MODELING OF WEEDS INTERFERENCE PERIODS IN BEAN

The research objective was to determine the effects of spacing and seeding density of common bean to the period prior to weed interference (PPI) and weed period prior to economic loss (WEEPPEL). The treatments consisted of periods of coexistence between culture and the weeds, with 0 to 10, 0 to 20, 0 to 30, 0 to 40, 0 to 50, 0 to 60, 0 to 70, and 0 to 80 days and a control maintained without weeds. In addition to the periods of coexistence, there were still studies with an inter-row of 0.45 and 0.60 m, 10 and 15 plants m(-1). The experimental delineation used was randomized blocks with four repetitions per treatment. The grain productivity of the culture had a reduction of 63, 50, 42 and 57% when the coexistence with the weed plants was during the entire cycle of the culture for a row spacing of 0.45 m and a seeding density of 10 and 15 plants per meter; and a row spacing of 0.60m and a seeding density of 10 and 15 plants per meter, respectively. The PPI occurred in 23, 27, 13, and 19 days after crop emergence and WEEPPEL in 10, 9, 8, and 8 days, respectively.

Critical behavior in a cross-situational lexicon learning scenario

The associationist account for early word learning is based on the co-occurrence between referents and words. Here we introduce a noisy cross-situational learning scenario in which the referent of the uttered word is eliminated from the context with probability gamma, thus modeling the noise produced by out-of-context words. We examine the performance of a simple associative learning algorithm and find a critical value of the noise parameter gamma(c) above which learning is impossible. We use finite-size scaling to show that the sharpness of the transition persists across a region of order tau(-1/2) about gamma(c), where tau is the number of learning trials, as well as to obtain the learning error (scaling function) in the critical region. In addition, we show that the distribution of durations of periods when the learning error is zero is a power law with exponent -3/2 at the critical point. Copyright (C) EPLA, 2012

RNA Interference of Endochitinases in the Sugarcane Endophyte Trichoderma virens 223 Reduces Its Fitness as a Biocontrol Agent of Pineapple Disease

The sugarcane root endophyte Trichoderma virens 223 holds enormous potential as a sustainable alternative to chemical pesticides in the control of sugarcane diseases. Its efficacy as a biocontrol agent is thought to be associated with its production of chitinase enzymes, including N-acetyl-beta-D-glucosaminidases, chitobiosidases and endochitinases. We used targeted gene deletion and RNA-dependent gene silencing strategies to disrupt N-acetyl-beta-D-glucosaminidase and endochitinase activities of the fungus, and to determine their roles in the biocontrol of soil-borne plant pathogens. The loss of N-acetyl-beta-D-glucosaminidase activities was dispensable for biocontrol of the plurivorous damping-off pathogens Rhizoctonia solani and Sclerotinia sclerotiorum, and of the sugarcane pathogen Ceratocystis paradoxa, the causal agent of pineapple disease. Similarly, suppression of endochitinase activities had no effect on R. solani and S. sclerotiorum disease control, but had a pronounced effect on the ability of T. virens 223 to control pineapple disease. Our work demonstrates a critical requirement for T. virens 223 endochitinase activity in the biocontrol of C. paradoxa sugarcane disease, but not for general antagonism of other soil pathogens. This may reflect its lifestyle as a sugarcane root endophyte.

High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract Background The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery. Results Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer. Conclusions Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.