Cost-Effective Use of Silver Dressings for the Treatment of Hard-to-Heal Chronic Venous Leg Ulcers

Aim To estimate the cost-effectiveness of silver dressings using a health economic model based on time-to-wound-healing in hard-to-heal chronic venous leg ulcers (VLUs). Background Chronic venous ulceration affects 1–3% of the adult population and typically has a protracted course of healing, resulting in considerable costs to the healthcare system. The pathogenesis of VLUs includes excessive and prolonged inflammation which is often related to critical colonisation and early infection. The use of silver dressings to control this bioburden and improve wound healing rates remains controversial. Methods A decision tree was constructed to evaluate the cost-effectiveness of treatment with silver compared with non-silver dressings for four weeks in a primary care setting. The outcomes: ‘Healed ulcer’, ‘Healing ulcer’ or ‘No improvement’ were developed, reflecting the relative reduction in ulcer area from baseline to four weeks of treatment. A data set from a recent meta-analysis, based on four RCTs, was applied to the model. Results Treatment with silver dressings for an initial four weeks was found to give a total cost saving (£141.57) compared with treatment with non-silver dressings. In addition, patients treated with silver dressings had a faster wound closure compared with those who had been treated with non-silver dressings. Conclusion The use of silver dressings improves healing time and can lead to overall cost savings. These results can be used to guide healthcare decision makers in evaluating the economic aspects of treatment with silver dressings in hard-to-heal chronic VLUs

Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity

Fluids in cosmology

We review the role of fluids in cosmology by first introducing them in General Relativity and then by applying them to a FRW Universe's model. We describe how relativistic and non-relativistic components evolve in the background dynamics. We also introduce scalar fields to show that they are able to yield an inflationary dynamics at very early times (inflation) and late times (quintessence). Then, we proceed to study the thermodynamical properties of the fluids and, lastly, its perturbed kinematics. We make emphasis in the constrictions of parameters by recent cosmological probes.Comment: 34 pages, 4 figures, version accepted as invited review to the book "Computational and Experimental Fluid Mechanics with Applications to Physics, Engineering and the Environment". Version 2: typos corrected and references expande

Representing complex data using localized principal components with application to astronomical data

Often the relation between the variables constituting a multivariate data space might be characterized by one or more of the terms: ``nonlinear'', ``branched'', ``disconnected'', ``bended'', ``curved'', ``heterogeneous'', or, more general, ``complex''. In these cases, simple principal component analysis (PCA) as a tool for dimension reduction can fail badly. Of the many alternative approaches proposed so far, local approximations of PCA are among the most promising. This paper will give a short review of localized versions of PCA, focusing on local principal curves and local partitioning algorithms. Furthermore we discuss projections other than the local principal components. When performing local dimension reduction for regression or classification problems it is important to focus not only on the manifold structure of the covariates, but also on the response variable(s). Local principal components only achieve the former, whereas localized regression approaches concentrate on the latter. Local projection directions derived from the partial least squares (PLS) algorithm offer an interesting trade-off between these two objectives. We apply these methods to several real data sets. In particular, we consider simulated astrophysical data from the future Galactic survey mission Gaia.Comment: 25 pages. In "Principal Manifolds for Data Visualization and Dimension Reduction", A. Gorban, B. Kegl, D. Wunsch, and A. Zinovyev (eds), Lecture Notes in Computational Science and Engineering, Springer, 2007, pp. 180--204, http://www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-173750210-

A structurally distinct TGF-β mimic from an intestinal helminth parasite potently induces regulatory T cells

Helminth parasites defy immune exclusion through sophisticated evasion mechanisms, including activation of host immunosuppressive regulatory T (Treg) cells. The mouse parasite Heligmosomoides polygyrus can expand the host Treg population by secreting products that activate TGF-β signalling, but the identity of the active molecule is unknown. Here we identify an H. polygyrus TGF-β mimic (Hp-TGM) that replicates the biological and functional properties of TGF-β, including binding to mammalian TGF-β receptors and inducing mouse and human Foxp3+ Treg cells. Hp-TGM has no homology with mammalian TGF-β or other members of the TGF-β family, but is a member of the complement control protein superfamily. Thus, our data indicate that through convergent evolution, the parasite has acquired a protein with cytokine-like function that is able to exploit an endogenous pathway of immunoregulation in the host

Ferromagnetic Semiconductors: Moving Beyond (Ga,Mn)As

The recent development of MBE techniques for growth of III-V ferromagnetic semiconductors has created materials with exceptional promise in spintronics, i.e. electronics that exploit carrier spin polarization. Among the most carefully studied of these materials is (Ga,Mn)As, in which meticulous optimization of growth techniques has led to reproducible materials properties and ferromagnetic transition temperatures well above 150 K. We review progress in the understanding of this particular material and efforts to address ferromagnetic semiconductors as a class. We then discuss proposals for how these materials might find applications in spintronics. Finally, we propose criteria that can be used to judge the potential utility of newly discovered ferromagnetic semiconductors, and we suggest guidelines that may be helpful in shaping the search for the ideal material.Comment: 37 pages, 4 figure

Multiple Neural Oscillators and Muscle Feedback Are Required for the Intestinal Fed State Motor Program

After a meal, the gastrointestinal tract exhibits a set of behaviours known as the fed state. A major feature of the fed state is a little understood motor pattern known as segmentation, which is essential for digestion and nutrient absorption. Segmentation manifests as rhythmic local constrictions that do not propagate along the intestine. In guinea-pig jejunum in vitro segmentation constrictions occur in short bursts together with other motor patterns in episodes of activity lasting 40–60 s and separated by quiescent episodes lasting 40–200 s. This activity is induced by luminal nutrients and abolished by blocking activity in the enteric nervous system (ENS). We investigated the enteric circuits that regulate segmentation focusing on a central feature of the ENS: a recurrent excitatory network of intrinsic sensory neurons (ISNs) which are characterized by prolonged after-hyperpolarizing potentials (AHPs) following their action potentials. We first examined the effects of depressing AHPs with blockers of the underlying channels (TRAM-34 and clotrimazole) on motor patterns induced in guinea-pig jejunum, in vitro, by luminal decanoic acid. Contractile episode durations increased markedly, but the frequency and number of constrictions within segmenting bursts and quiescent period durations were unaffected. We used these observations to develop a computational model of activity in ISNs, excitatory and inhibitory motor neurons and the muscle. The model predicted that: i) feedback to ISNs from contractions in the circular muscle is required to produce alternating activity and quiescence with the right durations; ii) transmission from ISNs to excitatory motor neurons is via fast excitatory synaptic potentials (EPSPs) and to inhibitory motor neurons via slow EPSPs. We conclude that two rhythm generators regulate segmentation: one drives contractions within segmentation bursts, the other the occurrence of bursts. The latter depends on AHPs in ISNs and feedback to these neurons from contraction of the circular muscle

Alcohol affects neuronal substrates of response inhibition but not of perceptual processing of stimuli signalling a stop response

Alcohol impairs inhibitory control, including the ability to terminate an initiated action. While there is increasing knowledge about neural mechanisms involved in response inhibition, the level at which alcohol impairs such mechanisms remains poorly understood. Thirty-nine healthy social drinkers received either 0.4g/kg or 0.8g/kg of alcohol, or placebo, and performed two variants of a Visual Stop-signal task during acquisition of functional magnetic resonance imaging (fMRI) data. The two task variants differed only in their instructions: in the classic variant (VSST), participants inhibited their response to a “Go-stimulus” when it was followed by a “Stop-stimulus”. In the control variant (VSST_C), participants responded to the “Go-stimulus” even if it was followed by a “Stop-stimulus”. Comparison of successful Stop-trials (Sstop)>Go, and unsuccessful Stop-trials (Ustop)>Sstop between the three beverage groups enabled the identification of alcohol effects on functional neural circuits supporting inhibitory behaviour and error processing. Alcohol impaired inhibitory control as measured by the Stop-signal reaction time, but did not affect other aspects of VSST performance, nor performance on the VSST_C. The low alcohol dose evoked changes in neural activity within prefrontal, temporal, occipital and motor cortices. The high alcohol dose evoked changes in activity in areas affected by the low dose but importantly induced changes in activity within subcortical centres including the globus pallidus and thalamus. Alcohol did not affect neural correlates of perceptual processing of infrequent cues, as revealed by conjunction analyses of VSST and VSST_C tasks. Alcohol ingestion compromises the inhibitory control of action by modulating cortical regions supporting attentional, sensorimotor and action-planning processes. At higher doses the impact of alcohol also extends to affect subcortical nodes of fronto-basal ganglia- thalamo-cortical motor circuits. In contrast, alcohol appears to have little impact on the early visual processing of infrequent perceptual cues. These observations clarify clinically-important effects of alcohol on behaviour

Visualizing 1D Regression

Regression is the study of the conditional distribution of the response y given the predictors x. In a 1D regression, y is independent of x given a single linear combination βTx of the predictors. Special cases of 1D regression include multiple linear regression, binary regression and generalized linear models. If a good estimate ˆb of some non-zero multiple cβ of β can be constructed, then the 1D regression can be visualized with a scatterplot of ˆbTx versus y. A resistant method for estimating cβ is presented along with applications