Photoreactions of group 6 metal carbonyls with olef i ns

Abstract -A scheme is presented, based on preparative and mechanistic studies, concerning the principles which govern the course of multiple photosubstitution of group 6 metal carbonyls with olefins: (i) after initial (n -olefin)M(CO) formation, photcdetachment of CO in cis-position to the olefin is strongly favoured over frans-CO dissociation; (ii) a (n2-C=C) M subunit with frarrs-orfhogonal position of the olefins is distinctly more stable than other geometries. This is rationalized in terms of competitive demand of CO and olefin ligands for metal d electron density, whereby the single-faced n-acceptor character of the olefin plays a crucial role. -Sequential photosubstitution of M(C0)6 with olefins yields (n2-olefin)M(C0)5 and, ultimately, trans-(n -olefin) M(C0)4, as verified for all three group 6 metals. Quantum yield measurements (0.72 for W and 0.61 for Cr in the first step: ca. 0.5 for W and ca. 0.04 for Cr in the second step: at A = 302 nm) and studies revealing the role of cis-(n -olefin)2M(C0)4 were performed with E-cyclooctene, which exhibits exceptionally strong bonding to transition metals. In accord with the above principles, photosubstitution of (l14-norbornadiene)M(C0)4 complexes yields bornadiene)M(CO) . Implications of these findings with respect to photocatalytic processes are 3 briefly discussed

Soil microbial CNP and respiration responses to organic matter and nutrient additions: evidence from a tropical soil incubation

Soil nutrient availability has a strong influence on the fate of soil carbon (C) during microbial decomposition, contributing to Earth's C balance. While nutrient availability itself can impact microbial physiology and C partitioning between biomass and respiration during soil organic matter decomposition, the availability of labile C inputs may mediate the response of microorganisms to nutrient additions. As soil organic matter is decomposed, microorganisms retain or release C, nitrogen (N) or phosphorus (P) to maintain a stoichiometric balance. Although the concept of a microbial stoichiometric homeostasis has previously been proposed, microbial biomass CNP ratios are not static, and this may have very relevant implications for microbial physiological activities. Here, we tested the hypothesis that N, P and potassium (K) nutrient additions impact C cycling in a tropical soil due to microbial stoichiometric constraints to growth and respiration, and that the availability of energy-rich labile organic matter in the soil (i.e. leaf litter) mediates the response to nutrient addition. We incubated tropical soil from French Guiana with a ¹³C labeled leaf litter addition and with mineral nutrient additions of +K, +N, +NK, +PK and +NPK for 30 days. We found that litter additions led to a ten-fold increase in microbial respiration and a doubling of microbial biomass C, along with greater microbial N and P content. We found some evidence that P additions increased soil CO² fluxes. Additionally, we found microbial biomass CP and NP ratios varied more widely than CN in response to nutrient and organic matter additions, with important implications for the role of microorganisms in C cycling. The addition of litter did not prime soil organic matter decomposition, except in combination with +NK fertilization, indicating possible P-mining of soil organic matter in this P-poor tropical soil. Together, these results point toward an ultimate labile organic substrate limitation of soil microorganisms in this tropical soil, but also indicate a complex interaction between C, N, P and K availability. This highlights the difference between microbial C cycling responses to N, P, or K additions in the tropics and explains why coupled C, N and P cycling modeling efforts cannot rely on strict microbial stoichiometric homeostasis as an underlying assumption

Aurora kinases are expressed in medullary thyroid carcinoma (MTC) and their inhibition suppresses in vitro growth and tumorigenicity of the MTC derived cell line TT

International audienceBACKGROUND: The Aurora kinase family members, Aurora-A, -B and -C, are involved in the regulation of mitosis, and alterations in their expression are associated with cell malignant transformation. To date no information on the expression of these proteins in medullary thyroid carcinoma (MTC) are available. We here investigated the expression of the Aurora kinases in human MTC tissues and their potential use as therapeutic targets. METHODS: The expression of the Aurora kinases in 26 MTC tissues at different TNM stages was analyzed at the mRNA level by quantitative RT-PCR. We then evaluated the effects of the Aurora kinase inhibitor MK-0457 on the MTC derived TT cell line proliferation, apoptosis, soft agar colony formation, cell cycle and ploidy. RESULTS: The results showed the absence of correlation between tumor tissue levels of any Aurora kinase and tumor stage indicating the lack of prognostic value for these proteins. Treatment with MK-0457 inhibited TT cell proliferation in a time- and dose-dependent manner with IC50 = 49.8 ± 6.6 nM, as well as Aurora kinases phosphorylation of substrates relevant to the mitotic progression. Time-lapse experiments demonstrated that MK-0457-treated cells entered mitosis but were unable to complete it. Cytofluorimetric analysis confirmed that MK-0457 induced accumulation of cells with ≥ 4N DNA content without inducing apoptosis. Finally, MK-0457 prevented the capability of the TT cells to form colonies in soft agar. CONCLUSIONS: We demonstrate that Aurora kinases inhibition hampered growth and tumorigenicity of TT cells, suggesting its potential therapeutic value for MTC treatment

Bayesian Time-Series Models for Continuous Fault Detection and Recognition in Industrial Robotic Tasks

This paper presents the application of a Bayesian nonparametric time-series model to process monitoring and fault classification for industrial robotic tasks. By means of an alignment task performed with a real robot, we show how the proposed approach allows to learn a set of sensor signature models encoding the spatial and temporal correlations among wrench measurements recorded during a number of successful task executions. Using these models, it is possible to detect continuously and on-line deviations from the expected sensor readings. Separate models are learned for a set of possible error scenarios involving a human modifying the workspace configuration. These non-nominal task executions are correctly detected and classified with an on-line algorithm, which opens the possibility for the development of error-specific recovery strategies. Our work is complementary to previous approaches in robotics, where process monitors based on probabilistic models, but limited to contact events, were developed for control purposes. Instead, in this paper we focus on capturing dynamic models of sensor signatures throughout the whole task, therefore allowing continuous monitoring and extending the system ability to interpret and react to errors.status: publishe