627 research outputs found
Research and identfication of new genes and pathogenetic variants involved in Intellectual Disability
No full textIntellectual Disability (ID) is one of the most common neurodevelopmental disorders, affecting between 1.5-2% of individuals in the general population. This pathology has a serious impact on the affected individuals, their families and also on the health care system. Understanding the genetic mechanisms implicated in the disease is challenging, since ID includes a wide spectrum of possible underlying disorders and the genetic variants determining the disease are highly heterogeneous, requiring the application of different approaches and techniques, from cytogenetic analysis to the application of most recent NGS strategies. In the last decades, big steps forward have been done in the search of the genetics determinants for ID, however today less then half of the patients receive a molecular diagnosis. Moreover, the continue reporting of new ID-genes suggests that many of the genetic variants causing ID still need to be discovered and understood. The aim of the thesis is to identify new genes and genetic variants involved in ID, with the use of diverse approaches and methodologies.
The first stage of the study has been the screening of a cohort of nonsyndromic ID patients with a gene-panel specific for non-syndromic ID. This approach has led to the discover of 6 novel putative mutations and, when possible, the impact of the variation has been evaluated in silico, with an analysis of the protein structure. The screening also led to the selection of two patients that underwent to whole-exome sequencing analysis with the aim to identify the causative variant beyond the most common genes for the disease. Notably, we have discovered 2 X-linked mutations having likely a pathogenetic role. One is a missense mutation in CLCN4, a gene member of the chloride channel family that only recently has been demonstrated to cause ID. Another missense mutation has been found in ALG13 gene that has been associated with X-linked non-syndromic ID only once but without a clear explanation of its functioning.
The second part of the thesis concerns the investigation on genetic variants having a mild impact on the phenotype. We performed a Runs of Homozygosity study to investigate the role of distant inbreeding in ID. The analysis has revealed that the global amount of homozygosity and the number of homozygous stretches are associated with the degree of the impairment. Finally, we also designed an association study for the Y chromosome to investigate the presence of variants implicated in the development of cognitive function in this genomic region. We analysed the general cognitive function measured in 5 cross-sectional cohorts but did not find evidence for an association on the Y chromosome
Can we predict firms’ innovativeness? The identification of innovation performers in an Italian region through a supervised learning approach
No full textThe study shows the feasibility of predicting firms’ expenditures in innovation, as reported in the Community Innovation Survey, applying a supervised machine-learning approach on a sample of Italian firms. Using an integrated dataset of administrative records and balance sheet data, designed to include all informative variables related to innovation but also easily accessible for most of the cohort, random forest algorithm is implemented to obtain a classification model aimed to identify firms that are potential innovation performers. The performance of the classifier, estimated in terms of AUC, is 0.794. Although innovation investments do not always result in patenting, the model is able to identify 71.92% of firms with patents. More encouraging results emerge from the analysis of the inner working of the model: predictors identified as most important—such as firm size, sector belonging and investment in intangible assets—confirm previous findings of literature, but in a completely different framework. The outcomes of this study are considered relevant for both economic analysts, because it demonstrates the potential of data-driven models for understanding the nature of innovation behaviour, and practitioners, such as policymakers or venture capitalists, who can benefit by evidence-based tools in the decision-making process
Rezension zu: Ilaria Bignamini/Clare Hornsby, Digging and Dealing in Eighteenth-Century Rome. With additional research by Irma Della Giovampaola and Jonathan Yarker (New Haven and London 2010)
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Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit
No full textInterpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for Long Short-Term Memory (LSTM) neural network that provides a useful picture on the influence of the several input variables included in the model.
A cohort of 10,616 patients with cardiovascular diseases is selected from the MIMIC III dataset, an openly available database of electronic health records (EHRs) including all patients admitted to an ICU at Boston’s Medical Centre. For each patient, we consider a 10-length sequence of 1-hour windows in which 48 clinical parameters are extracted to predict the occurrence of death in the next 7 days. Inspired from the recent developments in the field of attention mechanisms for sequential data, we implement a recurrent neural network with LSTM cells incorporating an attention mechanism to identify features driving model’s decisions over time.
The performance of the LSTM model, measured in terms of AUC, is 0.790 (SD = 0.015). Regard our primary objective, i.e. model interpretability, we investigate the role of attention weights. We find good correspondence with driving predictors of a transparent model (r = 0.611, 95% CI [0.395, 0.763]). Moreover, most influential features identified at the cohort-level emerge as known risk factors in the clinical context.
Despite the limitations of study dataset, this work brings further evidence of the potential of attention mechanisms in making deep learning model more interpretable and suggests the application of this strategy for the sequential analysis of EHRs
Ygen : The first systematic assessment of the influence of human Y chromosome variation on a wide range of health-related traits
No full textHomozygosity caused by consanguineous union has long been associated with an increased prevalence of rare Mendelian disorders. In contrast, the role of homozygosity in relation to quantitative traits and complex disease suscep- tibility is less well established. Recent work has shown that an increased bur- den of homozygous DNA segments (defined as the fraction of each genome in any Run of Homozygosity > 1.5 Mb, or FROH) is associated with reduced height and cognitive ability in diverse human populations. Here, we assess the scope of inbreeding depression in humans by analysing the effect of FROH on 41 quantitative traits of public health and evolutionary interest, in >500,000 individuals from >100 cohorts worldwide. Phenotypes studied include anthro- pometry, lipids, liver, lung and kidney function, cognition, glycaemia, fertility, inflammation, electrocardiography and haematology. We confirm the findings of previous work, and also show that increased FROH is associated with reduced values of several components of evolutionary fitness. The constancy of these effects across different levels of homozygosity and across diverse populations in which social confounding more plausibly engenders the opposite effect, strengthens the argument that FROH has a causal effect. In addition, we inves- tigate the magnitude of inbreeding depression between men and women to ex- plore whether sex-specific dominance may provide a mechanism, independent of the sex-chromosomes, by which males and females might adapt to different selective pressures. We investigate the mechanism of inbreeding depression by exploring different measures of homozygosity. Long homozygous segments arise from recent common ancestry and bring all variants, including rare causal variants, into a homozygous state. In contrast, shorter homozygous segments may arise from more ancient common ancestry and thus capture only the dominance effects of more common variants. Using multivariate linear models we show that FROH is more predictive of inbreeding depression than traditional estimates of inbreeding coefficient based on individual SNP homozygosity
Data of cost-optimal solutions and retrofit design methods for school renovation in a warm climate
No full textAbstract"Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings" (Paolo Maria Congedo, Delia D’Agostino, Cristina Baglivo, Giuliano Tornese, Ilaria Zacà) [1] is the paper that refers to this article. It reports the data related to the establishment of several variants of energy efficient retrofit measures selected for two existing school buildings located in the Mediterranean area. In compliance with the cost-optimal analysis described in the Energy Performance of Buildings Directive and its guidelines (EU, Directive, EU 244,) [2,3], these data are useful for the integration of renewable energy sources and high performance technical systems for school renovation. The data of cost-efficient high performance solutions are provided in tables that are explained within the following sections.The data focus on the describe school refurbishment sector to which European policies and investments are directed. A methodological approach already used in previous studies about new buildings is followed (Baglivo Cristina, Congedo Paolo Maria, D׳Agostino Delia, Zacà Ilaria, 2015; IlariaZacà, Delia D’Agostino, Paolo Maria Congedo, Cristina Baglivo; Baglivo Cristina, Congedo Paolo Maria, D’Agostino Delia, Zacà Ilaria, 2015; Ilaria Zacà, Delia D’Agostino, Paolo Maria Congedo, Cristina Baglivo, 2015; Paolo Maria Congedo, Cristina Baglivo, IlariaZacà, Delia D’Agostino,2015) [4–8]. The files give the cost-optimal solutions for a kindergarten (REF1) and a nursery (REF2) school located in Sanarica and Squinzano (province of Lecce Southern Italy). The two reference buildings differ for construction period, materials and systems.The eleven tables provided contain data about the localization of the buildings, geometrical features and thermal properties of the envelope, as well as the energy efficiency measures related to walls, windows, heating, cooling, dhw and renewables. Output values of energy consumption, gas emission and costs are given for a financial and a macro-economic analysis.This data article provides 288 and 96 combinations for REF1 and REF2, respectively. The output values are obtained using the software ProCasaClima 2015v.2.0
Author Correction: Gluten consumption and inflammation affect the development of celiac disease in at-risk children
No full textThe original version of this Article contained an error in the spelling of the authors Renata Auricchio, Ilaria Calabrese, Martina Galatola, Donatella Cielo, Fortunata Carbone, Marianna Mancuso, Giuseppe Matarese, Riccardo Troncone, Salvatore Auricchio & Luigi Greco which were incorrectly given as Auricchio Renata, Calabrese Ilaria, Galatola Martina, Cielo Donatella, Carbone Fortunata, Mancuso Marianna, Matarese Giuseppe, Troncone Riccardo, Auricchio Salvatore & Greco Luigi. The original article has been corrected
microRNAs combined to radiomic features as a predictor of complete clinical response after neoadjuvant radio-chemotherapy for locally advanced rectal cancer: a preliminary study
No full textObjective: To define a predictive Artificial Intelligence (AI) algorithm based on the integration of a set of biopsy-based microRNAs expression data and radiomic features to understand their potential impact in predicting clinical response (CR) to neoadjuvant radio-chemotherapy (nRCT). The identification of patients who would truly benefit from nRCT for Locally Advanced Rectal Cancer (LARC) could be crucial for an improvement in a tailored therapy. Methods: Forty patients with LARC were retrospectively analyzed. An MRI of the pelvis before and after nRCT was performed. In the diagnostic biopsy, the expression levels of 7 miRNAs were measured and correlated with the tumor response rate (TRG), assessed on the surgical sample. The accuracy of complete CR (cCR) prediction was compared for i) clinical predictors; ii) radiomic features; iii) miRNAs levels; and iv) combination of radiomics and miRNAs. Results: Clinical predictors showed the lowest accuracy. The best performing model was based on the integration of radiomic features with miR-145 expression level (AUC-ROC = 0.90). AI algorithm, based on radiomics features and the overexpression of miR-145, showed an association with the TRG class and demonstrated a significant impact on the outcome. Conclusion: The pre-treatment identification of responders/NON-responders to nRCT could address patients to a personalized strategy, such as total neoadjuvant therapy (TNT) for responders and upfront surgery for non-responders. The combination of radiomic features and miRNAs expression data from images and biopsy obtained through standard of care has the potential to accelerate the discovery of a noninvasive multimodal approach to predict the cCR after nRCT for LARC
Pt(II) and Pt(IV) Complexes with a Major Component of Royal Jelly as Innovative Antitumor Drug Candidates.
No full textPlatinum-based drugs, such as cisplatin, are clinically used for the treatment of many solid tumors with great success; however, outcomes are limited by the toxicity and resistance of some tumors. Recently, the interest towards the use of natural products as anti-cancer drugs has grown worldwide since they are easily available and relatively safe. In particular, the main and distinctive fatty acid in royal jelly, trans-10-hydroxy-2-decenoic acid (10-HDA), has been demonstrated to have anti-tumor, immunomodulatory, collagen promoting, and antimelanogenesis properties. Thus, in this study, we aimed to combine the 10-HDA functionality with a platinum moiety. The first compounds that we isolated were: [Pt(O-10-HDA)(2)(1R,2R-DACH)] (1; DACH = diaminocyclohexane), which can be considered a multifunctional prodrug analog of oxaliplatin in which the oxalate has been substituted with two carboxylate-bonded 10-HDA ligands, and the organometallic complex [Pt(O,C-10-HDA)(1R,2R-DACH)] (2) in which a single 10-HDA ligand coordinates to Pt through both a carboxylate oxygen and the deprotonated C(3) vinylic carbon. Cyclometalated complexes with a s (Pt-C) bond have also proven to be endowed with relevant anticancer activity. Our investigation has also been extended to the Pt(iv) derivatives of 2, trans-[Pt(OH)(2)(O,C-10-HDA)(1R,2R-DACH)] and trans-[Pt(BzO)(2)(O,C-10-BzODA)(1R,2R-DACH)] (10-BzODA = benzoate in place of the hydroxyl group in 10-HDA), having in the axial position either two hydroxido or two benzoato ligands (3 and 4, respectively). For comparison, analogues of compounds 2, 3, and 4 having ethylenediamine in place of diaminocyclohexane as the carrier ligand (compounds 2a, 3a, and 4a, respectively) were also synthesized. All compounds were fully characterized by elemental analysis, ESI-MS, and NMR spectroscopy. The mechanism of formation of complexes 1 and 2 was also investigated by solution NMR. Finally, as a preliminary investigation, the in vitro cytotoxicity of the new Pt(ii) and Pt(iv) compounds was tested against a panel of human tumor cell lines. Interestingly, the Pt(iv) benzoate derivatives 4 and 4a showed discrete activity against most of the tested tumor cell lines while the metallate complex 2 was found to be more active than cisplatin and oxaliplatin only against the pancreatic tumor cell line PSN-1
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