Prevalence and risk factors for atopic dermatitis in Greenlandic children.

BACKGROUND: The epidemiology of atopic dermatitis (AD) in Greenland has been sparsely investigated. AIM: To examine the point and overall prevalence, cumulative incidence at different ages, and associated risk factors for AD among children in Greenland. METHODS: Between 2019 and 2020, three towns in Greenland, representing 48% of the total population, were visited. A cross-sectional study was conducted, including children aged 0-7 years attending daycare centres. Parents completed a questionnaire with questions on AD and related risk factors. A diagnosis of AD was based on the UK Working Party's criteria along with a clinical examination. RESULTS: In total, 839 children aged 0-7 years were included. The overall prevalence of AD was 35% according to physician's diagnosis and assessment. The point prevalence was 28% and peaked among 1-year-old children (36%) and declined with age. The cumulative incidence at ages 1-6 years varied between 29% and 41% and was highest in 1-year-old children and showed a slight decline with increasing age. In the fully adjusted multivariate model, AD was associated with being of Inuit descent [odds ratio (OR) 1.7, 95% confidence interval (CI) 1.1-2.8]; food allergy in the child (OR 3.6, 95% CI 2.3-5.6); ear infection in the child (OR 1.4, 95% CI 1.0-1.9); having a mother with a high educational level (OR 1.5, 95% CI 1.0-2.3); maternal atopy (OR 1.4, 95% CI 1.1-2.0); and paternal atopy (OR 2.0, 95% CI 1.5-2.8). No environmental risk factors were identified. CONCLUSION: The overall prevalence of AD in children in Greenland is high and has likely increased over the past 20 years. The point prevalence was highest in the youngest children indicating early onset of disease. Inuit descent, family atopy predisposition and having a higher socioeconomic status (based on parental educational level and housing) increased the risk of AD. Insight into possible Inuit-specific genetic predisposition is needed.

Improved Battery Cycle Life Prediction Using a Hybrid Data-Driven Model Incorporating Linear Support Vector Regression and Gaussian.

The ability to accurately predict lithium-ion battery life-time already at an early stage of battery usage is critical for ensuring safe operation, accelerating technology development, and enabling battery second-life applications. Many models are unable to effectively predict battery life-time at early cycles due to the complex and nonlinear degrading behavior of lithium-ion batteries. In this study, two hybrid data-driven models, incorporating a traditional linear support vector regression (LSVR) and a Gaussian process regression (GPR), were developed to estimate battery life-time at an early stage, before more severe capacity fading, utilizing a data set of 124 battery cells with lifetimes ranging from 150 to 2300 cycles. Two type of hybrid models, here denoted as A and B, were proposed. For each of the models, we achieved 1.1 % (A) and 1.4 % (B) training error, and similarly, 8.3 % (A) and 8.2 % (B) test error. The two key advantages are that the error percentage is kept below 10 % and that very low error values for the training and test sets were observed when utilizing data from only the first 100 cycles.The proposed method thus appears highly promising for predicting battery life during early cycles.

Binder assisted graphene derivatives as lubricants in copper: Improved tribological performance for industrial application.

Originally derived from graphite, high-quality single-layer graphene is an excellent anti-wear and -friction additive in metal matrix. Here, the tribological performance of 3 different commercialized graphene derivatives (e.g., graphene oxide [GO], reduced graphene oxide [RGO], and graphene nanoplatelet [GNP]) as additives in a Cu matrix, were investigated from an industrial perspective. To increase the interaction of graphene derivatives with Cu particles, and addressing the aggregation problem of the graphene derivatives, different binders (polyvinyl alcohol [PVA] and cellulose nanocrystals [CNC]) were introduced into the system. Benefiting from such a strategy, a uniform distribution of the graphene derivatives in Cu matrix was achieved with graphene loading up to 5 wt %. After high-temperature sintering, the graphene is preserved and well distributed in the Cu matrix. It was found that the GNP-containing sample shows the most stable friction coefficient behavior. However, GO and RGO also improve the tribological performance of Cu under different circumstances.

Structure and function of negative feedback loops at the interface of genetic and metabolic networks.

The molecular network in an organism consists of transcription/translation regulation, protein-protein interactions/modifications and a metabolic network, together forming a system that allows the cell to respond sensibly to the multiple signal molecules that exist in its environment. A key part of this overall system of molecular regulation is therefore the interface between the genetic and the metabolic network. A motif that occurs very often at this interface is a negative feedback loop used to regulate the level of the signal molecules. In this work we use mathematical models to investigate the steady state and dynamical behaviour of different negative feedback loops. We show, in particular, that feedback loops where the signal molecule does not cause the dissociation of the transcription factor from the DNA respond faster than loops where the molecule acts by sequestering transcription factors off the DNA. We use three examples, the bet, mer and lac systems in Escherichia coli, to illustrate the behaviour of such feedback loops.

Genetic regulation of fluxes: iron homeostasis of Escherichia coli.

Iron is an essential trace-element for most organisms. However, because high concentration of free intracellular iron is cytotoxic, cells have developed complex regulatory networks that keep free intracellular iron concentration at optimal range, allowing the incorporation of the metal into iron-using enzymes and minimizing damage to the cell. We built a mathematical model of the network that controls iron uptake and usage in the bacterium Escherichia coli to explore the dynamics of iron flow. We simulate the effect of sudden decrease or increase in the extracellular iron level on intracellular iron distribution. Based on the results of simulations we discuss the possible roles of the small RNA RyhB and the Fe-S cluster assembly systems in the optimal redistribution of iron flows. We suggest that Fe-S cluster assembly is crucial to prevent the accumulation of toxic levels of free intracellular iron when the environment suddenly becomes iron rich.

Efficient degradation and expression prioritization with small RNAs.

We build a simple model for feedback systems involving small RNA (sRNA) molecules based on the iron metabolism system in the bacterium E. coli, and compare it with the corresponding system in H. pylori which uses purely transcriptional regulation. This reveals several unique features of sRNA-based regulation that could be exploited by cells. Firstly, we show that sRNA regulation can maintain a smaller turnover of target mRNAs than transcriptional regulation, without sacrificing the speed of response to external shocks. Secondly, we propose that a single sRNA can prioritize the usage of different target mRNAs. This suggests that sRNA regulation would be more common in more complex systems which need to co-regulate many mRNAs efficiently.

Biased partitioning of the multidrug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.

The molecular mechanisms underlying phenotypic variation in isogenic bacterial populations remain poorly understood. We report that AcrAB-TolC, the main multidrug efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex formation. Mother cells inheriting old poles are phenotypically distinct and display increased drug efflux activity relative to daughters. Consequently, we find systematic and long-lived growth differences between mother and daughter cells in the presence of subinhibitory drug concentrations. A simple model for biased partitioning predicts a population structure of long-lived and highly heterogeneous phenotypes. This straightforward mechanism of generating sustained growth rate differences at subinhibitory antibiotic concentrations has implications for understanding the emergence of multidrug resistance in bacteria.

Combinatorial Study of Gradient Ag-Al Thin Films: Microstructure, Phase Formation, Mechanical and Electrical Properties.

A combinatorial approach is applied to rapidly deposit and screen Ag-Al thin films to evaluate the mechanical, tribological, and electrical properties as a function of chemical composition. Ag-Al thin films with large continuous composition gradients (6-60 atom % Al) were deposited by a custom-designed combinatorial magnetron sputtering system. X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), scanning and transmission electron microscopy (SEM and TEM), X-ray photoelectron spectroscopy (XPS), nanoindentation, and four-point electrical resistance screening were employed to characterize the chemical composition, structure, and physical properties of the films in a time-efficient way. For low Al contents (<13 atom %), a highly (111)-textured fcc phase was formed. At higher Al contents, a (002)-textured hcp solid solution phase was formed followed by a fcc phase in the most Al-rich regions. No indication of a µ phase was observed. The Ag-Al films with fcc-Ag matrix is prone to adhesive material transfer leading to a high friction coefficient (>1) and adhesive wear, similar to the behavior of pure Ag. In contrast, the hexagonal solid solution phase (from ca. 15 atom %Al) exhibited dramatically reduced friction coefficients (about 15% of that of the fcc phase) and dramatically reduced adhesive wear when tested against the pure Ag counter surface. The increase in contact resistance of the Ag-Al films is limited to only 50% higher than a pure Ag reference sample at the low friction and low wear region (19-27 atom %). This suggests that a hcp Ag-Al alloy can have a potential use in sliding electrical contact applications and in the future will replace pure Ag in specific electromechanical applications.

Aging mechanism as the "down side" of adaptation: a network approach.

Many diverse hypotheses on aging are in play. All from "aging genes" over decreasing telomere length to increased level of gene mutations has been suggested to determine an organism's lifespan, but no unifying theory exists. As part of a growing interest toward more integrative approaches in the field we propose a simplistic model based on the "use-it-or-lose-it" concept: we hypothesize that biological aging is a systemic property and the down side of adaptation in complex biological networks at various levels of organization: from brain over the immune system to specialized tissues or organs. The simple dynamical model undergoes three phases during its lifetime: (1) general plasticity (childhood), (2) optimization/adaptation to given conditions (youth and adolescence) and (3) steady state associated with high rigidity (aging). Furthermore, our model mimics recent data on the dynamics of the immune system during aging and, although simplistic, thus captures essential characteristics of the aging process. Finally, we discuss the abstract model in relation to current knowledge on aging and propose experimental setups for testing some of the theoretical predictions.