Altered glucose-dependent secretion of glucagon and ACTH is associated with insulin resistance, assessed by population analysis

This study aimed to characterize how the dysregulation of counter-regulatory hormones can contribute to insulin resistance and potentially to diabetes. Therefore, we investigated the association between insulin sensitivity and the glucose- and insulin-dependent secretion of glucagon, adrenocorticotropic hormone (ACTH), and cortisol in non-diabetic individuals using a population model analysis. Data, from hyperinsulinemic–hypoglycemic clamps, were pooled for analysis, including 52 individuals with a wide range of insulin resistance (reflected by glucose infusion rate 20–60 min; GIR 20–60min). Glucagon secretion was suppressed by glucose and, to a lesser extent, insulin. The GIR20–60min and BMI were identified as predictors of the insulin effect on glucagon. At no rmoglycemia (5 mmol/L), a 90% suppression of glucagon was achieved at insulin concentrations of 16.3 and 43.4 μU/mL in individuals belonging to the highest and lowest quanti les of insulin sensitivity, respectively. Insulin resistance of glucagon secretion explained the elevated fasting glucagon for individuals with a low GIR20–60min. ACTH secretion was suppressed by glucose and not affected by insulin. The GIR20–60min was superior to other measures as a predictor of glucose-dependent ACTH secretion, with 90% suppression of ACTH secretion by glucose at 3.1 and 3.5 mmol/L for insulin-sensitive and insulin-resista nt individuals, respectively. This difference may appear small but shifts the suppression rang e into normoglycemia for individuals with insulin resistance, thus, leading to earli er and greater ACTH/cortisol response when the glucose falls. Based on modeling of pooled glucose-clamp data, insulin resistance was associated with generally elevated glucagon and a potentiated cortisol-axis response to hypoglycemia, and over time both hormonal pathways may therefore contribute to dysglycemia and possibly type 2 diabetes

Ultrafast modification of the electronic structure of a correlated insulator

A nontrivial balance between Coulomb repulsion and kinematic effects determines the electronic structure of correlated electron materials. The use of electromagnetic fields strong enough to rival these native microscopic interactions allows us to study the electronic response as well as the time scales and energies involved in using quantum effects for possible applications. We use element specific transient x ray absorption spectroscopy and high harmonic generation to measure the response to ultrashort off resonant optical fields in the prototypical correlated electron insulator NiO. Surprisingly, fields of up to 0.22 V lead to no detectable changes in the correlated Ni 3d orbitals contrary to previous predictions. A transient directional charge transfer is uncovered, a behavior that is captured by first principles theory. Our results highlight the importance of retardation effects in electronic screening and pinpoints a key challenge in functionalizing correlated materials for ultrafast device operatio

Lagrangian ocean analysis: fundamentals and practices

Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing

Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology

Background: A recent dialogue in the field of play, learn, and teach outdoors (referred to as “PLaTO” hereafter) demonstrated the need for developing harmonized and consensus-based terminology, taxonomy, and ontology for PLaTO. This is important as the field evolves and diversifies in its approaches, contents, and contexts over time and in different countries, cultures, and settings. Within this paper, we report the systematic and iterative processes undertaken to achieve this objective, which has built on the creation of the global PLaTO-Network (PLaTO-Net). Methods: This project comprised of four major methodological phases. First, a systematic scoping review was conducted to identify common terms and definitions used pertaining to PLaTO. Second, based on the results of the scoping review, a draft set of key terms, taxonomy, and ontology were developed, and shared with PLaTO members, who provided feedback via four rounds of consultation. Third, PLaTO terminology, taxonomy, and ontology were then finalized based on the feedback received from 50 international PLaTO member participants who responded to ≥ 3 rounds of the consultation survey and dialogue. Finally, efforts to share and disseminate project outcomes were made through different online platforms. Results: This paper presents the final definitions and taxonomy of 31 PLaTO terms along with the PLaTO-Net ontology model. The model incorporates other relevant concepts in recognition that all the aspects of the model are interrelated and interconnected. The final terminology, taxonomy, and ontology are intended to be applicable to, and relevant for, all people encompassing various identities (e.g., age, gender, culture, ethnicity, ability). Conclusions: This project contributes to advancing PLaTO-based research and facilitating intersectoral and interdisciplinary collaboration, with the long-term goal of fostering and strengthening PLaTO’s synergistic linkages with healthy living, environmental stewardship, climate action, and planetary health agendas. Notably, PLaTO terminology, taxonomy and ontology will continue to evolve, and PLaTO-Net is committed to advancing and periodically updating harmonized knowledge and understanding in the vast and interrelated areas of PLaTO

Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps

We examine the impact of horizontal resolution and model time step on the climate of the OpenIFS version 43r3 atmospheric general circulation model. A series of simulations for the period 1979–2019 are conducted with various horizontal resolutions (i.e. ∼100, ∼50, and ∼25 km) while maintaining the same time step (i.e. 15 min) and using different time steps (i.e. 60, 30, and 15 min) at 100 km horizontal resolution. We find that the surface zonal wind bias is significantly reduced over certain regions such as the Southern Ocean and the Northern Hemisphere mid-latitudes and in tropical and subtropical regions at a high horizontal resolution (i.e. ∼25 km). Similar improvement is evident too when using a coarse-resolution model (∼100 km) with a smaller time step (i.e. 30 and 15 min). We also find improvements in Rossby wave amplitude and phase speed, as well as in weather regime patterns, when a smaller time step or higher horizontal resolution is used. The improvement in the wind bias when using the shorter time step is mostly due to an increase in shallow and mid-level convection that enhances vertical mixing in the lower troposphere. The enhanced mixing allows frictional effects to influence a deeper layer and reduces wind and wind speed throughout the troposphere. However, precipitation biases generally increase with higher horizontal resolutions or smaller time steps, whereas the surface air temperature bias exhibits a small improvement over North America and the eastern Eurasian continent. We argue that the bias improvement in the highest-horizontal-resolution (i.e. ∼25 km) configuration benefits from a combination of both the enhanced horizontal resolution and the shorter time step. In summary, we demonstrate that, by reducing the time step in the coarse-resolution (∼100 km) OpenIFS model, one can alleviate some climate biases at a lower cost than by increasing the horizontal resolution.</p

Requirements for multi-level systems pharmacology models to reach end-usage : the case of type 2 diabetes

We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets, corresponding multi-level mathematical models are needed, i.e. models that simultaneously capture multiple layers of the biological, physiological and disease-level organization (also referred to as quantitative systems pharmacology-QSP-models). However, today's multi-level models are not yet embedded in end-usage applications, neither in drug research and development nor in the clinic. Given the expectations and claims made historically, this seemingly slow adoption may seem surprising. Therefore, we herein consider a specific example-type 2 diabetes-and critically review the current status and identify key remaining steps for these models to become mainstream in the future. This overview reveals how, today, we may use models to ask scientific questions concerning, e.g., the cellular origin of insulin resistance, and how this translates to the whole-body level and short-term meal responses. However, before these multi-level models can become truly useful, they need to be linked with the capabilities of other important existing models, in order to make them 'personalized' (e.g. specific to certain patient phenotypes) and capable of describing long-term disease progression. To be useful in drug development, it is also critical that the developed models and their underlying data and assumptions are easily accessible. For clinical end-usage, in addition, model links to decision-support systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.Funding agencies: Swedish Research Council; Swedish Diabetes Foundation; Linkoping Initiative within Life Science Technologies; CENIIT; Ostergotland County Council; EU [FP7-HEALTH-305707]; AstraZeneca</p