Mass Spectrometry Fingerprinting Research Articles

Identifying Key Markers for Monofloral (Eucalyptus, Rosemary, and Orange Blossom) and Multifloral Honey Differentiation in the Spanish Market by UHPLC-Q-Orbitrap-High-Resolution Mass Spectrometry Fingerprinting and Chemometrics.

Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R2Y = 0.929-0.981 and Q2 = 0.868-0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin's impact on honey by identifying novel markers not previously described.

Liquid biopsy of peripheral blood using mass spectrometry detects primary extramedullary disease in multiple myeloma patients

Multiple myeloma (MM) is the second most prevalent hematological malignancy, characterized by infiltration of the bone marrow by malignant plasma cells. Extramedullary disease (EMD) represents a more aggressive condition involving the migration of a subclone of plasma cells to paraskeletal or extraskeletal sites. Liquid biopsies could improve and speed diagnosis, as they can better capture the disease heterogeneity while lowering patients’ discomfort due to minimal invasiveness. Recent studies have confirmed alterations in the proteome across various malignancies, suggesting specific changes in protein classes. In this study, we show that MALDI-TOF mass spectrometry fingerprinting of peripheral blood can differentiate between MM and primary EMD patients. We constructed a predictive model using a supervised learning method, partial least squares-discriminant analysis (PLS-DA) and evaluated its generalization performance on a test dataset. The outcome of this analysis is a method that predicts specifically primary EMD with high sensitivity (86.4%), accuracy (78.4%), and specificity (72.4%). Given the simplicity of this approach and its minimally invasive character, this method provides rapid identification of primary EMD and could prove helpful in clinical practice.

Microfluidic Chip Coupled with MALDI-TOF MS for Multitarget Detection of Allergens in Crucian Carp (Carassius auratus).

The goal of the present study was to establish a rapid, simple method for simultaneous allergy testing of sera from multiple fish-allergic patients. Sera from fish-allergic patients were pooled and used for capturing allergens in fish muscle of crucian carp (Carassius auratus), which was studied as a fish model. Sarcoplasmic proteins of crucian carp (Carassius auratus) were extracted for the analysis of allergens. Anti-human IgE antibody-functionalized magnetic beads were utilized to collect IgE antibodies from human pooled sera. The isolation of allergenic proteins was immunomagnetically performed in microfluidic channels, and the elution of the captured allergenic proteins was done with 5% (v/v) acetic acid aqueous solution. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and peptide mass fingerprinting were used for the analysis of tryptic digests of eluted proteins. Ten potential allergenic proteins were identified from crucian carp (Carassius auratus). The present protocol provides a rapid, efficient, and simple method for simultaneous detection of multiple allergens, based on multitargeted antibodies from pooled sera of allergic patients. The constructed multiple antibody-modified MBs can be applied for the deallergenicity of food matrices. The efficiency of allergen detection can be greatly improved, with promising application in allergen discovery and filtration for other muscle-based foods.

Quality Evaluation of Calyx of Diospyros Kaki Thunb. by Ultra-High Performance Liquid Chromatography – Mass Spectrometry (UHPLC-MS) Profiling and Fingerprinting and Chemometrics

Calyx of Diospyros kaki Thunb. (DKC), a famous traditional Chinese medicine, has a remarkable therapeutic effect on hiccups but its quality control is insufficient. In the study, a method was established by ultra-high performance liquid chromatography – mass spectrometry (UHPLC-MS). 17 peaks were observed in the mass spectrum and their chemical structures were preliminarily identified, including 3 organic acids and 14 flavonoids. The reference UHPLC fingerprint was built based on 25 batches of DKC samples, containing 15 common peaks. 11 batches of DKC samples from Guangxi and Hebei were superior to other 14 batches, sharing high similarity from 0.966 to 0.988 with the reference fingerprint. The chemometric methods, including hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA), were used to distinguish the DKC samples. The recognition methods clearly distinguished the medicinal materials from different regions, indicating that the main chemical constituents leading to the differences were protocatechuic acid, 4-hydroxybenzoic acid, rutin (presumptive result based on MS data), isoquercitrin, kaempferol, and hyperoside. The established fingerprint method is simple, rapid, repeatable, and specific and provides a reference for the quality evaluation of DKC.

Insights into flavor formation of braised chicken: Based on E-nose, GC–MS, GC-IMS, and UPLC-Q-Exactive-MS/MS

Effects of braising duration on volatile organic compounds (VOCs) and lipids in chicken were investigated. Aroma profiles identified by an electronic nose were effective in differentiating braising stages. During braising process, a total of 25 key VOCs were detected in braised chicken, and sample braised for 210 min exhibited the highest level of key VOCs. Additionally, a gas chromatography mass spectrometry fingerprint was established to evaluate the distribution of VOCs throughout the braising process. Partial least square discriminant analysis indicated that 2-heptanone, 3-methyl-2-butanone, octanal, nonanal, butanal, (E)-2-pentenal, 1-octen-3-ol, 1-hexanol, pentanal, hexanal, and 1-pentanol significantly affected flavor characteristics of braised chicken. Furthermore, 88 differential lipids were screened, and glycerolipids metabolic was found to be main metabolic pathway during braising process. Triglycerides (TG) and phosphatidyl ethanolamine (PE), such as TG (16:0/18:1/18:2), TG (18:0/18:1/18:2), TG (18:1/18:2/18:3), TG (18:1/18:1/18:2), PE (O-18:2/18:2), PE(O-18:2/18:1), and TG (16:0/16:1/18:2), played a vital role in the generation of VOCs.

Application of sandpaper spray ionization mass spectrometry to comprehensively examine maple leaves infected with distinct fungi.

This study describes a novel application for sandpaper spray ionization mass spectrometry (SPS-MS), to examine the surface of maple tree (Acer sp.) leaves. By comparing mass spectrometry fingerprints, healthy leaves from those infected with powdery mildew and Rhytisma acerinum were distinguished. Leaves were grated with sandpaper, cut into triangles, and placed before the mass spectrometer, with the addition of a methanol-formic acid solution. Multivariate statistical analysis categorized the samples into three groups. Overall, SPS-MS effectively analyzed leaves with infectious microorganisms, potentially aiding in the creation of fungal identification databanks.

A novel, robust peptidyl-lys metalloendopeptidase from Trametes coccinea recombinantly expressed in Komagataella phaffii

A novel peptidyl-lys metalloendopeptidase (Tc-LysN) from Tramates coccinea was recombinantly expressed in Komagataella phaffii using the native pro-protein sequence. The peptidase was secreted into the culture broth as zymogen (~38 kDa) and mature enzyme (~19.8 kDa) simultaneously. The mature Tc-LysN was purified to homogeneity with a single step anion-exchange chromatography at pH 7.2. N-terminal sequencing using TMTpro Zero and mass spectrometry of the mature Tc-LysN indicated that the pro-peptide was cleaved between the amino acid positions 184 and 185 at the Kex2 cleavage site present in the native pro-protein sequence. The pH optimum of Tc-LysN was determined to be 5.0 while it maintained ≥60% activity between pH values 4.5—7.5 and ≥30% activity between pH values 8.5—10.0, indicating its broad applicability. The temperature maximum of Tc-LysN was determined to be 60 °C. After 18 h of incubation at 80 °C, Tc-LysN still retained ~20% activity. Organic solvents such as methanol and acetonitrile, at concentrations as high as 40% (v/v), were found to enhance Tc-LysN’s activity up to ~100% and ~50%, respectively. Tc-LysN’s thermostability, ability to withstand up to 8 M urea, tolerance to high concentrations of organic solvents, and an acidic pH optimum make it a viable candidate to be employed in proteomics workflows in which alkaline conditions might pose a challenge. The nano-LC-MS/MS analysis revealed bovine serum albumin (BSA)’s sequence coverage of 84% using Tc-LysN which was comparable to the sequence coverage of 90% by trypsin peptides.Key points•A novel LysN from Trametes coccinea (Tc-LysN) was expressed in Komagataella phaffii and purified to homogeneity•Tc-LysN is thermostable, applicable over a broad pH range, and tolerates high concentrations of denaturants•Tc-LysN was successfully applied for protein digestion and mass spectrometry fingerprinting

Target and non-target screening of biomarkers in wastewater: towards a unique analytical methodology for sample preparation.

This study aims to optimize a single preparation methodology based on solid-phase extraction (SPE) that could fit both target and non-target screening of organic biomarkers in raw wastewater, allowing the cross-comparison of results obtained from a same dataset. The efficiency of SPE sorbents used alone (HLB) or in combination in a multilayer cartridge was evaluated based on (i) the extraction recovery and matrix effect in environmental samples (surface water and wastewater) for a list of biomarkers (pharmaceuticals, licit and illicit drugs, artificial sweeteners, isoprostanes, polyphenols) and (ii) a number of detected features and their intensity in HRMS. The selected method uses a combination of three SPE sorbents mixed together (HLB, X-AW and X-CW) and seems to take full advantage of each, providing satisfactory validation parameters (recovery, instrumental limit of detection, linearity range and limit of quantification) over a large range of physico-chemical properties while ensuring promising results for non-target screening applications. Of the 65 targeted compounds, nearly all of them (47) were detected in wastewater influent samples with concentration above the limit of quantification, while at the same time over 10 000 features were recorded according to the high resolution mass spectrometry (HRMS) fingerprint, holding out the promise that a common protocol for these two analyses, with their very contrasting constraints and objectives, is possible.

Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) Fingerprinting and Chemometrics for Coffee Classification and Authentication.

Nowadays, the quality of natural products is an issue of great interest in our society due to the increase in adulteration cases in recent decades. Coffee, one of the most popular beverages worldwide, is a food product that is easily adulterated. To prevent fraudulent practices, it is necessary to develop feasible methodologies to authenticate and guarantee not only the coffee's origin but also its variety, as well as its roasting degree. In the present study, a C18 reversed-phase liquid chromatography (LC) technique coupled to high-resolution mass spectrometry (HRMS) was applied to address the characterization and classification of Arabica and Robusta coffee samples from different production regions using chemometrics. The proposed non-targeted LC-HRMS method using electrospray ionization in negative mode was applied to the analysis of 306 coffee samples belonging to different groups depending on the variety (Arabica and Robusta), the growing region (e.g., Ethiopia, Colombia, Nicaragua, Indonesia, India, Uganda, Brazil, Cambodia and Vietnam), and the roasting degree. Analytes were recovered with hot water as the extracting solvent (coffee brewing). The data obtained were considered the source of potential descriptors to be exploited for the characterization and classification of the samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). In addition, different adulteration cases, involving nearby production regions and different varieties, were evaluated by pairs (e.g., Vietnam Arabica-Vietnam Robusta, Vietnam Arabica-Cambodia and Vietnam Robusta-Cambodia). The coffee adulteration studies carried out with partial least squares (PLS) regression demonstrated the good capability of the proposed methodology to quantify adulterant levels down to 15%, accomplishing calibration and prediction errors below 2.7% and 11.6%, respectively.

Application of Nontarget High-Resolution Mass Spectrometry Fingerprints for Qualitative and Quantitative Source Apportionment: A Real Case Study.

High-resolution mass spectrometry (HRMS) provides extensive chemical data, facilitating the differentiation and quantification of contaminants of emerging concerns (CECs) in aquatic environments. This study utilizes liquid chromatography-HRMS for source apportionment in Chebei Stream, an urban water stream in Guangzhou, South China. Initially, 254 features were identified as potential CECs by the nontarget screening (NTS) method. We then established 1689, 1317, and 15,759 source-specific HRMS fingerprints for three distinct sources, the mainstream (C3), the tributary (T2), and the rain runoff (R1), qualitatively assessing the contribution from each source downstream. Subsequently, 32, 55, and 3142 quantitative fingerprints were isolated for sites C3, T2, and R1, respectively, employing dilution curve screening for source attribution. The final contribution estimates downstream from sites C3, T2, and R1 span 32-96, 12-23, and 8-23%, respectively. Cumulative contributions from these sources accurately mirrored actual conditions, fluctuating between 103 and 114% across C6 to C8 sites. Yet, with further tributary integration, the overall source contribution dipped to 52%. The findings from this research present a pioneering instance of applying HRMS fingerprints for qualitative and quantitative source tracking in real-world scenarios, which empowers the development of more effective strategies for environmental protection.

Combination of in silico prediction and convolutional neural network framework for targeted screening of metabolites from LC-HRMS fingerprints: A case study of “Pericarpium Citri Reticulatae - FructusAurantii”

In this study, a novel approach is introduced, merging in silico prediction with a Convolutional Neural Network (CNN) framework for the targeted screening of in vivo metabolites in Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) fingerprints. Initially, three predictive tools, supplemented by literature, identify potential metabolites for target prototypes derived from Traditional Chinese Medicines (TCMs) or functional foods. Subsequently, a CNN is developed to minimize false positives from CWT-based peak detection. The Extracted Ion Chromatogram (EIC) peaks are then annotated using MS-FINDER across three levels of confidence. This methodology focuses on analyzing the metabolic fingerprints of rats administered with "Pericarpium Citri Reticulatae - Fructus Aurantii" (PCR-FA). Consequently, 384 peaks in positive mode and 282 in negative mode were identified as true peaks of probable metabolites. By contrasting these with “blank serum” data, EIC peaks of adequate intensity were chosen for MS/MS fragment analysis. Ultimately, 14 prototypes (including flavonoids and lactones) and 40 metabolites were precisely linked to their corresponding EIC peaks, thereby providing deeper insight into the pharmacological mechanism. This innovative strategy markedly enhances the chemical coverage in the targeted screening of LC-HRMS metabolic fingerprints.

Nontarget Insights into the Fate of Cl-/Br-Containing DOM in Leachate during Membrane Treatment.

Halogenated organic compounds in wastewater are persistent and bioaccumulative contaminants of great concern, but few are known at the molecular level. Herein, we focus on nontarget screening of halogenated dissolved organic matter (DOM) in highly concentrated organic matrices of waste leachates and their concentrates. Solid-phase extraction (SPE) was optimized before capturing halogenated signatures via HaloSeeker 2.0 software on mining full-scan high-resolution mass spectrometry (HRMS) fingerprints. This study identified 438 Cl-/Br-containing DOM formulas in 21 leachates and membrane concentrates. Among them, 334 formulas were achieved via SPE with mixed-sorbent cartridges (mixed-SPE), surpassing the 164 formulas achieved through Bond Elut PPL cartridges (PPL-SPE). Herein, only four samples identified via PPL-SPE exhibited a resolution of >50% for extracted Cl-/Br-containing DOM by either SPE. The halogenated DOM constituted 6.87% of the total DOM mass features. Nevertheless, more abundant adsorbable organic halogens deciphered waste leachates and highly concentrated waste streams as reservoirs for halogenated contaminants. Remarkably, 75.7-98.1% of Cl-/Br-containing DOM in primary membrane concentrates remained stable through the secondary membrane treatment, indicating the persistence of these unknown contaminants even post-treatment.

A novel heteroleptic Cu(II)-phenanthroline-UDCA complex as lipoxygenase inhibitor and ER-stress inducer in cancer cell lines

A new heteroleptic copper(II) compound named C0-UDCA was prepared by reaction of [Cu(phen)2(OH2)](ClO4)2 (C0) with the bile ursodeoxycholic acid (UDCA). The resulting compound is able to inhibit the lipoxygenase enzyme showing more efficacy than the precursors C0 and UDCA. Molecular docking simulations clarified the interactions with the enzyme as due to allosteric modulation. The new complex shows antitumoral effect on ovarian (SKOV-3) and pancreatic (PANC-1) cancer cells at the Endoplasmic Reticulum (ER) level by activating the Unfolded Protein Response. In particular, the chaperone BiP, the pro-apoptotic protein CHOP and the transcription factor ATF6 are upregulated in the presence of C0-UDCA. The combination of Intact Cell MALDI-MS and statistical analysis have allowed us to discriminate between untreated and treated cells based on their mass spectrometry fingerprints.

Using the UPLC-QTOF-MS Fingerprinting Coupled with Clustering Analysis to Verify the Quality Control of Fritillaria przewalskii Maxim

Background: A method is proposed as follows to establish the ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) fingerprinting and content determination for Fritillaria przewalskii Maxim. (FPM). Materials and Methods: The separation was developed using an Acquity UPLC CSH C18 column (2.1 mm × 100 mm, 1.7 µm). The gradient elution was carried out with acetonitrile solution with 0.1% acetic acid (containing 0.01 mol L−1 ammonium acetate) as the mobile phase, with the flow rate of 0.4 mL min−1, column temperature of 30°C, and injection volume of 2 µL. Fourteen batches of samples were analyzed under the above chromatographic conditions to ascertain the fingerprint of FPM sourced in different areas. A total of 45 common peaks were selected for analysis. Two chromatographic peaks were identified by comparison with the standard compound, and simultaneous content determination of the two compounds was carried out. These two compounds were identified as two alkaloids, peiminine and peimisine. SPSS 25.0 and SIMCA 14.1 were used for cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) on the peak area of the 45 common peaks of FPM. Results: Results from this showed that samples sourced from different regions could be successfully divided into three groups based on their origin. The contents of peiminine and peimisine in different batches of FPM ranged from 57.92 to 76.01 µg/g and 118.12 to 167.39 µg/g. A quick and convenient identification using UPLC fingerprinting combined with PCA was then established to differentiate among FPM samples from different growing regions. Conclusion: This method may prove to be helpful for the quality evaluation and control of FPM and related medicinal plants in the future.

Discriminant Analysis of Gentiana Headspace Gas Chromatography – Mass Spectrometry Extract Data from In Vitro Cultures

Abstract A set of Gentiana L. species was successfully grown in vitro under the same conditions, and 72 samples from various cultures of these species (root, shoot, cotyledon callus, hypocotyl callus, and root callus) were obtained. The investigated species were G. affinis, G. andrewsii, G. bhutanica, G. burseri, G. cachemirica, G. capitata, G. crassicaulis, G. dahurica, G. decumbens, G. freyniana, G. frigida, G. gelida, G. grossheimii, G. kurroo, G. macrophylla, G. paradoxa, G. robusta, G. scabra, G. septemfida, G. siphonantha, and G. tianschanica. The obtained samples were extracted with a methanol-acetone-water (3:1:1) mixture, evaporated to dryness, and subjected to thin layer chromatography (TLC) on silica gel in sandwich mode with ethyl acetate-methanol-water (8:2:2) as the mobile phase. The resulting dry extracts were subjected to gas chromatography – mass spectrometry (GC-MS) fingerprinting of the headspace volatile fraction. Total ion count and average mass spectrum vectors were collected as two blocks and scaled independently to form a complex dataset. The major direction separating root or shoot samples from callus samples was found not to be fully associated with the highest variance as this information was placed in the first and fourth principal components of the principal component analysis (PCA). Therefore, linear discriminant analysis was performed on the first four (only the informative) components to reveal features responsible for the separation of culture types in the multivariate space.

Authenticity discrimination of Pulsatillae Radix based on dry-process REIMS fingerprinting combined with machine learning

In this study, rapid evaporative ionization mass spectrometry(REIMS) fingerprints of 388 samples of roots of Pulsatilla chinensis(PC) and its common counterfeits, roots of P. cernua and roots of Anemone tomentosa were analyzed based on REIMS combined with machine learning. The samples were determined by REIMS through dry burning, and the REIMS data underwent cluster analysis, similarity analysis(SA), and principal component analysis(PCA). After dimensionality reduction by PCA, the data were analyzed by similarity analysis and self-organizating map(SOM), followed by modeling. The results indicated that the REIMS fingerprints of the samples showed the characteristics of variety differences and the SOM model could accurately distinguish PC, P. cernua, and A. tomentosa. REIMS combined with machine learning algorithm has a broad application prospect in the field of traditional Chinese medicine.

Molecular-level degradation pathways of black phosphorus revealed by mass spectrometry fingerprinting.

Understanding the molecular mechanism of material transformation raises a great challenge for material characterization techniques. As a promising 2D material, the application potential of black phosphorus (BP) is seriously compromised by its environmental instability. However, until now, the degradation mechanism of BP remains ambiguous. Here we show that by using laser desorption ionization mass spectrometry (LDI-MS) fingerprinting it is possible to unravel the degradation pathways of BP at the molecular level without any chemical labeling. We found that BP-based materials can generate intrinsic phosphorus cluster (Pn+ or Pn-) fingerprint peaks in LDI-MS in both positive-ion and negative-ion modes, which allows the degradation processes of BP materials to be monitored by providing abundant mass information about intermediates and products with the sample-to-sample RSDs in the range of 1.0-28.4%. The stability of BP or cerium-encapsulated BP was monitored under ambient and increased temperature conditions for up to 20 or 180 days. Notably, by using LDI-MS fingerprinting, we reveal an unreported BP degradation pathway, i.e., nitrogen (N2)-addition oxidation, in addition to the direct oxidation pathway. Our results not only enable an in-depth understanding of the chemical instability of BP, but also, importantly, demonstrate a new powerful platform for monitoring and characterization of material transformation.

Analysis and Annotation of Phospholipids by Mass Spectrometry-Based Metabolomics.

Phospholipids are essential components of membrane lipid bilayers and serve as precursors of multiple signaling molecules, so alterations in their homeostasis are associated with the pathogenesis of numerous diseases. In this context, the application of mass spectrometry-based metabolomics has demonstrated great potential to comprehensively characterize the human phospholipidome. In this chapter, we describe an untargeted method for the determination of phospholipids and other related metabolites in a variety of biological matrices, including plasma/serum, erythrocytes, and tissues, based on the combination of high-throughput direct mass spectrometry fingerprinting and subsequent profiling by ultra-high-performance reversed-phase liquid chromatography coupled to mass spectrometry. Furthermore, we also review the characteristic fragmentation patterns of phospholipids with the aim of providing simple guidelines for their straightforward annotation.

Flavor Characterization and Imitation Flavor Identification Using Gas Chromatography-Orbitrap Mass Spectrometry Fingerprinting

Flavor Characterization and Imitation Flavor Identification Using Gas Chromatography-Orbitrap Mass Spectrometry Fingerprinting

Aggregation of Multimodal ICE-MS Data into Joint Classifier Increases Quality of Brain Cancer Tissue Classification

Mass spectrometry fingerprinting combined with multidimensional data analysis has been proposed in surgery to determine if a biopsy sample is a tumor. In the specific case of brain tumors, it is complicated to obtain control samples, leading to model overfitting due to unbalanced sample cohorts. Usually, classifiers are trained using a single measurement regime, most notably single ion polarity, but mass range and spectral resolution could also be varied. It is known that lipid groups differ significantly in their ability to produce positive or negative ions; hence, using only one polarity significantly restricts the chemical space available for sample discrimination purposes. In this work, we have developed an approach employing mass spectrometry data obtained by eight different regimes of measurement simultaneously. Regime-specific classifiers are trained, then a mixture of experts techniques based on voting or mean probability is used to aggregate predictions of all trained classifiers and assign a class to the whole sample. The aggregated classifiers have shown a much better performance than any of the single-regime classifiers and help significantly reduce the effect of an unbalanced dataset without any augmentation.