A new three-locus model for rootstock-induced dwarfing in apple revealed by genetic mapping of root bark percentage

Rootstock-induced dwarfing of apple scions revolutionized global apple production during the twentieth century, leading to the development of modern intensive orchards. A high root bark percentage (the percentage of the whole root area constituted by root cortex) has previously been associated with rootstock induced dwarfing in apple. In this study, the root bark percentage was measured in a full-sib family of ungrafted apple rootstocks and found to be under the control of three loci. Two QTL for root bark percentage were found to co-localise to the same genomic regions on chromosome 5 and chromosome 11 previously identified as controlling dwarfing, Dw1 and Dw2, respectively. A third QTL was identified on chromosome 13 in a region that has not been previously associated with dwarfing. The development of closely linked 3 Sequence-tagged site STS markers improved the resolution of allelic classes thereby allowing the detection of dominance and epistatic interactions between loci, with high root bark percentage only occurring in specific allelic combinations. In addition, we report a significant negative correlation between root bark percentage and stem diameter (an indicator of tree vigour), measured on a clonally propagated grafted subset of the mapping population. The demonstrated link between root bark percentage and rootstock-induced dwarfing of the scion leads us to propose a three-locus model that is able to explain levels of dwarfing from the dwarf ‘M.27’ to the semi-invigorating rootstock ‘M.116’. Moreover, we suggest that the QTL on chromosome 13 (Rb3) might be analogous to a third dwarfing QTL, Dw3 that has not previously been identified.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

NEONATAL HANDLING AND THE MATERNAL ODOR PREFERENCE IN RAT PUPS: INVOLVEMENT OF MONOAMINES AND CYCLIC AMP RESPONSE ELEMENT-BINDING PROTEIN PATHWAY IN THE OLFACTORY BULB

Early-life environmental events, such as the handling procedure, can induce long-lasting alterations upon several behavioral and neuroendocrine systems. However, the changes within the pups that could be causally related to the effects in adulthood are still poorly understood. In the present study, we analyzed the effects of neonatal handling on behavioral (maternal odor preference) and biochemical (cyclic AMP response element-binding protein (CREB) phosphorylation, noradrenaline (NA), and serotonin (5-HT) levels in the olfactory bulb (OB)) parameters in 7-day-old male and female rat pups. Repeated handling (RH) abolished preference for the maternal odor in female pups compared with nonhandled (NH) and the single-handled (SH) ones, while in RH males the preference was not different than NH and SH groups. In both male and female pups, RH decreased NA activity in the OB, but 5-HT activity increased only in males. Since preference for the maternal odor involves the synergic action of NA and 5-HT in the OB, the maintenance of the behavior in RH males could be related to the increased 5-HT activity, in spite of reduction in the NA activity in the OB. RH did not alter CREB phosphorylation in the OB of both male and females compared with NH pups. The repeated handling procedure can affect the behavior of rat pups in response to the maternal odor and biochemical parameters related to the olfactory learning mechanism. Sex differences were already detected in 7-day-old pups. Although the responsiveness of the hypothalamic-pituitary-adrenal axis to stressors is reduced in the neonatal period, environmental interventions may impact behavioral and biochemical mechanisms relevant to the animal at that early age. (C) 2009 IBRO. Published by Elsevier Ltd. All rights reserved.

Auriculo-condylar syndrome: mapping of a first locus and evidence for genetic heterogeneity

Auriculo-condylar syndrome (ACS), an autosomal dominant disorder of first and second pharyngeal arches, is characterized by malformed ears (`question mark ears`), prominent cheeks, microstomia, abnormal temporomandibular joint, and mandibular condyle hypoplasia. Penetrance seems to be complete, but there is high inter-and intra-familial phenotypic variation, with no evidence of genetic heterogeneity. We herein describe a new multigeneration family with 11 affected individuals (F1), in whom we confirm intra-familial clinical variability. Facial asymmetry, a clinical feature not highlighted in other ACS reports, was highly prevalent among the patients reported here. The gene responsible for ACS is still unknown and its identification will certainly contribute to the understanding of human craniofacial development. No chromosomal rearrangements have been associated with ACS, thus mapping and positional cloning is the best approach to identify this disease gene. To map the ACS gene, we conducted linkage analysis in two large ACS families, F1 and F2 (F2; reported elsewhere). Through segregation analysis, we first excluded three known loci associated with disorders of first and second pharyngeal arches (Treacher Collins syndrome, oculo-auriculo-vertebral spectrum, and Townes-Brocks syndrome). Next, we performed a wide genome search and we observed evidence of linkage to 1p21.1-q23.3 in F2 (LOD max 3.01 at theta = 0). Interestingly, this locus was not linked to the phenotype segregating in F1. Therefore, our results led to the mapping of a first locus of ACS (ACS1) and also showed evidence for genetic heterogeneity, suggesting that there are at least two loci responsible for this phenotype.

Mapping low- and high-density clouds in astrophysical nebulae by imaging forbidden line emission

Emission line ratios have been essential for determining physical parameters such as gas temperature and density in astrophysical gaseous nebulae. With the advent of panoramic spectroscopic devices, images of regions with emission lines related to these physical parameters can, in principle, also be produced. We show that, with observations from modern instruments, it is possible to transform images taken from density-sensitive forbidden lines into images of emission from high- and low-density clouds by applying a transformation matrix. In order to achieve this, images of the pairs of density-sensitive lines as well as the adjacent continuum have to be observed and combined. We have computed the critical densities for a series of pairs of lines in the infrared, optical, ultraviolet and X-rays bands, and calculated the pair line intensity ratios in the high- and low-density limit using a four- and five-level atom approximation. In order to illustrate the method, we applied it to Gemini Multi-Object Spectrograph (GMOS) Integral Field Unit (GMOS-IFU) data of two galactic nuclei. We conclude that this method provides new information of astrophysical interest, especially for mapping low- and high-density clouds; for this reason, we call it `the ld/hd imaging method`.

Gene Mapping of 18S and 5S rDNA Genes in the Karyotype of the Three-Spot Gourami Trichogaster trichopterus (Perciformes, Osphronemidae)

Ornamental fish culture is important as an economic activity and for biodiversity conservation as well. The species of the genus Trichogaster (Perciformes, Osphronemidae), popularly known as three-spot gourami, are among the several commercial species raised around the world. In the present work, eight specimens of Thrichogaster trichopterus from aquarium trade facilities were analyzed. The karyotype was composed of 23 pairs of subtelo/acrocentric chromosomes. Fluorescent in situ hybridization allowed identifying the 18S ribosomal gene at telomeric region on long arms of the largest acrocentric pair. On the other hand, the 5S rRNA gene is located at a proximal region on a pair of medium-sized chromosomes. Such information is extremely useful in face of the risks of introduction and the development of ornamental fish trade, once many fish species can be identified only by genetic studies.

OntoMap: an ontology-based architecture to perform the semantic mapping between an interlingua and software components

This paper is about the use of natural language to communicate with computers. Most researches that have pursued this goal consider only requests expressed in English. A way to facilitate the use of several languages in natural language systems is by using an interlingua. An interlingua is an intermediary representation for natural language information that can be processed by machines. We propose to convert natural language requests into an interlingua [universal networking language (UNL)] and to execute these requests using software components. In order to achieve this goal, we propose OntoMap, an ontology-based architecture to perform the semantic mapping between UNL sentences and software components. OntoMap also performs component search and retrieval based on semantic information formalized in ontologies and rules.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

Gamma Knife(A (R)) 3-D Dose Distribution Mapping by Magnetic Resonance Imaging

In medical processes where ionizing radiation is used, dose planning and dose delivery are the key elements to patient safety and treatment success, particularly, when the delivered dose in a single session of treatment can be an order of magnitude higher than the regular doses of radiotherapy. Therefore, the radiation dose should be well defined and precisely delivered to the target while minimizing radiation exposure to surrounding normal tissues [1]. Several methods have been proposed to obtain three-dimensional (3-D) dose distribution [2, 3]. In this paper, we propose an alternative method, which can be easily implemented in any stereotactic radiosurgery center with a magnetic resonance imaging (MRI) facility. A phantom with or without scattering centers filled with Fricke gel solution is irradiated with Gamma Knife(A (R)) system at a chosen spot. The phantom can be a replica of a human organ such as head, breast or any other organ. It can even be constructed from a real 3-D MR image of an organ of a patient using a computer-aided construction and irradiated at a specific region corresponding to the tumor position determined by MRI. The spin-lattice relaxation time T (1) of different parts of the irradiated phantom is determined by localized spectroscopy. The T (1)-weighted phantom images are used to correlate the image pixels intensity to the absorbed dose and consequently a 3-D dose distribution with a high resolution is obtained.