Comparison between a linear ion trap and a triple quadruple MS in the sensitive detection of large peptides at femtomole amounts on column.

In addition to the importance of sample preparation and extract separation, MS detection is a key factor in the sensitive quantification of large undigested peptides. In this article, a linear ion trap MS (LIT-MS) and a triple quadrupole MS (TQ-MS) have been compared in the detection of large peptides at subnanomolar concentrations. Natural brain natriuretic peptide, C-peptide, substance P and D-Junk-inhibitor peptide, a full D-amino acid therapeutic peptide, were chosen. They were detected by ESI and simultaneous MS(1) and MS(2) acquisitions. With direct peptide infusion, MS(2) spectra revealed that fragmentation was peptide dependent, milder on the LIT-MS and required high collision energies on the TQ-MS to obtain high-intensity product ions. Peptide adsorption on surfaces was overcome and peptide dilutions ranging from 0.1 to 25 nM were injected onto an ultra high-pressure LC system with a 1 mm id analytical column and coupled with the MS instruments. No difference was observed between the two instruments when recording in LC-MS(1) acquisitions. However, in LC-MS(2) acquisitions, a better sensitivity in the detection of large peptides was observed with the LIT-MS. Indeed, with the three longer peptides, the typical fragmentation in the TQ-MS resulted in a dramatic loss of sensitivity (> or = 10x).

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

IRM cardiaque en évolution: de grandes études multicentriques en 2012 [Cardiac MR in development: the large multicenter CMR studies in 2012].

The results of several large multicenter CMR studies were reported in 2012, thus, constantly corroborating the evidence on CMR performance. In this review, we present results of the MR-IMPACT programme and the CE-MARC study, which demonstrated the superiority of perfusion-CMR over gated SPECT for the workup of suspected CAD, the currently available data from the European CMR registry, comprising almost 30,000 patients from 57 participating centers in 15 European countries, and finally, the results of the Advisa-MRI study, which documented the safety of a MRI-compatible pacemaker system. These large trials and others set the basis for the recommendations in the new European guidelines on heart failure to use CMR as a first line method if echocardiographic quality is inadequate or the etiology of heart failure is unclear.

The co-evolution of social institutions, demography, and large-scale human cooperation.

Human cooperation is typically coordinated by institutions, which determine the outcome structure of the social interactions individuals engage in. Explaining the Neolithic transition from small- to large-scale societies involves understanding how these institutions co-evolve with demography. We study this using a demographically explicit model of institution formation in a patch-structured population. Each patch supports both social and asocial niches. Social individuals create an institution, at a cost to themselves, by negotiating how much of the costly public good provided by cooperators is invested into sanctioning defectors. The remainder of their public good is invested in technology that increases carrying capacity, such as irrigation systems. We show that social individuals can invade a population of asocials, and form institutions that support high levels of cooperation. We then demonstrate conditions where the co-evolution of cooperation, institutions, and demographic carrying capacity creates a transition from small- to large-scale social groups.

Phase III study of ACVBP versus ACVBP plus rituximab for patients with localized low-risk diffuse large B-cell lymphoma (LNH03-1B).

Background The superiority of a chemotherapy with doxorubicin, cyclophosphamide, vindesine, bleomycin and prednisone (ACVBP) in comparison with cyclophosphamide, doxorubicin, vincristin and prednisone plus radiotherapy for young patients with localized diffuse large B-cell lymphoma (DLBCL) was previously demonstrated. We report the results of a trial which evaluates the role of rituximab combined with ACVBP (R-ACVBP) in these patients. Patients and methods Untreated patients younger than 66 years with stage I or II DLBCL and no adverse prognostic factors of the age-adjusted International Prognostic Index were randomly assigned to receive three cycles of ACVBP plus sequential consolidation with or without the addition of four infusions of rituximab. Results A total of 223 patients were randomly allocated to the study, 110 in the R-ACVBP group and 113 in the ACVBP group. After a median follow-up of 43 months, our 3-year estimate of event-free survival was 93% in the R-ACVBP group and 82% in the ACVBP group (P = 0.0487). Three-year estimate of progression-free survival was increased in the R-ACVBP group (95% versus 83%, P = 0.0205). Overall survival did not differ between the two groups with a 3-year estimates of 98% and 97%, respectively (P = 0.686). Conclusion In young patients with low-risk localized DLBCL, rituximab combined with three cycles of ACVBP plus consolidation is significantly superior to ACVBP plus consolidation alone.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.