A) were used to assess strain-specific patterns. Data analysis was performed by t-distributed stochastic neighbor embedding (t-SNE) of mass spectrometry imaging data, using manual reference tissue classification in histological specimens. This procedure allowed for obtaining distinct element patterns in infected tissue for all three bacterial strains and for comparing those to patterns observed in healthy mice or after sterile inflammation of the valve. In tissue from infected mice, increased concentrations of calcium, zinc, and magnesium were observed compared to noninfected mice. Between S. aureus strains, pronounced variations were observed for manganese. The presented approach is sensitive for detection of S. aureus infection. For strain-specific tissue characterization, however, further improvements such as establishing a database with elemental fingerprints may be required.

A Preliminary Study of Geographic Traceability of Soil Physical Evidence: Machine Learning Recognition of Elemental Fingerprints and Morphological Features

A Preliminary Study of Geographic Traceability of Soil Physical Evidence: Machine Learning Recognition of Elemental Fingerprints and Morphological Features