Real Time Mass Spectrometry Research Articles

Metal-organic frameworks-based microtrapper for real-time monitoring of targeted analyte and mechanism study

Interstitial fluid (ISF) provides important information of clinical value and physiological significance beyond blood tests for obtaining more precise health information and disease theranostics. Generally, current strategies are limited to simple extraction with time-consuming follow-up procedures. Facing challenges in efficient and real-time monitoring of target analytes in transdermal ISF, we develop metal-organic framework (MOF)-functionalized microneedle (MN) patches to achieve efficient antibiotics sampling, coupling direct analysis in real time mass spectrometry (DART-MS). The MOF MN microtrapper is constructed in a double-layered structure with a hard core and a better tissue penetration was accomplished. The MOF-based microtrapper manifests good in-vitro and in-vivo antibiotics tracking capability with a semi-quantitative method established. Moreover, the hydrogen-bond driven interaction is clarified by using molecular dynamics simulations (MDS) and related computational analysis. Good penetration safety is confirmed by histological analysis with promising clinical transnationality. We anticipate MOF MN-based microdevices provide a versatile minimally invasive strategy for transdermal ISF extraction and an extendable platform for a range of target molecules monitoring, including drugs, metabolites, biomarkers, et c, with promising clinical transnationality.

Rapid Screening of Vaping Liquids by DART-MS.

E-cigarette, or vaping, product use-associated lung injury was reported in over 2800 cases from August 2019 to February 2020. Samples of vaping products were submitted for laboratory analysis in conjunction with investigation of the outbreak. A rapid screening method that was selective and sensitive for multiple analytes was required to aid in the investigation. To develop a multi-analyte method capable of screening vaping liquid samples that consumed small amounts of sample, required minimal sample preparation and analysis time, employed automated data processing, and provided the necessary sensitivity and selectivity. Vaping liquids were dissolved in acetonitrile and sampled with DIP-it® tips. The tips were analyzed by direct analysis in real-time mass spectrometry (DART-MS) and the resulting data processed with TraceFinder™ software. Laboratory-fortified samples consisting of various analytes and matrixes were evaluated prior to the analysis of submitted samples. The method was successful at detecting all target analytes in all matrixes evaluated, although the method detection limits varied by analyte/matrix combination: from 0.1% nicotine in poly(propylene glycol) average Mn 1000 (the lowest level evaluated) to 5.0% poly(ethylene glycol) average Mn 400 in cannabis concentrate. Results for the analysis of submitted samples by this method compared favorably to GC-MS and FTIR results. The DART-MS method met the objective of speed, sensitivity, and selectivity (although certain cannabinoid isomers could not be distinguished). The method may be easily adapted or expanded for additional analytes. This is a simple DART-MS method for screening vaping liquids for substances of concern in less than 2 min per sample.

The characterization of disperse dyes in polyester fibers using DART mass spectrometry.

Textile fibers alone are highly prevalent in our environment, and not only are there a wide variety of fibers, but generally, consumer textiles are colored. Given the variety of crime locations where dyes are encountered and the potential circumstances, a rapid, preparation free analysis of samples is highly beneficial. This study has characterized a collection of commercially available textiles dyes by verifying the chemical structure, collecting reference spectra, and developing a method to analyze dyed fibers via Direct Analysis in Real-Time (DART) mass spectrometry. A methodology for direct analysis of pieces of fabric and single thread samples of polyester fibers dyed with disperse dyes was developed. The presence of 31 target dyes on fibers whose structures were previously established via high-resolution mass spectrometry was confirmed. Dyed fabrics containing mixtures of dyes in varying concentrations were also evaluated to determine whether each dye in the composition could be detected. The DART-MS methodology was sensitive and positively characterized disperse dyes in polyester fibers, allowing for blind identification of mixtures with the assistance of a high-resolution mass spectrometry database.

Qualitative Analysis of Real Drug Evidence Using DART-MS and the Inverted Library Search Algorithm.

Chromatographic-less mass spectrometry techniques like direct analysis in real-time mass spectrometry (DART-MS) are steadily being employed as seized drug screening tools. However, these newer analytical platforms require new computational methods to best make use of the collected data. The inverted library search algorithm (ILSA) is a recently developed method designed specifically for working with mass spectra of mixtures collected with DART-MS and has been implemented as a function in the NIST/NIJ DART-MS data interpretation tool (DIT). This paper demonstrates how DART-MS and the ILSA/DIT can be used to analyze seized drug evidence, while discussing insights gathered during the evaluation of 92 adjudicated case samples. The evaluation verified that the combination of DART-MS and the ILSA/DIT can be used as an informative tool to help analysts screen seized drug evidence but also revealed several factors─such as the influence of incorporating multiple in-source fragmentation spectra and the effect of scoring thresholds─an analyst must consider while employing these methods. Use cases demonstrating the benefit of the nonscoring metrics provided by the ILSA/DIT and demonstrating how the ILSA/DIT can be used to identify novel substances are also presented. A summary of considerations for using the ILSA/DIT for drug screening concludes this paper.

Natural Deep Eutectic Solvent-Based Dispersive Liquid-Liquid Microextraction Coupled with Direct Analysis in Real Time Mass Spectrometry: A Green Temperature-Mediated Analytical Strategy.

Green analytical chemistry (GAC) represents a rapidly growing research field that aims at developing novel analytical approaches with minimal consumption of hazardous reagents and solvents. The current study reports on a GAC methodology exploiting the unique physicochemical properties of natural deep eutectic solvents (NADESs), a supposedly environmentally friendly class of solvents. Based on a temperature-mediated strategy, the NADESs were manipulated to undergo multiple phase transitions for favorable functionality and performance. As proof-of-concept demonstrations, both hydrophobic and hydrophilic NADESs were prepared for the extraction and analysis of eight phthalate esters in aqueous samples (food simulants) and three aflatoxins in oily samples (edible oils), respectively. NADES-based dispersive liquid-liquid microextraction (DLLME) was employed to achieve high-efficiency sample pretreatment. Afterward, the NADESs were transformed from liquids into solids by tuning the peripheral temperature for a convenient phase separation from the sample matrices. The solidified NADES extracts were melted and vaporized at elevated temperatures by transmission-mode direct analysis in real time (DART) for further quadrupole-Orbitrap high-resolution mass spectrometry (Q-Orbitrap HRMS) analysis. The developed protocol was validated, achieving good repeatability with relative standard deviations (RSDs) of less than 9% and satisfactory sensitivity with limits of detection (LODs) and quantitation (LOQs) ranging from 0.1 to 0.8 and 0.2 to 2.0 μg/kg, respectively. The greenness of the analytical methodology was assessed with the calculated scores of 0.66 and 0.57 for the hydrophobic and hydrophilic NADES-based protocols, respectively. The method was applied to marketed samples, highlighting the great potential for green chemical analysis.

Incorporating measurement variability when comparing sets of high-resolution mass spectra

Mass spectra are an important signature by which compounds can be identified. We recently formulated a mathematical approach for incorporating measurement variability when comparing sets of high-resolution mass spectra. Leveraging replicate mass spectra, we construct high-dimensional consensus mass spectra—representing each of the compared analytes—and compute the similarity between these data structures. In this paper, we present this approach and discuss its applications and limitations when trying to discriminate methamphetamine and phentermine using in-source collision induced dissociation mass spectra collected with direct analysis in real time mass spectrometry.

Permeation of human scent through laboratory examination gloves.

It is generally accepted in the canine detection industry that a barrier (such as a glove) should be used between a human and evidence or canine training aids in order to prevent contamination and cross-contamination as well as protect the handler from hazardous materials. However, no studies exist evaluating this assumption. Further, there is no published literature examining the different types of gloves for their utility in handling evidence or training materials used in canine detection work. This study was the first of its kind to address these gaps in the literature. First, GloGerm™ was used as a proxy for human scent and odor(s)/particulate(s) to visualize potential contamination. Then, three types of gloves (nitrile, two layers of nitrile, latex, and polyethylene) were tested for the permeation of human scent using furfural as a proof of concept, followed by pooled human sweat. Finally, the inherent odor of each glove type was identified. Two analytical techniques were used simultaneously as static and standoff dynamic detection systems, respectively: solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) and direct analysis in real time-mass spectrometry (DART-MS). Using a double layer of nitrile gloves was the most effective in preventing furfural permeation from the analytical standard, while a single layer of nitrile prevented furfural from permeating from human sweat up to 2h. Polyethylene gloves allowed the highest amount of furfural permeation but had no inherent odor detected. Headspace analysis detected two compounds for nitrile gloves and four compounds for latex gloves, but the nitrile compounds had a higher relative abundance.

Real-time metabolic monitoring under exhaustive exercise and evaluation of ventilatory threshold by breathomics: Independent validation of evidence and advances.

Breath analysis was coupled with ergo-spirometry for non-invasive profiling of physio-metabolic status under exhaustive exercise. Real-time mass-spectrometry based continuous analysis of exhaled metabolites along with breath-resolved spirometry and heart rate monitoring were executed while 14 healthy adults performed ergometric ramp exercise protocol until exhaustion. Arterial blood lactate level was analyzed at defined time points. Respiratory-cardiac parameters and exhalation of several blood-borne volatiles changed continuously with the course of exercise and increasing workloads. Exhaled volatiles mirrored ventilatory and/or hemodynamic effects and depended on the origin and/or physicochemical properties of the substances. At the maximum workload, endogenous isoprene, methanethiol, dimethylsulfide, acetaldehyde, butanal, butyric acid and acetone concentrations decreased significantly by 74, 25, 35, 46, 21, 2 and 2%, respectively. Observed trends in exogenous cyclohexadiene and acetonitrile mimicked isoprene profile due to their similar solubility and volatility. Assignment of anaerobic threshold was possible via breath acetone. Breathomics enabled instant profiling of physio-metabolic effects and anaerobic thresholds during exercise. Profiles of exhaled volatiles indicated effects from muscular vasoconstriction, compartmental distribution of perfusion, extra-alveolar gas-exchange and energy homeostasis. Sulfur containing compounds and butyric acid turned out to be interesting for investigations of combined diet and exercise programs. Reproducible metabolic breath patterns have enhanced scopes of breathomics in sports science/medicine.

Inkjet ink classification and source prediction based on direct analysis in real-time mass spectrometry (DART-MS) via mass imaging and convolutional neural network (CNN)

This paper presents mass spectrometry imaging (MSI) as an intuitive method of showing the differences between inks, and provides a novel method of ink source prediction based on direct analysis in real-time mass spectrometry (DART-MS) spectral analysis. The ink database comprised 106 types of ink from three brands (Canon, Epson, and HP) with high market share. High-dimensionality reduction methods, such as principal component analysis (PCA), non-negative matrix factorization (NMF), and probabilistic latent semantic analysis (pLSA), were used to reduce the dimensions of the mass spectral data. Characteristics and statistical descriptions of the mass spectra of each ink are given in this paper. Then, MSI was used to visualize the results after PCA, NMF, and pLSA. Finally, a convolutional neural network (CNN) was applied to the data after high-dimensionality reductions, which helped predict the ink source. Results showed efficient and excellent performance of machine-learning analysis in ink source prediction using one pixel in MSI (100% for black, magenta, and yellow inks; 99.6% for cyan ink). In addition, a blind test was used to validate the performance of the CNN model, with results showing that the more pixels used, the more accurate the results. Therefore, we strongly recommend wide-area detection of ink to ensure accurate results.

Authentication of Edible Insects' Powders by the Combination of DART-HRMS Signatures: The First Application of Ambient Mass Spectrometry to Screening of Novel Food.

This feasibility study reports the use of direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) in profiling the powders from edible insects, as well as the potential for the identification of different insect species by classification modeling. The basis of this study is the revolution that has occurred in the field of analytical chemistry, with the improved capability of ambient mass spectrometry to authenticate food matrices. In this study, we applied DART-HRMS, coupled with mid-level data fusion and a learning method, to discriminate between Acheta domesticus (house cricket), Tenebrio molitor (yellow mealworm), Locusta migratoria (migratory locust), and Bombyx mori (silk moth). A distinct metabolic fingerprint was observed for each edible insect species, while the Bombyx mori fingerprint was characterized by highly abundant linolenic acid and quinic acid; palmitic and oleic acids are the statistically predominant fatty acids in black soldier fly (Hermetia illucens). Our chemometrics also revealed that the amino acid proline is a discriminant molecule in Tenebrio molitor, whereas palmitic and linoleic acids are the most informative molecular features of the house cricket (Acheta domesticus). Good separation between the four different insect species was achieved, and cross-validation gave 100% correct identification for all training samples. The performance of the random forest classifier was examined on a test set and produced excellent results, in terms of overall accuracy, sensitivity, and specificity. These results demonstrate the reliability of the DART-HRMS as a screening method in a future quality control scenario to detect complete substitution of insect powders.

Influence of the Electrode-Electrolyte Interface on the Product Distribution of the HMF Electroreduction

The electrochemical reduction of 5-hydroxymethylfurfural (HMF), a biomass-based platform chemical, is a promising route towards the defossilization of the transportation sector. It yields fuels, such as 2,5-dimethylfuran (DMF), and fuel precursors, such as 2,5-dihydroxymethylfuran (DHMF) and 5,5’-bis(hydroxylmethyl)hydrofuroin (BHH), while requiring only renewable resources. In order to control the selectivity of this reaction and to optimize the yield of the desired target compound, it is important to understand the reaction mechanisms towards the individual products and the influence of various system parameters. We utilize two complementary methods, namely electrochemical real-time mass spectrometry (EC-RTMS) and quantitative batch electrolysis in a flow reactor, to obtain further insights into the electrochemical HMF reduction mechanisms and the interplay between the electrode and electrolyte. While EC-RTMS is a fast screening technique, which allows for the analysis of transient processes, the batch electrolysis in the flow reactor enables product quantification by high-performance liquid chromatography (HPLC) and gas chromatography (GC) and the calculation of reaction selectivities and faradaic efficiencies. With these techniques, we were able to investigate the influence of various system parameters, such as the electrode material, the applied potential and the composition of the electrolyte, on the product distribution and propose reaction mechanisms towards the individual products.[1] References [1] R. Kloth, D. V. Vasilyev, K. J. J. Mayrhofer, I. Katsounaros, Electroreductive 5-Hydroxymethylfurfural Dimerization on Carbon Electrodes ChemSusChem 2021, 14, 5245. Figure 1

Composition of Nonextractable Polyphenols from Sweet Cherry Pomace Determined by DART-Orbitrap-HRMS and Their In Vitro and In Vivo Potential Antioxidant, Antiaging, and Neuroprotective Activities

Sweet cherry pomace is an important source of phenolic compounds with beneficial health properties. As after the extraction of phenolic compounds, a phenolic fraction called nonextractable polyphenols (NEPs) remains usually retained in the extraction residue, alkaline and acid hydrolyses and enzymatic-assisted extraction (EAE) were carried out in this work to recover NEPs from the residue of conventional extraction from sweet cherry pomace. In vitro and in vivo evaluation of the antioxidant, antihypertensive, antiaging, and neuroprotective capacities employing Caenorhabditis elegans was achieved for the first time. Extractable phenolic compounds and NEPs were separated and identified by families by high-performance thin-layer chromatography (HPTLC) with UV/Vis detection. A total of 39 phenolic compounds were tentatively identified in all extracts by direct analysis in real-time high-resolution mass spectrometry (DART-Orbitrap-HRMS). EAE extracts presented the highest in vitro and in vivo antioxidant capacity as well as the highest in vivo antiaging and neuroprotective capacities. These results showed that NEPs with interesting biological properties are retained in the extraction residue, being usually underestimated and discarded.

Similarity network fusion for aggregating headspace GC–MS and direct analysis in real time–mass spectrometry data from solid samples to enhance species identification efficiency of high–temperature heated wood

Pterocarpus santalinus and Pterocarpus tinctorius are commonly used species of the genus Pterocarpus in the wood trade. Although both of them have been listed in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) since 2019, it is still critical to identify them in terms of plant taxonomy. Currently, high-temperature heating is an accepted treatment method for high-density wood species such as Pterocarpus to improve dimensional stability and restore previous drying defects partially. It has proved challenging to identify the high-temperature (e.g., 120 °C) heated wood from these two species. Thus, this study approaches species identification of two Pterocarpus of high-temperature (e.g., 120 °C) heated solid wood samples using headspace–gas chromatography–mass spectrometry (HS–GC–MS). Besides, a computational analytical method named similarity network fusion (SNF) was proposed to aggregate data in two different types, respectively, derived from the HS–GC–MS and direct analysis in real time–mass spectrometry (DART–MS) to explore the feasibility of improving the efficiency and accuracy of wood species discrimination. The SNF exhibits more significant differences and higher predictive accuracy (100%) between P. santalinus and P. tinctorius than that based on the HS–GC–MS data (77.78%) or DART–MS (66.67%) alone. These results demonstrated the capability of the HS–GC–MS technique in the analysis of high-temperature heated solid wood and the potential of multidimensional or comprehensive data sets based on the SNF algorithm in the field of wood species identification.

Aperture Size Influences Oxidation in Positive-Ion Nitrogen Direct Analysis in Real Time Mass Spectrometry.

Direct Analysis in Real Time (DART) mass spectrometry commonly uses helium as the DART gas. With the looming helium shortage, other gases are being evaluated for DART. Nitrogen is inexpensive and readily available, making it a desirable alternative. However, NO+ reagent ions present in positive-ion nitrogen DART result in extensive oxidation for many compounds. The DART source uses a ceramic insulator cap to protect the operator from electrical shock. The most common cap has an aperture with a 2.5 mm inner diameter, through which the gas exits the DART source. By using a cap with a narrow (0.5 mm) ID, oxidation can be significantly reduced for nitrogen DART. The 0.5 mm cap is hypothesized to reduce back-diffusion of atmospheric oxygen into the DART source, with a reduction in the relative abundance of NO+ and increase in the relative abundance of [(H2O)2 + H]+ as the reactive species responsible for ionization of the analytes.

Simultaneous determination of multiple flavorings in infant formula by direct analysis in real time-mass spectrometry

The excessive flavorings in food are a growing public health concern, particularly in foods for infants and children. A rapid and simple method for simultaneous detection of multiple flavorings in food is urgently needed. In this work, a method with direct analysis in real time-mass spectrometry has been developed and applied to the simultaneous determination of four flavorings, including maltol, ethyl maltol, vanillin, and ethyl vanillin. The ionization efficiency of flavor compounds in the quantitatively-dip-it probe mode was compared with that in the quick strip mode, which revealed that a solvent-assisted ionization mechanism might be involved in the ionization process. The developed method showed good linearity (R2 > 0.99) in the range from 5 to 1000 μg L−1, sensitivity (LODs <3.3 μg L−1), recoveries (84.8%–96.9%), satisfactory repeatability (RSD <14.3%, n = 5), and high-throughout (12 infant formula samples completed in 15 min). The LOQs (0.55–1.1 mg kg−1) for the infant formula sample were much lower than the regulatory limits. The developed method provided an alternative way to monitor the excessive addition of flavorings.

Direct analysis in real time high-resolution mass spectrometry for authenticity assessment of lamb

In comparison to more traditional methods of determining food authenticity, such as gas chromatography analysis, the primary advantages of DART-HRMS include its high speed and throughput of analysis. This study used a non-targeted metabolomics method based on real-time high-resolution mass spectrometry combined with chemometric analysis to distinguish lamb samples from four regions. Orthogonal least squares-discriminant analysis revealed a distinct difference between these four lamb regions. The potential markers were chosen based on the variable's importance in projection values, variance, and fold change. A total of 79 markers were identified using the matching chemistry database. These markers differed significantly between lambs in four regions according to heatmap analysis. The linear discriminatory analysis model had an initial classification rate of 100.0% and a cross-validation accuracy of 82.50% on the identified markers. The research demonstrates that DART-HRMS can perform a rapid authentication evaluation of lamb samples.

Quantifying Smoke Taint in California Wines by Immersive Sorbent Sheet Extraction Prior to Direct Analysis in Real-Time Mass Spectrometry (DART-MS)

Measuring volatile phenols in wine is essential in ensuring superior wine quality. A new analytical technique, called solid-phase mesh-enhanced sorption from headspace (SPMESH), was modified with direct immersion (DI) conditions and coupled to direct analysis in real time–mass spectrometry (DART–MS) to be used to detect smoke taint in winemaking.

HDM, interfacing thermal analysis and ambient ionisation mass spectrometry

Thermomicroscopy (aka hot-stage microscopy) has been shown to be an excellent complimentary tool when used in conjunction with other analytical techniques, such as DSC and TGA. The optical data obtained from thermomicroscopy aid in the elucidation of complex events, often seen in many thermoanalytical profiles. Here, a system linking hot-stage microscopy and direct analysis in real-time mass spectrometry is described. This combination allows the simultaneous detection of both physical and chemical properties of a material as it is heated. Results showcasing the benefits of this combination include the thermal separation of energetic materials, the analysis of 3D printer filaments, and the profiling of trace materials including paint chips and fibres.

Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry.

The differentiation of positional isomers is a well established analytical challenge for forensic laboratories. As more novel psychoactive substances (NPSs) are introduced to the illicit drug market, robust yet efficient methods of isomer identification are needed. Although current literature suggests that Direct Analysis in Real Time–Time-of-Flight mass spectrometry (DART-ToF) with in-source collision induced dissociation (is-CID) can be used to differentiate positional isomers, it is currently unclear whether this capability extends to positional isomers whose only structural difference is the precise location of a single substitution on an aromatic ring. The aim of this work was to determine whether chemometric analysis of DART-ToF data could offer forensic laboratories an alternative rapid and robust method of differentiating NPS positional ring isomers. To test the feasibility of this technique, three positional isomer sets (fluoroamphetamine, fluoromethamphetamine, and methylmethcathinone) were analyzed. Using a linear rail for consistent sample introduction, the three isomers of each type were analyzed 96 times over an eight-week timespan. The classification methods investigated included a univariate approach, the Welch t test at each included ion; a multivariate approach, linear discriminant analysis; and a machine learning approach, the Random Forest classifier. For each method, multiple validation techniques were used including restricting the classifier to data that was only generated on one day. Of these classification methods, the Random Forest algorithm was ultimately the most accurate and robust, consistently achieving out-of-bag error rates below 5%. At an inconclusive rate of approximately 5%, a success rate of 100% was obtained for isomer identification when applied to a randomly selected test set. The model was further tested with data acquired as a part of a different batch. The highest classification success rate was 93.9%, and error rates under 5% were consistently achieved.

Discovery of the directionally detoxification effect and chemical mechanism of Ginseng-Fuzi co-decoction based on real-time online filtration electrospray ionization mass spectrometry

BackgroundThe synergic action of compound prescriptions is an important feature and core advantage of traditional medicine. Ginseng-Fuzi decoction is a classic compatible phytomedicine in China, of which Ginseng can effectively reduce the toxicity of Fuzi in clinical, but the detoxification chemical mechanism is still unclear. PurposeDevelop a novel method for real-time tracking and monitoring of complex substances in the decoction system of traditional Chinese medicine to uncover the detoxification effect Ginseng on Fuzi and explore the possible chemical reaction mechanism of Ginseng-Fuzi co-decoction. MethodsA novel real-time monitoring system, online filtration electrospray ionization mass spectrometry, was developed for extremely complex substances analysis in the decoction of traditional medicine compounds to uncover the directionally detoxification effect and the mechanism of compatibility interaction. ResultsNine key alkaloids and 7 ginsenosides in Ginseng-Fuzi decoction were simultaneously in-situ monitoring in positive ion mode or negative ion mode respectively. Both types of targeted analytes had satisfactory MS signal response for real-time qualitative and quantitative analysis with high precision (RSD < 14.04%) and low LLODs (0.002 ng/ml-10 ng/ml). Through long-term tracking analysis, the exact detoxification and synergistic effect of Ginseng-Fuzi decoction were confirmed as the concentration of main toxic alkaloids decreased (e.g. the content of mesaconitine has been reduced by about 38%) and the main active monoester alkaloids increased obviously. More importantly, the possible molecular mechanism of the detoxification effect of Ginseng compatibility was revealed for the first time, which was the nucleophilic substitution reaction of diester alkaloids catalyzed by fatty acids. ConclusionThis study revealed the exact effect of co-decoction of Ginseng and Fuzi at the molecular level and the chemical reaction mechanism of fatty acid-catalyzed degradation of toxic diester-type alkaloids. The comprehensive multi-component real-time monitoring strategy for complex traditional medicine compounds developed and implemented here has important demonstration significance for revealing the scientific connotation of the compatibility of compound traditional medicine.