Role of Electrolyte pH on Water Oxidation for Iridium Oxides.

Understanding the effect of noncovalent interactions of intermediates at the polarized catalyst-electrolyte interface on water oxidation kinetics is key for designing more active and stable electrocatalysts. Here, we combine operando optical spectroscopy, X-ray absorption spectroscopy (XAS), and surface-enhanced infrared absorption spectroscopy (SEIRAS) to probe the effect of noncovalent interactions on the oxygen evolution reaction (OER) activity of IrOx in acidic and alkaline electrolytes. Our results suggest that the active species for the OER (Ir4.x+-*O) binds much stronger in alkaline compared with acid at low coverage, while the repulsive interactions between these species are higher in alkaline electrolytes. These differences are attributed to the larger fraction of water within the cation hydration shell at the interface in alkaline electrolytes compared to acidic electrolytes, which can stabilize oxygenated intermediates and facilitate long-range interactions between them. Quantitative analysis of the state energetics shows that although the *O intermediates bind more strongly than optimal in alkaline electrolytes, the larger repulsive interaction between them results in a significant weakening of *O binding with increasing coverage, leading to similar energetics of active states in acid and alkaline at OER-relevant potentials. By directly probing the electrochemical interface with complementary spectroscopic techniques, our work goes beyond conventional computational descriptors of the OER activity to explain the experimentally observed OER kinetics of IrOx in acidic and alkaline electrolytes.

Electrographic monitoring for seizure detection in the neonatal unit: current status and future direction.

Neonatal neurocritical intensive care is dedicated to safeguarding the newborn brain by prioritising clinical practices that promote early identification, diagnosis and treatment of brain injuries. The most common newborn neurological emergency is neonatal seizures, which may also be the initial clinical indication of neurological disease. A high seizure burden in the newborn period independently contributes to increased mortality and morbidity. The majority of seizures in newborns are subclinical (without clinical presentation), and hence identification may be difficult. Neuromonitoring techniques most frequently used to monitor brain wave activity include conventional electroencephalography (cEEG) or amplitude-integrated EEG (aEEG). cEEG with video is the gold standard for diagnosing and treating seizures. Many neonatal units do not have access to cEEG, and frequently those that do, have little access to real-time interpretation of monitoring. IMPACT: EEG monitoring is of no benefit to an infant without expert interpretation. Whilst EEG is a reliable cot-side tool and of diagnostic and prognostic use, both conventional EEG and amplitude-integrated EEG have strengths and limitations, including sensitivity to seizure activity and ease of interpretation. Automated seizure detection requires a sensitive and specific algorithm that can interpret EEG in real-time and identify seizures, including their intensity and duration.

Group sequential two-stage preference designs.

The two-stage preference design (TSPD) enables inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased estimates for selection and preference effects, where a selection effect occurs when patients who prefer one treatment respond differently than those who prefer another, and a preference effect is the difference in response caused by an interaction between the patient's preference and the actual treatment they receive. One potential barrier to adopting TSPD in practice, however, is the relatively large sample size required to estimate selection and preference effects with sufficient power. To address this concern, we propose a group sequential two-stage preference design (GS-TSPD), which combines TSPD with sequential monitoring for early stopping. In the GS-TSPD, pre-planned sequential monitoring allows investigators to conduct repeated hypothesis tests on accumulated data prior to full enrollment to assess study eligibility for early trial termination without inflating type I error rates. Thus, the procedure allows investigators to terminate the study when there is sufficient evidence of treatment, selection, or preference effects during an interim analysis, thereby reducing the design resource in expectation. To formalize such a procedure, we verify the independent increments assumption for testing the selection and preference effects and apply group sequential stopping boundaries from the approximate sequential density functions. Simulations are then conducted to investigate the operating characteristics of our proposed GS-TSPD compared to the traditional TSPD. We demonstrate the applicability of the design using a study of Hepatitis C treatment modality.

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016-2022.

BACKGROUND/AIMS: The stepped-wedge cluster randomized trial (SW-CRT), in which clusters are randomized to a time at which they will transition to the intervention condition - rather than a trial arm - is a relatively new design. SW-CRTs have additional design and analytical considerations compared to conventional parallel arm trials. To inform future methodological development, including guidance for trialists and the selection of parameters for statistical simulation studies, we conducted a review of recently published SW-CRTs. Specific objectives were to describe (1) the types of designs used in practice, (2) adherence to key requirements for statistical analysis, and (3) practices around covariate adjustment. We also examined changes in adherence over time and by journal impact factor. METHODS: We used electronic searches to identify primary reports of SW-CRTs published 2016-2022. Two reviewers extracted information from each trial report and its protocol, if available, and resolved disagreements through discussion. RESULTS: We identified 160 eligible trials, randomizing a median (Q1-Q3) of 11 (8-18) clusters to 5 (4-7) sequences. The majority (122, 76%) were cross-sectional (almost all with continuous recruitment), 23 (14%) were closed cohorts and 15 (9%) open cohorts. Many trials had complex design features such as multiple or multivariate primary outcomes (50, 31%) or time-dependent repeated measures (27, 22%). The most common type of primary outcome was binary (51%); continuous outcomes were less common (26%). The most frequently used method of analysis was a generalized linear mixed model (112, 70%); generalized estimating equations were used less frequently (12, 8%). Among 142 trials with fewer than 40 clusters, only 9 (6%) reported using methods appropriate for a small number of clusters. Statistical analyses clearly adjusted for time effects in 119 (74%), for within-cluster correlations in 132 (83%), and for distinct between-period correlations in 13 (8%). Covariates were included in the primary analysis of the primary outcome in 82 (51%) and were most often individual-level covariates; however, clear and complete pre-specification of covariates was uncommon. Adherence to some key methodological requirements (adjusting for time effects, accounting for within-period correlation) was higher among trials published in higher versus lower impact factor journals. Substantial improvements over time were not observed although a slight improvement was observed in the proportion accounting for a distinct between-period correlation. CONCLUSIONS: Future methods development should prioritize methods for SW-CRTs with binary or time-to-event outcomes, small numbers of clusters, continuous recruitment designs, multivariate outcomes, or time-dependent repeated measures. Trialists, journal editors, and peer reviewers should be aware that SW-CRTs have additional methodological requirements over parallel arm designs including the need to account for period effects as well as complex intracluster correlations.

Characteristics of water quality mitigation measures that lead to greater adoption on farms.

Globally, agriculture is a significant pressure on water quality. While nutrient and sediment loss from agricultural land to water can be scientifically complex, mitigation measures primarily focus on reducing farm nutrient stocks or blocking loss pathways. The appropriateness of mitigation measures is dependent on the identification of specific context-related risks on individual farms. However, advisers also need to consider the likelihood of uptake of measures by farmers. Past research has looked at uptake of particular mitigation measures or a small range of measures. This research expands the literature with an analysis of uptake of a broad and diverse range of measures. Farm characteristics, farmer norms, knowledge required and costs (direct and indirect) associated with individual mitigation measures are investigated to identify factors that could influence greater adoption. Results show that alignment to farmer norms and lower specific costs were associated with high adoption rates. These results have implications for advisers in relation to the selection of measures most likely to be adopted by farmers, and also for policy-makers in relation to the need to incentivise the adoption of high-cost measures.

Probing Degradation in Lithium Ion Batteries with On-Chip Electrochemistry Mass Spectrometry.

The rapid uptake of lithium ion batteries (LIBs) for large scale electric vehicle and energy storage applications requires a deeper understanding of the degradation mechanisms. Capacity fade is due to the complex interplay between phase transitions, electrolyte decomposition and transition metal dissolution; many of these poorly understood parasitic reactions evolve gases as a side product. Here we present an on-chip electrochemistry mass spectrometry method that enables ultra-sensitive, fully quantified and time resolved detection of volatile species evolving from an operating LIB. The technique's electrochemical performance and mass transport is described by a finite element model and then experimentally used to demonstrate the variety of new insights into LIB performance. We show the versatility of the technique, including (a) observation of oxygen evolving from a LiNiMnCoO2 cathode and (b) the solid electrolyte interphase formation reaction on graphite in a variety of electrolytes, enabling the deconvolution of lithium inventory loss (c) the first direct evidence, by virtue of the improved time resolution of our technique, that carbon dioxide reduction to ethylene takes place in a lithium ion battery. The emerging insight will guide and validate battery lifetime models, as well as inform the design of longer lasting batteries.

Sleep state organisation of moderate to late preterm infants in the neonatal unit.

BACKGROUND: Sleep supports neurodevelopment and sleep architecture reflects brain maturation. This prospective observational study describes the nocturnal sleep architecture of healthy moderate to late preterm (MLP) infants in the neonatal unit at 36 weeks post menstrual age (PMA). METHODS: MLP infants, in the neonatal unit of a tertiary hospital in Ireland from 2017 to 2018, had overnight continuous electroencephalography (cEEG) with video for a minimum 12 h at 36 weeks PMA. The total sleep time (TST) including periods of active sleep (AS), quiet sleep (QS), indeterminate sleep (IS), wakefulness and feeding were identified, annotated and quantified. RESULTS: A total of 98 infants had cEEG with video monitoring suitable for analysis. The median (IQR) of TST in the 12 h period was 7.09 h (IQR 6.61-7.76 h), 4.58 h (3.69-5.09 h) in AS, 2.02 h (1.76-2.36 h) in QS and 0.65 h (0.48-0.89 h) in IS. The total duration of AS was significantly lower in infants born at lower GA (p = 0.007) whilst the duration of individual QS periods was significantly higher (p = 0.001). CONCLUSION: Overnight cEEG with video at 36 weeks PMA showed that sleep state architecture is dependent on birth GA. Infants with a lower birth GA have less AS and more QS that may have implications for later neurodevelopment. IMPACT: EEG provides objective information about the sleep organisation of the moderate to late preterm (MLP) infant. Quantitative changes in sleep states occur with each week of advancing gestational age (GA). Active sleep (AS) is the dominant sleep state that was significantly lower in infants born at lower GA. MLP infants who were exclusively fed orally had a shorter total sleep time and less AS compared to infants who were fed via nasogastric tube.

Maximin optimal cluster randomized designs for assessing treatment effect heterogeneity.

Cluster randomized trials (CRTs) are studies where treatment is randomized at the cluster level but outcomes are typically collected at the individual level. When CRTs are employed in pragmatic settings, baseline population characteristics may moderate treatment effects, leading to what is known as heterogeneous treatment effects (HTEs). Pre-specified, hypothesis-driven HTE analyses in CRTs can enable an understanding of how interventions may impact subpopulation outcomes. While closed-form sample size formulas have recently been proposed, assuming known intracluster correlation coefficients (ICCs) for both the covariate and outcome, guidance on optimal cluster randomized designs to ensure maximum power with pre-specified HTE analyses has not yet been developed. We derive new design formulas to determine the cluster size and number of clusters to achieve the locally optimal design (LOD) that minimizes variance for estimating the HTE parameter given a budget constraint. Given the LODs are based on covariate and outcome-ICC values that are usually unknown, we further develop the maximin design for assessing HTE, identifying the combination of design resources that maximize the relative efficiency of the HTE analysis in the worst case scenario. In addition, given the analysis of the average treatment effect is often of primary interest, we also establish optimal designs to accommodate multiple objectives by combining considerations for studying both the average and heterogeneous treatment effects. We illustrate our methods using the context of the Kerala Diabetes Prevention Program CRT, and provide an R Shiny app to facilitate calculation of optimal designs under a wide range of design parameters.

Evaluation of Sleep Practices and Knowledge in Neonatal Healthcare.

BACKGROUND: Developmental care is designed to optimize early brain maturation by integrating procedures that support a healing environment. Protecting preterm sleep is important in developmental care. However, it is unclear to what extent healthcare professionals are aware of the importance of sleep and how sleep is currently implemented in the day-to-day care in the neonatal intensive care unit (NICU). PURPOSE: Identifying the current state of knowledge among healthcare professionals regarding neonatal sleep and how this is transferred to practice. METHODS: A survey was distributed among Dutch healthcare professionals. Three categories of data were sought, including (1) demographics of respondents; (2) questions relating to sleep practices; and (3) objective knowledge questions relating to sleep physiology and importance of sleep. Data were analyzed using Spearman's rho test and Cramer's V test. Furthermore, frequency tables and qualitative analyses were employed. RESULTS: The survey was completed by 427 participants from 34 hospitals in 25 Dutch cities. While healthcare professionals reported sleep to be especially important for neonates admitted in the NICU, low scores were achieved in the area of knowledge of sleep physiology. Most healthcare professionals (91.8%) adapted the timing of elective care procedures to sleep. However, sleep assessments were not based on scientific knowledge. Therefore, the difference between active sleep and wakefulness may often be wrongly assessed. Finally, sleep is rarely discussed between colleagues (27.4% regularly/always) and during rounds (7.5%-14.3% often/always). IMPLICATIONS: Knowledge about sleep physiology should be increased through education among neonatal healthcare professionals. Furthermore, sleep should be considered more often during rounds and handovers.

Evolution of early cerebral NIRS in hypoxic ischaemic encephalopathy.

AIM: To describe early cerebral oxygenation (cSO2 ) and fractional tissue oxygen extraction (FTOE) values and their evolution over the first days of life in infants with all grades of hypoxic-ischaemic encephalopathy (HIE) and to determine whether cSO2 and FTOE measured early (6 and 12 h) can predict short-term outcome. METHODS: Prospective, observational study of cerebral near-infrared spectroscopy (NIRS) in infants >36 weeks' gestation with HIE. Ten one-hour epochs of cSO2 and FTOE were extracted for each infant over the first 84 h. Infants with moderate and severe HIE received therapeutic hypothermia (TH). Abnormal outcome was defined as abnormal magnetic resonance imaging (MRI) and/or death. RESULTS: Fifty-eight infants were included (28 mild, 24 moderate, 6 severe). Median gestational age was 39.9 weeks (IQR 38.1-40.7) and birthweight was 3.35 kgs (IQR 2.97-3.71). cSO2 increased and FTOE decreased over the first 24 h in all grades of HIE. Compared to the moderate group, infants with mild HIE had significantly higher cSO2 at 6 h (p = 0.003), 9 h (p = 0.009) and 12 h (p = 0.032) and lower FTOE at 6 h (p = 0.016) and 9 h (0.029). cSO2 and FTOE at 6 and 12 h did not predict abnormal outcome. CONCLUSION: Infants with mild HIE have higher cSO2 and lower FTOE than those with moderate or severe HIE in the first 12 h of life. cSO2 increased in all grades of HIE over the first 24 h regardless of TH status.

Development of an Electronic Medical Tool to Facilitate Allocation of Limited Resources in Times of Crisis.

The COVID-19 pandemic has made decisions about resource allocation and reallocation real possibilities even in high-resource settings. In April 2020, in preparation for such an eventuality, Atlantic Health System began to develop a real-time instrument built into the EMR to assist with such decisions. The instrument calculated the modified Sequential Organ Failure Assessment for all patients admitted, in real time, to assist triage teams make decisions if crisis standards of care were declared. A pilot assessment of the instrument was performed using retrospective data by nine members of the triage teams, who were asked to identify the six patients at highest risk of reallocation. Agreement about which patients were at highest risk of resource reallocation was good, but not perfect. All raters agreed on five of the six patients, but only seven of nine agreed on the final patient. Among the six consensus selections for reallocation, five died prior to hospital discharge. All patients at highest risk of reallocation had a predicted life expectancy of less than 1 year. In conclusion, the instrument was easy to use, and the concordance among raters was good but not perfect. Predicted life expectance was a major determinant of the triage score.

Using Direct-to-Consumer Genetic Testing Results to Accelerate Alzheimer Disease Clinical Trial Recruitment.

INTRODUCTION: The apolipoprotein E (APOE) gene is the strongest known genetic risk factor for sporadic Alzheimer disease (AD). APOE can be used as an enrichment strategy or inclusion criterion for AD prevention trials. Personal genomics companies market direct-to-consumer (DTC) genetic tests, including APOE. We assessed DTC APOE testing usage among enrollees of the University of California Irvine Consent-to-Contact Registry, an online recruitment registry, and attitudes toward using this information in clinical trial recruitment. METHODS: We emailed links to an electronic survey to registry enrollees age 50 years or older. We assessed participants' use of DTC services, willingness to learn APOE status, and willingness to share genetic information. Logistic regression models assessed relationships between DTC testing usage and demographic characteristics, and with willingness to share results to assist trial recruitment. RESULTS: Among 1312 responders (57% response rate), few (7%) had used DTC testing for APOE. Non-Hispanic Asian enrollees were 93% less likely to have used DTC testing, compared with non-Hispanic Whites [95% confidence interval: (0.01, 0.67)]. Willingness to share APOE information for study recruitment was >90% for both users and nonusers. CONCLUSIONS: Matching participants to trials on the basis of DTC APOE information may be an effective way to streamline AD prevention trial recruitment.

Defining national biogenic methane targets: Implications for national food production & climate neutrality objectives.

Methane is a short-lived greenhouse gas (GHG) modelled distinctly from long-lived GHGs such as carbon dioxide and nitrous oxide to establish global emission budgets for climate stabilisation. The Paris Agreement requires a 24-47% reduction in global biogenic methane emissions by 2050. Separate treatment of methane in national climate policies will necessitate consideration of how global emission budgets compatible with climate stabilisation can be downscaled to national targets, but implications of different downscaling rules for national food production and climate neutrality objectives are poorly understood. This study addresses that knowledge gap by examining four methods to determine national methane quotas, and two methods of GHG aggregation (GWP100 and GWP*) across four countries with contrasting agriculture, forestry and other land use (AFOLU) sectors and socio-economic contexts (Brazil, France, India and Ireland). Implications for production of methane-intensive food (milk, meat, eggs and rice) in 2050 and national AFOLU climate neutrality targets are explored. It is assumed that methane quotas are always filled by food production where sufficient land is available. Global methane budgets for 1.5 °C scenarios are downscaled to national quotas based on: grand-parenting (equal percentage reductions across countries); equity (equal per capita emissions); ability (emission reductions proportionate to GDP); animal protein security (emissions proportionate to animal protein production in 2010). The choice of allocation method changes national methane quotas by a factor of between 1.7 (India) and 6.7 (Ireland). Despite projected reductions in emission-intensities, livestock production would need to decrease across all countries except India to comply with quotas under all but the most optimistic sustainable intensification scenarios. The extent of potential afforestation on land spared from livestock production is decisive in achieving climate neutrality. Brazil and Ireland could maintain some degree of milk and beef export whilst achieving territorial climate neutrality, but scenarios that comply with climate neutrality in India produce only circa 30% of national calorie and protein requirements via rice and livestock. The downscaling of global methane budgets into national policy targets in an equitable and internationally acceptable manner will require simultaneous consideration of the interconnected priorities of food security and (land banks available for) carbon offsetting.

More than two decades of Agri-Environment schemes: Has the profile of participating farms changed?

The agri-food sector is under increased pressure from consumers to improve on the sustainability of production processes. Policies that incentivise farmers to improve environmental performance, such as agri-environment schemes (AES), are increasingly important. Understanding the choice to participate in these programmes aids policymakers in designing schemes that meet participation and environmental goals. While a number of studies have investigated the decision using cross-sectional data on one or multiple locations, very few have used longitudinal data to investigate the impact of institutional changes over time. Using Ireland as a case study, this paper uses a nationally representative panel of data spanning 23 years to model the impact of scheme and policy changes on the type of farms participating in AES. This paper argues that environmental issues surrounding intensive farms (such as the loss of nutrients and sediment to water and greenhouse gas emissions) are not being optimally addressed in scheme design and further development of such programmes is needed to reduce negative environmental impacts.

A discrete choice experiment exploring farmer preferences for insurance against extreme weather events.

Agriculture represents one of the most vulnerable sectors to extreme weather events that are projected to increase with climate change. Insurance has been advocated as a more efficient means to ensure financial security to farmers, than post-disaster aid for damages. A potential drawback of insurance however, is that unless carefully designed it could dis-incentivise farmers to engage in wider farm adaptation measures or lead to more risk-taking behaviour. This paper analyses the attractiveness of publicly-backed climate risk insurance offerings to farmers and explores their preferences for elements of insurance schemes that do not negatively affect incentives for wider farm adaptation. Specifically, a discrete choice experiment is used to reveal Irish farmers' preferences for multi-annual insurance contracts and weather-indexed versus traditional indemnity insurance and cost. Results indicate that a majority of farmers are willing to buy publicly-backed insurance for protection from extreme weather events. Younger farmers, farmers who currently have farm insurance, farmers from certain geographical locations and farmers who have been previously affected by extreme weather events are more likely to buy insurance. With respect to the design of insurance schemes, farmers prefer multi-annual coverage versus annual renewal. They also prefer indexed-insurance and have a strong preference for cheaper coverage. Despite the important role that insurance could play in protecting farms financially from damage caused by extreme weather events, few studies have examined preference for weather-indexed insurance within a European context. New evidence on farmer preferences and intended behaviours is therefore critical to inform policy in this area.

An Introduction to Neonatal EEG.

Newborn care has witnessed significant improvements in survival, but ongoing concerns persist about neurodevelopmental outcome. Protecting the newborn brain is the focus of neurocritical care in the intensive care unit. Brain-focused care places emphasis on clinical practices supporting neurodevelopment in conjunction with early detection, diagnosis, and treatment of brain injury. Technology now facilitates continuous cot-side monitoring of brain function. Neuromonitoring techniques in neonatal intensive care units include the use of electroencephalography (EEG) or amplitude-integrated EEG (aEEG) and near-infrared spectroscopy. This article aims to provide an introduction to EEG, which is appropriate for neonatal healthcare professionals.

Variance estimation for the Kappa statistic in the presence of clustered data and heterogeneous observations.

We present a methodology motivated by a controlled trial designed to validate SPOT GRADE, a novel surgical bleeding severity scale. Briefly, the study was designed to quantify inter- and intra-surgeon agreement for characterizing the severity of surgical bleeds via a Kappa statistic. Multiple surgeons were presented with a randomized sequence of controlled bleeding videos and asked to apply the rating system to characterize each wound. Each video was shown multiple times to quantify intra-surgeon reliability, creating clustered data. In addition, videos within the same category may have had different classification probabilities due to changes in blood flow rates and wound sizes. In this work, we propose a new variance estimator for the Kappa statistic, for use in clustered data as well as heterogeneity among items within the same classification category. We then apply this methodology to data from the SPOT GRADE trial.

Afforestation: Replacing livestock emissions with carbon sequestration.

In Ireland, agriculture accounts for 33% of national greenhouse gas (GHG) emissions. Ireland faces significant challenges in terms of emissions reduction and is well off course in terms of meeting binding European Union targets. Flexibility mechanisms will allow Ireland to offset 5.6% of its commitment via sequestration in biomass and soils and land use change. Agricultural emissions in Ireland are largely driven by livestock production. As such, the purpose of this research is to estimate the net GHG emission benefit resulting from a land use change with forest replacing livestock systems (dairy, beef cattle and sheep). We estimate the total carbon sequestration in biomass and harvested wood products, along with the total emissions avoided from each livestock system on a per hectare basis. In addition, the paper compares the social cost of carbon to the average income per hectare of each livestock system. Finally, a hypothetical national planting scenario is modelled using plausible planting rates. Results indicate that the greatest carbon benefit is achieved when forest replaces dairy production. This is due to high emissions per hectare from dairy systems, and greater sequestration potential in higher-yielding forests planted on better quality soils associated with dairy production. The inclusion of harvested wood products in subsequent rotations has the potential to enhance GHG mitigation and offset terrestrial carbon loss. A hypothetical national planting scenario, afforesting 100,000 ha substituting dairy, beef cattle and sheep livestock systems could abate 13.91 Mt CO2e after 10 years, and 150.14 Mt CO2e (unthinned plantations) or 125.89 Mt CO2e (thinned plantations) over the course of the rotation. These results highlight the critical role for forest land use change in meeting the urgent need to tackle rising agricultural emissions.

Label-Free Time-of-Flight Secondary Ion Mass Spectrometry Imaging of Sulfur-Producing Enzymes inside Microglia Cells following Exposure to Silver Nanowires.

There are no methods sensitive enough to detect enzymes within cells, without the use of analyte labeling. Here we show that it is possible to detect protein ion signals of three different H2S-synthesizing enzymes inside microglia after pretreatment with silver nanowires (AgNW) using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Protein fragment ions, including the fragment of amino acid (C4H8N+ = 70 amu), fragments of the sulfur-producing cystathionine-containing enzymes, and the Ag+ ion signal could be detected without the use of any labels; the cells were mapped using the C4H8N+ amino acid fragment. Scanning electron microscopy imaging and energy-dispersive X-ray chemical analysis showed that the AgNWs were inside the same cells imaged by TOF-SIMS and transformed chemically into crystalline Ag2S within cells in which the sulfur-producing proteins were detected. The presence of these sulfur-producing cystathionine-containing enzymes within the cells was confirmed by Western blots and confocal microscopy images of fluorescently labeled antibodies against the sulfur-producing enzymes. Label-free TOF-SIMS is very promising for the label-free identification of H2S-contributing enzymes and their cellular localization in biological systems. The technique could in the future be used to identify which of these enzymes are most contributory.

Acetaminophen and Acetylsalicylic Acid Exposure in a Preterm Infant after Maternal Overdose.

Here, we review the case of a 26 1/7 weeks' gestation premature female infant born to a mother who intentionally ingested a large quantity of Tylenol, aspirin, quetiapine, and prenatal vitamins. The neonate subsequently had markedly elevated levels of both Tylenol and aspirin when checked on the first day of life. While overall clinically stable, the neonate did demonstrate coagulopathy as evidenced by abnormal coagulation studies. Both poison control and a pediatric gastroenterologist/hepatologist were consulted. She successfully tolerated a course of N-acetylcysteine; her subsequent Tylenol level was markedly decreased and the neonate exhibited no further effects of toxicity. The salicylate level decreased on its own accord. To our knowledge, this is the first report of a neonate at 26 weeks' gestation that has been successfully managed for supratherapeutic concentrations of acetaminophen and acetylsalicylic acid secondary to maternal ingestion. While rare, this case may serve as a reference for the effectiveness of N-acetylcysteine in premature infants in such instances.