Enzymatic degradation of starch thermoplastic blends using samples of different thickness

The material studied was a thermoplastic blend of corn starch with a poly(ethylene-vinyl alcohol) copolymer, SEVA-C. The influence of both the material’s exposed surface and enzyme concentration on degradation kinetics was studied. As α-amylase is present in the blood plasma, experiments were performed, varying the material thickness and the α-amylase between 50 and 100 units/l, at 37°C, lasting up to 90 days. Four different batches using SEVA-C and starch samples of different thickness were performed. The positive correlation between degradation rate and the exposed material surface was confirmed, since thin films with larger exposed surfaces were degraded faster than thick square plates having the same total mass. The degradation extent depends on the total amount of amorphous starch present in the formulation rather than on the amount of enzyme used and the minimum thickness to ensure maximum degradation was estimated to be close to 0.25 mm

Working Group Report: Heavy-Ion Physics and Quark-Gluon Plasma

This is the report of Heavy Ion Physics and Quark-Gluon Plasma at WHEPP-09 which was part of Working Group-4. Discussion and work on some aspects of Quark-Gluon Plasma believed to have created in heavy-ion collisions and in early universe are reported.Comment: 20 pages, 6 eps figures, Heavy-ion physics and QGP activity report in "IX Workshop on High Energy Physics Phenomenology (WHEPP-09)" held in Institute of Physics, Bhubaneswar, India, during January 3-14, 2006. To be published in PRAMANA - Journal of Physics (Indian Academy of Science

Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks

We have compared a recently developed module-based algorithm LeMoNe for reverse-engineering transcriptional regulatory networks to a mutual information based direct algorithm CLR, using benchmark expression data and databases of known transcriptional regulatory interactions for Escherichia coli and Saccharomyces cerevisiae. A global comparison using recall versus precision curves hides the topologically distinct nature of the inferred networks and is not informative about the specific subtasks for which each method is most suited. Analysis of the degree distributions and a regulator specific comparison show that CLR is 'regulator-centric', making true predictions for a higher number of regulators, while LeMoNe is 'target-centric', recovering a higher number of known targets for fewer regulators, with limited overlap in the predicted interactions between both methods. Detailed biological examples in E. coli and S. cerevisiae are used to illustrate these differences and to prove that each method is able to infer parts of the network where the other fails. Biological validation of the inferred networks cautions against over-interpreting recall and precision values computed using incomplete reference networks.Comment: 13 pages, 1 table, 6 figures + 6 pages supplementary information (1 table, 5 figures

Late Onset Neuromyelitis Optica Spectrum Disorders (LONMOSD) from a Nationwide Portuguese Study: Anti-AQP4 Positive, Anti-MOG Positive and Seronegative Subgroups

Introduction: Several neuroimmunological disorders have distinct phenotypes according to the age of onset, as in multiple sclerosis or myasthenia gravis. It is also described that late onset NMOSD (LONMOSD) has a different phenotype. Objective: To describe the clinical/demographic characteristics of the LONMOSD and distinguish them from those with early onset (EONMOSD). Methods: From a nationwide Portuguese NMOSD study we analyzed the clinical/demographic characteristics of the LONMOSD. Results: From the 180 Portuguese patients 45 had disease onset after 50 years old, 80% were female. 23 had anti-AQP4 antibodies (51.1%), 13 anti-MOG antibodies (28.9%) and 9 were double seronegative (20.0%). The most common presenting phenotypes in LONMOSD were transverse myelitis (53.3%) and optic neuritis (26.7%), without difference from EONMOSD (p = 0.074). The mean EDSS for LONMOSD was 6.0 (SD=2.8), after a mean follow-up time of 4.58 (SD=4.47) years, which was significantly greater than the mean EDSS of EONMOSD (3.25, SD=1.80)(p = 0.022). Anti-AQP4 antibodies positive LONMOSD patients had increased disability compared to anti-MOG antibodies positive LONMOSD (p = 0.022). The survival analysis showed a reduced time to use a cane for LONMOSD, irrespective of serostatus (p<0.001). Conclusions: LONMOSD has increased disability and faster progression, despite no differences in the presenting clinical phenotype were seen in our cohort.info:eu-repo/semantics/publishedVersio

Inferring the role of transcription factors in regulatory networks

<p>Abstract</p> <p>Background</p> <p>Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays.</p> <p>Results</p> <p>We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of <it>E. coli </it>extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to <it>S. cerevisiae </it>transcriptional network (2419 nodes and 4344 interactions), by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions). In addition, we report predictions for 14.5% of all interactions.</p> <p>Conclusion</p> <p>Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine a significant portion of regulatory effects. This is a key practical asset compared to statistical methods for network reconstruction. We demonstrate that our approach is able to provide accurate predictions, even when the network is incomplete and the data is noisy.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Neuromyelitis Optica Spectrum Disorders: a Nationwide Portuguese Clinical Epidemiological Study

Introduction: Neuromyelitis optica spectrum disorder (NMOSD) is a rare disorder in which astrocyte damage and/or demyelination often cause severe neurological deficits. Objective: To identify Portuguese patients with NMOSD and assess their epidemiological/clinical characteristics. Methods: This was a nationwide multicenter study. Twenty-four Portuguese adult and 3 neuropediatric centers following NMOSD patients were included. Results: A total of 180 patients met the 2015 Wingerchuk NMOSD criteria, 77 were AQP4-antibody positive (Abs+), 67 MOG-Abs+, and 36 seronegative. Point prevalence on December 31, 2018 was 1.71/100,000 for NMOSD, 0.71/100,000 for AQP4-Abs+, 0.65/100,000 for MOG-Abs+, and 0.35/100,000 for seronegative NMOSD. A total of 44 new NMOSD cases were identified during the two-year study period (11 AQP4-Abs+, 27 MOG-Abs+, and 6 seronegative). The annual incidence rate in that period was 0.21/100,000 person-years for NMOSD, 0.05/100,000 for AQP4-Abs+, 0.13/100,000 for MOG-Abs+, and 0.03/100,000 for seronegative NMOSD. AQP4-Abs+ predominated in females and was associated with autoimmune disorders. Frequently presented with myelitis. Area postrema syndrome was exclusive of this subtype, and associated with higher morbidity/mortality than other forms of NMOSD. MOG-Ab+ more often presented with optic neuritis, required less immunosuppression, and had better outcome. Conclusion: Epidemiological/clinical NMOSD profiles in the Portuguese population are similar to other European countries.info:eu-repo/semantics/publishedVersio