Membrane-Active Epithelial Keratin 6A Fragments (KAMPs) Are Unique Human Antimicrobial Peptides with a Non-αβ Structure.

Antibiotic resistance is a pressing global health problem that threatens millions of lives each year. Natural antimicrobial peptides and their synthetic derivatives, including peptoids and peptidomimetics, are promising candidates as novel antibiotics. Recently, the C-terminal glycine-rich fragments of human epithelial keratin 6A were found to have bactericidal and cytoprotective activities. Here, we used an improved 2-dimensional NMR method coupled with a new protocol for structural refinement by low temperature simulated annealing to characterize the solution structure of these kerain-derived antimicrobial peptides (KAMPs). Two specific KAMPs in complex with membrane mimicking sodium dodecyl sulfate (SDS) micelles displayed amphipathic conformations with only local bends and turns, and a central 10-residue glycine-rich hydrophobic strip that is central to bactericidal activity. To our knowledge, this is the first report of non-αβ structure for human antimicrobial peptides. Direct observation of Staphylococcus aureus and Pseudomonas aeruginosa by scanning and transmission electron microscopy showed that KAMPs deformed bacterial cell envelopes and induced pore formation. Notably, in competitive binding experiments, KAMPs demonstrated binding affinities to LPS and LTA that did not correlate with their bactericidal activities, suggesting peptide-LPS and peptide-LTA interactions are less important in their mechanisms of action. Moreover, immunoprecipitation of KAMPs-bacterial factor complexes indicated that membrane surface lipoprotein SlyB and intracellular machineries NQR sodium pump and ribosomes are potential molecular targets for the peptides. Results of this study improve our understanding of the bactericidal function of epithelial cytokeratin fragments, and highlight an unexplored class of human antimicrobial peptides, which may serve as non-αβ peptide scaffolds for the design of novel peptide-based antibiotics

Dynamic spin-lattice coupling and nematic fluctuations in NaFeAs

We use inelastic neutron scattering to study acoustic phonons and spin excitations in single crystals of NaFeAs, a parent compound of iron pnictide superconductors. NaFeAs exhibits a tetragonal-to-orthorhombic structural transition at $T_s\approx 58$ K and a collinear antiferromagnetic (AF) order at $T_N\approx 45$ K. While longitudinal and out-of-plane transverse acoustic phonons behave as expected, the in-plane transverse acoustic phonons reveal considerable softening on cooling to $T_s$, and then harden on approaching $T_N$ before saturating below $T_N$. In addition, we find that spin-spin correlation lengths of low-energy magnetic excitations within the FeAs layer and along the $c$-axis increase dramatically below $T_s$, and show weak anomaly across $T_N$. These results suggest that the electronic nematic phase present in the paramagnetic tetragonal phase is closely associated with dynamic spin-lattice coupling, possibly arising from the one-phonon-two-magnon mechanism

Parentage Influence On Gene Expression Under Acidification Revealed Through Single-Embryo Sequencing

The dissolution of anthropogenic carbon dioxide (CO2) in seawater has altered its carbonate chemistry in the process of ocean acidification (OA). OA affects the viability of marine species. In particular, calcifying organisms and their early planktonic larval stages are considered vulnerable. These organisms often utilize energy reserves for metabolism rather than growth and calcification as supported by bulk RNA-sequencing (RNA-seq) experiments. Yet, transcriptomic profiling of a bulk sample reflects the average gene expression of the population, neglecting the variations between individuals, which forms the basis for natural selection. Here, we used single-embryo RNA-seq on larval sea urchin Heliocidaris crassispina, which is a commercially and ecologically valuable species in East Asia, to document gene expression changes to OA at an individual and family level. Three paternal half-sibs groups were fertilized and exposed to 3 pH conditions (ambient pH 8.0, 7.7 and 7.4) for 12 h prior to sequencing and oxygen consumption assay. The resulting transcriptomic profile of all embryos can be distinguished into four clusters, with differences in gene expressions that govern biomineralization, cell differentiation and patterning, as well as metabolism. While these responses were influenced by pH conditions, the male identities also had an effect. Specifically, a regression model and goodness of fit tests indicated a significant interaction between sire and pH on the probability of embryo membership in different clusters of gene expression. The single-embryo RNA-seq approach is promising in climate stressor research because not only does it highlight potential impacts before phenotypic changes were observed, but it also highlights variations between individuals and lineages, thus enabling a better determination of evolutionary potential

Edgetic perturbation models of human inherited disorders

Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes' and ‘edges', respectively. Better understanding of genotype-to-phenotype relationships in human disease will require modeling of how disease-causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal') and interaction-specific or edge-specific (‘edgetic') alterations. Global computational analyses of ∼50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies

The NRF2-mediated oxidative stress response pathway is associated with tumor cell resistance to arsenic trioxide across the NCI-60 panel

<p>Abstract</p> <p>Background</p> <p>Drinking water contaminated with inorganic arsenic is associated with increased risk for different types of cancer. Paradoxically, arsenic trioxide can also be used to induce remission in patients with acute promyelocytic leukemia (APL) with a success rate of approximately 80%. A comprehensive study examining the mechanisms and potential signaling pathways contributing to the anti-tumor properties of arsenic trioxide has not been carried out.</p> <p>Methods</p> <p>Here we applied a systems biology approach to identify gene biomarkers that underlie tumor cell responses to arsenic-induced cytotoxicity. The baseline gene expression levels of 14,500 well characterized human genes were associated with the GI₅₀ data of the NCI-60 tumor cell line panel from the developmental therapeutics program (DTP) database. Selected biomarkers were tested <it>in vitro</it> for the ability to influence tumor susceptibility to arsenic trioxide.</p> <p>Results</p> <p>A significant association was found between the baseline expression levels of 209 human genes and the sensitivity of the tumor cell line panel upon exposure to arsenic trioxide. These genes were overlayed onto protein-protein network maps to identify transcriptional networks that modulate tumor cell responses to arsenic trioxide. The analysis revealed a significant enrichment for the oxidative stress response pathway mediated by nuclear factor erythroid 2-related factor 2 (NRF2) with high expression in arsenic resistant tumor cell lines. The role of the NRF2 pathway in protecting cells against arsenic-induced cell killing was validated in tumor cells using shRNA-mediated knock-down.</p> <p>Conclusions</p> <p>In this study, we show that the expression level of genes in the NRF2 pathway serve as potential gene biomarkers of tumor cell responses to arsenic trioxide. Importantly, we demonstrate that tumor cells that are deficient for NRF2 display increased sensitivity to arsenic trioxide. The results of our study will be useful in understanding the mechanism of arsenic-induced cytotoxicity in cells, as well as the increased applicability of arsenic trioxide as a chemotherapeutic agent in cancer treatment.</p

Meta-analysis Followed by Replication Identifies Loci in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as Associated with Systemic Lupus Erythematosus in Asians

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic involvement and ethnic differences. Susceptibility genes identified so far only explain a small portion of the genetic heritability of SLE, suggesting that many more loci are yet to be uncovered for this disease. In this study, we performed a meta-analysis of genome-wide association studies on SLE in Chinese Han populations and followed up the findings by replication in four additional Asian cohorts with a total of 5,365 cases and 10,054 corresponding controls. We identified genetic variants in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as associated with the disease. These findings point to potential roles of cell-cycle regulation, autophagy, and DNA demethylation in SLE pathogenesis. For the region involving TET3 and that involving CDKN1B, multiple independent SNPs were identified, highlighting a phenomenon that might partially explain the missing heritability of complex diseases

Drug interventions for the treatment of obesity in children and adolescents

BACKGROUND: Child and adolescent obesity has increased globally, and can be associated with significant short- and long-term health consequences. OBJECTIVES: To assess the efficacy of drug interventions for the treatment of obesity in children and adolescents. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, PubMed (subsets not available on Ovid), LILACS as well as the trial registers ICTRP (WHO) and ClinicalTrials.gov. Searches were undertaken from inception to March 2016. We checked references and applied no language restrictions. SELECTION CRITERIA: We selected randomised controlled trials (RCTs) of pharmacological interventions for treating obesity (licensed and unlicensed for this indication) in children and adolescents (mean age under 18 years) with or without support of family members, with a minimum of three months' pharmacological intervention and six months' follow-up from baseline. We excluded interventions that specifically dealt with the treatment of eating disorders or type 2 diabetes, or included participants with a secondary or syndromic cause of obesity. In addition, we excluded trials which included growth hormone therapies and pregnant participants. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trial quality and extracted data following standard Cochrane methodology. Where necessary we contacted authors for additional information. MAIN RESULTS: We included 21 trials and identified eight ongoing trials. The included trials evaluated metformin (11 trials), sibutramine (six trials), orlistat (four trials), and one trial arm investigated the combination of metformin and fluoxetine. The ongoing trials evaluated metformin (four trials), topiramate (two trials) and exenatide (two trials). A total of 2484 people participated in the included trials, 1478 participants were randomised to drug intervention and 904 to comparator groups (91 participants took part in two cross-over trials; 11 participants not specified). Eighteen trials used a placebo in the comparator group. Two trials had a cross-over design while the remaining 19 trials were parallel RCTs. The length of the intervention period ranged from 12 weeks to 48 weeks, and the length of follow-up from baseline ranged from six months to 100 weeks.Trials generally had a low risk of bias for random sequence generation, allocation concealment and blinding (participants, personnel and assessors) for subjective and objective outcomes. We judged approximately half of the trials as having a high risk of bias in one or more domain such as selective reporting.The primary outcomes of this review were change in body mass index (BMI), change in weight and adverse events. All 21 trials measured these outcomes. The secondary outcomes were health-related quality of life (only one trial reported results showing no marked differences; very low certainty evidence), body fat distribution (measured in 18 trials), behaviour change (measured in six trials), participants' views of the intervention (not reported), morbidity associated with the intervention (measured in one orlistat trial only reporting more new gallstones following the intervention; very low certainty evidence), all-cause mortality (one suicide in the orlistat intervention group; low certainty evidence) and socioeconomic effects (not reported).Intervention versus comparator for mean difference (MD) in BMI change was -1.3 kg/m(2) (95% confidence interval (CI) -1.9 to -0.8; P < 0.00001; 16 trials; 1884 participants; low certainty evidence). When split by drug type, sibutramine, metformin and orlistat all showed reductions in BMI in favour of the intervention.Intervention versus comparator for change in weight showed a MD of -3.9 kg (95% CI -5.9 to -1.9; P < 0.00001; 11 trials; 1180 participants; low certainty evidence). As with BMI, when the trials were split by drug type, sibutramine, metformin and orlistat all showed reductions in weight in favour of the intervention.Five trials reported serious adverse events: 24/878 (2.7%) participants in the intervention groups versus 8/469 (1.7%) participants in the comparator groups (risk ratio (RR) 1.43, 95% CI 0.63 to 3.25; 1347 participants; low certainty evidence). A total 52/1043 (5.0%) participants in the intervention groups versus 17/621 (2.7%) in the comparator groups discontinued the trial because of adverse events (RR 1.45, 95% CI 0.83 to 2.52; 10 trials; 1664 participants; low certainty evidence). The most common adverse events in orlistat and metformin trials were gastrointestinal (such as diarrhoea, mild abdominal pain or discomfort, fatty stools). The most frequent adverse events in sibutramine trials included tachycardia, constipation and hypertension. The single fluoxetine trial reported dry mouth and loose stools. No trial investigated drug treatment for overweight children. AUTHORS' CONCLUSIONS: This systematic review is part of a series of associated Cochrane reviews on interventions for obese children and adolescents and has shown that pharmacological interventions (metformin, sibutramine, orlistat and fluoxetine) may have small effects in reduction in BMI and bodyweight in obese children and adolescents. However, many of these drugs are not licensed for the treatment of obesity in children and adolescents, or have been withdrawn. Trials were generally of low quality with many having a short or no post-intervention follow-up period and high dropout rates (overall dropout of 25%). Future research should focus on conducting trials with sufficient power and long-term follow-up, to ensure the long-term effects of any pharmacological intervention are comprehensively assessed. Adverse events should be reported in a more standardised manner specifying amongst other things the number of participants experiencing at least one adverse event. The requirement of regulatory authorities (US Food and Drug Administration and European Medicines Agency) for trials of all new medications to be used in children and adolescents should drive an increase in the number of high quality trials

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</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