Explore the vast range of titles available.

Automated monitoring of the QT interval is increasingly common in a variety of clinical settings. A better understanding of how the heart-rate-corrected QT interval (QTc) evolves in early postnatal life is needed before its clinical utility in neonates can be determined. This study aimed to use real-time bedside monitoring as a tool to describe the QTc evolution of premature neonates during the first week of life. All neonates born at a gestation age (GA) of 31 weeks or later and admitted to the level 2 intensive care nursery of the authors’ institution between December 2012 and March 2013 were included in this study. The authors prospectively collected QTc values at 15-min intervals during the first week of life, then used two-way analysis of variance (ANOVA) to compare these data among three GA cohorts: 31 to <34 weeks (cohort A), 34 to <37 weeks (cohort B), and ≥37 weeks (cohort C). All the cohorts demonstrated a statistically significant decline in the 24-h average QTc during the first 3–4 days of life before reaching a stable baseline. No diurnal variation in the QTc was identified in any of the study patients. Marked variability and a progressive decline in the QTc of premature neonates occur during the first 3–4 days of life. Understanding this phenomenon is imperative when screening programs for the early detection of QT prolongation are considered.

A 17-year-old male was transferred to the pediatric intensive care unit for evaluation of acute liver failure. He was recently released from an alcohol treatment center with acute onset of chest pain. Cardiac workup was negative but he was found to have abnormal coagulation studies and elevated liver transaminases. Other evaluations included a normal toxicology screen and negative acetaminophen level. Autoimmune and infectious workups were normal providing no identifiable cause of his acute liver failure. He initially denied any ingestions or illicit drug use but on further query he admitted taking niacin in an attempt to obscure the results of an upcoming drug test. Niacin has been touted on the Internet as an aid to help pass urine drug tests though there is no evidence to support this practice. Niacin toxicity has been associated with serious multisystem organ failure and fulminant hepatic failure requiring liver transplantation. Pediatric providers should be aware of the risks associated with niacin toxicity and other experimental medical therapies that may be described on the Internet or other nonreputable sources.

Background The amount of clinical information that providers encounter daily creates an environment for information overload and medical error. To create a more efficient EMR human-computer interface, we aimed to understand clinical information needs among NICU providers. Methods A web-based survey to evaluate 98 data items was created and distributed to NICU providers. Participants were asked to rate the importance of each data item in helping them make routine clinical decisions in the NICU. Results There were 23 responses (92% – response rate) with participants distributed among four clinical roles. The top 5 items with the highest mean score were daily weight , pH , pCO2 , FiO2, and blood culture results. When compared by clinical role groupings, supervisory physicians gave individual data item ratings at the extremes of the scale when compared to providers more responsible for the daily clinical care of NICU patients. Conclusion NICU providers demonstrate a need for large amounts of EMR data to help guide clinical decision making with differences found when comparing by clinical role. When creating an EMR interface in the NICU there may be a need to offer options for varying degrees of viewable data densities depending on clinical role.

Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses. Plain Language Summary Water availability is critical for plants to maintain normal function, so droughts have considerable impact on natural ecosystems. However, predicting the impact of future drought on ecosystems is hard because current global models make systematic errors in their predictions of plant responses when water is scarce. In turn, uncertainty in the modeled terrestrial water and carbon cycles remains high. Here, we evaluate a range of new modeling approaches that have the capacity to mechanistically capture plant responses to water stress. Both in theoretical experiments and comparisons to observations, we find large differences among these new modeling approaches in response to water availability and atmospheric dryness. Importantly, some approaches achieve what seems like “good” performance through compensatory mechanisms that are not supported by observations and/or through incorrect representation of plant processes. Our results provide important guidance for future model development, by highlighting areas in need of continued research, and by constraining the range of approaches presently able to reduce uncertainty in modeled plant responses and suitable for inclusion in global models. Key Points Parameter identifiability differs among stomatal conductance schemes, implying some are more suitable to global modeling than others In some schemes, seemingly good performance can result from misrepresentation of physiological processes and sensitivities to model drivers We identify a subset of hydraulics‐based stomatal optimization approaches that could improve predictive capacity in novel climate spaces

The Aerosol, Radiation and Clouds in southern Africa (AEROCLO-sA) project investigates the role of aerosols on the regional climate of southern Africa. This is a unique environment where natural and anthropogenic aerosols and a semipermanent and widespread stratocumulus (Sc) cloud deck are found. The project aims to understand the dynamical, chemical, and radiative processes involved in aerosol–cloud–radiation interactions over land and ocean and under various meteorological conditions. The AEROCLO-sA field campaign was conducted in August and September of 2017 over Namibia. An aircraft equipped with active and passive remote sensors and aerosol in situ probes performed a total of 30 research flight hours. In parallel, a ground-based mobile station with state-of-the-art in situ aerosol probes and remote sensing instrumentation was implemented over coastal Namibia, and complemented by ground-based and balloonborne observations of the dynamical, thermodynamical, and physical properties of the lower troposphere. The focus laid on mineral dust emitted from salty pans and ephemeral riverbeds in northern Namibia, the advection of biomass-burning aerosol plumes from Angola subsequently transported over the Atlantic Ocean, and aerosols in the marine boundary layer at the ocean–atmosphere interface. This article presents an overview of the AEROCLO-sA field campaign with results from the airborne and surface measurements. These observations provide new knowledge of the interactions of aerosols and radiation in cloudy and clear skies in connection with the atmospheric dynamics over southern Africa. They will foster new advanced climate simulations and enhance the capability of spaceborne sensors, ultimately allowing a better prediction of future climate and weather in southern Africa

Trait-based analyses have shown great potential to advance our understanding of terrestrial ecosystem processes and functions. However, challenges remain in adequately synthesising a multidimensional and covarying trait space. Reducing the number of studied traits while identifying the most informative ones is increasingly recognized as a priority in functional ecology. Here, we develop a trait reduction procedure based on network analysis of a global dataset comprising 27 traits in three steps. We first construct all possible reduced networks and identify optimal reduced networks that capture the structure of the full 27-trait network. Then we apply the constraints on trait consistency to identified optimal reduced networks and establish consistent network series across ecoregions. We find the best performing networks that capture the three main dimensions of the full network (hydrological safety, leaf economic strategy, and plant reproduction and competition) and the global variance of network metrics. Finally, we find a parsimonious representation of trait covariation strategies is achieved by a 10-trait network which preserves 60% of all the original information while costing only 20.1% of the full suite of traits. Our results show the network reduction approach can improve our understanding on the main plant strategies and facilitate the future trait-based research. Using network analysis, the authors propose a trait reduction procedure to identify the most informative traits while preserving the functional complexity of trait space.

We, the undersigned, stand as a unified community of stakeholders and key opinion leaders deeply concerned about forced opioid tapering in patients receiving longterm prescription opioid therapy for chronic pain. This is a large-scale humanitarian issue. Our specific concerns involve: • rapid, forced opioid tapering among outpatients; • mandated opioid tapers that require aggressive opioid dose reductions over a defined period, even when that period is an extended one. Opioid tapering guidelines were created, in part, to decrease harm to patients resulting from high-dose opioid therapy for chronic pain. However, countless “legacy patients” with chronic pain who were progressively escalated to high opioid doses, often over many years, now face additional and very serious risks resulting from rapid tapering or related policies that mandate extreme dose reductions that are aggressive and unrealistic.

Despite the addition of several new agents to the armamentarium for the treatment of multiple myeloma (MM) in the last decade and improvements in outcomes, the refractory and relapsing disease continues to take a great toll, limiting overall survival. Therefore, additional novel approaches are needed to improve outcomes for MM patients. The oncogenic transcription factor MYC drives cell growth, differentiation and tumor development in many cancers. MYC protein levels are tightly regulated by the proteasome and an increase in MYC protein expression is found in more than 70% of all human cancers, including MM. In addition to the ubiquitin-dependent degradation of MYC by the 26S proteasome, MYC levels are also regulated in a ubiquitin-independent manner through the REGγ activation of the 20S proteasome. Here, we demonstrate that a small molecule activator of the 20S proteasome, TCH-165, decreases MYC protein levels, in a manner that parallels REGγ protein-mediated MYC degradation. TCH-165 enhances MYC degradation and reduces cancer cell growth in vitro and in vivo models of multiple myeloma by enhancing apoptotic signaling, as assessed by targeted gene expression analysis of cancer pathways. Furthermore, 20S proteasome enhancement is well tolerated in mice and dogs. These data support the therapeutic potential of small molecule-driven 20S proteasome activation for the treatments of MYC-driven cancers, especially MM.

Stomatal conductance schemes that optimise with respect to photosynthetic and hydraulic functions have been proposed to address biases in land-surface model (LSM) simulations during drought. However, systematic evaluations of both optimality-based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimisation approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviours differ in response to abiotic changes. We also evaluate the models against leaf-level observations of gas-exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361-3286 mm yr-1. We find that models differ in how easily parameterised they are, due to: (i) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (ii) low influence parameters, (iii) sensitivities to environmental drivers. In both the idealised experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapour pressure deficit. For example, stomatal closure rates at high vapour pressure deficit range between -45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf-gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.