Interfertility between Armillaria cepistipes and A. sinapina

Des études ont rapporté que des lignées européennes d'Armillaria cepistipes étaient interfertiles avec trois lignées américaines d'Armillaria désignées par les termes espèce biologique nord-américaine (NABS) V (A sinapina), NABS X et NABS XI. Une telle interfertilité entre les espèces soulève des doutes au sujet de l'utilisation de binômes latins distincts pour des espèces pouvant se reproduire. Cette interfertilité a été ré-examinée en mettant 24 isolats haploïdes d'A cepistipes européen en présence de 23 isolats 6'A. sinapina d'Amérique du Nord et d'Asie. Les appariements individuels ont été effectués de façon indépendante au moins une fois à l'Université Laval (Canada) et à NNRA Clermont-Ferrand (France). Des 420 appariements interspécifiques effectués à l'Université Laval, deux étaient positifs et sept étaient ambigus, pour un total de 2,1 % de tous les appariements. Des 506 appariements effectués à Clermont-Ferrand, 10 étaient positifs et 24 étaient ambigus pour un total de 6,7 % des appariements. Les différences dans les résultats de ces appariements peuvent être expliquées par les températures d'incubation, ainsi que par les différents types et concentrations d'extrait de malt utilisés dans chaque laboratoire. Les bas niveaux d'interfertilité trouvés entre A cepistipes et A. sinapina peuvent résulter de l'absence de barrières génétiques habituellement présentes entre des espèces sympatriques. Ce bas niveau d'interfertilité reflète des différences entre la morphologie, la répartition et les habitats des deux espèces d'Armillaria, et appuie la conservation de dénominations d'espèces distinctes.European strains of Armillaria cepistipes were reported to be interfertile with strains from three American Armillaria species known as North American Biological Species (NABS) V (A sinapina), NABS X and NABS XI. Such interfertility between species raises some doubts about using different Latin binomials for species capable of mating. This interfertility was reinvestigated by mating 24 haploid isolates of European A cepistipes with 23 isolates of A sinapinafrom North America and Asia. Individual pairings were independently performed at least once at Universite Laval, Canada and at INRA Clermont-Ferrand, France. From the 420 interspecific pairings performed at Laval, two were positive and seven were ambiguous for a total of 2.1% of all the pairings. From the 506 pairings made at Clermont-Ferrand, 10 were positive and 24 were ambiguous for a total of 6.7%. The differences in the pairing results may be explained by incubation temperatures, and the different types and concentrations of malt extract used at each laboratory. The low levels of interfertility found between A. cepistipes and A. sinapina may result from the absence of genetic barriers that are usually present between sympatric species. This low level of interfertility reflects differences in morphology, distribution, and habitat for these two species of Armillaria and this supports the retention of different species denominations

DPDRC, a novel machine learning method about the decision process for dimensionality reduction before clustering

This paper examines the critical decision process of reducing the dimensionality of a dataset before applying a clustering algorithm. It is always a challenge to choose between extracting or selecting features. It is not obvious to evaluate the importance of the features since the most popular methods to do it are usually intended for a supervised learning technique process. This paper proposes a novel method called “Decision Process for Dimensionality Reduction before Clustering” (DPDRC). It chooses the best dimensionality reduction method (selection or extraction) according to the data scientist’s parameters and the profile of the data, aiming to apply a clustering process at the end. It uses a Feature Ranking Process Based on Silhouette Decomposition (FRSD) algorithm, a Principal Component Analysis (PCA) algorithm, and a K-means algorithm along with its metric, the Silhouette Index (SI). This paper presents five scenarios based on different parameters. This research also aims to discuss the impacts, advantages, and disadvantages of each choice that can be made in this unsupervised learning process

In-plasma analysis of plasma–surface interactions

During deposition, modification, and etching of thin films and nanomaterials in reactive plasmas, many active species can interact with the sample simultaneously. This includes reactive neutrals formed by fragmentation of the feed gas, positive ions, and electrons generated by electron-impact ionization of the feed gas and fragments, excited states (in particular, long-lived metastable species), and photons produced by spontaneous de-excitation of excited atoms and molecules. Notably, some of these species can be transiently present during the different phases of plasma processing, such as etching of thin layer deposition. To monitor plasma–surface interactions during materials processing, a new system combining beams of neutral atoms, positive ions, UV photons, and a magnetron plasma source has been developed. This system is equipped with a unique ensemble of in-plasma surface characterization tools, including (1) a Rutherford Backscattering Spectrometer (RBS), (2) an Elastic Recoil Detector (ERD), and (3) a Raman spectroscopy system. RBS and ERD analyses are carried out using a differentially pumped 1.7 MV ion beam line Tandetron accelerator generating a beam at grazing incidence. The ERD system is equipped with an absorber and is specifically used to detect H initially bonded to the surface; higher resolution of surface H is also available through nuclear reaction analysis. In parallel, an optical port facing the substrate is used to perform Raman spectroscopy analysis of the samples during plasma processing. This system enables fast monitoring of a few Raman peaks over nine points scattered on a 1.6 × 1.6 mm2 surface without interference from the inherent light emitted by the plasma. Coupled to the various plasma and beam sources, the unique set of in-plasma surface characterization tools detailed in this study can provide unique time-resolved information on the modification induced by plasma. By using the ion beam analysis capability, the atomic concentrations of various elements in the near-surface (e.g., stoichiometry and impurity content) can be monitored in real-time during plasma deposition or etching. On the other hand, the evolution of Raman peaks as a function of plasma processing time can contribute to a better understanding of the role of low-energy ions in defect generation in irradiation-sensitive materials, such as monolayer graphene

Behavior and Impact of Zirconium in the Soil–Plant System: Plant Uptake and Phytotoxicity

Because of the large number of sites they pollute, toxic metals that contaminate terrestrial ecosystems are increasingly of environmental and sanitary concern (Uzu et al. 2010, 2011; Shahid et al. 2011a, b, 2012a). Among such metals is zirconium (Zr), which has the atomic number 40 and is a transition metal that resembles titanium in physical and chemical properties (Zaccone et al. 2008). Zr is widely used in many chemical industry processes and in nuclear reactors (Sandoval et al. 2011; Kamal et al. 2011), owing to its useful properties like hardness, corrosion-resistance and permeable to neutrons (Mushtaq 2012). Hence, the recent increased use of Zr by industry, and the occurrence of the Chernobyl and Fukashima catastrophe have enhanced environmental levels in soil and waters (Yirchenko and Agapkina 1993; Mosulishvili et al. 1994 ; Kruglov et al. 1996)

Agriculture in the Trans-Pacific Partnership

The Trans-Pacific Partnership is a trade and investment agreement under negotiation by 12 countries in the Pacific Rim. This report assesses this partnership's potential impacts on the region's agriculture in 2025

Immune Cell Recruitment and Cell-Based System for Cancer Therapy

Immune cells, such as cytotoxic T lymphocytes, natural killer cells, B cells, and dendritic cells, have a central role in cancer immunotherapy. Conventional studies of cancer immunotherapy have focused mainly on the search for an efficient means to prime/activate tumor-associated antigen-specific immunity. A systematic understanding of the molecular basis of the trafficking and biodistribution of immune cells, however, is important for the development of more efficacious cancer immunotherapies. It is well established that the basis and premise of immunotherapy is the accumulation of effective immune cells in tumor tissues. Therefore, it is crucial to control the distribution of immune cells to optimize cancer immunotherapy. Recent characterization of various chemokines and chemokine receptors in the immune system has increased our knowledge of the regulatory mechanisms of the immune response and tolerance based on immune cell localization. Here, we review the immune cell recruitment and cell-based systems that can potentially control the systemic pharmacokinetics of immune cells and, in particular, focus on cell migrating molecules, i.e., chemokines, and their receptors, and their use in cancer immunotherapy