Evidence and modeling of turbulence bifurcation in L-mode confinement transitions on Alcator C-Mod

© 2020 Author(s). Analysis and modeling of rotation reversal hysteresis experiments show that a single turbulent bifurcation is responsible for the Linear to Saturated Ohmic Confinement (LOC/SOC) transition and concomitant intrinsic rotation reversal on Alcator C-Mod. Plasmas on either side of the reversal exhibit different toroidal rotation profiles and therefore different turbulence characteristics despite the profiles of density and temperature, which are indistinguishable within measurement uncertainty. Elements of this bifurcation are also shown to persist for auxiliary heated L-modes. The deactivation of subdominant (in the linear growth rate and contribution to heat transport) ion temperature gradient and trapped electron mode instabilities is identified as the only possible change in turbulence within a reduced quasilinear transport model across the reversal, which is consistent with the measured profiles and inferred heat and particle fluxes. Experimental constraints on a possible change from strong to weak turbulence, outside the description of the quasilinear model, are also discussed. These results indicate an explanation for the LOC/SOC transition that provides a mechanism for the hysteresis through the dynamics of subdominant modes and changes in their relative populations and does not involve a change in the most linearly unstable ion-scale drift-wave instability

Elevation and cholera: an epidemiological spatial analysis of the cholera epidemic in Harare, Zimbabwe, 2008-2009

BACKGROUND: In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009. METHODS: We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs. RESULTS: This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%. CONCLUSION: This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic

Identification and validation of a QTL influencing bitter pit symptoms in apple (Malus x domestica)

Bitter pit is one of the most economically important physiological disorders affecting apple fruit production, causing soft discrete pitting of the cortical flesh of the apple fruits which renders them unmarketable. The disorder is heritable; however, the environment and cultural practices play a major role in expression of symptoms. Bitter pit has been shown to be controllable to a certain extent using calcium sprays and dips; however, their use does not entirely prevent the incidence of the disorder. Previously, bitter pit has been shown to be controlled by two dominant genes, and markers on linkage group 16 of the apple genome were identified that were significantly associated with the expression of bitter pit symptoms in a genome-wide association study. In this investigation, we identified a major QTL for bitter pit defined by two microsatellite (SSR) markers. The association of the SSRs with the bitter pit locus, and their ability to predict severe symptom expression, was confirmed through screening of individuals with stable phenotypic expression from an additional mapping progeny. The data generated in this current study suggest a two gene model could account for the control of bitter pit symptom expression; however, only one of the loci was detectable, most likely due to dominance of alleles carried by both parents of the mapping progeny used. The SSR markers identified are cost-effective, robust and multi-allelic and thus should prove useful for the identification of seedlings with resistance to bitter pit using marker-assisted selection in apple breeding programs

Correlation between in vitro cytotoxicity and in vivo lethal activity in mice of epsilon toxin mutants from Clostridium perfringens

Epsilon toxin (Etx) from Clostridium perfringens is a pore-forming protein with a lethal effect on livestock, producing severe enterotoxemia characterized by general edema and neurological alterations. Site-specific mutations of the toxin are valuable tools to study the cellular and molecular mechanism of the toxin activity. In particular, mutants with paired cysteine substitutions that affect the membrane insertion domain behaved as dominant-negative inhibitors of toxin activity in MDCK cells. We produced similar mutants, together with a well-known non-toxic mutant (Etx-H106P), as green fluorescent protein (GFP) fusion proteins to perform in vivo studies in an acutely intoxicated mouse model. The mutant (GFP-Etx-I51C/A114C) had a lethal effect with generalized edema, and accumulated in the brain parenchyma due to its ability to cross the blood-brain barrier (BBB). In the renal system, this mutant had a cytotoxic effect on distal tubule epithelial cells. The other mutants studied (GFP-Etx-V56C/F118C and GFP-Etx-H106P) did not have a lethal effect or cross the BBB, and failed to induce a cytotoxic effect on renal epithelial cells. These data suggest a direct correlation between the lethal effect of the toxin, with its cytotoxic effect on the kidney distal tubule cells, and the ability to cross the BBB

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally

Clostridium perfringens epsilon toxin increases the small intestinal permeability in mice and rats

Epsilon toxin is a potent neurotoxin produced by Clostridium perfringens types B and D, an anaerobic bacterium that causes enterotoxaemia in ruminants. In the affected animal, it causes oedema of the lungs and brain by damaging the endothelial cells, inducing physiological and morphological changes. Although it is believed to compromise the intestinal barrier, thus entering the gut vasculature, little is known about the mechanism underlying this process. This study characterizes the effects of epsilon toxin on fluid transport and bioelectrical parameters in the small intestine of mice and rats. The enteropooling and the intestinal loop tests, together with the single-pass perfusion assay and in vitro and ex vivo analysis in Ussing's chamber, were all used in combination with histological and ultrastructural analysis of mice and rat small intestine, challenged with or without C. perfringens epsilon toxin. Luminal epsilon toxin induced a time and concentration dependent intestinal fluid accumulation and fall of the transepithelial resistance. Although no evident histological changes were observed, opening of the mucosa tight junction in combination with apoptotic changes in the lamina propria were seen with transmission electron microscopy. These results indicate that C. perfringens epsilon toxin alters the intestinal permeability, predominantly by opening the mucosa tight junction, increasing its permeability to macromolecules, and inducing further degenerative changes in the lamina propria of the bowel. © 2009 Goldstein et al

The Virtual Physiological Human: Ten Years After

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype–phenotype interaction and by a “systemic” nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible—the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done

What has finite element analysis taught us about diabetic foot disease and its management?:a systematic review

Over the past two decades finite element (FE) analysis has become a popular tool for researchers seeking to simulate the biomechanics of the healthy and diabetic foot. The primary aims of these simulations have been to improve our understanding of the foot's complicated mechanical loading in health and disease and to inform interventions designed to prevent plantar ulceration, a major complication of diabetes. This article provides a systematic review and summary of the findings from FE analysis-based computational simulations of the diabetic foot.A systematic literature search was carried out and 31 relevant articles were identified covering three primary themes: methodological aspects relevant to modelling the diabetic foot; investigations of the pathomechanics of the diabetic foot; and simulation-based design of interventions to reduce ulceration risk.Methodological studies illustrated appropriate use of FE analysis for simulation of foot mechanics, incorporating nonlinear tissue mechanics, contact and rigid body movements. FE studies of pathomechanics have provided estimates of internal soft tissue stresses, and suggest that such stresses may often be considerably larger than those measured at the plantar surface and are proportionally greater in the diabetic foot compared to controls. FE analysis allowed evaluation of insole performance and development of new insole designs, footwear and corrective surgery to effectively provide intervention strategies. The technique also presents the opportunity to simulate the effect of changes associated with the diabetic foot on non-mechanical factors such as blood supply to local tissues.While significant advancement in diabetic foot research has been made possible by the use of FE analysis, translational utility of this powerful tool for routine clinical care at the patient level requires adoption of cost-effective (both in terms of labour and computation) and reliable approaches with clear clinical validity for decision making

Glioma stem cells invasive phenotype at optimal stiffness is driven by MGAT5 dependent mechanosensing.

BACKGROUND: Glioblastomas stem-like cells (GSCs) by invading the brain parenchyma, remains after resection and radiotherapy and the tumoral microenvironment become stiffer. GSC invasion is reported as stiffness sensitive and associated with altered N-glycosylation pattern. Glycocalyx thickness modulates integrins mechanosensing, but details remain elusive and glycosylation enzymes involved are unknown. Here, we studied the association between matrix stiffness modulation, GSC migration and MGAT5 induced N-glycosylation in fibrillar 3D context. METHOD: To mimic the extracellular matrix fibrillar microenvironments, we designed 3D-ex-polyacrylonitrile nanofibers scaffolds (NFS) with adjustable stiffnesses by loading multiwall carbon nanotubes (MWCNT). GSCs neurosphere were plated on NFSs, allowing GSCs migration and MGAT5 was deleted using CRISPR-Cas9. RESULTS: We found that migration of GSCs was maximum at 166 kPa. Migration rate was correlated with cell shape, expression and maturation of focal adhesion (FA), Epithelial to Mesenchymal Transition (EMT) proteins and (β1,6) branched N-glycan binding, galectin-3. Mutation of MGAT5 in GSC inhibited N-glycans (β1-6) branching, suppressed the stiffness dependence of migration on 166 kPa NFS as well as the associated FA and EMT protein expression. CONCLUSION: MGAT5 catalysing multibranched N-glycans is a critical regulators of stiffness induced invasion and GSCs mechanotransduction, underpinning MGAT5 as a serious target to treat cancer