'Tough'-constructions and their derivation

This article addresses the syntax of the notorious 'tough' (-movement) construction (TC) in English. TCs exhibit a range of apparently contradictory empirical properties suggesting that their derivation involves the application of both A-movement and A'-movement operations. Given that within previous Principles and Parameters models TCs have remained “unexplained and in principle unexplainable” (Holmberg 2000: 839) due to incompatibility with constraints on theta-assignment, locality, and Case, this article argues that the phase-based implementation of the Minimalist program (Chomsky 2000, 2001, 2004) permits a reanalysis of null wh-operators capable of circumventing the previous theoretical difficulties. Essentially, 'tough'-movement consists of A-moving a constituent out of a “complex” null operator which has already undergone A'-movement, a “smuggling” construction in the terms of Collins (2005a,b

On the Topic of Pseudoclefts

This paper presents arguments in favor of a pseudocleft analysis of a certain class of sentences in Malagasy, despite the lack of an overt wh-element. It is shown that voice morphology on the verb creates an operator-variable relationship much like the one created by wh-movement in free relatives in English and other languages. The bulk of the paper argues in favor of an inversion analysis of specificational pseudoclefts in Malagasy: a predicate DP is fronted to a topic position from within a small clause constituent. Moreover, it is shown that the same inversion occurs in equative and specificational sentences in Malagasy, which suggests that these types of sentences share the same syntactic structure. The proposed analysis also provides support for the view that specificational pseudoclefts have a topic \u3e focus structure, where the wh-clause has been overtly topicalized

Exome Sequencing Reveals Comprehensive Genomic Alterations across Eight Cancer Cell Lines

It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the “exome”) can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ∼95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data

Effects of Once-Weekly Exenatide on Cardiovascular Outcomes in Type 2 Diabetes.

Abstract BACKGROUND: The cardiovascular effects of adding once-weekly treatment with exenatide to usual care in patients with type 2 diabetes are unknown. METHODS: We randomly assigned patients with type 2 diabetes, with or without previous cardiovascular disease, to receive subcutaneous injections of extended-release exenatide at a dose of 2 mg or matching placebo once weekly. The primary composite outcome was the first occurrence of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke. The coprimary hypotheses were that exenatide, administered once weekly, would be noninferior to placebo with respect to safety and superior to placebo with respect to efficacy. RESULTS: In all, 14,752 patients (of whom 10,782 [73.1%] had previous cardiovascular disease) were followed for a median of 3.2 years (interquartile range, 2.2 to 4.4). A primary composite outcome event occurred in 839 of 7356 patients (11.4%; 3.7 events per 100 person-years) in the exenatide group and in 905 of 7396 patients (12.2%; 4.0 events per 100 person-years) in the placebo group (hazard ratio, 0.91; 95% confidence interval [CI], 0.83 to 1.00), with the intention-to-treat analysis indicating that exenatide, administered once weekly, was noninferior to placebo with respect to safety (P<0.001 for noninferiority) but was not superior to placebo with respect to efficacy (P=0.06 for superiority). The rates of death from cardiovascular causes, fatal or nonfatal myocardial infarction, fatal or nonfatal stroke, hospitalization for heart failure, and hospitalization for acute coronary syndrome, and the incidence of acute pancreatitis, pancreatic cancer, medullary thyroid carcinoma, and serious adverse events did not differ significantly between the two groups. CONCLUSIONS: Among patients with type 2 diabetes with or without previous cardiovascular disease, the incidence of major adverse cardiovascular events did not differ significantly between patients who received exenatide and those who received placebo. (Funded by Amylin Pharmaceuticals; EXSCEL ClinicalTrials.gov number, NCT01144338 .)

Gene Expression Analyses of Mouse Aortic Endothelium in Response to Atherogenic Stimuli

OBJECTIVE: Endothelial cells are central to the initiation of atherosclerosis, yet there has been limited success in studying their gene expression in the mouse aorta. To address this, we developed a method for determining the global transcriptional changes that occur in the mouse endothelium in response to atherogenic conditions and applied it to investigate inflammatory stimuli. APPROACH AND RESULTS: We characterized a method for the isolation of endothelial cell RNA with high purity directly from mouse aortas and adapted this method to allow for the treatment of aortas ex vivo before RNA collection. Expression array analysis was performed on endothelial cell RNA isolated from control and hyperlipidemic prelesion mouse aortas, and 797 differentially expressed genes were identified. We also examined the effect of additional atherogenic conditions on endothelial gene expression, including ex vivo treatment with inflammatory stimuli, acute hyperlipidemia, and age. Of the 14 most highly differentially expressed genes in endothelium from prelesion aortas, 8 were also perturbed significantly by ≥1 atherogenic conditions: 2610019E17Rik, Abca1, H2-Ab1, H2-D1, Pf4, Ppbp, Pvrl2, and Tnnt2. CONCLUSIONS: We demonstrated that RNA can be isolated from mouse aortic endothelial cells after in vivo and ex vivo treatments of the murine vessel wall. We applied these methods to identify a group of genes, many of which have not been described previously as having a direct role in atherosclerosis, that were highly regulated by atherogenic stimuli and may play a role in early atherogenesis