3,976 research outputs found
The substrate specificity of cruzipain 2, a cysteine protease isoform from Trypanosoma cruzi
Papain-like cysteine proteases are important for the survival of the flagellated protozoa Trypanosoma cruzi, the causative agent of Chagas' Disease. the lysosomal cysteine protease designated as cruzipain or cruzain, is the archetype of a multigene family of related isoforms. We investigated the substrate specificity of the cruzipain 2 isoform using internally quenched fluorogenic substrates. We found that cruzipain 2 and cruzain differ substantially regarding the specificity in the S-2, S-1(') and S-2(') pockets. Our study indicates that cruzipain 2 has a more restricted specificity than cruzain, suggesting that these isoforms might act on distinct natural substrates.Univ Fed Rio de Janeiro, Inst Biofis Carlos Chagas Filho, BR-21949900 Rio de Janeiro, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilWeb of Scienc
Why 'scaffolding' is the wrong metaphor : the cognitive usefulness of mathematical representations.
The metaphor of scaffolding has become current in discussions of the cognitive help we get from artefacts, environmental affordances and each other. Consideration of mathematical tools and representations indicates that in these cases at least (and plausibly for others), scaffolding is the wrong picture, because scaffolding in good order is immobile, temporary and crude. Mathematical representations can be manipulated, are not temporary structures to aid development, and are refined. Reflection on examples from elementary algebra indicates that Menary is on the right track with his ‘enculturation’ view of mathematical cognition. Moreover, these examples allow us to elaborate his remarks on the uniqueness of mathematical representations and their role in the emergence of new thoughts.Peer reviewe
Training emergency services’ dispatchers to recognise stroke: an interrupted time-series analysis
Background: Stroke is a time-dependent medical emergency in which early presentation to specialist care reduces death and dependency. Up to 70% of all stroke patients obtain first medical contact from the Emergency Medical Services (EMS). Identifying ‘true stroke’ from an EMS call is challenging, with over 50% of strokes being misclassified.
The aim of this study was to evaluate the impact of the training package on the recognition of stroke by Emergency Medical Dispatchers (EMDs).
Methods: This study took place in an ambulance service and a hospital in England using an interrupted time-series
design. Suspected stroke patients were identified in one week blocks, every three weeks over an 18 month period,
during which time the training was implemented. Patients were included if they had a diagnosis of stroke (EMS or
hospital). The effect of the intervention on the accuracy of dispatch diagnosis was investigated using binomial
(grouped) logistic regression.
Results: In the Pre-implementation period EMDs correctly identified 63% of stroke patients; this increased to 80%
Post-implementation. This change was significant (p=0.003), reflecting an improvement in identifying stroke patients
relative to the Pre-implementation period both the During-implementation (OR=4.10 [95% CI 1.58 to 10.66]) and Post-implementation (OR=2.30 [95% CI 1.07 to 4.92]) periods. For patients with a final diagnosis of stroke who had been dispatched as stroke there was a marginally non-significant 2.8 minutes (95% CI −0.2 to 5.9 minutes, p=0.068)reduction between Pre- and Post-implementation periods from call to arrival of the ambulance at scene.
Conclusions: This is the first study to develop, implement and evaluate the impact of a training package for EMDs with
the aim of improving the recognition of stroke. Training led to a significant increase in the proportion of stroke patients dispatched as such by EMDs; a small reduction in time from call to arrival at scene by the ambulance also appeared likely. The training package has been endorsed by the UK Stroke Forum Education and Training, and is free to access on-line
High Energy Gamma-Ray Emission From Blazars: EGRET Observations
We will present a summary of the observations of blazars by the Energetic
Gamma Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory
(CGRO). EGRET has detected high energy gamma-ray emission at energies greater
than 100 MeV from more that 50 blazars. These sources show inferred isotropic
luminosities as large as ergs s. One of the most
remarkable characteristics of the EGRET observations is that the gamma-ray
luminosity often dominates the bolometric power of the blazar. A few of the
blazars are seen to exhibit variability on very short time-scales of one day or
less. The combination of high luminosities and time variations seen in the
gamma-ray data indicate that gamma-rays are an important component of the
relativistic jet thought to characterize blazars. Currently most models for
blazars involve a beaming scenario. In leptonic models, where electrons are the
primary accelerated particles, gamma-ray emission is believed to be due to
inverse Compton scattering of low energy photons, although opinions differ as
to the source of the soft photons. Hardronic models involve secondary
production or photomeson production followed by pair cascades, and predict
associated neutrino production.Comment: 16 pages, 7 figures, style files included. Invited review paper in
"Observational Evidence for Black Holes in the Universe," 1999, ed. S. K.
Chakrabarti (Dordrecht: Kluwer), 215-23
Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings
Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating
Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems
A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud
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Predictability of evolutionary trajectories in fitness landscapes
Experimental studies on enzyme evolution show that only a small fraction of
all possible mutation trajectories are accessible to evolution. However, these
experiments deal with individual enzymes and explore a tiny part of the fitness
landscape. We report an exhaustive analysis of fitness landscapes constructed
with an off-lattice model of protein folding where fitness is equated with
robustness to misfolding. This model mimics the essential features of the
interactions between amino acids, is consistent with the key paradigms of
protein folding and reproduces the universal distribution of evolutionary rates
among orthologous proteins. We introduce mean path divergence as a quantitative
measure of the degree to which the starting and ending points determine the
path of evolution in fitness landscapes. Global measures of landscape roughness
are good predictors of path divergence in all studied landscapes: the mean path
divergence is greater in smooth landscapes than in rough ones. The
model-derived and experimental landscapes are significantly smoother than
random landscapes and resemble additive landscapes perturbed with moderate
amounts of noise; thus, these landscapes are substantially robust to mutation.
The model landscapes show a deficit of suboptimal peaks even compared with
noisy additive landscapes with similar overall roughness. We suggest that
smoothness and the substantial deficit of peaks in the fitness landscapes of
protein evolution are fundamental consequences of the physics of protein
folding.Comment: 14 pages, 7 figure
Nitrogen uptake and internal recycling in Zostera marina exposed to oyster farming: eelgrass potential as a natural biofilter
Oyster farming in estuaries and coastal lagoons frequently overlaps with the distribution of seagrass meadows, yet there are few studies on how this aquaculture practice affects seagrass physiology. We compared in situ nitrogen uptake and the productivity of Zostera marina shoots growing near off-bottom longlines and at a site not affected by oyster farming in San Quintin Bay, a coastal lagoon in Baja California, Mexico. We used benthic chambers to measure leaf NH4 (+) uptake capacities by pulse labeling with (NH4)-N-15 (+) and plant photosynthesis and respiration. The internal N-15 resorption/recycling was measured in shoots 2 weeks after incubations. The natural isotopic composition of eelgrass tissues and vegetative descriptors were also examined. Plants growing at the oyster farming site showed a higher leaf NH4 (+) uptake rate (33.1 mmol NH4 (+) m(-2) day(-1)) relative to those not exposed to oyster cultures (25.6 mmol NH4 (+) m(-2) day(-1)). We calculated that an eelgrass meadow of 15-16 ha (which represents only about 3-4 % of the subtidal eelgrass meadow cover in the western arm of the lagoon) can potentially incorporate the total amount of NH4 (+) excreted by oysters (similar to 5.2 x 10(6) mmol NH4 (+) day(-1)). This highlights the potential of eelgrass to act as a natural biofilter for the NH4 (+) produced by oyster farming. Shoots exposed to oysters were more efficient in re-utilizing the internal N-15 into the growth of new leaf tissues or to translocate it to belowground tissues. Photosynthetic rates were greater in shoots exposed to oysters, which is consistent with higher NH4 (+) uptake and less negative delta C-13 values. Vegetative production (shoot size, leaf growth) was also higher in these shoots. Aboveground/belowground biomass ratio was lower in eelgrass beds not directly influenced by oyster farms, likely related to the higher investment in belowground biomass to incorporate sedimentary nutrients
FIRE (facilitating implementation of research evidence) : a study protocol
Research evidence underpins best practice, but is not always used in healthcare. The Promoting Action on Research Implementation in Health Services (PARIHS) framework suggests that the nature of evidence, the context in which it is used, and whether those trying to use evidence are helped (or facilitated) affect the use of evidence. Urinary incontinence has a major effect on quality of life of older people, has a high prevalence, and is a key priority within European health and social care policy. Improving continence care has the potential to improve the quality of life for older people and reduce the costs associated with providing incontinence aids
Primary care management for optimized antithrombotic treatment [PICANT]: study protocol for a cluster-randomized controlled trial
Background: Antithrombotic treatment is a continuous therapy that is often performed in general practice and requires careful safety management. The aim of this study is to investigate whether a best practice model that applies major elements of case management, including patient education, can improve antithrombotic management in primary health care in terms of reducing major thromboembolic and bleeding events.
Methods: This 24-month cluster-randomized trial will be performed in 690 adult patients from 46 practices. The trial intervention will be a complex intervention involving general practitioners, health care assistants and patients with an indication for oral anticoagulation. To assess adherence to medication and symptoms in patients, as well as to detect complications early, health care assistants will be trained in case management and will use the Coagulation-Monitoring-List (Co-MoL) to regularly monitor patients. Patients will receive information (leaflets and a video), treatment monitoring via the Co-MoL and be motivated to perform self-management. Patients in the control group will continue to receive treatment-as-usual from their general practitioners. The primary endpoint is the combined endpoint of all thromboembolic events requiring hospitalization, and all major bleeding complications. Secondary endpoints are mortality, hospitalization, strokes, major bleeding and thromboembolic complications, severe treatment interactions, the number of adverse events, quality of anticoagulation, health-related quality of life and costs. Further secondary objectives will be investigated to explain the mechanism by which the intervention is effective: patients' assessment of chronic illness care, self-reported adherence to medication, general practitioners' and health care assistants' knowledge, patients' knowledge and satisfaction with shared decision making. Practice recruitment is expected to take place between July and December 2012. Recruitment of eligible patients will start in July 2012. Assessment will occur at three time points: baseline (T0), follow-up after 12 (T1) and after 24 months (T2).
Discussion: The efficacy and effectiveness of individual elements of the intervention, such as antithrombotic interventions, self-management concepts in orally anticoagulated patients and the methodological tool, case-management, have already been extensively demonstrated. This project foresees the combination of several proven instruments, as a result of which we expect to profit from a reduction in the major complications associated with antithrombotic treatment
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