Optimization of conditions for in vitro pollen germination and pollen tube growth of date palm (Phoenix dactylifera L.)

Pollen germination and pollen tube growth might have a significant effect on fruit and seed production. This study was conducted to investigate the best medium for pollen germination and pollen tube growth of date palm male. Significant differences in percentages of pollen germination and pollen tube growth were observed between mediums. The use agar-based medium containing 5% of sucrose, 0.20 g/l boric acid, 0.42 g/l calcium nitrate, 0.1 g/l potassium nitrate and 0.22 g/l magnesium sulfate gave the best results in terms of germination and/or tube growth. The germination percentage was declined with polyethylene glycol and naphthaleneacetic acid, and inhibited completely with fructose, glucose and date extract. These results could have  implications not only for optimizing pollen management in date palm but also to select the best pollinizer for this specie.Keywords:<i> In vitro</i> pollen germination; Sucrose; Fructose; Glucose;  Naphthaleneacetic acid; basal medium

New Coordinative Compounds with 4-(4’-pyridyl)pyridinium Disubstituted Monoylides

The complexes with manganese(II), iron(II), cobalt(II), nickel(II) and copper(II) of 2-(4, 4’-bipyridin-1-ium-1-yl)-1-(4-bromophenylamino)-3-(4-methoxyphenyl)-3-oxo-1-thioxopropan-2-ide (ylide, Y) were synthesized and characterized. The obtained compounds with 1 : 2 metal/ligand ratios have been characterized by FTIR, UV Vis spectroscopy, ESI MS spectrometry, molecular conductance, magnetic measurements and thermal analysis. The ylide ligand forms chelates with metallic (II) ions through their amide nitrogen and oxygen atoms

Finding the Positive Nearest-Neighbor in Recommender Systems

Abstract Recommender systems make suggestions about products or services based on matching known or estimated preferences of users with properties of products or services (contentbased), or properties of other users considered to be similar (collaborative filtering). Collaborative filtering is widely used in Ecommerce. To generate accurate recommendations, the properties of a new user must be matched with those of existing users as accurately as possible. The available data is very large, and the matching must be computed in real time. We introduce algorithms that use “positive ” nearest-neighbor matching in the sparse datasets typical of collaborative filtering to find near neighbors whose attribute values exceed those of each new user. The algorithms use singular value decomposition as a dimension-reduction technique. Making this idea effective requires careful attention to details such as normalization. Experimental results are reported for a movie recommendation dataset. For n users and m objects, reasonable matches can be found in time O(m log n), using O(nm) storage

Large-Scale Resource Selection in Grids

Abstract. Grid resource selection requires matching job requirements to available resources. This is a difficult problem when the number of attributes for each resource is large. We present an algorithm that uses the Singular Value Decomposition to encode each resource’s properties by a single value. Jobs are matched by using the same encoding to produce a value that can be rapidly compared to those of the resources. We show that reasonable matches can be found in time O(m log n) where n is the number of resources and m the number of attributes for which a job might have requirements. This is in contrast to “approximate nearest neighbor ” techniques which require either time or storage exponential in m

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In a publish/subscribe paradigm, user service discovery requires matching user preferences to available published services, e.g., a user may want to find if there is a Chinese restaurant close by. This is a difficult problem when users are mobile, wirelessly connected to a network, and dynamically roaming in different environments. The magnitude of the problem increases with respect to the number of attributes for each user’s preference criteria, as matches must be done in real-time. We present an algorithm that uses Singular Value Decomposition to encode each service properties in a few values. Users’ preference criteria are matched by using the same encoding to produce a value that can be rapidly compared to those of the services. We show that reasonable matches can be found in time O(m log n) where n is the number of publications and m the number of attributes in the preference criteria (subscription). This is in contrast to “approximate nearest neighbor ” techniques, which require either time or storage exponential in m. Keywords: Publish/subscribe, nearest neighbor search, multidimensional search, high dimensional data space, Singular Valu

<i>In vitro</i> assays impact of (A) Trichostatin A and (B) Oligomycin A on LGTV replication.

<p>Trichostatin (TSA) and Oligomycin A (OligoA) concentrations on the x-axis, percent cell viability on the right y-axis, and virus release in pfu/mL on the left y-axis. Compound assays out of Vero cells are shown in the left panels and out of ISE6 cells are shown in the right panels. Release of LGTV was assessed by viral titer (pfu/ml) using plaque assays in BHK15 cells. Cell viability was determined with alamarBlue reagent and fluorescent assay and percentage was normalized against solvent only control in both LGTV-infected and mock-treated ISE6/Vero cells. * denotes p<0.05 and *** denotes p<0.001. Standard error shown in error bars with five technical replicates. Two biological replicate experiments were completed.</p

ISE6 proteins associated with the TCA cycle and glutaminolysis.

<p>ISE6 glutaminolysis and mTOR signaling proteins altered with LGTV infection are shown. GDH denotes glutamate dehydrogenase enzymes and Glase denotes glutaminase enzymes. ISCWxxxxxx denotes corresponding VB accession ID for corresponding <i>I</i>. <i>scapularis</i> protein.</p

ISE6 proteins identified in KEGG pathways with differential expression following LGTV, UV-LGTV and mock treatment.

<p>(A) Total number of ISE6 cell proteins categorized by treatment and change in expression (increase/decrease/no change). Total number of proteins showing (B) increased expression, (C) decreased expression, and (D) no change in expression following LGTV infection and UV-LGTV treatment as compared to mock-treated cells and in LGTV-infected cells as compared to UV-LGTV-treated cells. Proteins were categorized by the KEGG classes for cellular function: metabolism, genetic information processing (GIP), environmental information processing (EIP), cellular processes (CP), and organismal systems (OS).</p