Self-control strength in the relation between trait test anxiety and state anxiety

The present research examined whether in a test situation, the relation between trait test anxiety and state anxiety depends on the momentary availability of self-control strength. Since self-control strength is crucial for emotion regulation, we assume that trait test anxiety is more closely related to state anxiety if self-control strength is depleted than if it is not depleted. We conducted an experiment with 119 undergraduates in which we measured trait test anxiety, manipulated availability of self-control strength, and assessed state anxiety after a test announcement. Consistent with the assumption, multiple regression analyses revealed that trait test anxiety and state anxiety were positively related if self-control strength was depleted, but were not related if self-control strength was intact.

Social Support at the Workplace, Motivation to Transfer, and Training Transfer: A Multi-Level Indirect Effects Model

Supervisor support, peer support and transfer motivation have been identified as important predictors for training transfer. Transfer motivation is supposed to mediate the support–training transfer relationship. Especially after team training interventions that include all team members (i.e., intact-team training), individual perception of these factors might be shared among team members. However, an integration of the team level in the training transfer process is rare, yet still needed. Analyzing 194 employees from 34 teams in the context of intact-team training interventions, we found similar relationships and processes at both levels of analysis: Social support enhances transfer motivation at the individual and team levels. Furthermore, motivation to transfer increases training transfer and serves as a connecting mechanism in the social support–training transfer link. The results underline the importance of (1) considering multiple levels in theories and research about the training transfer process and (2) ensuring the practice of individual-directed support and a shared, supportive climate within teams.

Towards a new model of care: integrating mental health, substance use, and somatic care

Although research and clinical interventions for patients with dual disorders have been described since as early as the 1980s, the day-to-day treatment of these patients remains problematic and challenging in many countries. Throughout this book, many approaches and possible pathways have been outlined. Based upon these experiences, some key points can be extracted in order to guide to future developments. (1) New diagnostic approaches are warranted when dealing with patients who have multiple problems, given the limitations of the current categorical systems. (2) Greater emphasis should be placed on secondary prevention and early intervention for children and adolescents at an increased risk of later-life dual disorders. (3) Mental, addiction, and somatic care systems can be integrated, adopting a patient-focused approach to care delivery. (4) Recovery should be taken into consideration when defining treatment intervention and outcome goals. (5) It is important to reduce societal risk factors, such as poverty and early childhood adversity. (6) More resources are needed to provide adequate mental health care in the various countries. The development of European guidance initiatives would provide benefits in many of these areas, making it possible to ensure a more harmonized standard of care for patients with dual disorders.

Bilateral uterine vessel ligation as a model of intrauterine growth restriction in mice

BACKGROUND Intrauterine growth restriction (IUGR) occurs in up to 10% of pregnancies and is considered as a major risk to develop various diseases in adulthood, such as cardiovascular diseases, insulin resistance, hypertension or end stage kidney disease. Several IUGR models have been developed in order to understand the biological processes linked to fetal growth retardation, most of them being rat or mouse models and nutritional models. In order to reproduce altered placental flow, surgical models have also been developed, and among them bilateral uterine ligation has been frequently used. Nevertheless, this model has never been developed in the mouse, although murine tools display multiple advantages for biological research. The aim of this work was therefore to develop a mouse model of bilateral uterine ligation as a surgical model of IUGR. RESULTS In this report, we describe the set up and experimental data obtained from three different protocols (P1, P2, P3) of bilateral uterine vessel ligation in the mouse. Ligation was either performed at the cervical end of each uterine horn (P1) or at the central part of each uterine horn (P2 and P3). Time of surgery was E16 (P1), E17 (P2) or E16.5 (P3). Mortality, maternal weight and abortion parameters were recorded, as well as placentas weights, fetal resorption, viability, fetal weight and size. Results showed that P1 in test animals led to IUGR but was also accompanied with high mortality rate of mothers (50%), low viability of fetuses (8%) and high resorption rate (25%). P2 and P3 improved most of these parameters (decreased mortality and improved pregnancy outcomes; improved fetal viability to 90% and 27%, respectively) nevertheless P2 was not associated to IUGR contrary to P3. Thus P3 experimental conditions enable IUGR with better pregnancy and fetuses outcomes parameters that allow its use in experimental studies. CONCLUSIONS Our results show that bilateral uterine artery ligation according to the protocol we have developed and validated can be used as a surgical mouse model of IUGR.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

A numerical model for inert gas transport in the lung based on fractal airway morphology

Patients suffering from cystic fibrosis (CF) show thick secretions, mucus plugging and bronchiectasis in bronchial and alveolar ducts. This results in substantial structural changes of the airway morphology and heterogeneous ventilation. Disease progression and treatment effects are monitored by so-called gas washout tests, where the change in concentration of an inert gas is measured over a single or multiple breaths. The result of the tests based on the profile of the measured concentration is a marker for the severity of the ventilation inhomogeneity strongly affected by the airway morphology. However, it is hard to localize underlying obstructions to specific parts of the airways, especially if occurring in the lung periphery. In order to support the analysis of lung function tests (e.g. multi-breath washout), we developed a numerical model of the entire airway tree, coupling a lumped parameter model for the lung ventilation with a 4th-order accurate finite difference model of a 1D advection-diffusion equation for the transport of an inert gas. The boundary conditions for the flow problem comprise the pressure and flow profile at the mouth, which is typically known from clinical washout tests. The natural asymmetry of the lung morphology is approximated by a generic, fractal, asymmetric branching scheme which we applied for the conducting airways. A conducting airway ends when its dimension falls below a predefined limit. A model acinus is then connected to each terminal airway. The morphology of an acinus unit comprises a network of expandable cells. A regional, linear constitutive law describes the pressure-volume relation between the pleural gap and the acinus. The cyclic expansion (breathing) of each acinus unit depends on the resistance of the feeding airway and on the flow resistance and stiffness of the cells themselves. Special care was taken in the development of a conservative numerical scheme for the gas transport across bifurcations, handling spatially and temporally varying advective and diffusive fluxes over a wide range of scales. Implicit time integration was applied to account for the numerical stiffness resulting from the discretized transport equation. Local or regional modification of the airway dimension, resistance or tissue stiffness are introduced to mimic pathological airway restrictions typical for CF. This leads to a more heterogeneous ventilation of the model lung. As a result the concentration in some distal parts of the lung model remains increased for a longer duration. The inert gas concentration at the mouth towards the end of the expirations is composed of gas from regions with very different washout efficiency. This results in a steeper slope of the corresponding part of the washout profile.

Multiple programmed cell death pathways are involved in N-methyl-N-nitrosourea-induced photoreceptor degeneration.

PURPOSE: To identify programmed cell death (PCD) pathways involved in N-methyl-N-nitrosourea (MNU)-induced photoreceptor (PR) degeneration. METHODS: Adult C57BL/6 mice received a single MNU i.p. injection (60 mg/kg bodyweight), and were observed over a period of 7 days. Degeneration was visualized by H&E overview staining and electron microscopy. PR cell death was measured by quantifying TUNEL-positive cells in the outer nuclear layer (ONL). Activity measurements of key PCD enzymes (calpain, caspases) were used to identify the involved cell death pathways. Furthermore, the expression level of C/EBP homologous protein (CHOP) and glucose-regulated protein 78 (GRP78), key players in endoplasmic reticulum (ER) stress-induced apoptosis, was analyzed using quantitative real-time PCR. RESULTS: A decrease in ONL thickness and the appearance of apoptotic PR nuclei could be detected beginning 3 days post-injection (PI). This was accompanied by an increase of TUNEL-positive cells. Significant upregulation of activated caspases (3, 9, 12) was found at different time periods after MNU injection. Additionally, several other players of nonconventional PCD pathways were also upregulated. Consequently, calpain activity increased in the ONL, with a maximum on day 7 PI and an upregulation of CHOP and GRP78 expression beginning on day 1 PI was found. CONCLUSIONS: The data indicate that regular apoptosis is the major cause of MNU-induced PR cell death. However, alternative PCD pathways, including ER stress and calpain activation, are also involved. Knowledge about the mechanisms involved in this mouse model of PR degeneration could facilitate the design of putative combinatory therapeutic approaches.

Transient Earth system responses to cumulative carbon dioxide emissions: linearities, uncertainties, and probabilities in an observation-constrained model ensemble

Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An  ∼ 1000-member ensemble of the Bern3D-LPJ carbon–climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Neuroenhancement and the strength model of self-control

Neuroenhancement (NE), the use of substances as a means to enhance performance, has garnered considerable scientific attention of late. While ethical and epidemiological publications on the topic accumulate, there is a lack of theory-driven psychological research that aims at understanding psychological drivers of NE. In this perspective article we argue that self-control strength offers a promising theory-based approach to further understand and investigate NE behavior. Using the strength model of self-control, we derive two theory-driven perspectives on NE-self-control research. First, we propose that individual differences in state/trait self-control strength differentially affect NE behavior based on one’s individual experience of NE use. Building upon this, we outline promising research questions that (will) further elucidate our understanding of NE based on the strength model’s propositions. Second, we discuss evidence indicating that popular NE substances (like Methylphenidate) may counteract imminent losses of self-control strength. We outline how further research on NE’s effects on the ego-depletion effect may further broaden our understanding of the strength model of self-control.

Multiple causes of the Younger Dryas cold period

The Younger Dryas cooling event disrupted the overall warming trend in the North Atlantic region during the last deglaciation. Climate change during the Younger Dryas was abrupt and thus provides insights into the sensitivity of the climate system to perturbations. The sudden Younger Dryas cooling has traditionally been attributed to a shutdown of the Atlantic Meridional Overturning Circulation by meltwater discharges. However, alternative explanations such as strong negative radiative forcing14 and a shift in atmospheric circulation have also been offered. Here we investigate the importance of these different forcings in coupled climate model experiments constrained by data assimilation. We find that the Younger Dryas climate signal as registered in proxy evidence is best simulated using a combination of processes: a weakened Atlantic Meridional Overturning Circulation, moderate negative radiative forcing and an altered atmospheric circulation. We conclude that none of the individual mechanisms alone provide a plausible explanation for the Younger Dryas cold period. We suggest that the triggers for abrupt climate changes such as the Younger Dryas are more complex than suggested so far, and that studies on the response of the climate system to perturbations should account for this complexity.

MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

The Microwave Emission Model of Layered Snowpacks (MEMLS) was originally developed for microwave emissions of snowpacks in the frequency range 5–100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like- and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS) is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment) campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/projects/snowtools/memls.html.

Privacy-preserving genomic testing in the clinic: a model using HIV treatment

PURPOSE The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. METHODS We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. RESULTS A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. CONCLUSIONS The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med advance online publication 14 January 2016Genetics in Medicine (2016); doi:10.1038/gim.2015.167.

MYB-FL controls gain and loss of floral UV absorbance, a key trait affecting pollinator preference and reproductive isolation

Adaptations to new pollinators involve multiple floral traits, each requiring coordinated changes in multiple genes. Despite this genetic complexity, shifts in pollination syndromes have happened frequently during angiosperm evolution. Here we study the genetic basis of floral UV absorbance, a key trait for attracting nocturnal pollinators. In Petunia, mutations in a single gene, MYB-FL, explain two transitions in UV absorbance. A gain of UV absorbance in the transition from bee to moth pollination was determined by a cis-regulatory mutation, whereas a frameshift mutation caused subsequent loss of UV absorbance during the transition from moth to hummingbird pollination. The functional differences in MYB-FL provide insight into the process of speciation and clarify phylogenetic relationships between nascent species.

The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like

The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12 h time in bed (TIB)] following 12 h of wakefulness were interleaved with three nights of recovery sleep (12 h TIB) following 36 h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25 Hz frequency bins between 0.75 and 16.0 Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait.

Immune cell trafficking across the barriers of the central nervous system in multiple sclerosis and stroke

Each year about 650,000 Europeans die from stroke and a similar number lives with the sequelae of multiple sclerosis (MS). Stroke and MS differ in their etiology. Although cause and likewise clinical presentation set the two diseases apart, they share common downstream mechanisms that lead to damage and recovery. Demyelination and axonal injury are characteristics of MS but are also observed in stroke. Conversely, hallmarks of stroke, such as vascular impairment and neurodegeneration, are found in MS. However, the most conspicuous common feature is the marked neuroinflammatory response, marked by glia cell activation and immune cell influx. In MS and stroke the blood-brain barrier is disrupted allowing bone marrow-derived macrophages to invade the brain in support of the resident microglia. In addition, there is a massive invasion of auto-reactive T-cells into the brain of patients with MS. Though less pronounced a similar phenomenon is also found in ischemic lesions. Not surprisingly, the two diseases also resemble each other at the level of gene expression and the biosynthesis of other proinflammatory mediators. While MS has traditionally been considered to be an autoimmune neuroinflammatory disorder, the role of inflammation for cerebral ischemia has only been recognized later. In the case of MS the long track record as neuroinflammatory disease has paid off with respect to treatment options. There are now about a dozen of approved drugs for the treatment of MS that specifically target neuroinflammation by modulating the immune system. Interestingly, experimental work demonstrated that drugs that are in routine use to mitigate neuroinflammation in MS may also work in stroke models. Examples include Fingolimod, glatiramer acetate, and antibodies blocking the leukocyte integrin VLA-4. Moreover, therapeutic strategies that were discovered in experimental autoimmune encephalomyelitis (EAE), the animal model of MS, turned out to be also effective in experimental stroke models. This suggests that previous achievements in MS research may be relevant for stroke. Interestingly, the converse is equally true. Concepts on the neurovascular unit that were developed in a stroke context turned out to be applicable to neuroinflammatory research in MS. Examples include work on the important role of the vascular basement membrane and the BBB for the invasion of immune cells into the brain. Furthermore, tissue plasminogen activator (tPA), the only established drug treatment in acute stroke, modulates the pathogenesis of MS. Endogenous tPA is released from endothelium and astroglia and acts on the BBB, microglia and other neuroinflammatory cells. Thus, the vascular perspective of stroke research provides important input into the mechanisms on how endothelial cells and the BBB regulate inflammation in MS, particularly the invasion of immune cells into the CNS. In the current review we will first discuss pathogenesis of both diseases and current treatment regimens and will provide a detailed overview on pathways of immune cell migration across the barriers of the CNS and the role of activated astrocytes in this process. This article is part of a Special Issue entitled: Neuro inflammation: A common denominator for stroke, multiple sclerosis and Alzheimer's disease, guest edited by Helga de Vries and Markus Swaninger.