Evolution of leaf-form in land plants linked to atmospheric CO2 decline in the Late Palaeozoic era

The widespread appearance of megaphyll leaves, with their branched veins and planate form, did not occur until the close of the Devonian period at about 360 Myr ago. This happened about 40 Myr after simple leafless vascular plants first colonized the land in the Late Silurian/Early Devonian, but the reason for the slow emergence of this common feature of present-day plants is presently unresolved. Here we show, in a series of quantitative analyses using fossil leaf characters and biophysical principles, that the delay was causally linked with a 90% drop in atmospheric pCO2 during the Late Palaeozoic era. In contrast to simulations for a typical Early Devonian land plant, possessing few stomata on leafless stems, those for a planate leaf with the same stomatal characteristics indicate that it would have suffered lethal overheating, because of greater interception of solar energy and low transpiration. When planate leaves first appeared in the Late Devonian and subsequently diversified in the Carboniferous period, they possessed substantially higher stomatal densities. This observation is consistent with the effects of the pCO2 on stomatal development and suggests that the evolution of planate leaves could only have occurred after an increase in stomatal density, allowing higher transpiration rates that were sufficient to maintain cool and viable leaf temperatures

Fully gapped topological surface states in Bi2_2Se3_3 films induced by a d-wave high-temperature superconductor

Topological insulators are a new class of materials, that exhibit robust gapless surface states protected by time-reversal symmetry. The interplay between such symmetry-protected topological surface states and symmetry-broken states (e.g. superconductivity) provides a platform for exploring novel quantum phenomena and new functionalities, such as 1D chiral or helical gapless Majorana fermions, and Majorana zero modes which may find application in fault-tolerant quantum computation. Inducing superconductivity on topological surface states is a prerequisite for their experimental realization. Here by growing high quality topological insulator Bi$_2$Se$_3$ films on a d-wave superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ using molecular beam epitaxy, we are able to induce high temperature superconductivity on the surface states of Bi$_2$Se$_3$ films with a large pairing gap up to 15 meV. Interestingly, distinct from the d-wave pairing of Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$, the proximity-induced gap on the surface states is nearly isotropic and consistent with predominant s-wave pairing as revealed by angle-resolved photoemission spectroscopy. Our work could provide a critical step toward the realization of the long sought-after Majorana zero modes.Comment: Nature Physics, DOI:10.1038/nphys274

Molecular Approaches to Identify Cryptic Species and Polymorphic Species within a Complex Community of Fig Wasps

Cryptic and polymorphic species can complicate traditional taxonomic research and both of these concerns are common in fig wasp communities. Species identification is very difficult, despite great effort and the ecological importance of fig wasps. Herein, we try to identify all chalcidoid wasp species hosted by one species of fig, using both morphological and molecular methods. We compare the efficiency of four different DNA regions and find that ITS2 is highly effective for species identification, while mitochondrial COI and Cytb regions appear less reliable, possibly due to the interference signals from either nuclear copies of mtDNA, i.e. NUMTs, or the effects of Wolbachia infections. The analyses suggest that combining multiple markers is the best choice for inferring species identifications as any one marker may be unsuitable in a given case

Effects of Combined Aspirin and Clopidogrel Therapy on Cardiovascular Outcomes: A Systematic Review and Meta-Analysis

BACKGROUND: Aspirin and clopidogrel monotherapies are effective treatments for preventing vascular disease. However, new evidence has emerged regarding the use of combined aspirin and clopidogrel therapy to prevent cardiovascular events. We therefore performed a comprehensive systematic review and meta-analysis to evaluate the benefits and harms of combined aspirin and clopidogrel therapy on major cardiovascular outcomes. METHODOLOGY/PRINCIPAL FINDINGS: We systematically searched Medline, Embase, the Cochrane Central Register of Controlled Trials, reference lists of articles, and proceedings of major meetings to identify studies to fit our analysis. Eligible studies were randomized controlled trials assessing the effect of combined aspirin and clopidogrel therapy compared with aspirin or clopidogrel monotherapy. We identified 7 trials providing data with a total of 48248 patients. These studies reported 5134 major cardiovascular events, 1626 myocardial infarctions, 1927 strokes, and 1147 major bleeding events. Overall, the addition of aspirin to clopidogrel therapy as compared to single drug therapy resulted in a 9% RR reduction (95%CI, 2 to 17) in major cardiovascular events, 14% RR reduction (95%CI, 3 to 24) in myocardial infarction, 16% RR reduction (95%CI, 1 to 28) in stroke, and 62% RR increase (95%CI, 26 to 108) in major bleeding events. We also present the data as ARR to explore net value as the reduction in cardiovascular events. Overall, we observed that combined therapy yielded 1.06% decrease (95%CI, 0.23% to 1.99%) in major cardiovascular events and 1.23% increase (95%CI, 0.52% to 2.14%) in major bleeding events. CONCLUSION/SIGNIFICANCE: Although the addition of aspirin to clopidogrel resulted in small relative reductions in major cardiovascular events, myocardial infarction, and stroke, it also resulted in a relative increase in major bleeding events. In absolute terms the benefits of combined therapy, a 1.06% reduction in major cardiovascular events, does not outweigh the harms, a 1.23% increase in major bleeding events

Exploiting likely-positive and unlabeled data to improve the identification of protein-protein interaction articles

<p>Abstract</p> <p>Background</p> <p>Experimentally verified protein-protein interactions (PPI) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be made faster by ranking newly-published articles' relevance to PPI, a task which we approach here by designing a machine-learning-based PPI classifier. All classifiers require labeled data, and the more labeled data available, the more reliable they become. Although many PPI databases with large numbers of labeled articles are available, incorporating these databases into the base training data may actually reduce classification performance since the supplementary databases may not annotate exactly the same PPI types as the base training data. Our first goal in this paper is to find a method of selecting likely positive data from such supplementary databases. Only extracting likely positive data, however, will bias the classification model unless sufficient negative data is also added. Unfortunately, negative data is very hard to obtain because there are no resources that compile such information. Therefore, our second aim is to select such negative data from unlabeled PubMed data. Thirdly, we explore how to exploit these likely positive and negative data. And lastly, we look at the somewhat unrelated question of which term-weighting scheme is most effective for identifying PPI-related articles.</p> <p>Results</p> <p>To evaluate the performance of our PPI text classifier, we conducted experiments based on the BioCreAtIvE-II IAS dataset. Our results show that adding likely-labeled data generally increases AUC by 3~6%, indicating better ranking ability. Our experiments also show that our newly-proposed term-weighting scheme has the highest AUC among all common weighting schemes. Our final model achieves an F-measure and AUC 2.9% and 5.0% higher than those of the top-ranking system in the IAS challenge.</p> <p>Conclusion</p> <p>Our experiments demonstrate the effectiveness of integrating unlabeled and likely labeled data to augment a PPI text classification system. Our mixed model is suitable for ranking purposes whereas our hierarchical model is better for filtering. In addition, our results indicate that supervised weighting schemes outperform unsupervised ones. Our newly-proposed weighting scheme, TFBRF, which considers documents that do not contain the target word, avoids some of the biases found in traditional weighting schemes. Our experiment results show TFBRF to be the most effective among several other top weighting schemes.</p

The calcimimetic R-568 induces apoptotic cell death in prostate cancer cells

<p>Abstract</p> <p>Background</p> <p>Increased serum level of parathyroid hormone (PTH) was found in metastatic prostate cancers. Calcimimetic R-568 was reported to reduce PTH expression, to suppress cell proliferation and to induce apoptosis in parathyroid cells. In this study, we investigated the effect of R-568 on cellular survival of prostate cancer cells.</p> <p>Methods</p> <p>Prostate cancer cell lines LNCaP and PC-3 were used in this study. Cellular survival was determined with MTT, trypan blue exclusion and fluorescent Live/Death assays. Western blot assay was utilized to assess apoptotic events induced by R-568 treatment. JC-1 staining was used to evaluate mitochondrial membrane potential.</p> <p>Results</p> <p>In cultured prostate cancer LNCaP and PC-3 cells, R-568 treatment significantly reduced cellular survival in a dose- and time-dependent manner. R-568-induced cell death was an apoptotic event, as evidenced by caspase-3 processing and PARP cleavage, as well as JC-1 color change in mitochondria. Knocking down calcium sensing receptor (CaSR) significantly reduced R-568-induced cytotoxicity. Enforced expression of Bcl-xL gene abolished R-568-induced cell death, while loss of Bcl-xL expression led to increased cell death in R-568-treated LNCaP cells,.</p> <p>Conclusion</p> <p>Taken together, our data demonstrated that calcimimetic R-568 triggers an intrinsic mitochondria-related apoptotic pathway, which is dependent on the CaSR and is modulated by Bcl-xL anti-apoptotic pathway.</p

Sustained Release of Multiple Growth Factors from Injectable Polymeric System as a Novel Therapeutic Approach Towards Angiogenesis

The aim was to investigate that a bio-degradable alginate and poly lactide-co-glycolide (PLG) system capable of delivering growth factors sequentially would be superior to single growth factor delivery in promoting neovascularization and improving perfusion

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Predicting Target DNA Sequences of DNA-Binding Proteins Based on Unbound Structures

DNA-binding proteins such as transcription factors use DNA-binding domains (DBDs) to bind to specific sequences in the genome to initiate many important biological functions. Accurate prediction of such target sequences, often represented by position weight matrices (PWMs), is an important step to understand many biological processes. Recent studies have shown that knowledge-based potential functions can be applied on protein-DNA co-crystallized structures to generate PWMs that are considerably consistent with experimental data. However, this success has not been extended to DNA-binding proteins lacking co-crystallized structures. This study aims at investigating the possibility of predicting the DNA sequences bound by DNA-binding proteins from the proteins' unbound structures (structures of the unbound state). Given an unbound query protein and a template complex, the proposed method first employs structure alignment to generate synthetic protein-DNA complexes for the query protein. Once a complex is available, an atomic-level knowledge-based potential function is employed to predict PWMs characterizing the sequences to which the query protein can bind. The evaluation of the proposed method is based on seven DNA-binding proteins, which have structures of both DNA-bound and unbound forms for prediction as well as annotated PWMs for validation. Since this work is the first attempt to predict target sequences of DNA-binding proteins from their unbound structures, three types of structural variations that presumably influence the prediction accuracy were examined and discussed. Based on the analyses conducted in this study, the conformational change of proteins upon binding DNA was shown to be the key factor. This study sheds light on the challenge of predicting the target DNA sequences of a protein lacking co-crystallized structures, which encourages more efforts on the structure alignment-based approaches in addition to docking- and homology modeling-based approaches for generating synthetic complexes

Large-scale Synthesis of β-SiC Nanochains and Their Raman/Photoluminescence Properties

Although the SiC/SiO2 nanochain heterojunction has been synthesized, the chained homogeneous nanostructure of SiC has not been reported before. Herein, the novel β-SiC nanochains are synthesized assisted by the AAO template. The characterized results demonstrate that the nanostructures are constructed by spheres of 25–30 nm and conjoint wires of 15–20 nm in diameters. Raman and photoluminescence measurements are used to explore the unique optical properties. A speed-alternating vapor–solid (SA-VS) growth mechanism is proposed to interpret the formation of this typical nanochains. The achieved nanochains enrich the species of one-dimensional (1D) nanostructures and may hold great potential applications in nanotechnology