Soil flooding creates composite and complex stress in plants known as either submergence or waterlogging stress depending on the depth of the water table. In nature, these stresses are important ...factors dictating the species composition of the ecosystem. On agricultural land, they cause economic damage associated with long-term social consequences. The understanding of the plant molecular responses to these two stresses has benefited from research studying individual components of the stress, in particular low-oxygen stress. To a lesser extent, other associated stresses and plant responses have been incorporated into the molecular framework, such as ion and ROS signaling, pathogen susceptibility, and organ-specific expression and development. In this review, we aim to highlight known or suspected components of submergence/waterlogging stress that have not yet been thoroughly studied at the molecular level in this context, such as miRNA and retrotransposon expression, the influence of light/dark cycles, protein isoforms, root architecture, sugar sensing and signaling, post-stress molecular events, heavy-metal and salinity stress, and mRNA dynamics (splicing, sequestering, and ribosome loading). Finally, we explore biotechnological strategies that have applied this molecular knowledge to develop cultivars resistant to flooding or to offer alternative uses of flooding-prone soils, like bioethanol and biomass production.
In this paper, we deal with inference about the structural parameters in a heteroscedastic functional measurement error models under the normal distribution assumption. Given a minimal sufficient ...statistic for the incidental parameters, the conditional maximum likelihood (CML) approach is used. We show that CML estimators have explicit expressions and their sampling distribution is exact. We also show that the classical test statistics to test hypotheses of interest coincide and have exact distributions. We apply the statistical inference tools developed to a data set on comparison of measurement methods.
•Inference on the structural parameters in a functional measurement error model.•Minimal sufficient statistic for the incidental parameters.•We apply the developed methodology to a data set on comparison of measurement methods.
We provide a model capable of accounting for the multiferroicity in certain materials. The model's base is on free electrons and spin moments coupled within nonrelativistic quantum mechanics. The ...synergistic interplay between the magnetic and electric degrees of freedom that turns into the multiferroic phenomena occurs at a profound quantum mechanical level, conjured by Berry's phases and the quantum theory of polarization. Our results highlight the geometrical nature of the multiferroic order parameter that naturally leads to magnetoelectric domain walls, with promising technological potential.
A new family of generalized distributions Cordeiro, Gauss M.; de Castro, Mário
Journal of statistical computation and simulation,
07/2011, Letnik:
81, Številka:
7
Journal Article
Recenzirano
Kumaraswamy Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79-88 introduced a distribution for double-bounded random processes with ...hydrological applications. For the first time, based on this distribution, we describe a new family of generalized distributions (denoted with the prefix 'Kw') to extend the normal, Weibull, gamma, Gumbel, inverse Gaussian distributions, among several well-known distributions. Some special distributions in the new family such as the Kw-normal, Kw-Weibull, Kw-gamma, Kw-Gumbel and Kw-inverse Gaussian distribution are discussed. We express the ordinary moments of any Kw generalized distribution as linear functions of probability weighted moments (PWMs) of the parent distribution. We also obtain the ordinary moments of order statistics as functions of PWMs of the baseline distribution. We use the method of maximum likelihood to fit the distributions in the new class and illustrate the potentiality of the new model with an application to real data.
Patients who used oral glucocorticoids for asthma were able to reduce the dose of treatment more successfully when dupilumab, a monoclonal antibody targeting signaling through the interleukin-4 and ...interleukin-13 receptor, was added to their regimen than when placebo was added.
Successful mathematical modeling of biological processes relies on the expertise of the modeler to capture the essential mechanisms in the process at hand and on the ability to extract useful ...information from empirical data. A model is said to be structurally unidentifiable, if different quantitative sets of parameters provide the same observable outcome. This is typical (but not exclusive) of partially observed problems in which only a few variables can be experimentally measured. Most of the available methods to test the structural identifiability of a model are either too complex mathematically for the general practitioner to be applied, or require involved calculations or numerical computation for complex non-linear models. In this work, we present a new analytical method to test structural identifiability of models based on ordinary differential equations, based on the invariance of the equations under the scaling transformation of its parameters. The method is based on rigorous mathematical results but it is easy and quick to apply, even to test the identifiability of sophisticated highly non-linear models. We illustrate our method by example and compare its performance with other existing methods in the literature.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This document provides clinical recommendations for the management of severe asthma. Comprehensive evidence syntheses, including meta-analyses, were performed to summarise all available evidence ...relevant to the European Respiratory Society/American Thoracic Society Task Force's questions. The evidence was appraised using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach and the results were summarised in evidence profiles. The evidence syntheses were discussed and recommendations formulated by a multidisciplinary Task Force of asthma experts, who made specific recommendations on six specific questions. After considering the balance of desirable and undesirable consequences, quality of evidence, feasibility, and acceptability of various interventions, the Task Force made the following recommendations: 1) suggest using anti-interleukin (IL)-5 and anti-IL-5 receptor α for severe uncontrolled adult eosinophilic asthma phenotypes; 2) suggest using a blood eosinophil cut-point ≥150 μL
to guide anti-IL-5 initiation in adult patients with severe asthma; 3) suggest considering specific eosinophil (≥260 μL
) and exhaled nitric oxide fraction (≥19.5 ppb) cut-offs to identify adolescents or adults with the greatest likelihood of response to anti-IgE therapy; 4) suggest using inhaled tiotropium for adolescents and adults with severe uncontrolled asthma despite Global Initiative for Asthma (GINA) step 4-5 or National Asthma Education and Prevention Program (NAEPP) step 5 therapies; 5) suggest a trial of chronic macrolide therapy to reduce asthma exacerbations in persistently symptomatic or uncontrolled patients on GINA step 5 or NAEPP step 5 therapies, irrespective of asthma phenotype; and 6) suggest using anti-IL-4/13 for adult patients with severe eosinophilic asthma and for those with severe corticosteroid-dependent asthma regardless of blood eosinophil levels. These recommendations should be reconsidered as new evidence becomes available.
Background Previous studies have identified asthma phenotypes based on small numbers of clinical, physiologic, or inflammatory characteristics. However, no studies have used a wide range of variables ...using machine learning approaches. Objectives We sought to identify subphenotypes of asthma by using blood, bronchoscopic, exhaled nitric oxide, and clinical data from the Severe Asthma Research Program with unsupervised clustering and then characterize them by using supervised learning approaches. Methods Unsupervised clustering approaches were applied to 112 clinical, physiologic, and inflammatory variables from 378 subjects. Variable selection and supervised learning techniques were used to select relevant and nonredundant variables and address their predictive values, as well as the predictive value of the full variable set. Results Ten variable clusters and 6 subject clusters were identified, which differed and overlapped with previous clusters. Patients with traditionally defined severe asthma were distributed through subject clusters 3 to 6. Cluster 4 identified patients with early-onset allergic asthma with low lung function and eosinophilic inflammation. Patients with later-onset, mostly severe asthma with nasal polyps and eosinophilia characterized cluster 5. Cluster 6 asthmatic patients manifested persistent inflammation in blood and bronchoalveolar lavage fluid and exacerbations despite high systemic corticosteroid use and side effects. Age of asthma onset, quality of life, symptoms, medications, and health care use were some of the 51 nonredundant variables distinguishing subject clusters. These 51 variables classified test cases with 88% accuracy compared with 93% accuracy with all 112 variables. Conclusion The unsupervised machine learning approaches used here provide unique insights into disease, confirming other approaches while revealing novel additional phenotypes.
Short courses of systemic corticosteroids (SCS), both oral and injectable, are very effective for the resolution of acute asthma symptoms, including exacerbations. However, the benefits of SCS, even ...short courses, must be balanced against the impact of their side-effects. While the adverse consequences of long-term use are widely recognised, there appears to be a perception in the medical community that short courses of SCS are safe. Limited but growing evidence in the literature suggests that even very brief dosing periods (3-7 days) of SCS are enough to cause significantly negative outcomes for patients. Short courses of SCS are associated with increased risk of adverse events including loss of bone density, hypertension and gastrointestinal ulcers/bleeds, in addition to serious impacts on mental health. Strategies to improve asthma control are recommended, including: 1) as-needed combination therapies in mild asthma; 2) risk factor reduction; 3) improving adherence/inhaler technique; 4) earlier initiation of add-on therapies; 5) use of biologics in appropriate patients; 6) development of new therapies to better control the disease; and 7) widespread education of the medical community. We propose that patients and primary care physicians should consider a cumulative SCS dose of 1 g per year as a highly relevant and easy-to-recall threshold.
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