ABSTRACT
Urinary tract infections (UTIs) are a major global health problem and are caused predominantly by uropathogenic Escherichia coli (UPEC). UTIs are a leading cause of prescription antimicrobial use. Incessant increase in antimicrobial resistance in UPEC and other uropathogens poses a serious threat to the current treatment practices. Copper is an effector of nutritional immunity that impedes the growth of pathogens during infection. We hypothesized that copper would augment the toxicity of select small molecules against bacterial pathogens. We conducted a small molecule screening campaign with a library of 51,098 molecules to detect hits that inhibit a UPEC ΔtolC mutant in a copper-dependent manner. A molecule, denoted as E. coli inhibitor or ECIN, was identified as a copper-responsive inhibitor of wild-type UPEC strains. Our gene expression and metal content analysis results demonstrate that ECIN works in concert with copper to exacerbate Cu toxicity in UPEC. ECIN has a broad spectrum of activity against pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus. Subinhibitory levels of ECIN eliminate UPEC biofilm formation. Transcriptome analysis of UPEC treated with ECIN reveals induction of multiple stress response systems. Furthermore, we demonstrate that L-cysteine rescues the growth of UPEC exposed to ECIN. In summary, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC.IMPORTANCEUrinary tract infection (UTI) is a ubiquitous infectious condition affecting millions of people annually. Uropathogenic Escherichia coli (UPEC) is the predominant etiological agent of UTI. However, UTIs are becoming increasingly difficult to resolve with antimicrobials due to increased antimicrobial resistance in UPEC and other uropathogens. Here, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC. In addition to E. coli, this small molecule also inhibits pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus.
Subject(s)
Anti-Bacterial Agents , Copper , Microbial Sensitivity Tests , Urinary Tract Infections , Uropathogenic Escherichia coli , Uropathogenic Escherichia coli/drug effects , Uropathogenic Escherichia coli/genetics , Copper/pharmacology , Anti-Bacterial Agents/pharmacology , Urinary Tract Infections/microbiology , Urinary Tract Infections/drug therapy , Small Molecule Libraries/pharmacology , Methicillin-Resistant Staphylococcus aureus/drug effects , Methicillin-Resistant Staphylococcus aureus/genetics , Gene Expression Regulation, Bacterial/drug effects , Escherichia coli Proteins/genetics , Escherichia coli Proteins/metabolism , Escherichia coli Proteins/antagonists & inhibitors , Pseudomonas aeruginosa/drug effects , Pseudomonas aeruginosa/genetics , Acinetobacter baumannii/drug effects , Acinetobacter baumannii/genetics , Escherichia coli Infections/microbiology , Escherichia coli Infections/drug therapyABSTRACT
Approximately one-in-ten reproductive age adults in the USA follow a plant-based diet, yet there is limited information on the influence of vegan and vegetarian diets on the mineral composition of breast milk. This study explored the major and trace mineral composition in breast milk and associations with maternal diet patterns. We used a cross-sectional design to collect a single sample of breast milk from individuals following vegan (n 23), vegetarian (n 19) and omnivore (n 21) diet patterns. Plant-based diet (n 42) was defined as following either vegan or vegetarian diets. Sixteen minerals were assessed using inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry. Data were evaluated using traditional statistical techniques and five different machine learning approaches. The distribution of Se (median; quartile 1 and 3) was significantly different between groups (vegetarians 21, 18-26 µg/l; vegans 19, 18-25 µg/l and omnivores 17, 14-20 µg/l; P = 0·007) using a Kruskal-Wallis test. Machine learning techniques also identified Se as a potential biomarker for differentiating breast milk by maternal diet pattern. Individuals following a plant-based diet generally had a lower BMI, higher breast milk Se and lower breast milk I and Fe concentrations compared with those following omnivore diets. This suggests that maternal dietary pattern (plant-based v. omnivore) may be helpful clinical information to consider when caring for the breast-feeding dyad, with the strongest evidence related to differences in Se concentration.
Subject(s)
Trace Elements , Vegans , Adult , Humans , Female , Lactation , Cross-Sectional Studies , Diet , Diet, Vegan , Diet, Vegetarian , Vegetarians , Milk, Human/chemistryABSTRACT
Copper and superoxide are used by the phagocytes to kill bacteria. Copper is a host effector encountered by uropathogenic Escherichia coli (UPEC) during urinary tract infection in a non-human primate model, and in humans. UPEC is exposed to higher levels of copper in the gut prior to entering the urinary tract. Effects of pre-exposure to copper on bacterial killing by superoxide has not been reported. We hypothesized that copper-replete E. coli is more sensitive to killing by superoxide in vitro, and in activated macrophages. We utilized wild-type UPEC strain CFT073, and its isogenic mutants lacking copper efflux systems, superoxide dismutases (SODs), regulators of a superoxide dismutase, and complemented mutants to address this question. Surprisingly, our results reveal that copper protects UPEC against killing by superoxide in vitro. This copper-dependent protection was amplified in the mutants lacking copper efflux systems. Increased levels of copper and manganese were detected in UPEC exposed to sublethal concentration of copper. Copper activated the transcription of sodA in a SoxR- and SoxS-dependent manner resulting in enhanced levels of SodA activity. Importantly, pre-exposure to copper increased the survival of UPEC within RAW264.7 and bone marrow-derived murine macrophages. Loss of SodA, but not SodB or SodC, in UPEC obliterated copper-dependent protection from superoxide in vitro, and from killing within macrophages. Collectively, our results suggest a model in which sublethal levels of copper trigger the activation of SodA and SodC through independent mechanisms that converge to promote the survival of UPEC from killing by superoxide. A major implication of our findings is that bacteria colonizing copper-rich milieus are primed for efficient detoxification of superoxide.
Subject(s)
Copper/pharmacology , Escherichia coli Infections/drug therapy , Host-Pathogen Interactions/drug effects , Superoxide Dismutase/metabolism , Superoxides/toxicity , Urinary Tract Infections/drug therapy , Uropathogenic Escherichia coli/drug effects , Animals , Escherichia coli Infections/chemically induced , Escherichia coli Infections/microbiology , Female , Gene Expression Regulation, Bacterial , Mice , Mice, Inbred C57BL , Mice, Inbred CBA , Superoxide Dismutase/genetics , Urinary Tract Infections/chemically induced , Urinary Tract Infections/microbiologyABSTRACT
The extrapolation approach, traditionally used with standard additions (SA), is compared with the alternative strategies of interpolation, reversed-axis, and normalization. The interpolation approach is based on employing twice the analytical signal recorded for the sample (ysam) to determine an unknown analyte concentration. In the reversed-axis strategy, x- and y-axes are swapped when building the SA calibration plot to facilitate uncertainty estimation. A new strategy, based on signal normalization using ysam, is also described and compared to the other approaches. Results from 3 instrumental methods, 396 sample replicates, 16 analytes, and 2 certified reference materials are included in this study. For most applications, all four SA approaches provide statistically similar trueness and precision. However, extrapolation and reversed-axis provide more consistent values (within narrower ranges) than the other strategies when employing inductively coupled plasma optical emission spectrometry (ICP OES). On the other hand, normalization provides better trueness for the less robust method of microwave-induced plasma OES (MIP OES), as it is capable of minimizing systematic errors associated with different points of the calibration curve. Normalization is particularly useful for quickly processing data, without the need for inspecting each individual calibration plot to identify outlying points. Reversed-axis and normalization are the most adequate approaches for SA applications involving MIP OES and ICP-based methods. In addition to providing similar accuracies to the traditional extrapolation approach, these strategies present the advantage of a simple uncertainty estimation, which can be easily calculated using commonly available software such as Microsoft Excel and R.
ABSTRACT
BACKGROUND: Precisely how silver nanoparticles (AgNPs) kill mammalian cells still is not fully understood. It is not clear if AgNP-induced damage differs from silver cation (Ag+), nor is it known how AgNP damage is transmitted from cell membranes, including endosomes, to other organelles. Cells can differ in relative sensitivity to AgNPs or Ag+, which adds another layer of complexity to identifying specific mechanisms of action. Therefore, we determined if there were specific effects of AgNPs that differed from Ag+ in cells with high or low sensitivity to either toxicant. METHODS: Cells were exposed to intact AgNPs, Ag+, or defined mixtures of AgNPs with Ag+, and viability was assessed. The level of dissolved Ag+ in AgNP suspensions was determined using inductively coupled plasma mass spectrometry. Changes in reactive oxygen species following AgNP or Ag+ exposure were quantified, and treatment with catalase, an enzyme that catalyzes the decomposition of H2O2 to water and oxygen, was used to determine selectively the contribution of H2O2 to AgNP and Ag+ induced cell death. Lipid peroxides, formation of 4-hydroxynonenol protein adducts, protein thiol oxidation, protein aggregation, and activation of the integrated stress response after AgNP or Ag+ exposure were quantified. Lastly, cell membrane integrity and indications of apoptosis or necrosis in AgNP and Ag+ treated cells were examined by flow cytometry. RESULTS: We identified AgNPs with negligible Ag+ contamination. We found that SUM159 cells, which are a triple-negative breast cancer cell line, were more sensitive to AgNP exposure less sensitive to Ag+ compared to iMECs, an immortalized, breast epithelial cell line. This indicates that high sensitivity to AgNPs was not predictive of similar sensitivity to Ag+. Exposure to AgNPs increased protein thiol oxidation, misfolded proteins, and activation of the integrated stress response in AgNP sensitive SUM159 cells but not in iMEC cells. In contrast, Ag+ cause similar damage in Ag+ sensitive iMEC cells but not in SUM159 cells. Both Ag+ and AgNP exposure increased H2O2 levels; however, treatment with catalase rescued cells from Ag+ cytotoxicity but not from AgNPs. Instead, our data support a mechanism by which damage from AgNP exposure propagates through cells by generation of lipid peroxides, subsequent lipid peroxide mediated oxidation of proteins, and via generation of 4-hydroxynonenal (4-HNE) protein adducts. CONCLUSIONS: There are distinct differences in the responses of cells to AgNPs and Ag+. Specifically, AgNPs drive cell death through lipid peroxidation leading to proteotoxicity and necrotic cell death, whereas Ag+ increases H2O2, which drives oxidative stress and apoptotic cell death. This work identifies a previously unknown mechanism by which AgNPs kill mammalian cells that is not dependent upon the contribution of Ag+ released in extracellular media. Understanding precisely which factors drive the toxicity of AgNPs is essential for biomedical applications such as cancer therapy, and of importance to identifying consequences of unintended exposures.
Subject(s)
Metal Nanoparticles , Silver , Animals , Cations , Cell Death , Hydrogen Peroxide/toxicity , Metal Nanoparticles/toxicity , Silver/toxicityABSTRACT
Few schools and child care facilities test for Pb in their drinking water. Reviewing the United States Environmental Protection Agency Lead and Copper rule data can contribute to guiding future legislation on Pb testing. This work aims to (i) identify variations in Pb levels in North Carolina school and child care drinking water by building age, (ii) evaluate the effect of corrosion control measures on reducing these levels, and (iii) evaluate the adequacy of Pb reporting limits according to modern instrumentation. To achieve these objectives, information on 26,608 water samples collected in 206 North Carolina child centers between 1991 and 2019 has been analyzed. Lead concentrations were above a recently proposed 5 µg/L trigger level in 12.3%, 10.4%, 7.5%, and 0.9% of samples from pre-1987, 1987-1990, 1991-2013, and post-2013 buildings, respectively. Thus, recently proposed legislation requiring testing only for pre-1987 (or pre-1991) buildings will fail to identify all centers at risk. The odds that a greater than 5 µg/L Pb level is detected has been decreasing over the years, with a faster decreasing rate for buildings reporting corrosion control. Over 15% of samples report a method detection limit of 5 µg/L. For accurate results, future legislation should require sub-µg/L detection limits, which are easily achievable with commonly available instrumentation.
Subject(s)
Drinking Water , Water Pollutants, Chemical , Child , Child Care , Humans , Lead/analysis , North Carolina , Schools , United States , Water Pollutants, Chemical/analysis , Water SupplyABSTRACT
Multi-isotope calibration (MICal) is a novel approach to calibration for inductively coupled plasma mass spectrometry (ICP-MS). In MICal, only two calibration solutions are required: solution A, composed of 50% v v-1 of sample and 50% v v-1 of a standard solution containing the analytes, and solution B, composed of 50% v v-1 of sample and 50% v v-1 of a blank solution. MICal is based on monitoring the signal intensities of several isotopes of the same analyte in solutions A and B. By plotting the analytical signals from solution A in the x-axis, and from solution B in the y-axis, the analyte concentration in the sample is calculated using the slope of that graph and the concentration of the reference standard added to solution A. As both solutions contain the same amount of sample, matrix-matching is easily achieved. In this proof-of-concept study, MICal was applied to the determination of Ba, Cd, Se, Sn, and Zn in seven certified reference materials with different matrices (e.g., plant materials, flours, and water). In most cases, MICal results presented no statistical difference from the certified values at a 95% confidence level. The new strategy was also compared with traditional calibration methods such as external calibration, internal standardization and standard additions, and recoveries were generally better for MICal. This is a simple, accurate, and fast alternative method for matrix-matching calibration in ICP-MS. Graphical abstract Multi-isotope calibration: fast and innovative matrix-matching calibration for ICP-MS.
ABSTRACT
Urinary tract infection (UTI) is a major global infectious disease affecting millions of people annually. Human urinary copper (Cu) content is elevated during UTI caused by uropathogenic Escherichia coli (UPEC). UPEC upregulates the expression of Cu efflux genes during clinical UTI in patients as an adaptive response to host-derived Cu. Whether Cu is mobilized to urine as a host response to UTI and its role in protection against UTI remain unresolved. To address these questions, we tested the hypothesis that Cu is a host effector mobilized to urine during UTI to limit bacterial growth. Our results reveal that Cu is mobilized to urine during UTI caused by the major uropathogens Proteus mirabilis and Klebsiella pneumoniae, in addition to UPEC, in humans. Ceruloplasmin, a Cu-containing ferroxidase, is found at higher levels in UTI urine than in healthy control urine and serves as the molecular source of urinary Cu during UTI. Our results demonstrate that ceruloplasmin decreases the bioavailability of iron in urine by a transferrin-dependent mechanism. Experimental UTI with UPEC in nonhuman primates recapitulates the increased urinary Cu content observed during clinical UTI. Furthermore, Cu-deficient mice are highly colonized by UPEC, indicating that Cu is involved in the limiting of bacterial growth within the urinary tract. Collectively, our results indicate that Cu is a host effector that is involved in protection against pathogen colonization of the urinary tract. Because urinary Cu levels are amenable to modulation, augmentation of the Cu-based host defense against UTI represents a novel approach to limiting bacterial colonization during UTI.
Subject(s)
Bacteriuria/microbiology , Bacteriuria/urine , Copper/urine , Host-Pathogen Interactions , Urinary Tract/microbiology , Animals , Bacterial Load , Ceruloplasmin/metabolism , Disease Models, Animal , Enzyme Activation , Humans , Ions/urine , Mice , Primates , Stress, Physiological , Urinary Tract/metabolismABSTRACT
Standard dilution analysis (SDA) is a novel calibration method that may be applied to most instrumental techniques that will accept liquid samples and are capable of monitoring two wavelengths simultaneously. It combines the traditional methods of standard additions and internal standards. Therefore, it simultaneously corrects for matrix effects and for fluctuations due to changes in sample size, orientation, or instrumental parameters. SDA requires only 200 s per sample with inductively coupled plasma optical emission spectrometry (ICP OES). Neither the preparation of a series of standard solutions nor the construction of a universal calibration graph is required. The analysis is performed by combining two solutions in a single container: the first containing 50% sample and 50% standard mixture; the second containing 50% sample and 50% solvent. Data are collected in real time as the first solution is diluted by the second one. The results are used to prepare a plot of the analyte-to-internal standard signal ratio on the y-axis versus the inverse of the internal standard concentration on the x-axis. The analyte concentration in the sample is determined from the ratio of the slope and intercept of that plot. The method has been applied to the determination of FD&C dye Blue No. 1 in mouthwash by molecular absorption spectrometry and to the determination of eight metals in mouthwash, wine, cola, nitric acid, and water by ICP OES. Both the accuracy and precision for SDA are better than those observed for the external calibration, standard additions, and internal standard methods using ICP OES.
ABSTRACT
Urinary tract infection (UTI) is a ubiquitous infectious condition, and uropathogenic Escherichia coli (UPEC) is the predominant causative agent of UTI. Copper (Cu) is implicated in innate immunity, including against UPEC. Cu is a trace element utilized as a co-factor, but excess Cu is toxic due to mismetalation of non-cognate proteins. E. coli precisely regulates Cu homeostasis via efflux systems. However, Cu import mechanisms into the bacterial cell are not clear. We hypothesized that Cu import defective mutants would exhibit increased resistance to Cu. This hypothesis was tested in a forward genetic screen with transposon (Tn5) insertion mutants in UPEC strain CFT073, and we identified 32 unique Cu-resistant mutants. Transposon and defined mutants lacking yhiM, which encodes a hypothetical inner membrane protein, were more resistant to Cu than parental strain. Loss of YhiM led to decreased cellular Cu content and increased expression of copA, encoding a Cu efflux pump. The CpxAR envelope stress response system was activated in the ΔyhiM mutant as indicated by increased expression of cpxP. Transcription of yhiM was regulated by CueR and CpxR, and the CpxAR system was essential for increased Cu resistance in the ΔyhiM mutant. Importantly, activation of CpxAR system in the ΔyhiM mutant was independent of NlpE, a known activator of this system. YhiM was required for optimal fitness of UPEC in a mouse model of UTI. Our findings demonstrate that YhiM is a critical mediator of Cu homeostasis and links bacterial adaptation to Cu stress with the CpxAR-dependent envelope stress response in UPEC.IMPORTANCEUPEC is a common bacterial infection. Bacterial pathogens are exposed to host-derived Cu during infection, including UTI. Here, we describe detection of genes involved in Cu homeostasis in UPEC. A UPEC mutant lacking YhiM, a membrane protein, exhibited dramatic increase in resistance to Cu. Our study demonstrates YhiM as a nexus between Cu stress and the CpxAR-dependent envelope stress response system. Importantly, our findings establish NlpE-independent activation of CpxAR system during Cu stress in UPEC. Collectively, YhiM emerges as a critical mediator of Cu homeostasis in UPEC and highlights the interlinked nature of bacterial adaptation to survival during Cu and envelope stress.
Subject(s)
Escherichia coli Infections , Escherichia coli Proteins , Urinary Tract Infections , Uropathogenic Escherichia coli , Animals , Mice , Copper/metabolism , Uropathogenic Escherichia coli/metabolism , Escherichia coli Infections/microbiology , Urinary Tract Infections/microbiology , Escherichia coli Proteins/genetics , Escherichia coli Proteins/metabolism , Membrane Proteins/genetics , Membrane Proteins/metabolism , Bacterial Outer Membrane Proteins/metabolism , Lipoproteins/metabolismABSTRACT
The use of mouthguards is advocated by the American Dental Association for orofacial injury prevention and teeth protection. However, the chemical environment in the mouth may cause harmful substances within the mouthguard's polymer material to leach out and be absorbed by the user. Considering this, the present study for the first time analyzed commercially available mouthguards and disclosed the presence of trace elements. Specifically, an analytical method was developed based on closed-vessel microwave-assisted digestion and plasma-based atomic spectrometry for determining toxic trace elements in mouthguard samples. Initially, 75 elements were assessed and, thereafter, quantified cadmium (Cd), copper (Cu) and lead (Pb) in each sample by inductively coupled plasma mass spectrometry (ICP-MS). Method validation was carried out by analyzing a certified reference material of Low-Density Polyethylene, and by addition and recovery experiments. Results for copper were further validated by ICP optical emission spectrometry (ICP-OES). While most samples exhibited elemental levels beneath the method's limit of quantification, Cd, Cu and Pb were detected in four samples. Remarkably, one sample had Cu levels exceeding safe limits by 109 times, highlighting potential toxicity risks. This initial research underscores the need for stricter contamination control in mouthguard materials to minimize potentially health hazards.
Subject(s)
Cadmium , Mouth Protectors , Trace Elements , Trace Elements/analysis , Cadmium/analysis , Copper/analysis , Spectrophotometry, Atomic , Lead/analysisABSTRACT
Purpose: Breast milk iodine concentration (BMIC) from vegan and vegetarian lactating mothers has not previously been evaluated. The goal of this study was to assess BMIC from vegans, vegetarians, and omnivores and to assess intake of iodine by breastfed infants. Materials and Methods: Breast milk samples from vegans (n = 12), vegetarians (n = 6), and omnivores (n = 12) living in the United States were analyzed. BMIC was determined at the mass-to-charge ratio (m/z) 127 by inductively coupled plasma mass spectrometry (ICP-MS) using an Agilent 8800 ICP-MS/MS (Agilent Technologies). Results: There was a significant difference in mean BMIC between participants following a plant-based diet (vegan and vegetarian, n = 18) compared with omnivores [4.42 versus 5.02 Ln(BMIC), respectively; p = 0.0405]. In linear regression to predict BMIC, vegan diet was a negative predictor (standardized ß = -0.409) and use of multi- or prenatal supplements was a positive predictor (standardized ß = 0.319). There were differences in the percentage of inadequate BMIC per maternal diet (75% vegan, 67% vegetarian, omnivore 58%) but this did not reach statistical significance. In 67% of the samples (20/30) BMIC was lower than the National Academy of Medicine's adequate intake (AI), assuming infant milk consumption of 0.78 L/day. Conclusions: Most samples from vegans and vegetarians contained a lower BMIC than AI for infants 0-6 months. Counseling of pregnant vegans and vegetarians should highlight importance of iodine supplementation during lactation. The findings are based on a small number of samples, especially for vegetarians, and thus, they need to be confirmed by larger studies.
Subject(s)
Iodine , Milk, Human , Infant , Female , Humans , Milk, Human/chemistry , Vegans , Diet, Vegan , Lactation , Prevalence , Tandem Mass Spectrometry , Breast Feeding , Diet , VegetariansABSTRACT
Background: The effects of coronavirus disease 2019 (COVID-19) remain a global public health emergency because of the ensuing economic burden and death. With robust research into vaccines, antibody treatments, and antiviral drugs for COVID-19, there is still a dearth of evidence on the role of an individual's nutritional status on the severity of COVID-19. Objective: This study aimed to investigate the association between selenium (Se) and zinc (Zn) status and COVID-19 severity among individuals diagnosed with COVID-19 in North Carolina. Methods: Subjects (n = 106) were recruited remotely as part of the Nutrition and COVID-19 in North Carolina (NC-NC) study and filled out online screening questionnaires and dietary surveys. Toenail samples from 97 participants were analyzed to determine Se and Zn concentrations. To assess the severity of severe acute respiratory coronavirus (SARS-CoV)-2 infection, subjects were asked about the presence and duration of 10 commonly reported symptoms. These responses were used to calculate a COVID-19 severity index (CSI). The relationship between Se and Zn status (intake and toenail concentrations) and CSI was explored using a regression analysis. Results: Our results showed that the median (25th, 75th percentiles) dietary Se and Zn intake from selected food sources were 65.2 µg (43.2, 112.9) and 4.3 mg (1.8, 8), respectively. Headache, cough, loss of smell or taste, and fever were reported by at least half of the participants. In stepwise regression analysis, among individuals with low Se and Zn intake (below the median), Se intake was inversely associated with increasing CSI (ß = -0.66; 95% CI: -1.21, -0.11; P = 0.02). Conclusions: Findings from this study support a potential benefit of increasing the intake of dietary Se to mitigate the severity of SARS-CoV-2 infection.
ABSTRACT
Nickel-metal hydride batteries (NiMH) are a secondary source of high aggregate value elements, such as nickel, manganese, cobalt, and rare earths, for which recycling typically involves acid lixiviation. Designing the recycling process requires accurate determination of the elements in the leachates, which is hindered by the high complexity of the matrix. In the present study, microwave-induced plasma atomic emission spectrometry (MIP-OES) was selected as the quantitative method for elemental analysis because of its environment friendliness and cost-effectiveness. Multi-energy calibration (MEC) was also pioneeringly evaluated to circumvent matrix effects and simplify the determination of Ce, La, Ni, Co, and Mn in sulfuric acid leachates of NiMH batteries by MIP-OES. The method's analytical performance and accuracy were critically compared with external standard calibration and the standard additions method. MEC yielded superior results, with analyte recoveries within 90-110%, precision (coefficients of variation) from 1.8% to 5.8%, and limits of detection of 10, 20, 1, 400, and 60 µg kg-1 for Ni, La, Mn, Ce, and Co, respectively. The results demonstrated the ability of MEC-MIP-OES to minimize matrix effects, as well as simplify and speed up the analysis of NiMH battery leachates, which is compatible with this high-demand analytical application.
ABSTRACT
Adv. Mater. 2018, 30, 1705796 https://doi.org/10.1002/adma.201705796 The above article, published online on January 15, 2018, in Wiley Online Library (https://doi.org/10.1002/adma.201705796), has been retracted by agreement between the authors, the journal Editor in Chief Jos Lenders, and Wiley-VCH GmbH. The retraction has been agreed on following concerns raised by a third party and a subsequent investigation at Wake Forest University. Data integrity issues were found in Figures 1a, S2b, and S17. As a result, the authors consider the conclusions of this article invalid.
ABSTRACT
Several species are simultaneously used for internal standardization to improve accuracy in inductively coupled plasma optical emission spectrometry (ICP-OES). In multi-internal standard calibration (MISC), signal ratios between the analyte and each of several internal standard species are used for calibration. A single calibration solution is required, and the MISC graph is built with intensity ratios calculated with analytical signals recorded for the sample (IA,sam) on the y-axis, while those recorded for the calibration standard (IA,std) are plot on the x-axis (i.e. IA,sam/IIS(i)vs. IA,std/IIS(i), where IIS(i) represents the signal intensity for a given internal standard species). Nine analytes (As, Cd, Cr, Cu, Fe, Mg, Mn, Pb and Zn), and two sets of internal standard species (i.e. Bi, Ge, In, Rh, Sc, Te, Tl and Y in solution, or eighteen emission lines from plasma naturally occurring Ar) were evaluated in this proof-of-concept study. The MISC method's efficiency was evaluated by analyte addition and recovery experiments and by analyzing two certified reference materials. Figures of merit for MISC (limit of detection, repeatability and trueness) were comparable to those obtained for the traditional external standard calibration (EC) and internal standard (IS) methods. Different from IS, MISC requires no time-consuming study to identify an ideal internal standard species, and signal biases are minimized by an averaged, more encompassing internal standardization effect.
Subject(s)
Calibration , Reference Standards , Spectrum AnalysisABSTRACT
Raman spectroscopy (RS) was used to identify and quantify different nitrogen species in fertilizers. This is a fast and inexpensive method that requires no extensive sample preparation. Urea and nitrate were determined at 1000 and 1045 cm-1, respectively. Calibration plots obtained for these analytes showed adequate linearity, with regression coefficients (r) of 0.9989 and 0.9976, respectively. Ammonium was determined by difference after total N determination by high-resolution continuum source flame molecular absorption spectrometry (HR-CS FMAS), which provided a calibration plot with r = 0.9960. The inline coupling of RS and HR-CS FMAS allowed for a fast sequential determination of ammonium, nitrate, and urea, with limits of detection of 0.03 mg/L ammonium, 0.03 mg/L nitrate, and 0.01 mg/L urea. Relative standard deviations were ≤ 11 %, and the external standard calibration method provided accurate results for all analytes determined in certified reference materials, raw materials, and commercial samples of fertilizers. For comparison purposes, all samples were also analyzed by traditional Kjeldahl method. The RS HR-CS FMAS method was further validated by addition and recovery experiments, which provided recoveries in the 93 - 113 % range.
Subject(s)
Ammonium Compounds , Fertilizers , Fertilizers/analysis , Nitrates , Nitrogen/analysis , Organic Chemicals , Spectrophotometry, Atomic/methods , Spectrum Analysis, Raman , UreaABSTRACT
The contamination of water sources by anthropogenic activities is a topic of growing interest in the scientific community. Therefore, robust analytical techniques for the determination and quantification of multiple substances are needed, which often require complex and time-consuming procedures. In this context, we describe a univariate calibration method to determine emerging multi-class contaminants in different water sources. The instrumental setup is composed of a lab-made glass electrochemical cell with three electrodes: Pt counter, Ag/AgCl reference, and BDD working electrodes. With this system, we were able to simultaneously quantify tert-butylhydroquinone, acetaminophen, estrone, sulfamethoxazole, enrofloxacin, caffeine, and ibuprofen by differential pulse voltammetry. Only two calibration solutions are required for the Single-shot Dilution Differential Pulse Voltammetric Calibration (SSD-DP-VC) method described here, which can significantly improve sample throughput. Two robust univariate calibration strategies were also applied and compared with SSD-DP-VC. The new method is simple, fast, and comparable with traditional calibration methods, showing similar precision and accuracy for all determinations evaluated.
Subject(s)
Boron , Diamond , Acetaminophen , Calibration , ElectrodesABSTRACT
Tungsten coil atomic emission spectrometry is an ideal technique for field applications because of its simplicity, low cost, low power requirement, and independence from cooling systems. A new, portable, compact design is reported here. The tungsten coil is extracted from an inexpensive 24 V, 250 W commercial light bulb. The coil is housed in a small, aluminum cell. The emission signal exits from a small aperture in the cell, while the bulk of the blackbody emission from the tungsten coil is blocked. The resulting spectra exhibit extremely low background signals. The atomization cell, a single lens, and a hand-held charge coupled device (CCD) spectrometer are fixed on a 1 × 6 × 30 cm ceramic base. The resulting system is robust and easily transported. A programmable, miniature 400 W solid-state constant current power supply controls the temperature of the coil. Fifteen elements are determined with the system (Ba, Cs, Li, Rb, Cr, Sr, Eu, Yb, Mn, Fe, Cu, Mg, V, Al, and Ga). The precision ranges from 4.3% to 8.4% relative standard deviation for repetitive measurements of the same solution. Detection limits are in the 0.04 to 1500 µg/L range. Accuracy is tested using standard reference materials for polluted water, peach leaves, and tomato leaves. For those elements present above the detection limit, recoveries range from 72% to 147%.
ABSTRACT
Supervised and unsupervised machine learning methods are used to evaluate matrix effects caused by carbon and easily ionizable elements (EIEs) on analytical signals of inductively coupled plasma optical emission spectrometry (ICP OES). A simple experimental approach was used to produce a series of synthetic solutions with varying levels of matrix complexity. Analytical lines (nâ¯=â¯29), with total line energies (Esum) in the 5.0-15.5â¯eV range, and non-analyte signals (nâ¯=â¯24) were simultaneously monitored throughout the study. Labeled (supervised learning) and unlabeled (unsupervised learning) data on normalized non-analyte signals (from plasma species) were used to train machine learning models to characterize matrix effect severity and predict analyte recoveries. Dimension reduction techniques, including principal component analysis, uniform manifold approximation and projection and t-distributed stochastic neighborhood embedding, were able to provide visual and quantitative representations that correlated well with observed matrix effects on low-energy atomic and high-energy ionic emission lines. Predictive models, including partial least squares regression and generalized linear models fit with the elastic net penalty, were tuned to estimate analyte recovery error when using the external standard calibration method (EC). The best predictive results were found for high-energy ionic analytical lines, e.g. Zn II 202.548â¯nm (Esumâ¯=â¯15.5â¯eV), with accuracy and R2 of 0.970 and 0.856, respectively. Two certified reference materials (CRMs) were used for method validation. The strategy described here may be used for flagging compromising matrix effects, and complement method validation based on addition/recovery experiments and CRMs analyses. Because the data analysis workflows feature signals from plasma-based species, there is potential for developing instrument software capable of alerting users in real time (i.e. before data processing) of inaccurate results when using EC.