Ideal maximum strengths and defect-induced softening in nanocrystalline-nanotwinned metals

Strengthening of metals through nanoscale grain boundaries and coherent twin boundaries is manifested by a maximum strength—a phenomenon known as Hall–Petch breakdown. Different softening mechanisms are considered to occur for nanocrystalline and nanotwinned materials. Here, we report nanocrystalline-nanotwinned Ag materials that exhibit two strength transitions dissimilar from the above mechanisms. Atomistic simulations show three distinct strength regions as twin spacing decreases, delineated by positive Hall–Petch strengthening to grain-boundary-dictated (near-zero Hall–Petch slope) mechanisms and to softening (negative Hall–Petch slope) induced by twin-boundary defects. An ideal maximum strength is reached for a range of twin spacings below 7 nm. We synthesized nanocrystalline-nanotwinned Ag with hardness 3.05 GPa—42% higher than the current record, by segregating trace concentrations of Cu impurity (\u3c1.0 weight (wt)%). The microalloy retains excellent electrical conductivity and remains stable up to 653 K; 215 K better than for pure nanotwinned Ag. This breaks the existing trade-off between strength and electrical conductivity, and demonstrates the potential for creating interface-dominated materials with unprecedented mechanical and physical properties

Gene Expression Profiles Deciphering Rice Phenotypic Variation between Nipponbare (Japonica) and 93-11 (Indica) during Oxidative Stress

Rice is a very important food staple that feeds more than half the world's population. Two major Asian cultivated rice (Oryza sativa L.) subspecies, japonica and indica, show significant phenotypic variation in their stress responses. However, the molecular mechanisms underlying this phenotypic variation are still largely unknown. A common link among different stresses is that they produce an oxidative burst and result in an increase of reactive oxygen species (ROS). In this study, methyl viologen (MV) as a ROS agent was applied to investigate the rice oxidative stress response. We observed that 93-11 (indica) seedlings exhibited leaf senescence with severe lesions under MV treatment compared to Nipponbare (japonica). Whole-genome microarray experiments were conducted, and 1,062 probe sets were identified with gene expression level polymorphisms between the two rice cultivars in addition to differential expression under MV treatment, which were assigned as Core Intersectional Probesets (CIPs). These CIPs were analyzed by gene ontology (GO) and highlighted with enrichment GO terms related to toxin and oxidative stress responses as well as other responses. These GO term-enriched genes of the CIPs include glutathine S-transferases (GSTs), P450, plant defense genes, and secondary metabolism related genes such as chalcone synthase (CHS). Further insertion/deletion (InDel) and regulatory element analyses for these identified CIPs suggested that there may be some eQTL hotspots related to oxidative stress in the rice genome, such as GST genes encoded on chromosome 10. In addition, we identified a group of marker genes individuating the japonica and indica subspecies. In summary, we developed a new strategy combining biological experiments and data mining to study the possible molecular mechanism of phenotypic variation during oxidative stress between Nipponbare and 93-11. This study will aid in the analysis of the molecular basis of quantitative traits

Generation of Functional CLL-Specific Cord Blood CTL Using CD40-Ligated CLL APC

PMCID: PMC3526610This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

A covalently bound inhibitor triggers EZH2 degradation through CHIP‐mediated ubiquitination

Abstract Enhancer of zeste homolog 2 (EZH2) has been characterized as a critical oncogene and a promising drug target in human malignant tumors. The current EZH2 inhibitors strongly suppress the enhanced enzymatic function of mutant EZH2 in some lymphomas. However, the recent identification of a PRC2‐ and methyltransferase‐independent role of EZH2 indicates that a complete suppression of all oncogenic functions of EZH2 is needed. Here, we report a unique EZH2‐targeting strategy by identifying a gambogenic acid (GNA) derivative as a novel agent that specifically and covalently bound to Cys668 within the EZH2‐SET domain, triggering EZH2 degradation through COOH terminus of Hsp70‐interacting protein (CHIP)‐mediated ubiquitination. This class of inhibitors significantly suppressed H3K27Me3 and effectively reactivated polycomb repressor complex 2 (PRC2)‐silenced tumor suppressor genes. Moreover, the novel inhibitors significantly suppressed tumor growth in an EZH2‐dependent manner, and tumors bearing a non‐GNA‐interacting C668S‐EZH2 mutation exhibited resistance to the inhibitors. Together, our results identify the inhibition of the signaling pathway that governs GNA‐mediated destruction of EZH2 as a promising anti‐cancer strategy

Transcriptome Analysis of the Model Protozoan, Tetrahymena thermophila, Using Deep RNA Sequencing

Background: The ciliated protozoan Tetrahymena thermophila is a well-studied single-celled eukaryote model organism for cellular and molecular biology. However, the lack of extensive T. thermophila cDNA libraries or a large expressed sequence tag (EST) database limited the quality of the original genome annotation. Methodology/Principal Findings: This RNA-seq study describes the first deep sequencing analysis of the T. thermophila transcriptome during the three major stages of the life cycle: growth, starvation and conjugation. Uniquely mapped reads covered more than 96 % of the 24,725 predicted gene models in the somatic genome. More than 1,000 new transcribed regions were identified. The great dynamic range of RNA-seq allowed detection of a nearly six order-of-magnitude range of measurable gene expression orchestrated by this cell. RNA-seq also allowed the first prediction of transcript untranslated regions (UTRs) and an updated (larger) size estimate of the T. thermophila transcriptome: 57 Mb, or about 55 % of the somatic genome. Our study identified nearly 1,500 alternative splicing (AS) events distributed over 5.2 % of T. thermophila genes. This percentage represents a two order-of-magnitude increase over previous EST-based estimates in Tetrahymena. Evidence of stage-specific regulation of alternative splicing was also obtained. Finally, our study allowed us to completely confirm about 26.8 % of the genes originally predicted by the gene finder, to correct coding sequence boundaries an

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Stereoselective Solid-State NaBH₄ Reduction of 1-Methylpentacyclo[5.4.0.0²,⁶.0³,¹⁰,0⁵,⁹]undecane-8, 11-Dione, Synthesis and Chemistry of Strained Alkenes, and Chemical and Microbial Synthesis of Racemic and Optically Active (S)-4-Hydroxy-2-Cyclohexenone

Part I. Reduction of the 1-methylpentacyclo [5.4.0.0²,⁶.0³,¹⁰,0⁵,⁹]undecane-8, 11-dione (9) with solid NaBH₄ resulted in highly stereoselective reduction of both C=O groups in the substrate, thereby affording the corresponding endo-8, endo-11-diol (11a). The configuration of 11a was established unequivocally by converting 11a into the corresponding cyclic thiocarbonate ester, 12. Part II. Z-1,2-Di(1'-adamantyl)ethene (14) was synthesized with a high degree of stereoselectively in four steps (Scheme 9 in Chapter 2). E-1,2-di(1'-adamantyl)ethene (15) was synthesized by iodine promoted isomerization of 14. Both structures were established unequivocally via single-crystal X-ray structural analysis. E-1-(exo-8'-Pentacyclo[5.4.0.0²,⁶.0³,¹⁰,0⁵,⁹]undecyl)-2-phenylethylene (16a) was synthesized, and its structure was established via analysis of its 1H, 13C, and 2D COSY NMR spectra. Part III. Reactions of electrophiles, i.e.,:CCl_2, PhSCl, and Br_2, to Z- and E-1,2-di(1'-adamantyl)ethenes (14 and 15, respectively) are described (Scheme 5, 8, 10, and 13 in Chapter 3). Structures of the corresponding products were established unequivocally via analysis of their respective one- and two-dimensional NMR spectra and/or single-crystal X-ray structural analysis. Part IV. An improved asymmetric synthesis of optically active (S)-4-hydroxy-2-cyclohexenone 1 (64%ee, determined via Mosher's method) has been developed (Scheme 5 in Chapter 4). The key step in this synthesis involves the baker's yeast reduction of 13. The absolute configuration of the major product, (S)-1, was established unequivocally via single-crystal X-ray structural analysis of a precursor. The optical purity of the major product 14a (80%de, 67%ee) was established via careful integration of relevant gated-decoupled 13C NMR spectra

Downregulation of lncRNA FGF12-AS2 suppresses the tumorigenesis of NSCLC via sponging miR-188-3p

Non-small-cell lung carcinoma (NSCLC) seriously threatens the health of human beings. Aberrant expression of lncRNAs has been confirmed to be related with the progression of multiple malignant tumors, including NSCLC. LncRNA FGF12-AS2 has been considered to be upregulated in NSCLC. However, the mechanism by which FGF12-AS2 promotes the tumorigenesis of NSCLC remains elusive