Quantum spin liquid states in the two dimensional kagome antiferromagnets, ZnxCu4-x(OD)6Cl2

A three-dimensional system of interacting spins typically develops static long-range order when it is cooled. If the spins are quantum (S = 1/2), however, novel quantum paramagnetic states may appear. The most highly sought state among them is the resonating valence bond (RVB) state in which every pair of neighboring quantum spins form entangled spin singlets (valence bonds) and the singlets are quantum mechanically resonating amongst all the possible highly degenerate pairing states. Here we provide experimental evidence for such quantum paramagnetic states existing in frustrated antiferromagnets, ZnxCu4-x(OD)6Cl2, where the S = 1/2 magnetic Cu2+ moments form layers of a two-dimensional kagome lattice. We find that in Cu4(OD)6Cl2, where distorted kagome planes are weakly coupled to each other, a dispersionless excitation mode appears in the magnetic excitation spectrum below ~ 20 K, whose characteristics resemble those of quantum spin singlets in a solid state, known as a valence bond solid (VBS), that breaks translational symmetry. Doping nonmagnetic Zn2+ ions reduces the distortion of the kagome lattice, and weakens the interplane coupling but also dilutes the magnetic occupancy of the kagome lattice. The VBS state is suppressed and for ZnCu3(OD)6Cl2 where the kagome planes are undistorted and 90% occupied by the Cu2+ ions, the low energy spin fluctuations in the spin liquid phase become featureless

A reversible light- and genotype-dependent acquired thermotolerance response protects the potato plant from damage due to excessive temperature

A powerful acquired thermotolerance response in potato was demonstrated and characterised in detail, showing the time course required for tolerance, the reversibility of the process and requirement for light. Potato is particularly vulnerable to increased temperature, considered to be the most important uncontrollable factor affecting growth and yield of this globally significant crop. Here, we describe an acquired thermotolerance response in potato, whereby treatment at a mildly elevated temperature primes the plant for more severe heat stress. We define the time course for acquiring thermotolerance and demonstrate that light is essential for the process. In all four commercial tetraploid cultivars that were tested, acquisition of thermotolerance by priming was required for tolerance at elevated temperature. Accessions from several wild-type species and diploid genotypes did not require priming for heat tolerance under the test conditions employed, suggesting that useful variation for this trait exists. Physiological, transcriptomic and metabolomic approaches were employed to elucidate potential mechanisms that underpin the acquisition of heat tolerance. This analysis indicated a role for cell wall modification, auxin and ethylene signalling, and chromatin remodelling in acclimatory priming resulting in reduced metabolic perturbation and delayed stress responses in acclimated plants following transfer to 40 °C

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure.</p> <p>Results and Discussion</p> <p>ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems</p> <p>Conclusion</p> <p>A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.</p

Human serum-derived hydroxy long-chain fatty acids exhibit anti-inflammatory and anti-proliferative activity

<p>Abstract</p> <p>Background</p> <p>Circulating levels of novel long-chain hydroxy fatty acids (called GTAs) were recently discovered in the serum of healthy subjects which were shown to be reduced in subjects with colorectal cancer (CRC), independent of tumor burden or disease stage. The levels of GTAs were subsequently observed to exhibit an inverse association with age in the general population. The current work investigates the biological activity of these fatty acids by evaluating the effects of enriched human serum extracts on cell growth and inflammation.</p> <p>Methods</p> <p>GTAs were extracted from commercially available bulk human serum and then chromatographically separated into enriched (GTA-positive) and depleted (GTA-negative) fractions. SW620, MCF7 and LPS stimulated RAW264.7 cells were treated with various concentrations of the GTA-positive and GTA-negative extracts, and the effects on cell growth and inflammation determined.</p> <p>Results</p> <p>Enriched fractions resulted in poly-ADP ribose polymerase (PARP) cleavage, suppression of NFκB, induction of IκBα, and reduction in NOS2 mRNA transcript levels. In RAW264.7 mouse macrophage cells, incubation with enriched fractions prior to treatment with LPS blocked the induction of several pro-inflammatory markers including nitric oxide, TNFα, IL-1β, NOS2 and COX2.</p> <p>Conclusions</p> <p>Our results show that human serum extracts enriched with endogenous long-chain hydroxy fatty acids possess anti-inflammatory and anti-proliferative activity. These findings support a hypothesis that the reduction of these metabolites with age may result in a compromised ability to defend against uncontrolled cell growth and inflammation, and could therefore represent a significant risk for the development of CRC.</p

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

Background Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (−28·4 to −2·9) for all diabetes, and by 21·0% (–33·0 to −5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (−13·6% [–28·4 to 3·4]) and for type 1 diabetes (−13·6% [–29·3 to 8·9]). Interpretation Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations.publishedVersio