Association of single nucleotide polymorphisms in LpIRI1 gene with freezing tolerance traits in perennial ryegrass

Perennial ryegrass is an important agricultural species, however, susceptible to winterkill. Freezing injury is caused primarily by ice formation. The LpIRI1 protein has the potential to inhibit ice recrystallization, thus minimize the damage. An association study was conducted using single nucleotide polymorphisms obtained through allele sequencing of the LpIRI1 gene and phenotypic data were collected using two phenotyping platforms in a perennial ryegrass association mapping population of 76 diverse genotypes. Winter survival (FWS) was evaluated under field conditions, while tiller survival (PTS) and electrolyte leakage (EL) at -8 °C and -12 °C were determined under controlled-environment conditions. Proline content (PC) in cold-acclimated plants was measured prior the freezing test. Significant variation in FWS, PTS, EL and PC was observed among genotypes in our panel. EL and PTS revealed significant negative correlations at -8 °C (rs = -0.40) and -12 °C (rs = -0.49). PC, however, did not show significant correlations with any of the measured traits, while FWS was correlated (rs = -0.48) with EL at -12 °C. The LpIRI1 gene was found to be highly polymorphic with an average SNP frequency of 1 SNP per 16 bp. Association analysis revealed two non-synonymous SNPs being associated with increased EL, both being located in the LpIRI1 leucine-rich repeat. The results indicate that allelic variation in the LpIRI1 gene plays an important role in the cell membrane integrity of perennial ryegrass during freezing, and can be exploited for developing more freezing tolerant cultivars

Yet another breakdown point notion: EFSBP - illustrated at scale-shape models

The breakdown point in its different variants is one of the central notions to quantify the global robustness of a procedure. We propose a simple supplementary variant which is useful in situations where we have no obvious or only partial equivariance: Extending the Donoho and Huber(1983) Finite Sample Breakdown Point, we propose the Expected Finite Sample Breakdown Point to produce less configuration-dependent values while still preserving the finite sample aspect of the former definition. We apply this notion for joint estimation of scale and shape (with only scale-equivariance available), exemplified for generalized Pareto, generalized extreme value, Weibull, and Gamma distributions. In these settings, we are interested in highly-robust, easy-to-compute initial estimators; to this end we study Pickands-type and Location-Dispersion-type estimators and compute their respective breakdown points.Comment: 21 pages, 4 figure

Pre-existing invasive fungal infection is not a contraindication for allogeneic HSCT for patients with hematologic malignancies: a CIBMTR study.

Patients with prior invasive fungal infection (IFI) increasingly proceed to allogeneic hematopoietic cell transplantation (HSCT). However, little is known about the impact of prior IFI on survival. Patients with pre-transplant IFI (cases; n=825) were compared with controls (n=10247). A subset analysis assessed outcomes in leukemia patients pre- and post 2001. Cases were older with lower performance status (KPS), more advanced disease, higher likelihood of AML and having received cord blood, reduced intensity conditioning, mold-active fungal prophylaxis and more recently transplanted. Aspergillus spp. and Candida spp. were the most commonly identified pathogens. 68% of patients had primarily pulmonary involvement. Univariate and multivariable analysis demonstrated inferior PFS and overall survival (OS) for cases. At 2 years, cases had higher mortality and shorter PFS with significant increases in non-relapse mortality (NRM) but no difference in relapse. One year probability of post-HSCT IFI was 24% (cases) and 17% (control, P<0.001). The predominant cause of death was underlying malignancy; infectious death was higher in cases (13% vs 9%). In the subset analysis, patients transplanted before 2001 had increased NRM with inferior OS and PFS compared with later cases. Pre-transplant IFI is associated with lower PFS and OS after allogeneic HSCT but significant survivorship was observed. Consequently, pre-transplant IFI should not be a contraindication to allogeneic HSCT in otherwise suitable candidates. Documented pre-transplant IFI is associated with lower PFS and OS after allogeneic HSCT. However, mortality post transplant is more influenced by advanced disease status than previous IFI. Pre-transplant IFI does not appear to be a contraindication to allogeneic HSCT

Reduced-bias estimator of the Conditional Tail Expectation of heavy-tailed distributions

International audienceSeveral risk measures have been proposed in the literature. In this paper, we focus on the estimation of the Conditional Tail Expectation (CTE). Its asymptotic normality has been first established in the literature under the classical assumption that the second moment of the loss variable is finite, this condition being very restrictive in practical applications. Such a result has been extended by Necir {\it et al.} (2010) in the case of infinite second moment. In this framework, we propose a reduced-bias estimator of the CTE. We illustrate the efficiency of our approach on a small simulation study and a real data analysis

Robust Estimators in Generalized Pareto Models

This paper deals with optimally-robust parameter estimation in generalized Pareto distributions (GPDs). These arise naturally in many situations where one is interested in the behavior of extreme events as motivated by the Pickands-Balkema-de Haan extreme value theorem (PBHT). The application we have in mind is calculation of the regulatory capital required by Basel II for a bank to cover operational risk. In this context the tail behavior of the underlying distribution is crucial. This is where extreme value theory enters, suggesting to estimate these high quantiles parameterically using, e.g. GPDs. Robust statistics in this context offers procedures bounding the influence of single observations, so provides reliable inference in the presence of moderate deviations from the distributional model assumptions, respectively from the mechanisms underlying the PBHT.Comment: 26pages, 6 figure

A statistical application of the quantile mechanics approach: MTM estimators for the parameters of t and gamma distributions

In this paper, we revisit the quantile mechanics approach, which was introduced by Steinbrecher and Shaw (Steinbrecher, G. &amp; Shaw, W. T. (2008) Quantile mechanics. European. J. Appl. Math.19, 87–112). Our objectives are (i) to derive the method of trimmed moments (MTM) estimators for the parameters of gamma and Student's t distributions, and (ii) to examine their large- and small-sample statistical properties. Since trimmed moments are defined through the quantile function of the distribution, quantile mechanics seems like a natural approach for achieving objective (i). To accomplish the second goal, we rely on the general large sample results for MTMs, which were established by Brazauskas et al. (Brazauskas, V., Jones, B. L. &amp; Zitikis, R. (2009) Robust fitting of claim severity distributions and the method of trimmed moments. J. Stat. Plan. Inference139, 2028–2043), and then use Monte Carlo simulations to investigate small-sample behaviour of the newly derived estimators. We find that, unlike the maximum likelihood method, which usually yields fully efficient but non-robust estimators, the MTM estimators are robust and offer competitive trade-offs between robustness and efficiency. These properties are essential when one employs gamma or Student's t distributions in such outlier-prone areas as insurance and finance.</jats:p

Přídolí carbon isotope trend and upper Silurian to lowermost Devonian chemostratigraphy based on sections in Podolia (Ukraine) and the East Baltic area

Insufficient knowledge of carbon isotope cycling in the latest Silurian initiated the study of two regions at the western and southwestern margins of Baltica in order to obtain a more complete picture about the carbon isotope trend through the Přídolí. Shallow and open shelf carbonate rocks of the Dniester River outcrops and Kotuzhiny core in Podolia and deep shelf rocks of the East Baltic area, especially the Lithuanian cores, were studied for bulk-rock isotope analysis. The data sets of both regions begin with the mid-Ludfordian excursion and include also some part of the lowermost Devonian. The data show a new minor twin positive δ13C excursion (peak values 0.8–1.7‰) in the upper Ludfordian. The Přídolí carbon isotope trend begins with a low of negative δ13C values, succeeded by the lower to middle Přídolí ‘stability’ interval (variable values below or close to 0‰ with a slight rising trend). The upper Přídolí begins with a medium to major excursion (peak values 2.3–4.5‰), which reflects the pattern of the carbon isotope trend on the west of the Baltica palaeocontinent. Its wider significance awaits confirmation from observations elsewhere. The carbon isotope excursion at the Silurian–Devonian boundary, named here the SIDE excursion (its δ13C values range from 1.6‰ in deep shelf settings to 3.8‰ in shallower ones and 4.5‰ in brachiopod shells), has been traced on several continents, and now also in Baltica. This excursion can serve as a well-dated global chemostratigraphic correlation tool. The shape of the excursion indicates the completeness of the studied section. We conclude that carbon isotope chemostratigraphy may contribute to subdividing the Přídolí Series into stages and that Baltica sensu lato seems to be the right place for such a development