Chip-based analysis of protein-protein interactions by fluorescence detection and on-chip immunoprecipitation combined with microLC-MS/MS analysis

A new chip-based method to identify protein-protein interactions was developed using the guanine nucleotide exchange factor GRF2 and two interacting proteins, Ras and calmodulin, as model proteins. A generic immobilization strategy for FLAG-tagged bait proteins on a protein-repellent streptavidin chip surface was implemented by presentation of an oriented anti-FLAG antibody. A flow cell device, integrating different chip surfaces, was developed, and the interaction of immobilized GRF2 with the two analytes was verified by fluorescence assays. On-chip tryptic digest assays were then performed on the capture surface and analyzed by microLC-MS/MS. The interaction of GRF2 with calmodulin and Ras was demonstrated, and the lower limit of detection was determined. We also implemented an on-chip immunoprecipitation assay to identify GRF2-binding partners from complex protein mixtures. Cells overexpressing FLAG-GRF2 were lysed and then incubated with the anti-FLAG chip. In addition to detecting GRF2, we also identified calmodulin, demonstrating that this technique can successfully identify endogenous levels of proteins, bound to recombinant bait proteins. This chip-based method has the advantage that no subsequent gel separations of protein complexes prior to LC-MS analysis are required and is therefore amenable to miniaturized high-throughput determination of protein-protein interactions.     

A general comparison of language learning from examples and from queries

In language learning, strong relationships between Gold-style models and query models have recently been observed: in some quite general setting Gold-style learners can be replaced by query learners and vice versa, without loss of learning capabilities. These ‘equalities’ hold in the context of learning indexable classes of recursive languages.     

Integration of beamforming and uncertainty-of-observation techniques for robust ASR in multi-source environments

This paper presents a new approach for increasing the robustness of multi-channel automatic speech recognition in noisy and reverberant multi-source environments. The proposed method uses uncertainty propagation techniques to dynamically compensate the speech features and the acoustic models for the observation uncertainty determined at the beamforming stage. We present and analyze two methods that allow integrating classical multi-channel signal processing approaches like delay and sum beamformers or Zelinski-type Wiener filters, with uncertainty-of-observation techniques like uncertainty decoding or modified imputation. An analysis of the results on the PASCAL-CHiME task shows that this approach consistently outperforms conventional beamformers with a minimal increase in computational complexity. The use of dynamic compensation based on observation uncertainty also outperforms conventional static adaptation with no need of adaptation data.     

Diterpene structure elucidation from 13cnmr spectra with inductive logic programming

We present a novel application ofInductive Logic Programming (ILP) to the problem of diterpene structure elucidation from 13 CNMR spectra. Diterpenes are organic compounds oflow molecular weight with a skeleton of 20 carbon atoms. They are of significant chemical and commercial interest because oftheir use as lead compounds in the search for new pharmaceutical effectors. The interpretation of diterpene 13 CNMR spectra normally requires specialists with detailed spectroscopic knowledge and substantial experience in natural products chemistry, specifically knowledge on peak patterns and chemical structures. Given a database ofpeak patterns for diterpenes with known structure, we apply several ILP approaches to discover correlations between peak patterns and chemical structure. The approaches used include first - order inductive learning, relational instance based learning, induction oflogical decision trees, and inductive constraint logic. Performance close to that of domain experts is achieved, which suffices for practical use.     

Status,causes and controls of cyanobacterial blooms in Lake Erie

The Laurentian Great Lakes are among the most prominent sources of fresh water in the world. Lake Erie's infamous cyanobacterial blooms have, however, threatened the health of this valuable freshwater resource for decades. Toxic blooms dominated by the cyanobacterium Microcystis aeruginosa have most recently been one of primary ecological concerns for the lake. These toxic blooms impact the availability of potable water, as well as public health and revenues from the tourism and fishery industries. The socioeconomic effects of these blooms have spurred research efforts to pinpoint factors that drive bloom events. Despite decades of research and mitigation efforts, these blooms have expanded both in size and duration in recent years. However, through continued joint efforts between the Canadian and United States governments, scientists, and environmental managers, identification of the factors that drive bloom events is within reach. This review provides a summary of historical and contemporary research efforts in the realm of Lake Erie's harmful cyanobacterial blooms, both in terms of experimental and management achievements and insufficiencies, as well as future directions on the horizon for the lake's research community.     

A hierarchical approach to simulate the packing density of particle mixtures on a computer

In many fields of materials science it is important to know how densely a particle mixture can be packed. The “packing density” is the ratio of the particle volume and the volume of the surrounding container needed for a random close packing of the particles. We present a method for estimating the packing density for spherical particles based on computer simulations only, i.e. without the need for additional experiments. Our method is particularly suited for particle mixtures with an extremely wide range of particle diameters as they occur e.g. in modern concrete mixtures. A single representative sample from such mixtures would be much larger than can be handled on present standard computers. In our hierarchical approach the diameter range is therefore divided into smaller intervals. Samples from these limited diameter intervals are drawn and their packing density is estimated from a simulated packing. The results are used to “fill” the interstices in the sample from the next larger particle interval. To account for the interaction between particles of different sizes we include larger particles into the sample of smaller ones. The larger ones act as part of the boundary during the packing. Thus we obtain more realistic estimates of how dense a fraction of particles can be packed within the whole mixture. The focus of this paper is on the divide-and-conquer approach and on how the simulation results from the fractions can be collected into an overall estimate of the packing density. We do not go into details of the simulation technique for the single packing. We compare our results to some experimental data to show that our method works at least as good as the classical analytical models like CPM without the need for any experiments.     

Logical Equivalence for Subtyping Object and Recursive Types

Subtyping in first order object calculi is studied with respect to the logical semantics obtained by identifying terms that satisfy the same set of predicates, as formalised through an assignment system. It is shown that equality in the full first order ς-calculus is modelled by this notion, which in turn is included in a Morris-style contextual equivalence. U. de’Liguoro’s research was partially supported by project PRIN’05 prot. 2005015785_003.     

Outcome of moderate carotid artery stenosis in patients who are asymptomatic

PURPOSE: The incidence rate of disease progression and stroke after the diagnosis of a moderate (50% to 79%) carotid stenosis was determined by means of color-flow duplex scanning. METHODS: During a 4-year period, 344 male veterans with moderate internal carotid artery stenoses, on one or both sides, were examined at regular intervals for a mean period of 25 months. Carotid color-flow scans were obtained semiannually. Clinical follow-up was performed to determine the incidence rate of amaurosis fugax, transient ischemic attacks, nonhemispheric symptoms, and strokes. RESULTS: New neurologic symptoms developed in 75 patients (21.8%). Fifty-one (14.8%) had ipsilateral symptoms during follow-up: 18 amaurosis fugax (5.2%), 14 transient ischemic attacks (4%), 5 nonhemispheric symptoms (1.4%), and 14 strokes (4%). Twenty-four patients (6.9%) had contralateral symptoms: 20 strokes (5.8%) and 4 transient ischemic attacks (1.2%). Life-table analysis showed that the annual rate of ipsilateral neurologic events was 8.1%, and the annual rate of stroke was 2.1%. Seventy-five patients (22%) died in the follow-up period. Disease progression to 80% to 99% stenosis or occlusion occurred in 71 of 458 vessels (15.5%). The internal carotid arteries that showed evidence of disease progression had a significantly higher initial peak systolic velocity (251 vs 190 cm/s; P <.0001) and end diastolic velocity (74 vs 52 cm/s; P < 0.0001). Black patients and patients with ischemic heart disease were at a higher risk for disease progression. We could not identify any atherosclerotic risk factors that reliably predicted patients in whom future ipsilateral neurologic symptoms were more likely to develop. However, there was an increased risk of stroke associated with progression of disease. CONCLUSION: Patients who are asymptomatic and who have moderate carotid stenoses are at significant risk for neurologic symptoms and death, but have a relatively low incidence rate of ipsilateral events. The initial flow characteristics in the stenotic vessel are predictive of future disease progression, but they are not helpful in identifying patients in whom symptoms will develop.     

Evaluation of basidiomycetous fungi for pretreatment of contaminated soil

BACKGROUND: For most dioxin‐contaminated sawmill soils, combustion is recommended. However, the process may be inefficient if the soil has a high organic matter content. The use of saprotrophic basidiomycetous fungi is an alternative for pretreatment of this kind of soil. A total of 147 fungi were evaluated for their ability to grow in sawmill soil. From this screening, the best soil colonizing fungi were selected to study their enzyme activities and degradation of soil organic matter. Pine (Pinus sylvestris) bark was used as a co‐substrate to propagate the fungi into the soil. The activities of manganese peroxidase (MnP), laccase, endo‐1,4‐β‐glucanase, endo‐1,4‐β‐xylanase, and endo‐1,4‐β‐mannanase were analysed from the inocula and fungal treated soil. RESULTS: The screening revealed that 56 out of 147 fungi were able to grow in non‐sterile soil, and most of them were litter‐decomposing fungi (LDF). In pine bark cultures, the highest enzyme activities were observed with Phanerochaete velutina, which produced 5 U g^?1 of MnP. The activity of endo‐1,4‐β‐glucanase was generally higher than that of other hydrolytic enzymes. The highest carbon loss from soil with a high organic matter content was achieved by P. velutina (3.4%) and Stropharia rugosoannulata (2.4%). CONCLUSIONS: Many LDF, and in addition the white‐rot fungus P. velutina, are potential degraders of soil organic matter since they showed good growth and respiratory activity. Pine bark was a suitable lignocellulosic co‐substrate and a good promoter of MnP activity. Copyright © 2009 Society of Chemical Industry