New York University

About: New York University is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 72380 authors who have published 165545 publications receiving 8334030 citations. The organization is also known as: NYU & University of the City of New York.

Exploring the Locus of Profitable Pollution Reduction

Abstract: In this paper, we explore the locus of profitable pollution reduction. We propose that managers underestimate the full value of some means of pollution reduction and so under exploit these means. Based on evidence from previous studies, we argue that waste prevention often provides unexpected innovation offsets, and that onsite waste treatment often provides unexpected cost. We use statistical methods to test the direction and significance of the relationship between the various means of pollution reduction and profitability. We find strong evidence that waste prevention leads to financial gain, but we find no evidence that firms profit from reducing pollution by other means. Indeed, we find evidence that the bene fits of waste prevention alone are responsible for the observed association between lower emissions and profitability.

Rule Learning by Seven-Month-Old Infants

Abstract: A fundamental task of language acquisition is to extract abstract algebraic rules. Three experiments show that 7-month-old infants attend longer to sentences with unfamiliar structures than to sentences with familiar structures. The design of the artificial language task used in these experiments ensured that this discrimination could not be performed by counting, by a system that is sensitive only to transitional probabilities, or by a popular class of simple neural network models. Instead, these results suggest that infants can represent, extract, and generalize abstract algebraic rules.

Increased proteasome-dependent degradation of the cyclin-dependent kinase inhibitor p27 in aggressive colorectal carcinomas.

Abstract: The cell-cycle inhibitor p27 is a potential tumor suppressor, but its gene has never been found inactivated in human tumors1–4. Because cell-cycle regulation of p27 cellular abundance occurs at the post-transcriptional level5–7, we analyzed p27 protein expression and degradation in human colorectal carcinomas. Proteasome-mediated degradation activity of p27 was compared with its protein levels in a subset of tumor samples. We found that carcinomas with low or absent p27 protein displayed enhanced proteolytic activity specific for p27, suggesting that low p27 expression can result from increased proteasome-mediated degradation rather than altered gene expression. Patients whose tumors expressed p27 had a median survival of 151 months, whereas patients who lacked p27 (10%) had a median survival of 69 months. By multivariate analysis, p27 was found to be an independent prognostic marker. Lack of p27 was associated with poor prognosis (2.9 risk ratio for death; P = 0.003). The absence of p27 protein expression is thus a powerful negative prognostic marker in colorectal carcinomas, particularly in stage II tumors, and thereby may help in the selection of patients who will benefit from adjuvant therapy. These data suggest that aggressive tumors may result from the selection of a clone or clones that lack p27 due to increased proteasome-mediated degradation.

The SCF ubiquitin ligase: insights into a molecular machine

Abstract: Ubiquitin ligases are well suited to regulate molecular networks that operate on a post-translational timescale. The F-box family of proteins - which are the substrate-recognition components of the Skp1-Cul1-F-box-protein (SCF) ubiquitin ligase - are important players in many mammalian functions. Here we explore a unifying and structurally detailed view of SCF-mediated proteolytic control of cellular processes that has been revealed by recent studies.

Stably maintained dendritic spines are associated with lifelong memories

Abstract: Connections between neurons are thought to be remodelled when we learn new tasks or acquire new information. However, this plasticity must also occur against a backdrop of stable memory maintenance. In mice, a paradigm of either enhanced sensory experience or specific motor learning produced new putative neuronal connections that remained stable alongside developmentally preserved connections much later in life. This suggests that learning can produce changes in the neuronal connectivity that can be stable for the lifetime of the network. Connections between neurons are thought to be remodelled when we learn new tasks or acquire new information; however, it is unclear how neural circuits undergo continuous synaptic changes during learning while maintaining lifelong memories. Here, by following post-synaptic dendritic spines in the mouse cortex, it is shown that a small fraction of new spines induced by novel experience are preserved and provide a structural basis for lifelong memory retention. Changes in synaptic connections are considered essential for learning and memory formation1,2,3,4,5,6. However, it is unknown how neural circuits undergo continuous synaptic changes during learning while maintaining lifelong memories. Here we show, by following postsynaptic dendritic spines over time in the mouse cortex7,8, that learning and novel sensory experience lead to spine formation and elimination by a protracted process. The extent of spine remodelling correlates with behavioural improvement after learning, suggesting a crucial role of synaptic structural plasticity in memory formation. Importantly, a small fraction of new spines induced by novel experience, together with most spines formed early during development and surviving experience-dependent elimination, are preserved and provide a structural basis for memory retention throughout the entire life of an animal. These studies indicate that learning and daily sensory experience leave minute but permanent marks on cortical connections and suggest that lifelong memories are stored in largely stably connected synaptic networks.