1,721,249 research outputs found
I “decostituiti" della "Sapienza”. Santi Romano, Maurizio Maraviglia e Carlo Costamagna
No full textIl contributo analizza le figure dei tre giuspubblicisti dell'Università di Roma "La Sapienza" (Santi Romano, Maurizio Maraviglia e Carlo Costamagna) sottoposti a procedimento di epurazione dopo la cadutra del fascismo
G runs in cystathionine beta-synthase c.833C/c.844_845ins68 mRNA are splicing silencers of pathogenic 3' splice sites.
No full textThe c.844_845ins68 is an evolutionary conserved polymorphism of the cystathionine beta-synthase gene that segregates with the pathogenic c.833C mutation and consists of a 68nt insertion duplicating the 3' splice site between intron 7 and exon 8. The gene rearrangement brought two GGGG runs close to each other and generated a splicing control element that allows the constitutive selection of the more distal 3' splice site in the c.844_854ins68 carriers. In this study, we have characterized functionally the two G4 runs within the duplication and have found that they work as silencers of the upstream potentially pathogenic 3' splice sites has been functionally characterized. This selection allows skipping of both the 68nt-insertion and the c.833C mutation, and is essential to preserve the wild-type ORF. Knocking down hnRNP H and F expression modulated the rescue of the proximal 3' splice site more than hnRNP H alone. These observations suggest that hnRNP H/F contribute jointly to prevention of CBS deficiency in c.844_854ins68 carriers by silencing the potentially pathogenic upstream acceptor site
A new accurate heuristics algorithm to solve the Rank Aggregation problem with a large number of objects
No full textThe analysis of preference rankings has become an important topic in the general field of data analysis in recent years. The classic meaning of preference rankings understood as orders expressed by a series of judges have been joined by the concept of judges is no longer always understood as human beings, but as resulting from automatic evaluation procedures. This paper provides a particle swarm-based optimization algorithm that provides an accurate solution to the rank aggregation problem, namely producing a ranking that best synthesizes the orderings stated by each judge, when the number of items to be evaluated is larg
Tirasemtiv (CK-2017357)
No full textThe identification of new targets for specific and effective therapies poses new challenges for the treatment of several muscle diseases causing weakness (e.g., amyotrophic lateral sclerosis [ALS]). Recent advances have pointed out that sarcomeres may represent potentially useful pharmacological targets. As a result, screening studies for activators of the troponin-tropomyosin complex have resulted in the identification and optimization of a selective fast skeletal troponin activator, tirasemtiv (CK-2017357), which sensitizes fast muscle fibers to calcium. The action of this drug causes an increase in muscle force development at submaximal activation. In vitro and in vivo experiments have further supported the proposed mechanism of action of tirasemtiv. Encouragingly, phase I and phase II trials in ALS patients have shown a favorable safety profile and efficacy in functional improvements of skeletal muscle performance and in reducing fatigability. For this reason, the target enhancement of contractility derived from administration of tirasemtiv may be capitalized upon for the treatment of several variable pathologies, from cardiac and skeletal muscle pathologies to other neuromuscular disorders and claudication
Characterization of the human TARDBP gene promoter
Full text linkThe expression of TDP-43, the main component of neuronal intracellular inclusions across a broad spectrum of ALS and FTD disorders, is developmentally regulated and studies in vivo have shown that TDP-43 overexpression can be toxic, even before observation of pathological aggregates. Starting from these observations, the regulation of its expression at transcriptional level might represent a further key element for the pathogenesis of neurodegenerative diseases. Therefore, we have characterized the human TARDBP promoter, in order to study the transcriptional mechanisms of expression. Mapping of cis-acting elements by luciferase assays in different cell outlined that the activity of the promoter seems to be higher in SH-SY5Y, Neuro2A, and HeLa than in HEK293. In addition, we tested effects of two SNPs found in the promoter region of ALS patients and observed no significant effect on transcription levels in all tested cell lines. Lastly, while TDP-43 overexpression did not affect significantly the activity of its promoter (suggesting that TDP-43 does not influence its own transcription), the presence of the 5'UTR sequence and of intron-1 splicing seem to impact positively on TDP-43 expression without affecting transcript stability. In conclusion, we have identified the region spanning nucleotides 451-230 upstream from the transcription start site as the minimal region with a significant transcription activity. These results lay an important foundation for exploring the regulation of the TARDBP gene transcription by exogenous and endogenous stimuli and the implication of transcriptional mechanisms in the pathogenesis of TDP-43 proteinopathies
Targeting RNA binding proteins involved in neurodegeneration
No full textDysfunctions at the level of RNA processing have recently been shown to play a fundamental role in the pathogenesis of many neurodegenerative diseases. Several proteins responsible for these dysfunctions (TDP-43, FUS/TLS, and hnRNP A/Bs) belong to the nuclear class of heterogeneous ribonucleoproteins (hnRNPs) that predominantly function as general regulators of both coding and noncoding RNA metabolism. The discovery of the importance of these factors in mediating neuronal death has represented a major paradigmatic shift in our understanding of neurodegenerative processes. As a result, these discoveries have also opened the way toward novel biomolecular screening approaches in our search for therapeutic options. One of the major hurdles in this search is represented by the correct identification of the most promising targets to be prioritized. These may include aberrant aggregation processes, protein-protein interactions, RNA-protein interactions, or specific cellular pathways altered by disease. In this review, we discuss these four major options together with their various advantages and drawbacks
Balancing performance and environmental efficiency: a multiclass classification study of textual data
No full textThis study evaluates Multiclass classification (MCC) strategies -- One-Vs-Rest (OVA), One-Vs-One (OVO), Best-of-Best (BOB), and Error-Correcting-Output-Codes (ECOC) -- using classifiers like Naïve Bayes, Random Forest, Linear Discriminant Analysis, Logistic Regression, Neural Networks, Support Vector Machine, and Threshold-based Naïve Bayes on the 20NewsGroup text dataset, well known in literature for its complexity. Findings shows that the choice of classifier significantly affects accuracy and computational effort. Threshold-based Naïve Bayes excels with OVO, OVA, and BOB but declines with ECOC. Artificial Neural Network and Random Forest, which are slowest, align well with BOB and OVA respectively. In contrast, Naïve Bayes and Logistic Regression stand out for speed, particularly with OVA. Along with the Support Vector Machine, these classifiers demonstrate versatility across all strategies, balancing accuracy and training time. Additionally, OVO and BOB prove to be advantageous for handling unbalanced data, by focusing on individual class pairings. OVA emerges as the fastest strategy, while ECOC's performance is classifier-dependent. Our analysis underscores the importance of selecting the appropriate classifier and strategy pairing in MCC tasks, particularly in imbalanced datasets. Importantly, this study underlines the environmental impact of computational choices, advocating for efficient, accurate predictions to minimize energy consumption and optimize machine learning applications' ecological footprint
TDP-43 high throughput screening analyses in neurodegeneration: Advantages and pitfalls
No full textDysfunctions in RNA processing and in particular the aberrant regulation of RNA binding proteins (RBPs) have recently been shown to play a fundamental role in the pathogenesis of neurodegenerative diseases. Understanding the pathogenic mechanisms involved will require the elucidation of the role(s) played by these RBPs in the general cell metabolism and neuronal survival in particular. In the past, the preferred approach has been to determine first of all the functional properties of the factor(s) of interest and then use this knowledge to determine targets in biologically relevant events. More recently, novel experimental approaches such as microarrays, RNA-seq and CLIP-seq have also become very popular to study RBPs. The advantage of these approaches, collectively known as high throughput screening (HTS), is their ability to determine gene expression changes or RNA/protein targets at a global cellular level. In theory, HTS strategies should be ideal for uncovering novel functional roles/targets of any RBP inside the cell. In practice, however, there are still difficulties in getting a coherent picture from all the huge amount of data they generate, frequently not validated experimentally and thus of unknown value. They may even act unfavorably towards a specific increase of knowledge of RBP functions, as the incomplete results are taken as solid data. In this work we will illustrate as an example the use of the HTS methodologies to characterize the interactions of a specific RBP: TDP-43. The multiple functions of this protein in RNA processing and its involvement in the pathogenesis of several forms of amyotrophic lateral sclerosis, frontotemporal lobar degeneration and other neurodegenerative diseases make it an excellent substrate for our analysis of the various advantages and limitations of different HTS experimental approaches
Iterative Threshold-based Naïve Bayes Classifier: an efficient Tb-NB improvement
No full textWhile analyzing online reviews on Booking.com, we proposed an ad-hoc classification model (Threshold-based Naïve Bayes Classifier, Tb-NB) to evaluate Customer Satisfaction, starting from the reviews' content, and predicting them as positive/negative. The log-likelihood ratios attributed to each word included in a review are then used to estimate a numeric sentiment score. In this paper we propose an improved version of Tb-NB called "iterative" Tb-NB. It results in a second step of Tb-NB: starting from the output of Tb-NB and reclassifying reviews with a probabilistic approach, it refines iteratively the threshold value used to classify a given subset of reviews
Splicing of constitutive upstream introns is essential for the recognition of intra-exonic suboptimal splice sites in the thrombopoietin gene
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