Pharmacokinetic parameter sets of alfentanil revisited: optimal parameters for use in target controlled infusion and anaesthesia display systems

Background In open TCI and anaesthesia display systems, the choice of pharmacokinetic (PK) parameter sets of opioids is clinically relevant. Accuracy and bias of the PK models may be affected by administration mode and the co-administered hypnotic drug. We retrospectively evaluated the performance of eight PK parameter sets for alfentanil in two data sets (infusion and bolus application). Methods With the dosing history from two studies in orthopaedic patients anaesthetized with propofol or inhalation anaesthetics the alfentanil plasma concentration over time was calculated with eight PK parameter sets. Median absolute performance error (MDAPE), log accuracy, median performance error (MDPE), log bias, Wobble, and Divergence were computed. Mann-Whitney rank test with Bonferroni correction was used for comparison between bolus and infusion data, repeated measures analysis of variance on ranks was used for comparison among parameter sets. Results The parameters by Scott (original and weight adjusted) and Fragen had a MDAPE ≤30% and a median log accuracy <0.15 independent of the administration mode, while MDPE was within ±20% and log bias nearly within ±0.1, respectively. The sets by Maitre and Lemmens were within these limits only in the bolus data. All other parameter sets were outside these limits. Conclusions In healthy orthopaedic patients, the PK parameters by Scott and by Maitre were equally valid when alfentanil was given as repeated boluses. When given as infusion, the Maitre parameters were less accurate and subject to a significant bias. We cannot exclude that the difference between bolus and infusion is partially because of the different hypnotics use

Revisiting Southern Hemisphere polar stratospheric temperature trends in WACCM: The role of dynamical forcing

The latest version of the Whole Atmosphere Community Climate Model (WACCM), which includes a new chemistry scheme and an updated parameterization of orographic gravity waves, produces temperature trends in the Antarctic lower stratosphere in excellent agreement with radiosonde observations for 1969-1998 as regards magnitude, location, timing, and persistence. The maximum trend, reached in November at 100hPa, is -4.42.8Kdecade(-1), which is a third smaller than the largest trend in the previous version of WACCM. Comparison with a simulation without the updated orographic gravity wave parameterization, together with analysis of the model's thermodynamic budget, reveals that the reduced trend is due to the effects of a stronger Brewer-Dobson circulation in the new simulations, which warms the polar cap. The effects are both direct (a trend in adiabatic warming in late spring) and indirect (a smaller trend in ozone, hence a smaller reduction in shortwave heating, due to the warmer environment)

Symptoms of Anxiety, Depression, and Aggression in Non-clinical Children: Relationships with Self-report and Performance-based Measures of Attention and Effortful Control

This study investigated the relation between the regulative trait of effortful control, and in particular attention control, and psychopathological symptoms in a sample of 207 non-clinical children aged 8–12 years. For this purpose, children completed self-report scales for measuring regulative traits and various types of psychopathological symptoms (i.e., anxiety, depression, and aggression) and were tested with a neuropsychological battery for measuring attention/effortful control capacity. Results indicated that self-report and performance-based measures of attention/effortful control were at best moderately correlated. Further, it was found that self-report indexes of attention/effortful control were clearly negatively related to psychopathological symptoms, which provides support for the notion that low regulation is associated with higher levels of psychopathology. Finally, the performance-based measure of attention/effortful control was not convincingly related to psychopathological symptoms

Molecular pathways involved in the synergistic interaction of the PKCβ inhibitor enzastaurin with the antifolate pemetrexed in non-small cell lung cancer cells

Conventional regimens have limited impact against non-small cell lung cancer (NSCLC). Current research is focusing on multiple pathways as potential targets, and this study investigated molecular mechanisms underlying the combination of the PKCβ inhibitor enzastaurin with the multitargeted antifolate pemetrexed in the NSCLC cells SW1573 and A549. Pharmacologic interaction was studied using the combination-index method, while cell cycle, apoptosis induction, VEGF secretion and ERK1/2 and Akt phosphorylation were studied by flow cytometry and ELISAs. Reverse transcription–PCR, western blot and activity assays were performed to assess whether enzastaurin influenced thymidylate synthase (TS) and the expression of multiple targets involved in cancer signaling and cell cycle distribution. Enzastaurin-pemetrexed combination was highly synergistic and significantly increased apoptosis. Enzastaurin reduced both phosphoCdc25C, resulting in G2/M checkpoint abrogation and apoptosis induction in pemetrexed-damaged cells, and GSK3β and Akt phosphorylation, which was additionally reduced by drug combination (−58% in A549). Enzastaurin also significantly reduced pemetrexed-induced upregulation of TS expression, possibly through E2F-1 reduction, whereas the combination decreased TS in situ activity (>50% in both cell lines) and VEGF secretion. The effects of enzastaurin on signaling pathways involved in cell cycle control, apoptosis and angiogenesis, as well as on the expression of genes involved in pemetrexed activity provide a strong experimental basis to their evaluation as pharmacodynamic markers in clinical trials of enzastaurin-pemetrexed combination in NSCLC patients

The different stratospheric influence on cold-extremes in Eurasia and North America

The stratospheric polar vortex can influence the tropospheric circulation and thereby winter weather in the mid-latitudes. Weak vortex states, often associated with sudden stratospheric warmings (SSW), have been shown to increase the risk of cold-spells especially over Eurasia, but its role for North American winters is less clear. Using cluster analysis, we show that there are two dominant patterns of increased polar cap heights in the lower stratosphere. Both patterns represent a weak polar vortex but they are associated with different wave mechanisms and different regional tropospheric impacts. The first pattern is zonally symmetric and associated with absorbed upward-propagating wave activity, leading to a negative phase of the North Atlantic Oscillation (NAO) and cold-air outbreaks over northern Eurasia. This coupling mechanism is well-documented in the literature and is consistent with the downward migration of the northern annular mode (NAM). The second pattern is zonally asymmetric and linked to downward reflected planetary waves over Canada followed by a negative phase of the Western Pacific Oscillation (WPO) and cold-spells in Central Canada and the Great Lakes region. Causal effect network (CEN) analyses confirm the atmospheric pathways associated with this asymmetric pattern. Moreover, our findings suggest the reflective mechanism to be sensitive to the exact region of upward wave-activity fluxes and to be state-dependent on the strength of the vortex. Identifying the causal pathways that operate on weekly to monthly timescales can pave the way for improved sub-seasonal to seasonal forecasting of cold spells in the mid-latitudes

Dynamics, stratospheric ozone, and climate change

Dynamics affects the distribution and abundance of stratospheric ozone directly through transport of ozone itself and indirectly through its effect on ozone chemistry via temperature and transport of other chemical species. Dynamical processes must be considered in order to understand past ozone changes, especially in the northern hemisphere where there appears to be significant low-frequency variability which can look “trend-like” on decadal time scales. A major challenge is to quantify the predictable, or deterministic, component of past ozone changes. Over the coming century, changes in climate will affect the expected recovery of ozone. For policy reasons it is important to be able to distinguish and separately attribute the effects of ozone-depleting substances and greenhouse gases on both ozone and climate. While the radiative-chemical effects can be relatively easily identified, this is not so evident for dynamics — yet dynamical changes (e.g., changes in the Brewer-Dobson circulation) could have a first-order effect on ozone over particular regions. Understanding the predictability and robustness of such dynamical changes represents another major challenge. Chemistry-climate models have recently emerged as useful tools for addressing these questions, as they provide a self-consistent representation of dynamical aspects of climate and their coupling to ozone chemistry. We can expect such models to play an increasingly central role in the study of ozone and climate in the future, analogous to the central role of global climate models in the study of tropospheric climate change

Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1

The Canadian Earth System Model version 5.0 (CanESM5.0), the most recent major version of the global climate model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) at Environment and Climate Change Canada (ECCC), has been used extensively in climate research and for providing future climate projections in the context of climate services. Previous studies have shown that CanESM5.0 performs well compared to other models and have revealed several model biases. To address these biases, the CCCma has recently initiated the “Analysis for Development” (A4D) activity, a coordinated analysis activity in support of CanESM development. Here we describe the goals and organization of this effort and introduce two variants (“p1” and “p2”) of a new CanESM version, CanESM5.1, which features important improvements as a result of the A4D activity. These improvements include the elimination of spurious stratospheric temperature spikes and an improved simulation of tropospheric dust. Other climate aspects of the p1 variant of CanESM5.1 are similar to those of CanESM5.0, while the p2 variant of CanESM5.1 features reduced equilibrium climate sensitivity and improved El Niño–Southern Oscillation (ENSO) variability as a result of intentional tuning of the atmospheric component. The A4D activity has also led to the improved understanding of other notable CanESM5.0 and CanESM5.1 biases, including the overestimation of North Atlantic sea ice, a cold bias over sea ice, biases in the stratospheric circulation and a cold bias over the Himalayas. It provides a potential framework for the broader climate community to contribute to CanESM development, which will facilitate further model improvements and ultimately lead to improved climate change information.</p

Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison

Abstract This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to Pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and Central Arctic sectors. The skill of dynamical and statistical models is generally comparable for Pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least three months in advance.</jats:p

Advancements in decadal climate predictability: the role of nonoceanic drivers

We review recent progress in understanding the role of sea ice, land surface, stratosphere, and aerosols in decadal-scale predictability and discuss the perspectives for improving the predictive capabilities of current Earth system models (ESMs). These constituents have received relatively little attention because their contribution to the slow climatic manifold is controversial in comparison to that of the large heat capacity of the oceans. Furthermore, their initialization as well as their representation in state-of-the-art climate models remains a challenge. Numerous extraoceanic processes that could be active over the decadal range are proposed. Potential predictability associated with the aforementioned, poorly represented, and scarcely observed constituents of the climate system has been primarily inspected through numerical simulations performed under idealized experimental settings. The impact, however, on practical decadal predictions, conducted with realistically initialized full-fledged climate models, is still largely unexploited. Enhancing initial-value predictability through an improved model initialization appears to be a viable option for land surface, sea ice, and, marginally, the stratosphere. Similarly, capturing future aerosol emission storylines might lead to an improved representation of both global and regional short-term climatic changes. In addition to these factors, a key role on the overall predictive ability of ESMs is expected to be played by an accurate representation of processes associated with specific components of the climate system. These act as “signal carriers,” transferring across the climatic phase space the information associated with the initial state and boundary forcings, and dynamically bridging different (otherwise unconnected) subsystems. Through this mechanism, Earth system components trigger low-frequency variability modes, thus extending the predictability beyond the seasonal scale