High-resolution Mass Spectrometry Research Articles

A pilot study on post-mortem determination of drug abuse on dental tissues

BackgroundPost-mortem toxicology constantly deals with the research of reliable alternative matrices to be applied in case of highly damaged corpses (such us carbonized, skeletonized, human remains, etc.). Teeth represent a promising alternative matrix since dental tissues are endowed by different features, resistance and stability after death. ScopeSince scant literature reported on the pharmacokinetics and mechanism of incorporation of xenobiotics into dental tissues, this pilot research aims to investigate whether in the pulp can be detected the same substances found in blood in drug related death cases. Secondly, the study is addressed to disclose the possible deposit of drugs in dental hard tissues (dentine and/or enamel), thus contributing to reconstruct the drug abuse history (timing, e.g.). Materials and MethodsThe study experimented with a novel method to separately analyse dental enamel, dentin, and pulp, applied to 10 teeth collected during autopsies of drug-related deaths along with blood and hair samples for classic toxicological analyses. Each tooth was prepared by “pulverization technique” and then analysed by gas chromatography paired with mass spectrometry (GC-MS) and ultra high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC/HR-MS) for searching cocaine, opiates, and metabolites. The results were then compared with those obtained from blood and hair samples. ResultsPreliminary results demonstrated that teeth differ from any other classic matrix (blood and hairs) since the qualitative correspondence of the detected substances between pulp and blood as well as dental hard tissues and hair suggests that they can be useful in post-mortem evaluation as a unique matrix for both acute and chronic assumptions of drugs. The mechanism of accumulation of substances in mineralized dental tissues emerged the most significant result, being influenced by the type of molecule and the method of assumption. The main limitation of this study is the limited availability of the sample and the absence of anamnestic information of the time, rates and method of drug assumption during life. Further research is necessary to systematically investigate the distribution of different substances within the different tissues of the tooth.

Targeted screening and profiling of massive components of colistimethate sodium by two-dimensional-liquid chromatography-mass spectrometry based on self-constructed compound database

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometric (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with 6 known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Mechanism and rational combinations with GP-2250, a novel oxathiazine derivative, in ovarian cancer.

GP-2250, a novel analog of taurultam (TRLT), has emerged as a potent anti-neoplastic drug; however, the mechanisms underlying its effects are not well understood. Here, we investigated the mechanism of action and the biological effects of GP-2250 using invitro and invivo models. We carried out a series of invitro (MTT assay, Annexin V/PI assay, colony formation assay, reverse-phase protein array [RPPA], and HRLC/IC analysis) to determine the biological activity of GP-2250 and investigate the mechanism of action. Invivo experiments were carried out to determine the therapeutic efficacy of GP-2250 alone and in combination with standard-of-care drugs (e.g., paclitaxel, cisplatin, topotecan, and poly ADP-ribose polymerase [PARP] inhibitors). We investigated the cytotoxic effect of GP-2250 in 10 ovarian cancer cell lines and found GP-2250 combined with a PARP inhibitor had the greatest synergy. RPPA revealed that GP-2250 inhibited hypoxia-inducible factor-1α, AKT, and mammalian target of rapamycin (mTOR) activation and expression. High-resolution mass spectrometry revealed that hexokinase2 activity and protein expression were significantly reduced by GP-2250 exposure. Furthermore, GP-2250 reduced glycolysis and ATP synthesis in cancer cells. An invivo pharmacodynamic experiment using the OVCAR8 mouse model demonstrated that 500 mg/kg GP-2250 was effective in downregulating AKT and mTOR activation and expression. In the invivo therapy experiment using an orthotopic mouse model, a combination of GP-2250 with either PARP inhibitors or bevacizumab showed a significant reduction of tumor weights and nodules compared to those treated with a vehicle, control IgG groups, or monotherapy groups. Taken together, our data indicate that GP-2250 exerts profound effects on tumor metabolism and, in combination with PARP inhibitors or bevacizumab, showed promising anti-tumor efficacy. These findings could have implications for the clinical development of GP-2250.

Structural characterization of nitazene analogs using electron ionization-mass spectrometry (EI-MS)

Nitazene analogs are among the most recent and potent additions to the novel synthetic opioid (NSO) market, and new analogs continue to emerge. Seized drug analysis commonly utilizes gas chromatography-electron ionization-mass spectrometry (GC-EI-MS), so it is therefore imperative to understand how nitazene analogs behave under EI-MS conditions, and how substitution at various sites on the molecule may impact the resulting EI mass spectra. This study characterizes the EI fragmentation behavior of 20 representative nitazene analogs that contain differing substitutions and proposes rational mechanisms to explain the observed behavior.A general EI fragmentation pathway for nitazene analogs was proposed, with the most common nitazene fragment ions being observed at m/z 86, m/z 107, m/z 58, and m/z 77. Characteristic ions were determined for different substitution groups, enabling the identification of diethyl, desethyl, pyrrolidine, and piperidine substitutions at the amine moiety, and different alkoxy chain lengths at the aromatic ring of the benzyl group. Mechanisms for the formation of these characteristic ions were proposed with the aid of isotopically labeled standards and high-resolution mass spectrometry measurements. To help with the interpretation of EI mass spectra for nitazene analogs, decision trees were developed that encompass the characteristic fragment ions observed for substitutions to the amine moiety and benzyl group, with additional criteria provided for substitutions to the benzimidazole moiety. This study summarizes the fragmentation patterns and characteristic fragment ions in the EI mass spectra of 20 representative nitazene analogs, which will aid the seized drug community in identifying novel nitazene analogs.

Revisiting the chloramination of phenolic compounds: Formation of novel high-molecular-weight nitrogenous disinfection byproducts

Disinfection is critical for ensuring water safety; however, the potential risks posed by disinfection byproducts (DBPs) have raised public concern. Previous studies have largely focused on low-molecular-weight DBPs with one or two carbon atoms, leaving the formation of high-molecular-weight DBPs (HMW DBPs, with more than two carbon atoms) less understood. This study explores the formation of HMW DBPs during the chloramination of phenolic compounds using a novel approach that combines high-resolution mass spectrometry with density functional theory (DFT) calculations. For the first time, we identified nearly 100 previously unreported HMW nitrogenous DBPs (N-DBPs), with nearly half of those being halogenated N-DBPs. These N-DBPs were tentatively identified as heterocyclic (e.g., pyrrole and pyridine analogs) and coupling heterocyclic N-DBPs. Through detailed structure analysis and DFT calculations, the key formation steps of heterocyclic N-DBPs (monochloramine-mediated ring-opening reactions of halobenzoquinones) and new bonding mechanisms (C-N, C-O, and C-C bonding) of the coupling heterocyclic N-DBPs were elucidated. The selective formation of these novel N-DBPs was significantly influenced by factors such as contact time, monochloramine dosage, pH, and bromide concentration. Our findings emphasize the occurrence of diverse HMW heterocyclic N-DBPs, which are likely toxicologically significant, underscoring the need for further research to evaluate and mitigate their potential health risks in water disinfection.

Untargeted metabolomic insights into plastisphere communities in European rivers.

Every year, rivers introduce a staggering amount of hundred kilotons of plastic into the Oceans. This plastic is inhabited by microorganisms known as the plastisphere, which can be transferred between different ecosystems through the transport of microplastics. Here, we simulated the microbial colonization of polyethylene-based plastic pellets that are classically used to manufacture large-scale plastic products. The pellets were immersed for 1month in four to five sampling stations along the river-to-sea continuum of nine of the major European rivers. This study presents the first untargeted metabolomics analysis of the plastisphere, by using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). The plastisphere metabolomes were similar in the Rhine and Rhone rivers, while being different from the Tiber and Loire rivers, which showed greater similarity to the Thames and Seine rivers. Interestingly, we found a clear distinction between plastisphere metabolomes from freshwater and marine water in most of the river-to-sea continuum, thus suggesting a complete segregation in plastisphere metabolites that is not consistent with a major transfer of microorganisms between the two contrasted ecosystems. Putative annotations of 189 discriminating metabolites suggested that lipid metabolism was significantly modulated. These results enlightened the relevance of using environmental metabolomic as complementary analysis to the current OMICs analysis.

LC-HRMS analysis of phospholipids bearing oxylipins

BackgroundSeveral oxylipins including hydroxy- and epoxy-polyunsaturated fatty acids act as lipid mediators. In biological samples they can be present as non-esterified form, but the major part occurs esterified in phospholipids (PL) or other lipids. Esterified oxylipins are quantified indirectly after alkaline hydrolysis as non-esterified oxylipins. However, in this indirect analysis the information in which lipid class oxylipins are bound is lost. In this work, an untargeted liquid chromatography high-resolution mass spectrometry (LC-HRMS) method for the direct analysis of PL bearing oxylipins was developped. ResultsOptimized reversed phase LC separation achieved a sufficient separation of isobaric and isomeric PL from different lipid classes bearing oxylipin positional isomers. Individual PL species bearing oxylipins were identified based on retention time, precursor ion and characteristic product ions. The bound oxylipin could be characterized based on product ions resulting from the α-cleavage occurring at the hydroxy/epoxy group. Phospholipid sn-1/sn-2 isomers were identified based on the neutral loss of the fatty acyl in the sn-2 position. A total of 422 individual oxPL species from 7 different lipid classes i.e., PI, PS, PC, PE, PC-P, PC-O, and PE-P were detected in human serum and cells. This method enabled to determine in which PL class supplemented oxylipins are incorporated in HEK293 cells: 20:4;15OH, 20:4;14Ep, and 20:5;14Ep were mostly bound to PI. 20:4;8Ep and 20:5;8Ep were esterified to PC and PE while other oxylipins were mainly found in PC. SignificanceThe developed LC-HRMS method enables the comprehensive detection as well as the semi-quantification of isobaric and isomeric PL species bearing oxylipins. With this method, we show that the position of the oxidation has a great impact and directs the incorporation of oxylipins into the different PL classes in human cells.

Laccase mediated transformation of fluoroquinolone antibiotics: Analyzing degradation pathways and assessing algal toxicity

Improper waste disposal or inadequate wastewater treatment can result in pharmaceuticals reaching water bodies, posing environmental hazards. In this study, crude extracts containing the laccase enzyme from Pleurotus florida, Pleurotus eryngii, and Pleurotus sajor caju were used to degrade the fluoroquinolone antibiotics (FQs) levofloxacin (LEV), norfloxacin (NOR), ciprofloxacin (CIP), ofloxacin (OFL), and enrofloxacin (ENR) in aqueous solutions. The results for the fungi derived laccase extracts were compared with those obtained using commercially sourced laccase. Proteomics analysis of the crude extracts confirmed the presence of laccase enzyme across all three tested species, with proteins matching those found in Trametes versicolor and Pleurotus ostreatus. In vivo studies were conducted using species pure lines of fungal whole cells. The highest degradation efficiency observed was 77.7% for LEV in the presence of P. sajor caju after 25 days of treatment. Degradation efficiencies ranged from approximately 60-72% for P. florida, 45–76% for P. eryngii, and 47–78% for P. sajor caju. A series of in vitro experiments were also conducted using crude extracts from the three species and outcomes compared with those obtained when commercial laccase was used confirmed laccase as the enzyme responsible for antibiotic removal. The degradation efficiencies in vitro surpassed those measured in vivo, ranging from approximately 91-98% for commercial laccase, 77–92% for P. florida, 76–92% for P. eryngii, and 78–88% for P. sajor caju. Liquid chromatography–high-resolution mass spectrometry (LC-MS/MS) identified the degradation products, indicating a consistent enzymatic degradation pathway targeting the piperazine moiety common to all tested FQs, irrespective of the initial antibiotic structure. Phytoplankton toxicity studies with Dunaliella tertiolecta were performed to aid in understanding the impact of emerging contaminants on ecosystems, and by-products were analysed for ecotoxicity to assess treatment efficacy. Laccase-mediated enzymatic oxidation shows promising results in reducing algal toxicity, notably with Pleurotus eryngii extract achieving a 97.7% decrease for CIP and a 90% decrease for LEV. These findings suggest the potential of these naturally sourced extracts in mitigating antibiotic contamination in aquatic ecosystems.

Rapid discrimination between wild and cultivated Ophiocordyceps sinensis through comparative analysis of label-free SERS technique and mass spectrometry

Ophiocordyceps sinensis is a genus of ascomycete fungi that has been widely used as a valuable tonic or medicine. However, due to over-exploitation and the destruction of natural ecosystems, the shortage of wild O. sinensis resources has led to an increase in artificially cultivated O. sinensis. To rapidly and accurately identify the molecular differences between cultivated and wild O. sinensis, this study employs surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms to distinguish the two O. sinensis categories. Specifically, we collected SERS spectra for wild and cultivated O. sinensis and validated the metabolic profiles of SERS spectra using Ultra-Performance Liquid Chromatography coupled with Orbitrap High-Resolution Mass Spectrometry (UPLC-Orbitrap-HRMS). Subsequently, we constructed machine learning classifiers to mine potential information from the spectral data, and the spectral feature importance map is determined through an optimized algorithm. The results indicate that the representative characteristic peaks in the SERS spectra are consistent with the metabolites identified through metabolomics analysis, confirming the feasibility of the SERS method. The optimized support vector machine (SVM) model achieved the most accurate and efficient capacity in discriminating between wild and cultivated O. sinensis (accuracy = 98.95%, 5-fold cross-validation = 98.38%, time = 0.89s). The spectral feature importance map revealed subtle compositional differences between wild and cultivated O. sinensis. Taken together, these results are expected to enable the application of SERS in the quality control of O. sinensis raw materials, providing a foundation for the efficient and rapid identification of their quality and origin.

Comparative analysis of feature annotation methods for SESI-HRMS in exhaled breath analysis

Secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a powerful method for the analysis of exhaled breath in real time. However, feature annotation is challenging due to the flow-injection nature of the technique. To evaluate alternative methods for enhancing feature annotation, a study was conducted where the exhaled breath of sixteen subjects was condensed and analyzed using dynamic headspace vacuum in-trap extraction gas chromatography-mass spectrometry (DHS-V-ITEX-GC–MS) and liquid chromatography coupled to mass spectrometry (LC-MS) using polar and reverse-phase conditions along with a data-independent MS2-acquisition method based on multiple injections. The annotation results obtained from these methods were compared to those from SESI-HRMS. The use of these techniques on breath condensate is unprecedented. The GC–MS method primarily detected compounds of exogenous origin, particularly additives in oral hygiene products like menthol. On the other hand, LC-MS detected a vast number of features, especially with the utilized data-independent acquisition method. Chemical classes to these features were assigned in-silico. In positive ion mode, mostly amino acids and amines were detected, while the largest group in negative ion mode consisted of carboxylic acids. Approximately 25% and 5% of SESI features had a corresponding match with LC-MS and GC–MS. While both GC–MS and LC-MS methods partially overlapped with the SESI features, there was limited overlap of both in the mass-to-charge range from 150 to 200. In conclusion, both GC–MS and LC-MS analysis of breath condensate can serve as supplementary tools for annotating features obtained from SESI-MS. However, to increase confidence in the annotation results, combining these methods with additional on-line fragmentation techniques is recommended.

Monitoring of OPFRs in WWTPs: Unveiling environmental insights with high resolution mass spectrometry

Exploring the occurrence pattern of organophosphate flame retardants (OPFRs) in environmental samples has attracted increasing attention lately. In the conventional wastewater treatment plants (WWTPs), OPFRs are not sufficiently removed and therefore are discharged to the aquatic environment. However, concerns arise from their release regarding the potential risk posed to organisms. Consequently, closely monitoring this group of emerging contaminants, along with the evaluation of the associated ecological risk are matters of utmost importance. Given the aforementioned information, influents and effluents from two WWTPs (WWTP-A and WWTP-S) in Thessaloniki were gathered during a 36-month sampling initiative spanning from 2020 to 2023 in order to evaluate the occurrence and concentration levels of OPFRs. The collected samples underwent solid-phase extraction and then preceded to analysis with a Q Exactive Focus Orbitrap mass analyzer. In the present study, except for the implementation of the target analysis approach, removal efficiencies and mass loads were further calculated. TBEP (tris-2-butoxyethylphosphate) and TEP (triethyl phosphate) were detected in all influent samples (%DF = 100 %) in WWTP-A while in WWTP-S only TCPP (tris-1-chloro-2-propyl phosphate) was omnipresent. In effluents of both WWTPs, only TEP maintained the same detection frequency (%DF = 100 %). The highest mean concentration levels in WWTP-S influents were calculated for TEP (327 ng/L) followed by TCPP (277 ng/L) while in WWTP-A the highest mean concentrations in influents were detected for TCPP (405 ng/L) and TDCP (Tris(1,3-dichloro-2-propyl)phosphate) (124 ng/L). In effluents, the highest mean concentration was reported for TCPP, in both WWTPs, reaching 295 ng/L and 240 ng/L in WWTP-S and WWTP-A respectively. Generally, OPFRs exhibited low to moderate average removal efficiencies. Positive and negative removal efficiencies were also noticed during the monitoring campaign. The average mass load in WWTP-S was as high as 10.1 mg/day/1000 inhabitants and in WWTP-A, 11 mg/day/1000 inhabitants in effluents. Finally, different mathematical tools were employed for the assessment of the risk posed to algae, invertebrates and fish. For the toxicity assessment in these three trophic levels the worst-case scenario was taken into consideration. Generally, all the target analytes presented low or medium values in all trophic levels for acute and chronic toxicity.

Exploring the feasibility of a single-protoplast proteomic analysis

BackgroundRecent advances in high-resolution mass spectrometry have now enabled the study of proteomes at the single-cell level, offering the potential to unveil novel aspects of cellular processes. Remarkably, there has been no prior attempt to investigate single-plant cell proteomes. In this study, we aimed to explore the feasibility of conducting a proteomic analysis on individual protoplasts.FindingsAs a result, our analysis identified 978 proteins from the 180 protoplasts, aligning with well-known biological processes in plant leaves, such as photosynthetic electron transport in photosystem II. Employing the SCP package in the SCoPE2 workflow revealed a notable batch effect and extensive missing values in the data. Following correction, we observed the heterogeneity in single-protoplast proteome expression. Comparing the results of single-protoplast proteomics with those of bulk leaf proteomics, we noted that only a small fraction of bulk data was detected in the single-protoplast proteomics data, highlighting a technical limitation of the current single-cell proteomics method.ConclusionsIn summary, we demonstrated the feasibility of conducting a single-protoplast proteomic experiment, revealing heterogeneity in plant cellular proteome expression. This underscores the importance of analyzing a substantial number of plant cells to discern statistically significant changes in plant cell proteomes upon perturbation such as abscisic acid treatment in future studies. We anticipate that our study will contribute to advancing single-protoplast proteomics in the near future.

Rock-to-Pharma: Characterization of Shale Oil-Based Nonbiological Complex Drugs along the Production Process by High-Resolution Mass Spectrometry.

Antibiotic resistance has become a primary concern in medicine because of the overuse and misuse of classical pharmaceuticals. Recently, nonbiological complex drugs (NBCDs) have gained interest for their complex pharmacological profiles. Bituminosulfonates, which have lately been tentatively allocated toward NBCDs, are pharmacologically well-studied and show low potential in resistance development. However, molecular composition knowledge is limited. With this work, we present a comprehensive approach to investigate the manufacturing process of complex pharmaceuticals like bituminosulfonates on a molecular level via Fourier-transform ion cyclotron resonance mass spectrometry. The application of various hyphenations and ionization techniques comprehensively covers the entire mass and polarity range of the matrix, and the high sensitivity enables the identification of significant and minor chemical alterations caused by the multistep manufacturing process. The distillation of the shale crude oil eliminates highly aromatic PAH and PASH constituents. ESI(-) revealed strong PAH- and PASH-sulfonate formation after reacting the shale oil distillate with sulfuric acid. Increasing alkylation reduced the sulfonation yield, instead causing oligomerization side reactions, as observed by APPI analysis. Furthermore, multidimensional gas chromatography coupled with high-resolution mass spectrometry verified core structural motifs. With this work, we demonstrate the high potential of FT-ICR MS in NBCD process analysis. The results also give valuable information for future pharmacological investigations focusing on specific compound classes or properties.

Machine Learning in Complex Organic Mixtures: Applying Domain Knowledge Allows for Meaningful Performance with Small Data Sets.

The ability to quantify individual components of complex mixtures is a challenge found throughout the life and physical sciences. An improved capacity to generate large data sets along with the uptake of machine-learning (ML)-based analysis tools has allowed for various "omics" disciplines to realize exceptional advances. Other areas of chemistry that deal with complex mixtures often do not leverage these advances. Environmental samples, for example, can be more difficult to access, and the resulting small data sets are less appropriate for unconstrained ML approaches. Herein, we present an approach to address this latter issue. Using a very small environmental data set─35 high-resolution mass spectra gathered from various solvent extractions of Canadian petroleum fractions─we show that the application of specific domain knowledge can lead to ML models with notable performance.

Improved multi-food allergen analysis of processed foods using HRAM-LC-MS/MS with an ELISA-validated extraction solution and MS sample prep kit.

Food allergens in processed foods are affected by heating, processing, and the food matrix. To conduct highly reliable tests, extracting allergens into test solutions is necessary for appropriate detection. In addition to the commonly used enzyme-linked immunosorbent assay (ELISA), liquid chromatography-mass spectrometry (LC-MS), which has the advantage of simultaneously detecting multiple allergens in foods, is being increasingly used. When managing food allergens at food manufacturing sites, obtaining the same measured values is desirable, regardless of the analytical method used. Therefore, in this study, we focused on the importance of pretreatment steps for LC-MS when examining food allergens in processed foods, which can be difficult to analyze. The ELISA method uses food extracts optimized for analyzing allergens in processed foods. We developed a high-resolution accurate mass spectrometry (HRAM)-LC-MS/MS method using the same food extract used in the ELISA method and an MS sample preparation kit. Multiple food allergen analysis was performed using 1, 5, 10, and 20ppm of allergen-incurred processed foods. Overall, a strong correlation was observed between the measured values of HRAM-LC-MS/MS and ELISA, demonstrating the applicability of multi-allergen analysis using LC-MS.

Prolonged Dark Chemical Processes in Secondary Organic Aerosols on Filters and in Aqueous Solution.

Secondary organic aerosol (SOA) represents a large fraction of atmospheric aerosol particles that significantly affect both the Earth's climate and human health. Laboratory-generated SOA or ambient particles are routinely collected on filters for a detailed chemical analysis. Such filter sampling is prone to artifactual changes in composition during collection, storage, sample workup, and analysis. In this study, we investigate the chemical composition differences in SOA generated in the laboratory, kept at room temperature as aqueous extracts or on filters, and analyzed in detail after a storage time of a day and up to 4 weeks using liquid chromatography coupled to high-resolution mass spectrometry. We observe significantly different temporal concentration changes for monomers and oligomers in both extracts and on filters. In SOA aqueous extracts, many monomers increase in concentration over time, while many dimers decay at the same time. In contrast, on filters, we observe a strong and persistent concentration increase of many dimers and a decrease of many monomers. This study highlights artifacts arising from SOA chemistry occurring during storage, which should be considered when detailed organic aerosol compositions are studied. The particle-phase reactions on filters can also serve as a model system for atmospheric particle aging processes.

Biomarker panels for fruit intake assessment: a metabolomics analysis in the ELSA-Brasil study.

Food intake biomarkers are used to estimate dietary exposure; however, selecting a single biomarker to evaluate a specific dietary component is difficult due to the overlap of diverse compounds from different foods. Therefore, combining two or more biomarkers can increase the sensitivity and specificity of food intake estimates. This study aimed to evaluate the ability of metabolite panels to distinguish between self-reported fruit consumers and non-consumers among participants in the Longitudinal Study of Adult Health. A total of 93 healthy adults of both sexes were selected from the Longitudinal Study of Adult Health. A 24-h dietary recall was obtained using the computer-assisted 24-h food recall GloboDiet software, and 24-h urine samples were collected from each participant. Metabolites were identified in urine using liquid chromatography coupled with high-resolution mass spectrometry by comparing their exact mass and fragmentation patterns using free-access databases. Multivariate receiver operating characteristic curve (ROC) analysis and partial least squares discriminant analysis were used to verify the ability of the metabolite combination to classify daily and non-daily fruit consumers. Fruit intake was identified using a 24h dietary recall (24h-DR). Bananas, grapes, and oranges are included in the summary. The panel of biomarkers exhibited an area under the curve (AUC) > 0.6 (Orange AUC = 0.665; Grape AUC = 0.622; Bananas AUC = 0.602; All fruits AUC = 0.679; Citrus AUC = 0.693) and variable importance projection score > 1.0, and these were useful for assessing the sensitivity and predictability of food intake in our population. A panel of metabolites was able to classify self-reported fruit consumers with strong predictive power and high specificity and sensitivity values except for banana and total fruit intake.

Chemometrics-based analysis of the phytochemical profile and antioxidant activity of Salvia species from Iran

In recent years, the exploration of the therapeutic potential of Salvia has gained considerable attention, leading to a growing number of scientific studies emphasizing its pharmacological properties. Despite this, therapeutic applications of Salvia remain underexploited, requiring further investigation. Iran is a major center for sage diversity in Asia, boasting 60 Salvia species, 17 of which are unique to the area. This study aimed to comprehensively explore and compare the extracts of 102 Salvia samples belonging to 20 distinct Salvia species from Iran, providing a deeper understanding of their specific polyphenol content and, consequently, their antioxidant capabilities and potential therapeutic uses. All samples were analyzed to determine the contents of total phenolics, total flavonoids, total tannin, photosynthetic pigments, and ascorbic acid, along with their antioxidant activity. These data were then combined with the forty distinct chemical fingerprints identified by ultrafast high-pressure liquid chromatography coupled with high-resolution mass spectrometry. Multivariate data analysis was employed to find correlations and differences among the huge number of data obtained and to identify Salvia species with similar phytochemical and/or antioxidant properties. The results show that each Salvia species is characterized by a distinct class of polyphenols recognized for their antidiabetic, anti-inflammatory, cardioprotective and neuroprotective properties. Overall, our findings reveal the potential of some Salvia species for targeted therapeutic applications and provide a rational basis for the development of Salvia-derived nutraceuticals, ultimately improving the prospects for the use of Salvia in medicine.

A 1,8-Naphthalimide-based Tripodal Fluorescent Chemosensor to Selectively Detect Copper Ions.

A 1,8-naphthalimide-based tripodal fluorescent ligand (L3) was synthesized through the copper (I) catalyzed Huisgen azide-alkyne cycloaddition reaction of 2-(2-azidoethyl)-6-morpholino-1H-benzo[de]isoquinoline-1,3(2H)-dione with triproparagylamine. Naphthalimide acts as the fluorophore while the triazole and amine nitrogens chelate the metal ion. L3 showed a selective fluorescence turn-off for Cu(II) over other metal ions in aqueous acetonitrile solution. A Job's plot, Benesi-Hildbrand plot and high-resolution mass spectrometry data confirm a 1:1 binding stoichiometry with a binding constant of 7.8 х105 M- 1 while addition of disodium EDTA demonstrates its reversibility. The structure and stability of the complex was supported by theoretical calculations. The limit of detection for Cu(II) was calculated to be 0.3 µM which is considerably lower than WHO recommended Cu(II) limit in drinking water.

Critical review of fluorescence and absorbance measurements as surrogates for the molecular weight and aromaticity of dissolved organic matter.

Dissolved organic matter (DOM) is ubiquitous in aquatic environments and challenging to characterize due to its heterogeneity. Optical measurements (i.e., absorbance and fluorescence spectroscopy) are popular characterization tools, because they are non-destructive, require small sample volumes, and are relatively inexpensive and more accessible compared to other techniques (e.g., high resolution mass spectrometry). To make inferences about DOM chemistry, optical surrogates have been derived from absorbance and fluorescence spectra to describe differences in spectral shape (e.g., E2:E3 ratio, spectral slope, fluorescence indices) or quantify carbon-normalized optical responses (e.g., specific absorbance (SUVA) or specific fluorescence intensity (SFI)). The most common interpretations relate these optical surrogates to DOM molecular weight or aromaticity. This critical review traces the genesis of each of these interpretations and, to the extent possible, discusses additional lines of evidence that have been developed since their inception using datasets comparing diverse DOM sources or strategic endmembers. This review draws several conclusions. More caution is needed to avoid presenting surrogates as specific to either molecular weight or aromaticity, as these physicochemical characteristics are often correlated or interdependent. Many surrogates are proposed using narrow contexts, such as fractionation of a limited number of samples or dependence on isolates. Further study is needed to determine if interpretations are generalizable to whole-waters. Lastly, there is a broad opportunity to identify why endmembers with low abundance of aromatic carbon (e.g., effluent organic matter, Antarctic lakes) often do not follow systematic trends with molecular weight or aromaticity as observed in endmembers from terrestrial environments with higher plant inputs.