130,786 research outputs found
Identification of a putative regulator of early-histone gene expression of Paracentrotus lividus
No full textDrosophila GAGA factor (GAF) is a nuclear protein, conserved along evolution, with multiple roles in gene
regulation, chromatin remodelling, Polycomb-dependent silencing, and insulator functions (1). GAF
recognizes and specifically binds GAGAG consensus DNA motif by its C2H2-type zinc-finger domain, and
interacts with other regulatory factors by its BTB/POZ domain. We have identified plGaga, a cDNA coding
for a putative GAF of the sea urchin P. lividus, which showed significant sequence similarity with
Drosophila and vertebrate GAFs. Real time RT-PCR revealed that the plGaga RNA is always present during
embryo development decreasing rapidly in abundance at the larval pluteus stage. We raised a specific
antibody against the sea urchin GAF and used it in whole-mount immunofluorescence assays, showing that
the protein was distributed predominantly to the nuclei of the whole embryo. By Chromatin
Immunoprecipitation experiments, we showed that the sea urchin GAF not only binds the sns5 insulator,
which is essential for the regulation of the sea urchin early-histone genes (2,3), but also to other GAGA
containing sequences in the early-histone gene cluster.
1 Matharu NK et al. 2010 JMB 400 (3): 434–447
2 Melfi R et Al. 2001 JMB (1); 304:753-63
3 Cavalieri V et al. 2013 Nucleic Acids Res 37: 7407-741
Geografia storica del territorio di Hadrianopolis nella valle del Drino (V sec. a.C. – 44 a.C)
No full textImplementing successful systematic Patient Reported Outcome and Experience Measures (PROMs and PREMs) in robotic oncological surgery—The role of physicians
No full textPatient Reported Outcome and Experience Measures (PROMs and PREMs) play an increasingly important role in monitoring the quality of the oncological pathway. The aim of this study is to describe the case of five hospitals a year after the adoption of PROMs and PREMs for robotic oncological colorectal surgery in Tuscany and to investigate how the clinicians can impact the process of implementation and the efficacy of such measures. We used 14 months of data from the five robotic centers in Tuscany. Above all, the physician's personal motivation to improve the treatment of patients, the teamwork, and the possibility to use data for research purposes proved to be the essential factors for their engagement and the successful implementation of patient reported measures. Physicians play a key role in the adoption of systematic PROMs and PREMs. The higher their level of engagement, the higher the collection success, both in terms of number of patients enrolled and response rates. Moreover, the collection of patient reported measures may become part of physicians' daily practice and may lead to a change in their relationship and communication with patients, as clinicians accept to have their job reviewed and are not afraid to be evaluated by their patients
Alle origini della conquista dell’Italia meridionale: Arduino e l’entrata dei Normanni a Melfi
No full textIl contributo analizza le fonti inerenti l'entrata dei Normanni a Melfi e la relazione esistente tra Impero, Normanni e Regno d'Italia attraverso la figura del milanese Arduino
Enhancing online isolation of intact allergenic proteins from vegetable samples by actively modulated two-dimensional liquid chromatography (2D-LC)
No full text
Optimization of a new lead promoting the readthrough of the nonsense mutations for CFTR rescue in human CF cells
No full textOptimization of a new lead promoting the readthrough of the nonsense mutations for CFTR rescue in human CF cells
Laura Lentini, Raffaella Melfi, Sara Baldassano, Marco Tutone, Aldo Di Leonardo, Andrea Pace, Ivana Pibiri
Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo
Background and rationale
Cystic Fibrosis patients with nonsense mutations in the CFTR gene have a more severe form of the disease. Nonsense mutations represent about 10% of the mutations that affect the CFTR gene and they are frequently associated to the classical F508 mutation (1). A potential treatment for this genetic alteration is to promote the translational readthrough of premature termination codons (PTCs) by Translational Read-Through-Inducing Drugs (TRIDs) (2-4).
Hypothesis and objectives
Our objective is to evaluate the functionality of the CFTR channel after treatment with a new molecule that we individuated in a precedent FFC project, and the activity of new lead molecules in cells stably expressing a nonsense-CFTR-mRNA (ns CFTR) in CF cellular model systems. We want also to study the supramolecular interactions among TRIDs, CFTR mRNA and the ribosomal A-site to identify the biological target and the mechanism of action.
Essential methods
QSAR, carried out on the basis of our preliminary results, will allow to achieve lead optimization and synthesize then a small library of analogs to be tested and compared to the Lead. We will mutagenize the CFTR cDNA by introducing the most diffuse nonsense mutations. Subsequently, FRT cells engineered with the vector expressing mutagenized nsCFTR, and nonsense-CF-human broncoepithelial cells will be grown in the air-liquid culture system to reproduce in vitro the epithelial organization. CFTR expression after treatments with our molecule will be evaluated by biomolecular techniques. CFTR activity will be revealed by specific CFTR-functionality assays. Finally, in vitro-in vivo (Zebrafish model) analyses of the safety profile for the set of synthesized molecules will complete the study.
Preliminary results
We screened the activity of several molecules synthetized by us in a precedent FFC project, identifying some molecules that showed high readthrough activity associated to the expression of the CFTR protein in ns CF immortalized cells.
Expected final results and their significance
We are confident that our findings will provide the validation of molecules with readthrough activity for the recovery of the CFTR function. Moreover, our pre-clinical study will assess the presence of toxic effects caused by the molecules in vivo.
References
1. Sermet-Gaudelus I, Boeck KD, Casimir GJ, Vermeulen F, Leal T, Mogenet A, Roussel D, Fritsch J, Hanssens L, Hirawat S, Miller NL, Constantine S, Reha A, Ajayi T, Elfring GL, Miller LL. Ataluren (PTC124) induces cystic fibrosis transmembrane conductance regulator protein expression and activity in children with nonsense mutation cystic fibrosis., Am J RespirCrit Care Med. 2010 Nov 15;182(10):1262-72.
2. Lentini L, Melfi R, Di Leonardo A, Spinello A, Barone G, Pace A, Palumbo Piccionello A, Pibiri I. Towards a rationale for the PTC124 (Ataluren) promoted read-through of premature stop codons: a computational approach and GFP-reporter cell-based assay. Mol. Pharm. 2014 11, 653-664.
3. Pibiri I, Lentini L, Melfi R, Gallucci G, Pace A, Spinello A, Barone G, Di Leonardo A. Enhancement of premature stop codon readthrough in the CFTR gene by Ataluren (PTC124) derivatives European Journal of Medicinal Chemistry 06/2015; 101.
4. Nagel-Wolfrum K, Möller F, Penner I, Baasov T4, Wolfrum U. Targeting Nonsense Mutations in Diseases with Translational Read-Through-Inducing Drugs (TRIDs), BioDrugs. 2016 Apr;30(2):49-74
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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