Retention Time Measurements Research Articles

Oxygen tracer diffusion in amorphous hafnia films for resistive memory.

The oxygen diffusion rate in hafnia (HfO2)-based resistive memory plays a pivotal role in enabling nonvolatile data retention. However, the information retention times obtained in HfO2 resistive memory devices are many times higher than the expected values obtained from oxygen diffusion measurements in HfO2 materials. In this study, we resolve this discrepancy by conducting oxygen isotope tracer diffusion measurements in amorphous hafnia (a-HfO2) thin films. Our results show that the oxygen tracer diffusion in amorphous HfO2 films is orders of magnitude lower than that of previous measurements on monoclinic hafnia (m-HfO2) pellets. Moreover, oxygen tracer diffusion is much lower in denser a-HfO2 films deposited by atomic layer deposition (ALD) than in less dense a-HfO2 films deposited by sputtering. The ALD films yield similar oxygen diffusion times as experimentally measured device retention times, reconciling this discrepancy between oxygen diffusion and retention time measurements. More broadly, our work shows how processing conditions can be used to control oxygen transport characteristics in amorphous materials without long-range crystal order.

Morphological and Behavioral Adaptations of Silk-Lovers (Plokiophilidae: Embiophila) for Their Lifestyle in the Silk Domiciles of Webspinners (Embioptera)

The diversity of true bugs gave rise to various lifestyles, including gaining advantage from other organisms. Plokiophilidae are cimicomorphan bugs that live in the silk constructions of other arthropods. One group, Embiophila, exclusively settles in the silk colonies of webspinners (Embioptera). We investigated the lifestyle of Embiophila using microscopy to study the micromorphology and material composition of the leg cuticle, choice assays and retention time measurements based on different characteristics of the embiopteran galleries and tilting experiments with different substrates to quantify the attachment performance of the bugs. Embiophila neither explicitly preferred embiopteran presence, nor required silk for locomotion, but the bugs preferred fibrous substrates during the choice experiments. The hairy attachment pad on the tibia showed the best attachment performance on substrates, with an asperity size of 1 µm. Additionally, very rough substrates enabled strong attachment, likely due to the use of claws. Our findings suggest that Embiophila settle in galleries of webspinners to benefit from the shelter against weather and predators and to feed on mites and other intruders. The combination of behavioral and functional morphological experiments enables insights into the life history of these silk-associated bugs, which would be highly challenging in the field due to the minute size and specialized lifestyle of Embiophila.

Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics.

Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching. This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation. The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.

Improving the monitoring of multi-class pesticides in baby foods using QuEChERS-UHPLC-Q-TOF with automated identification based on MS/MS similarity algorithms

A screening method was developed for the multi-residue analysis of pesticides in baby foods using QuEChERS and UHPLC-Q-TOF. For sample preparation, the two-buffered versions of QuEChERS and different purification procedures were studied. False negatives and false positives were determined using different thresholds mentioned in the literature on the retention time and accurate mass measurement detection criteria. To reach unequivocal identification, the fragmentation spectra of the pesticides were used. The information-dependant-acquisition (IDA) mode was optimized with a precursor-inclusion list (PIL) to limit the loss of MS/MS data. Then, the experimental fragmentation spectra were compared to those included in a homemade library, by assessing different MS/MS algorithms and similarity scores. The optimised method was validated according to SANTE/11312/2021 guidelines. 95% and 73% of the pesticides presented a screening detection limit (SDL) and a limit of identification (LOI) ≤ 0.1 mg.kg−1. One plasticizer was found in the investigated samples by a suspect-screening approach.

Equivalent Carbon Number and Interclass Retention Time Conversion Enhance Lipid Identification in Untargeted Clinical Lipidomics.

Chromatography is often used as a method for reducing sample complexity prior to analysis by mass spectrometry, and the use of retention time (RT) is becoming increasingly popular to add valuable supporting information in lipid identification. The RT of lipids with the same headgroup in reversed-phase separation can be predicted using the equivalent carbon number (ECN) model. This model describes the effects of acyl chain length and degree of saturation on lipid RT. For the first time, we have found a robust correlation in the chromatographic separation of lipids with different headgroups that share the same fatty acid motive. This relationship can be exploited to perform interclass RT conversion (IC-RTC) by building a model from RT measurements from lipid standards that allows the prediction of RT of one lipid subclass based on another. Here, we utilize ECN modeling and IC-RTC to build a glycerophospholipid RT library with 517 entries based on 136 tandem mass spectrometry-characterized lipid RTs from NIST SRM-1950 plasma and lipid standards. The library was tested on a patient cohort undergoing coronary artery bypass grafting surgery (n = 37). A total of 156 unique circulating glycerophospholipids were identified, of which 52 (1 LPG, 24 PE, 5 PG, 18 PI, and 9 PS) were detected with IC-RTC, thereby demonstrating the utility of this technique for the identification of lipid species not found in commercial standards.

Statistical Evaluation of the Standard Deviation of Chromatographic Retention Time in the Capillary Column Temperature Programming Mode

In the qualitative analysis of complex mixtures of unknown composition, a promising direction for increasing the reliability of the identification of substances is the joint use of several simultaneously determined analytical parameters. A combination of chromatographic methods with FTIR spectroscopy, mass spectrometry, or other methods is used. In solving complex analytical problems of industrial nature, it is economically expedient to use only chromatographic methods. In analyzing complex multicomponent mixtures with a high density of peaks in the chromatogram, the precision of the determination of retention time determines the reliability of the identification of substances and of the result of analysis, using identification both directly by the absolute retention time and by relative parameters derived from it (relative retention times, retention indices). The standard deviation of a measurement of the chromatographic retention time is a measure of precision. Experimental chromatographic retention times were obtained for analyzing a mixture by the following scheme: initial isotherm, temperature programming, final isotherm. A sharp increase (by one order of magnitude) in the numerical value of the standard deviation was noted at the step of temperature programming. A regression equation was obtained linking the point estimate of the standard deviation of the retention time and column temperature. The performance characteristic of the regression equation is obtained as a function that enables calculating the total standard uncertainty in the estimate of the standard deviation of the chromatographic retention time. The results can be used to refine chromatographic retention time and indices that ensure the reliable identification of substances.

Coherent magnetization reversal of a cylindrical nanomagnet in shape-anisotropy magnetic tunnel junctions

A shape-anisotropy magnetic tunnel junction (MTJ) holds promise for its scaling into single-digit nanometers while possessing high data-retention capability. Understanding magnetization reversal mode is crucial to quantify the thermal stability factor Δ for data retention with high accuracy. Here, we study magnetization reversal mode in the shape-anisotropy MTJ with a 15-nm-thick CoFeB layer by evaluating Δ from two different methods: switching probability and retention time measurements. We find that magnetization reversal coherently proceeds in the 15-nm-thick and X/1X-nm-diameter cylindrical nanomagnet in the shape-anisotropy MTJs, in contrast to the conventional interfacial-anisotropy MTJs with a smaller thickness and larger diameter. The coherent magnetization reversal of the shape-anisotropy MTJ is also confirmed by astroid curve measurements. This study provides insight into the development of ultrasmall and high-reliability MTJ devices.

A methodology employing retention modeling for achieving control space in liquid chromatography method development using quality by design approach

This study reports the application of retention modeling and quality by design practices for reverse-phase liquid chromatographic method development of a new chemical entity. Prior to the retention modeling, preliminary screening experiments were performed for the selection of stationary phase, organic modifiers, and method parameters. Based on the results of preliminary method conditions, tG-T (gradient time - temperature) 2-D modeling with 4 input runs, and tG-T-tc (gradient time-temperature-ternary composition) 3-D modeling with 12 input runs were designed to build a model for achieving the optimized separation. Modeling of reverse phase separations was based on the measurement of both retention times and peak areas. A design space with appropriate input variables and control strategy was established prior to optimization and robustness evaluation following the quality by design framework. DryLabⓇ was used to predict the optimized gradient profile and separation temperature. The robustness evaluation was carried out using the multiple factors at a time approach and the control space was established. The interdependence of control space and the control strategy was demonstrated by evaluating method robustness using two levels of system suitability criteria. The predictive accuracy of the retention modeling was established through experimental verification of the in-silico predictions. The quality by design based method development approach demonstrated the in-silico optimization as an integral component of reverse-phase chromatographic method development to evaluate the interplay of factors such as organic modifiers, separation temperature and gradient time, which greatly integrated and enhanced method robustness during method development.

Method development and validation for simultaneous estimation of amlodipine and Olmesartan in combined tablet dosage form by using RP-HPLC

The objective of the current study was to develop a simple, accurate, precise and rapid RP-HPLC method with subsequently validate as per ICH guidelines for the determination of Amlodipine (AML) and Olmesartan (OLM) using mobile phase [mixture of acetonitrile and methanol in the ratio of 60:40] as the solvent. The proposed method involves the measurement of Retention time at selected analytical wavelength. 260.0 nm was selected as the analytical wavelength. The retention time of AML and OLM was found to be 3.351 and 1.833 respectively. The linearity of the proposed method was investigated in the range of 5-25 µg/ml (r2 = 0.9999) for AML and 10-50 µg/ml (r2 = 0.9998) for OLM respectively. The method was statistically validated for its linearity, accuracy and precision. Both inter-day and intra-day variation was found to be showing less % RSD (Relative Standard Deviation) value indicating high grade of precision of the method.

Abstract 3122: Metabolic dysregulation and risk of non-alcoholic fatty liver disease in Mexican adults

Abstract Background: Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease and the fastest growing cause of cirrhosis in the United States (U.S.). This is very concerning because NAFLD-related cirrhosis is associated with hepatocellular carcinoma (HCC), the most common form of liver cancer. Latinos have the highest prevalence of NAFLD in the U.S., and the second highest incidence of and mortality from liver cancer, after American Indians. Known risk factors for NAFLD include obesity, metabolic syndrome, diabetes, and insulin resistance. Less is known about how specific metabolites may contribute to increased liver cancer susceptibility among Latinos despite the disproportionate burden of disease in this population. Methods: Using existing clinical data and biospecimens obtained from a longitudinal study in Mexico, we examined the association between metabolic dysregulation and NAFLD in a sample of Mexican adults. A nested case-control analysis was conducted using 100 cases of NAFLD and 100 healthy controls. Risk of NAFLD was assessed using metabolic markers supplemented by clinical data. NAFLD cases were clinically confirmed by a hepatologist using elevated liver enzyme tests (ALT >40 UI/L or AST >40 UI/L) and ultrasound of the liver, after excluding heavy or binge drinking (>2 drinks per day for males, >1 drink per day for females). 159 targeted metabolites were detected with a Thermo Scientific Q Exactive mass spectrometer run with polarity switching on full scan mode with a 65-975 m/z range. TraceFinder Software 4.1 (Thermo Scientific) was used to quantify metabolites using retention time and accurate mass measurements (< 5 ppm). Data analysis was carried out using in-house R scripts. Principal component analysis was constructed from metabolites identified as significant (p<0.05) using a Multiple Analysis of Covariance comparing the healthiest controls in our cohort (without diabetes or metabolic syndrome, n=46) to the least healthy cases (with diabetes and metabolic syndrome, n=24). Results: Out of 159 metabolites assessed, we found 25 metabolites to be significantly different between the groups after adjusting for age and sex. After further Bonferroni correction for multiple comparisons, eight were significantly increased in cases: Aconitate, Gluconic Acid, Glucose, Hexose Phosphate, Malate, and Phosphate; while two had significantly lower levels: Guanine and Inosine. Our findings indicate distinguishable changes in the serum metabolites of patients with NAFLD, which appear to be associated with more metabolic dysregulation. Conclusions: Our results support the use of mass spectrometry-based metabolomics as an appropriate tool to identify serum metabolite signatures associated with NAFLD disease progression. This tool may be useful in developing targeted liver cancer prevention strategies. These findings should be validated in larger studies that examine the trafficking of these identified prognostic metabolites through the liver. Citation Format: Yvonne N. Flores, Gerardo J. Sanchez, Johanna ten Hoeve, Aryana T. Amoon, Thomas Graeber, Beth A. Glenn, Folasade P. May, Francisco Durazo, Zuo-Feng Zhang, Jorge Salmerón, Brad H. Pollock, Roshan Bastani. Metabolic dysregulation and risk of non-alcoholic fatty liver disease in Mexican adults [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3122.

QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics.

The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A number of studies have applied machine learning to predict retention times, but applying a published machine learning model to different lab conditions is difficult. This is due to variation between chromatographic equipment, methods, and columns used for analysis. Recreating a machine learning model is likewise difficult without a dedicated bioinformatician. Herein we present QSRR Automator, a software package to automate retention time prediction model creation and demonstrate its utility by testing data from multiple chromatography columns from previous publications and in-house work. Analysis of these data sets shows similar accuracy to published models, demonstrating the software’s utility in metabolomic and lipidomic studies.

Biotransformation of phytoestrogens from soy in enzymatically characterized liver microsomes and primary hepatocytes of Atlantic salmon.

Efficient aquaculture is depending on sustainable protein sources. The shortage in marine raw materials has initiated a shift to "green aquafeeds" based on staple ingredients such as soy and wheat. Plant-based diets entail new challenges regarding fish health, product quality and consumer risks due to the possible presence of chemical contaminants, natural toxins and bioactive compounds like phytoestrogens. Daidzein (DAI), genistein (GEN) and glycitein (GLY) are major soy isoflavones with considerable estrogenic activities, potentially interfering with the piscine endocrine system and affecting consumers after carry-over. In this context, information on isoflavone biotransformation in fish is crucial for risk evaluation. We have therefore isolated hepatic fractions of Atlantic salmon (Salmo salar), the most important species in Norwegian aquaculture, and used them to study isoflavone elimination and metabolite formation. The salmon liver microsomes and primary hepatocytes were characterized with respect to phase I cytochrome P450 (CYP) and phase II uridine-diphosphate-glucuronosyltransferase (UGT) enzyme activities using specific probe substrates, which allowed comparison to results in other species. DAI, GEN and GLY were effectively cleared by UGT. Based on the measurement of exact masses, fragmentation patterns, and retention times in liquid chromatography high-resolution mass spectrometry, we preliminarily identified the 7-O-glucuronides as the main metabolites in salmon, possibly produced by UGT1A1 and UGT1A9-like activities. In contrast, the production of oxidative metabolites by CYP was insignificant. Under optimized assay conditions, only small amounts of mono-hydroxylated DAI were detectable. These findings suggested that bioaccumulation of phytoestrogens in farmed salmon and consumer risks from soy-containing aquafeeds are unlikely.

RP-HPLC Method for estimation of Alogliptin and Glibenclamide in Synthetic mixture

The objective of the current study was to develop simple, accurate, precise and rapid RP-HPLC method with subsequently validate as per ICH guidelines for the determination of Alogliptin benzoate and Glibenclamide hydrochloride using mobile phase [mixture of Acetonitrile: Phosphate buffer pH-3.6 and in the ratio of 65:35.The proposed method involves the measurement of Retention time at selected analytical wavelength. 240.0 nm. The retention time of Alogliptin benzoate (ALO) and Glibenclamide was found to be 5.055 and 2.838 respectively. The linearity of the proposed method was investigated in the range of 1-5 µg/ml (r = 0.9998) for ALO and 10-50µg/ml (r = 0.9999) for MET respectively. The method was statistically validated for linearity, accuracy and precision. Both inter-day and intra-day variation was found to be showing less % RSD (Relative Standard Deviation) value indicating high grade of precision of the method.

Monolithic Column Ion-Pair Chromatography with Indirect Ultraviolet Detection for the Determination of Three Acid Radical Anions Containing Fluorine in Ionic Liquids

A rapid ion-pair chromatographic method was developed on a monolithic column for the determination of trifluoroacetate, trifluoromethanesulfonate, and tetrafluoroborate. The three anions were successfully detected using indirect ultraviolet detection. These analyte anions were separated using a tetrabutylammonium hydroxide - p-toluenesulfonic acid – acetonitrile mobile phase on a silica-based monolithic column with an octadecyl functional group. The effects of detection wavelength, mobile phase, column temperature and flow rate on the retention of the anions were investigated. The chromatographic conditions were optimized and the retention properties were evaluated. Under the selected optimal conditions, the successful separation of the anions was achieved within 3.5 min. The detection limits were less than 1.0 mg/L for trifluoroacetate, trifluoromethanesulfonate, and tetrafluoroborate. The relative standard deviations for five repeated measurement of retention time and peak area were no more than 0.2%. The linear ranges extended across two orders of magnitude. The three anions in synthetic ionic liquid samples were successfully separated and detected by this method. The results show that the recoveries of this method were between 94.0% and 99.0%. The method was rapid, simple, and easy to use.

Oxygen‐Vacancy Induced Resistive Switching Effect in Mn‐Doped ZnO Memory Devices

The bipolar resistive switching behavior of Pt/Mn‐doped ZnO/InZnO memory devices is investigated in this study, and evidence has been found that this switching effect is due to defects. X‐ray photoelectron spectra indicate that significant amounts of oxygen‐vacancy defects are present in the Mn‐doped ZnO memory device. Superior bipolar resistive switching behavior has been observed in Mn‐doped ZnO memory devices. In contrast, this switching behavior is not present in the undoped ZnO memory device. Based on endurance and retention time measurements, these devices also show excellent reliability and stability, and the enhanced bipolar resistive switching behavior is consistent with changes in oxygen‐vacancy concentration. Especially, the resistive switching effect can be attributed to oxygen vacancy conductive filaments is found by depth‐profiling XPS spectra. These results clearly illustrate that oxygen vacancies are instrumental to the bipolar resistive switching effect in ZnO‐based memory devices. The bipolar resistive switching effect can therefore be attributed to the formation of oxygen‐vacancy defect conductive filaments. This study obviously demonstrate that high‐performance ZnO‐based memory devices can be fabricated by incorporating Mn.

New Photodegradation Products of the Fungicide Fluopyram: Structural Elucidation and Mechanism Identification.

Identifying the fate of agrochemicals is important to understand their potential risk for living organisms. We report here new photodegradation products (PPs) of the fungicide fluopyram. The PPs were produced by irradiating a fluopyram standard in 0.1% acetonitrile aqueous media by a 150-W medium pressure Hg-lamp that emits wavelengths between 200–280 nm. The structural elucidation of PPs was achieved by combining the retention time, isotopic pattern, targeted fragmentation, and accurate mass measurements using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high resolution-MS (HRMS). In addition to previously known PPs, seven new PPs of fluopyram were identified in this work: mainly dihydroxyl and hydroxylimide fluopyram as well as mono, di, and trihydroxyl lactam. Additionally, two PPs were found to be formed by rearrangement after the loss of H2C=CH2. Hence, the results of the work contribute to extending the current knowledge regarding the photoinduced fate of agrochemicals, and fluopyram in particular.

Liquid-chromatography retention order prediction for metabolite identification.

Liquid Chromatography (LC) followed by tandem Mass Spectrometry (MS/MS) is one of the predominant methods for metabolite identification. In recent years, machine learning has started to transform the analysis of tandem mass spectra and the identification of small molecules. In contrast, LC data is rarely used to improve metabolite identification, despite numerous published methods for retention time prediction using machine learning. We present a machine learning method for predicting the retention order of molecules; that is, the order in which molecules elute from the LC column. Our method has important advantages over previous approaches: We show that retention order is much better conserved between instruments than retention time. To this end, our method can be trained using retention time measurements from different LC systems and configurations without tedious pre-processing, significantly increasing the amount of available training data. Our experiments demonstrate that retention order prediction is an effective way to learn retention behaviour of molecules from heterogeneous retention time data. Finally, we demonstrate how retention order prediction and MS/MS-based scores can be combined for more accurate metabolite identifications when analyzing a complete LC-MS/MS run. Implementation of the method is available at https://version.aalto.fi/gitlab/bache1/retention_order_prediction.git.

Comparison of measured and recommended acceptance criteria for the analysis of seized drugs using Gas Chromatography–Mass Spectrometry (GC–MS)

Gas Chromatography–Mass Spectrometry (GC–MS) is a widely used analytical technique that has become a critical tool in many industries, including forensic science. Many governing bodies provide recommendations for the uncertainty of measurement for chemical substance identification, but existing guidelines often do not provide the numerical data to support the basis for their acceptance criteria. The guidelines therefore appear anecdotal and, if they are not continually updated, may not reflect modern instrument capabilities. This study provides data, with detailed interpretations, to assess the magnitudes and sources of measurement uncertainties of typical GC–MS data, as commonly practiced.Data analysis was conducted using 13 different drug standards from three different laboratories using five different GC–MS setups. The laboratories were not prescribed a set of instrumental parameters, but rather were asked to submit the parameters ordinarily practiced within their respective laboratories. An expanded uncertainty of two times the relative standard deviation (2σ) of replicate measurements was used to report the uncertainty of measurement for the retention time and relative ion abundance measurements made on each set-up.The retention time acceptance criteria currently recommended by many agencies are on the magnitude of ±2%, but such criteria are much wider than the measured within-week or within-month 2σ values, which are actually on the magnitude of ±0.20%. The measured uncertainties of relative ion abundances are similar to recommended acceptance criteria, but a careful assessment shows that ion abundances are not independently variable within a spectrum. Some ion abundances correlate with correlation co-efficients (R squared) that exceed 0.9. Acceptance criteria for the GC retention time measurements should therefore be stricter than most of the current recommended guidelines. The application of tighter acceptance criteria would provide: 1) an evidenced-based, statistical reason for making drug identifications; and 2) fewer type I errors (false positives) in seized drug analyses than provided by existing standards.

Evaluation of energy barrier of CoFeB/MgO magnetic tunnel junctions with perpendicular easy axis using retention time measurement

We investigate the energy barrier E that determines the thermal stability factor Δ, of CoFeB/MgO magnetic tunnel junctions (MTJs) with a perpendicular easy axis by retention time measurement as a function of temperature T and junction diameter D. E decreases with increasing T for all the studied MTJs. The temperature at which any particular value of E is obtained tends to decrease with decreasing D, indicating that the magnetization reversal in the MTJs is described by reversal models other than the nucleation model. We find that the temperature dependence of E correlates with that of spontaneous magnetization through the power law scaling relationship, which enables us to determine Δ at temperatures different from those used in the retention time measurement.

Multilevel conductance switching and carrier transport mechanisms of memory devices based on an ITO/PVK:Ag nanoparticles/Al structure

Multilevel conductance switching was achieved using silver nanoparticles (Ag NPs) embedded in poly(9-vinylcarbazole) (PVK) with a structure of ITO/PVK:Ag NPs/Al. The current-voltage (I-V) curves of the memory devices at low reading voltages showed three distinguished states of current. The memory devices exhibited non-volatile rewritable memory characteristics. The carrier transport mechanisms of the devices in each state were analyzed by theoretical models based on the experimental I-V data. In addition, retention time measurements showed clearly three current states with good data retention properties. From the retention times test, the average values of ON/OFF, ON/intermediate (INTERM) and INTERM/OFF current ratios of the memory devices were 1.7 × 106, 3.5 × 102 and 5.0 × 103, respectively.