494 research outputs found

    Climate change assessment for Mediterranean agricultural areas by statistical downscaling

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    In this paper we produce projections of seasonal precipitation for four Mediterranean areas: Apulia region (Italy), Ebro river basin (Spain), Po valley (Italy) and Antalya province (Turkey). We performed the statistical downscaling using Canonical Correlation Analysis (CCA) in two versions: in one case Principal Component Analysis (PCA) filter is applied only to predictor and in the other to both predictor and predictand. After performing a validation test, CCA after PCA filter on both predictor and predictand has been chosen. Sea level pressure (SLP) is used as predictor. Downscaling has been carried out for the scenarios A2 and B2 on the basis of three GCM's: the CCCma-GCM2, the Csiro-MK2 and HadCM3. Three consecutive 30-year periods have been considered. For Summer precipitation in Apulia region we also use the 500 hPa temperature (T500) as predictor, obtaining comparable results. Results show different climate change signals in the four areas and confirm the need of an analysis that is capable of resolving internal differences within the Mediterranean region. The most robust signal is the reduction of Summer precipitation in the Ebro river basin. Other significative results are the increase of precipitation over Apulia in Summer, the reduction over the Po-valley in Spring and Autumn and the increase over the Antalya province in Summer and Autumn

    A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). 1. Model description

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    A simple simulation model for growth of grapevine (Vitis vinifera L. cv. Sangiovese) is presented which mainly bases on analytical results from field experiments with plants free of visible stress and diseases. In the model leaf area development is defined as a function of temperature, biomass accumulation as a function of intercepted radiation and fruit growth is calculated from a linear increase of the fruit biomass index with time. The assumptions are discussed and comparisons between simulated and measured results are shown

    A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). 2. Model validation

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    A simple model for the simulation of growth and development of Sangiovese vines has been presented in a previous paper. In this paper the model is validated to examine whether the description of the physiological relationships in the model describe the growth of grapevine (cv. Sangiovese) realistically. Furthermore, the model was adapted and validated for the simulation of growth of another cultivar (cv. Cabernet Sauvignon). Comparisons of simulated and experimental data for both cultivars reveal that the model made good predictions of vine growth for the whole growing season

    The regulatory G4 motif of the Kirsten ras (KRAS) gene is sensitive to guanine oxidation: Implications on transcription

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    KRAS is one of the most mutated genes in human cancer. It is controlled by a G4 motif located upstream of the transcription start site. In this paper, we demonstrate that 8-oxoguanine (8-oxoG), being more abundant in G4 than in non-G4 regions, is a new player in the regulation of this oncogene. We designed oligonucleotides mimicking the KRAS G4-motif and found that 8-oxoG impacts folding and stability of the G-quadruplex. Dimethylsulphate-footprinting showed that the G-run carrying 8-oxoG is excluded from the G-tetrads and replaced by a redundant G-run in the KRAS G4-motif. Chromatin immunoprecipitation revealed that the base-excision repair protein OGG1 is recruited to the KRAS promoter when the level of 8-oxoG in the G4 region is raised by H2O2. Polyacrylamide gel electrophoresis evidenced that OGG1 removes 8-oxoG from the G4-motif in duplex, but when folded it binds to the G-quadruplex in a non-productive way. We also found that 8-oxoG enhances the recruitment to the KRAS promoter of MAZ and hnRNP A1, two nuclear factors essential for transcription. All this suggests that 8-oxoG in the promoter G4 region could have an epigenetic potential for the control of gene expression

    High-level multiplexing in digital PCR with intercalating dyes by coupling real-time kinetics and melting curve analysis.

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    Digital polymerase chain reaction (dPCR) is a mature technique that has enabled scientific breakthroughs in several fields. However, this technology is primarily used in research environments with high-level multiplexing representing a major challenge. Here, we propose a novel method for multiplexing, referred to as amplification and melting curve analysis (AMCA), which leverages the kinetic information in real-time amplification data and the thermodynamic melting profile using an affordable intercalating dye (EvaGreen). The method trains a system comprised of supervised machine learning models for accurate classification, by virtue of the large volume of data from dPCR platforms. As a case study, we develop a new 9-plex assay to detect mobilised colistin resistant (mcr) genes as clinically relevant targets for antimicrobial resistance. Over 100,000 amplification events have been analysed, and for the positive reactions, the AMCA approach reports a classification accuracy of 99.33 ± 0.13%, an increase of 10.0% over using melting curve analysis. This work provides an affordable method of high-level multiplexing without fluorescent probes, extending the benefits of dPCR in research and clinical settings

    Radiogenomics in clear cell renal cell carcinoma: correlations between advanced CT imaging (texture analysis) and microRNAs expression

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    Purpose: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs. Methods: In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort. Results: In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management. Conclusion: In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found

    Are non-coding rnas useful biomarkers in parathyroid tumorigenesis?

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    Tumors of the parathyroid glands are common endocrine diseases almost always characterized by parathyroid hormone hypersecretion that determines the clinical manifestations of primary hyperparathyroidism, such as fatigue, kidney problems, weakness, brittle bones, and other symptoms. Most parathyroid neoplasia are benign adenomas, although rare malignant forms have been described. They are heterogeneous in terms of clinical presentation and the associated signs and symptoms overlap with those of disease and aging. Furthermore, most patients with hypercalcemia are discovered during routine blood tests for other reasons. Surgical removal is considered the main therapeutic option to cure these endocrine tumors and, therefore, innovative therapeutic approaches are actively required. Recently, a growing number of studies have suggested that alterations to the epigenetic mechanisms could play a pivotal role in parathyroid tumorigenesis. Most of the attention has been focused on non-coding RNAs (ncRNAs) (i.e., miRNAs, lncRNAs, and circRNAs) whose expression profile has been found to be deregulated in parathyroid tumors. The aim of the present paper is to give an insight into the ncRNAs involved in parathyroid tumorigenesis, which could be used in the future either as innovative diagnostic biomarkers or as therapeutic targets for the treatment of this endocrine neoplasia

    MicroRNAs as potential biomarkers in pituitary adenomas

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    Pituitary adenomas (PAs) are one of the most common lesions of intracranial neoplasms, occurring in approximately 15% of the general population. They are typically benign, although some adenomas show aggressive behavior, exhibiting rapid growth, drug resistance, and invasion of surrounding tissues. Despite ongoing improvements in diagnostic and therapeutic strategies, late first diagnosis is common, and patients with PAs are prone to relapse. Therefore, earlier diagnosis and prevention of recurrence are of importance to improve patient care. MicroRNAs (miRNAs) are short non-coding single stranded RNAs that regulate gene expression at the post-transcriptional level. An increasing number of studies indicate that a deregulation of their expression patterns is related with pituitary tumorigenesis, suggesting that these small molecules could play a critical role in contributing to tumorigenesis and the onset of these tumors by acting either as oncosuppressors or as oncogenes, depending on the biological context. This paper provides an overview of miRNAs involved in PA tumorigenesis, which might serve as novel potential diagnostic and prognostic non-invasive biomarkers, and for the future development of miRNA-based therapeutic strategies for PAs
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