Commercially available mouthguards: Unearthing trace elements for the first time.

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.

The inner membrane protein YhiM links copper and CpxAR envelope stress responses in uropathogenic E. coli.

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.

Multi-energy calibration for determining critical metals in nickel-metal hydride battery residues by microwave-induced plasma atomic emission spectrometry.

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.

Retraction: Colloidal Cobalt Phosphide Nanocrystals as Trifunctional Electrocatalysts for Overall Water Splitting Powered by a Zinc-Air Battery.

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.

COVID-19 Severity Is Associated with Selenium Intake among Young Adults with Low Selenium and Zinc Intake in North Carolina.

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.

Major and trace mineral composition of milk from lactating women following vegan, vegetarian and omnivore diets.

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.

Prevalence and Predictors of Low Breast Milk Iodine Concentration in Women Following Vegan, Vegetarian, and Omnivore Diets.

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.

Raman spectroscopy coupled to high-resolution continuum source flame molecular absorption spectrometry for sequential determination of nitrogen species in fertilizers.

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.

Simultaneous quantification of seven multi-class organic molecules by single-shot dilution differential pulse voltammetric calibration.

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.

Multi-internal standard calibration applied to inductively coupled plasma optical emission spectrometry.

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.

The mechanism of cell death induced by silver nanoparticles is distinct from silver cations.

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.

Copper Resistance Promotes Fitness of Methicillin-Resistant Staphylococcus aureus during Urinary Tract Infection.

Urinary tract infection (UTI) is one of the most common infectious conditions affecting people in the United States and around the world. Our knowledge of the host-pathogen interaction during UTI caused by Gram-positive bacterial uropathogens is limited compared to that for Gram-negative pathogens. Here, we investigated whether copper and the primary copper-containing protein, ceruloplasmin, are mobilized to urine during naturally occurring UTI caused by Gram-positive uropathogens in patients. Next, we probed the role of copper resistance in the fitness of methicillin-resistant Staphylococcus aureus (MRSA) during experimental UTI in a murine model. Our findings demonstrate that urinary copper and ceruloplasmin content are elevated during UTI caused by Enterococcus faecalis, S. aureus, S. epidermidis, and S. saprophyticus. MRSA strains successfully colonize the urinary tract of female CBA mice with selective induction of inflammation in the kidneys but not the bladder. MRSA mutants lacking CopL, a copper-binding cell surface lipoprotein, and the ACME genomic region containing copL, exhibit decreased fitness in the mouse urinary tract compared to parental strains. Copper sensitivity assays, cell-associated copper and iron content, and bioavailability of iron during copper stress demonstrate that homeostasis of copper and iron is interlinked in S. aureus. Importantly, relative fitness of the MRSA mutant lacking the ACME region is further decreased in mice that receive supplemental copper compared to the parental strain. In summary, copper is mobilized to the urinary tract during UTI caused by Gram-positive pathogens, and copper resistance is a fitness factor for MRSA during UTI. IMPORTANCE Urinary tract infection (UTI) is an extremely common infectious condition affecting people throughout the world. Increasing antibiotic resistance in pathogens causing UTI threatens our ability to continue to treat patients in the clinics. Better understanding of the host-pathogen interface is critical for development of novel interventional strategies. Here, we sought to elucidate the role of copper in host-Staphylococcus aureus interaction during UTI. Our results reveal that copper is mobilized to the urine as a host response in patients with UTI. Our findings from the murine model of UTI demonstrate that copper resistance is involved in the fitness of methicillin-resistant S. aureus (MRSA) during interaction with the host. We also establish a critical link between adaptation to copper stress and iron homeostasis in S. aureus.

Low Doses of Silver Nanoparticles Selectively Induce Lipid Peroxidation and Proteotoxic Stress in Mesenchymal Subtypes of Triple-Negative Breast Cancer.

Molecular profiling of tumors shows that triple-negative breast cancer (TNBC) can be stratified into mesenchymal (claudin-low breast cancer; CLBC) and epithelial subtypes (basal-like breast cancer; BLBC). Subtypes differ in underlying genetics and in response to therapeutics. Several reports indicate that therapeutic strategies that induce lipid peroxidation or proteotoxicity may be particularly effective for various cancers with a mesenchymal phenotype such as CLBC, for which no specific treatment regimens exist and outcomes are poor. We hypothesized that silver nanoparticles (AgNPs) can induce proteotoxic stress and cause lipid peroxidation to a greater extent in CLBC than in BLBC. We found that AgNPs were lethal to CLBCs at doses that had little effect on BLBCs and were non-toxic to normal breast epithelial cells. Analysis of mRNA profiles indicated that sensitivity to AgNPs correlated with expression of multiple CLBC-associated genes. There was no correlation between sensitivity to AgNPs and sensitivity to silver cations, uptake of AgNPs, or proliferation rate, indicating that there are other molecular factors driving sensitivity to AgNPs. Mechanistically, we found that the differences in sensitivity of CLBC and BLBC cells to AgNPs were driven by peroxidation of lipids, protein oxidation and aggregation, and subsequent proteotoxic stress and apoptotic signaling, which were induced in AgNP-treated CLBC cells, but not in BLBC cells. This study shows AgNPs are a specific treatment for CLBC and indicates that stratification of TNBC subtypes may lead to improved outcomes for other therapeutics with similar mechanisms of action.

A genome-wide screen reveals the involvement of enterobactin-mediated iron acquisition in Escherichia coli survival during copper stress.

Copper (Cu) is a key transition metal that is involved in many important biological processes in a cell. Cu is also utilized by the immune system to hamper pathogen growth during infection. However, genome-level knowledge on the mechanisms involved in adaptation to Cu stress is limited. Here, we report the results of a genome-wide reverse genetic screen for Cu-responsive phenotypes in Escherichia coli. Our screen has identified novel genes involved in adaptation to Cu stress in E. coli. We detected multiple genes involved in the biosynthesis and uptake of enterobactin, a siderophore utilized for high-affinity TonB-dependent acquisition of iron (Fe), as critical players in survival under Cu intoxication. We demonstrated the specificity of Cu-dependent killing by chelation of Cu and by genetic complementation of tonB. Notably, TonB is involved in protection from Cu in both laboratory and uropathogenic strains of E. coli. Cu stress leads to increased expression of the genes involved in Fe uptake, indicating that Fur regulon is derepressed during exposure to excess Cu. Trace element analyses revealed that Fe homeostasis is dysregulated during Cu stress. Taken together, our data supports a model in which lack of enterobactin-dependent Fe uptake leads to exacerbation of Cu toxicity, and elucidates the intricate connection between the homeostasis of Cu and Fe in a bacterial cell.

Evaluation of different approaches to applying the standard additions calibration method.

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.

Effect of Genetic Crossing and Nutritional Management on the Mineral Composition of Carcass, Blood, Leather, and Viscera of Sheep.

The effect of genetic crossing and nutritional management on weight gain and the concentration of minerals and trace elements in the carcass, blood, leather, and viscera of sheep were evaluated. Several statistical strategies were used to evaluate the different elemental composition characteristics of pure breed animals, i.e., White Dorper (ODO), Ile de France (OIF), Texel (OTX), and Santa Inês (OSI), as well as their crossbreeds 1/2 White Dorper and 1/2 Santa Inês (ODS), 1/2 Ile de France, and 1/2 Santa Inês (OIS), 1/2 Texel × 1/2 Santa Inês (OTS). Three different diets were evaluated AL (ad libitum), R75, and R63 (75 and 63 g of dry matter/kg of the animal metabolic weight, respectively). Levels of Ca, Cu, Fe, K, Mg, Mn, P, S, and Zn were determined by inductively coupled plasma optical emission spectrometry (ICP OES). The concentration of inorganic elements in the different body components was not affected by the diet (P > 0.05), and OTX and OTS were the breeds with the highest weight gain. Random forest importance models demonstrated that Zn in the carcass, K, Ca, and Zn in blood, and K in leather are most associated with separating the different evaluated sheep's breeds. Crossbreeding the native Santa Inês breed with sheep of exotic breeds produces animals well adapted to confinement.

Machine learning tools to estimate the severity of matrix effects and predict analyte recovery in inductively coupled plasma optical emission spectrometry.

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 (n = 29), with total line energies (Esum) in the 5.0-15.5 eV range, and non-analyte signals (n = 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 202.548 nm (Esum = 15.5 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.

Survey of Lead in Drinking Water from Schools and Child Care Centers Operating as Public Water Suppliers in North Carolina, USA: Implications for Future Legislation.

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.

Copper primes adaptation of uropathogenic Escherichia coli to superoxide stress by activating superoxide dismutases.

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.

Soil nutrients and precipitation are major drivers of global patterns of grass leaf silicification.

Grasses accumulate high concentrations of silicon (Si) in their tissues, with potential benefits including herbivore defense, improved water balance, and reduced leaf construction costs. Although Si is one of the most widely varying leaf constituents among individuals, species, and ecosystems, the environmental forces driving this variation remain elusive and understudied. To understand relationships between environmental factors and grass Si accumulation better, we analyzed foliar chemistry of grasses from 17 globally distributed sites where nutrient inputs and grazing were manipulated. These sites span natural gradients in temperature, precipitation, and underlying soil properties, which allowed us to assess the relative importance of soil moisture and nutrients across variation in climate. Foliar Si concentration did not respond to large mammalian grazer exclusion, but significant variation in herbivore abundance among sites may have precluded the observation of defoliation effects at these sites. However, nutrient addition consistently reduced leaf Si, especially at sites with low soil nitrogen prior to nutrient addition. Additionally, a leaf-level trade-off between Si and carbon (C) existed that was stronger at arid sites than mesic sites. Our results suggest soil nutrient limitation favors investment in Si over C-based leaf construction, and that fixing C is especially costly relative to assimilating Si when water is limiting. Our results demonstrate the importance of soil nutrients and precipitation as key drivers of global grass silicification patterns.