Exogenous application of molybdenum affects the expression of CBF14 and the development of frost tolerance in wheat.

Wheat is able to cold acclimate in response to low temperatures and thereby increase its frost tolerance and the extent of this acclimation is greater in winter genotypes compared to spring genotypes. Such up-regulation of frost tolerance is controlled by Cbf transcription factors. Molybdenum (Mo) application has been shown to enhance frost tolerance of wheat and this study aimed to investigate the effect of Mo on the development of frost tolerance in winter and spring wheat. Results showed that Mo treatment increased the expression of Cbf14 in wheat under non-acclimating condition but did not alter frost tolerance. However, when Mo was applied in conjunction with exposure of plants to low temperature, Mo increased the expression of Cbf14 and enhanced frost tolerance in both spring and winter genotypes but the effect was more pronounced in the winter genotype. It was concluded that the application of Mo could be useful in situations where enhanced frost resistance is required. Further studies are proposed to elucidate the effect of exogenous of applications of Mo on frost resistance in spring and winter wheat at different growth stages

Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

Corrected score methods for estimating Bayesian networks with error-prone nodes

Motivated by inferring cellular signaling networks using noisy flow cytometry data, we develop procedures to draw inference for Bayesian networks based on error-prone data. Two methods for inferring causal relationships between nodes in a network are proposed based on penalized estimation methods that account for measurement error and encourage sparsity. We discuss consistency of the proposed network estimators and develop an approach for selecting the tuning parameter in the penalized estimation methods. Empirical studies are carried out to compare the proposed methods and a naive method that ignores measurement error with applications to synthetic data and to single cell flow cytometry data

Tailored or Routine Addition of an Antireflux Fundoplication in Laparoscopic Large Hiatal Hernia Repair: A Comparative Cohort Study

Contains fulltext : 98394.pdf (publisher's version ) (Open Access)BACKGROUND: There is controversy about the tailored or routine addition of an antireflux fundoplication in large hiatal hernia (type II-IV) repair. We investigated the strategy of selective addition of a fundoplication in patients with a large hiatal hernia and concomitant gastroesophageal reflux disease. METHODS: Between 2002 and 2008, 60 patients with a large hiatal hernia were evaluated preoperatively and 12 months after surgery by reflux-related symptoms, upper endoscopy, and esophageal 24-h pH monitoring. In patients with preoperatively documented gastroesophageal reflux disease, an antireflux fundoplication was added during hiatal hernia repair. RESULTS: An antireflux procedure was added in 35 patients and 25 patients underwent hiatal hernia repair only. Preoperative symptoms were improved or resolved in 31 patients (88.6%) in the group who had fundoplication and in 20 patients (87.0%) in the group who did not have fundoplication. In patients with fundoplication, esophagitis was present in 6 patients (22.2%) after surgery and abnormal esophageal acid exposure persisted in 11 (39.3%). Seven patients (38.9%) with hernia repair only developed abnormal esophageal acid exposure, and esophagitis was postoperatively generated in five (27.8%). In neither group did patients have new onset of daily heartburn or dysphagia. CONCLUSIONS: In patients with a large hiatal hernia associated with gastroesophageal reflux disease, addition of a fundoplication during hernia repair yields acceptable reduction of symptoms and does not generate symptomatic side effects. Objective control of reflux, however, is only moderate. Omission of an antireflux procedure in the absence of gastroesophageal reflux disease induced esophagitis in 28% and abnormal esophageal acid exposure in 39% of patients. Therefore, routine addition of an antireflux fundoplication should be recommended

vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

<p>Abstract</p> <p>Background</p> <p>The replication rate (or fitness) between viral variants has been investigated <it>in vivo </it>and <it>in vitro </it>for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness.</p> <p>Results</p> <p>Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1).</p> <p>Conclusions</p> <p>Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at <url>http://bis.urmc.rochester.edu/vFitness/</url>.</p

A global optimisation approach to range-restricted survey calibration

Survey calibration methods modify minimally unit-level sample weights to fit domain-level benchmark constraints (BC). This allows exploitation of auxiliary information, e.g. census totals, to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalization approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step Global Optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios, using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age-gender-region cross-tabulation (378 counts) from the 2011 Census in England and Wales

A global optimisation approach to range-restricted survey calibration

Survey calibration methods modify minimally unit-level sample weights to fit domain-level benchmark constraints (BC). This allows exploitation of auxiliary information, e.g. census totals, to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalization approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step Global Optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios, using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age-gender-region cross-tabulation (378 counts) from the 2011 Census in England and Wales

Explosive Nucleosynthesis: What we learned and what we still do not understand

This review touches on historical aspects, going back to the early days of nuclear astrophysics, initiated by B$^2$FH and Cameron, discusses (i) the required nuclear input from reaction rates and decay properties up to the nuclear equation of state, continues (ii) with the tools to perform nucleosynthesis calculations and (iii) early parametrized nucleosynthesis studies, before (iv) reliable stellar models became available for the late stages of stellar evolution. It passes then through (v) explosive environments from core-collapse supernovae to explosive events in binary systems (including type Ia supernovae and compact binary mergers), and finally (vi) discusses the role of all these nucleosynthesis production sites in the evolution of galaxies. The focus is put on the comparison of early ideas and present, very recent, understanding.Comment: 11 pages, to appear in Springer Proceedings in Physics (Proc. of Intl. Conf. "Nuclei in the Cosmos XV", LNGS Assergi, Italy, June 2018

Ten Simple Rules for Organizing an Unconference

This is an open access article distributed under the terms of the Creative Commons Attribution License.Peer Reviewe

A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study

BACKGROUND: This cohort study compared the prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill. METHODS: The relationships between SIG, lactate, anion gap (AG), anion gap albumin-corrected (AG-corrected), base excess or strong ion difference-effective (SIDe), all obtained within the first hour of intensive care unit (ICU) admission, and the hospital mortality of 6878 patients were analysed. The prognostic significance of each acid-base marker, both alone and in combination with the Admission Mortality Prediction Model (MPM0 III) predicted mortality, were assessed by the area under the receiver operating characteristic curve (AUROC). RESULTS: Of the 6878 patients included in the study, 924 patients (13.4 %) died after ICU admission. Except for plasma chloride concentrations, all acid-base markers were significantly different between the survivors and non-survivors. SIG (with lactate: AUROC 0.631, confidence interval [CI] 0.611-0.652; without lactate: AUROC 0.521, 95 % CI 0.500-0.542) only had a modest ability to predict hospital mortality, and this was no better than using lactate concentration alone (AUROC 0.701, 95 % 0.682-0.721). Adding AG-corrected or SIG to a combination of lactate and MPM0 III predicted risks also did not substantially improve the latter's ability to differentiate between survivors and non-survivors. Arterial lactate concentrations explained about 11 % of the variability in the observed mortality, and it was more important than SIG (0.6 %) and SIDe (0.9 %) in predicting hospital mortality after adjusting for MPM0 III predicted risks. Lactate remained as the strongest predictor for mortality in a sensitivity multivariate analysis, allowing for non-linearity of all acid-base markers. CONCLUSIONS: The prognostic significance of SIG was modest and inferior to arterial lactate concentration for the critically ill. Lactate concentration should always be considered regardless whether physiological, base excess or physical-chemical approach is used to interpret acid-base disturbances in critically ill patients