134 research outputs found

    Adrenal incidentaloma: a case of carcinoma

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    Adrenal incidentaloma (AI) is a term applied to an accidentally discovered adrenal mass on imaging performed for reasons unrelated to adrenal pathology. The widespread application of abdominal imaging procedure has resulted in an increased frequency of clinically silent adrenal masses. Although most AIs are nonfunctioning benign adenomas, a multidisciplinary approach with biochemical and radiological evaluation is needed to characterize these lesions and identify patients who are at high risk for hormonal or malignant evolution. Herein, we describe a case of a 69-year-old man with a pain at the base of right chest. On the basis of clinical evaluation, biochemical analysis, as well as imaging procedures, a diagnosis of right adrenocortical carcinoma was made. The patient underwent medical treatment

    Inducible SMARCAL1 knockdown in iPSC reveals a link between replication stress and altered expression of master differentiation genes

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    The Schimke immuno-osseous dysplasia is an autosomal recessive genetic osteochondrodysplasia characterized by dysmorphism, spondyloepiphyseal dysplasia, nephrotic syndrome and frequently T cell immunodeficiency. Several hypotheses have been proposed to explain pathophysiology of the disease, however, the mechanism by which SMARCAL1 mutations cause the syndrome is elusive. Here, we generated a conditional SMARCAL1 knockdown model in iPSCs to mimic conditions associated with the severe form the disease. Using multiple cellular endpoints, we characterized this model for the presence of phenotypes linked to the replication caretaker role of SMARCAL1. Our data show that conditional knockdown of SMARCAL1 in human iPSCs induces replication-dependent and chronic accumulation of DNA damage triggering the DNA damage response. Furthermore, they indicate that accumulation of DNA damage and activation of the DNA damage response correlates with increased levels of R-loops and replication-transcription interference. Finally, we provide evidence that SMARCAL1-deficient iPSCs maintain DNA damage response active beyond differentiation, possibly contributing to the observed altered expression of a subset of germ layer-specific master genes. Confirming the relevance of SMARCAL1 loss for the observed phenotypes, they are prevented or rescued after re-expression of wild-type SMARCAL1 in our iPSC model. In conclusion, our conditional SMARCAL1 knockdown model in iPSCs may represent a powerful model where studying pathogenetic mechanisms of severe Schimke immuno-osseous dysplasia

    Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities

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    Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented

    Role of vanadium and pyridine in heteropolycompounds for selective oxidation of alcohols with hydrogen peroxide

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    This study describes the application of heteropolyacids H3PMo12O40,H4SiMo12O40, H4PMo11VO40, H5PMo10V2O40, H9PMo6V6O40, and a hybrid pyridine-modified heteropolyacid with Keggin structure for selective oxidation of alcohols to ketones or aldehydes using aqueous hydrogen peroxide and acetonitrile as solvent. Performance of these different catalysts in 1-phenylethanol oxidation was studied. Influence of reaction temperature, amount of catalyst and hydrogen peroxide and reaction time on the yield of acetophenone was investigated to obtain optimal reaction conditions. Oxidation ability of the catalyst depended on the number of vanadium atoms present in the Keggin ion and to a lesser extent on pyridine substitution in the Keggin secondary structure. In order to explore the applicability of the method for selective oxidation of alcohols to ketones or aldehydes, various alcohols were investigated according to the general procedure using hybrid pyridine-modified heteropolyac

    Role of vanadium and pyridine in heteropolycompounds for selective oxidation of alcohols with hydrogen peroxide

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    This study describes the application of heteropolyacids H₃PMo₁₂O₄₀, H₄SiMo₁₂O₄₀, H₄PMo₁₁VO₄₀, H₅PMo₁₀V₂O₄₀, H₉PMo₆V₆O₄₀, and a hybrid pyridine-modified heteropolyacid with Keggin structure for selective oxidation of alcohols to ketones or aldehydes using aqueous hydrogen peroxide and acetonitrile as solvent. Performance of these different catalysts in 1-phenylethanol oxidation was studied. Influence of reaction temperature, amount of catalyst and hydrogen peroxide and reaction time on the yield of acetophenone was investigated to obtain optimal reaction conditions. Oxidation ability of the catalyst depended on the number of vanadium atoms present in the Keggin ion and to a lesser extent on pyridine substitution in the Keggin secondary structure. In order to explore the applicability of the method for selective oxidation of alcohols to ketones or aldehydes, various alcohols were investigated according to the general procedure using hybrid pyridine-modified heteropolyacid.Centro de Investigación y Desarrollo en Ciencias Aplicada

    Chronotropic Incompentence and Functional Capacity in CHF

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    SUMMARY Aim: To assess the effect of chronotropic incompetence on functional capacity in chronic heart failure (CHF) patients, as evaluated as NYHA and peak oxygen consumption (pVO2), focusing on the presence and dose of β-blocker treatment. Methods: Nine hundred and sixty-seven consecutive CHF patients were evaluated, 328 of whom were discarded because they failed to meet the study criteria. Of the 639 analyzed, 90 were not treated with β-blockers whereas the other 549 were. The latter were further subdivided in high (n = 184) and low (n = 365) β-blockers daily dose group in accordance with an arbitrary cut-off of 25 mg for carvedilol and of 5 mg for bisoprolol. Failure to achieve 80% of the percentage of maximum age predicted peak heart rate (%Max PHR) or of HR reserve (%HRR) constituted chronotropic incompetence. Results: No differences were found in NYHA or pVO2 between patients with and without β-blockers and, similarly, between high and low β-blocker dose groups. Twenty and sixty-nine percent of not β-blocked patients showed chronotropic incompetence according to %Max PHR and %HRR, respectively, whereas this prevalence rose to 61% and 84% in those on β-blocker therapy. Patients taking β-blockers without chronotropic incompetence, as inferable from both %Max PHR and %HRR, showed higher NYHA and pVO2 regardless of drug dose, whereas, in not β-blocked patients, only %HRR revealed a difference in functional capacity. At multivariable analysis, HR increase during exercise (ΔHR) was the variable most strongly associated to pVO2 (β: 0.572; SE: 0.008; P < 0.0001) and NYHA class (β: −0.499; SE: 0.001; P < 0.0001). Conclusions: ΔHR is a powerful predictor of CHF severity regardless of the presence of β-blocker therapy and of β-blocker daily dose

    Validity of machine learning in predicting giant cell arteritis flare after glucocorticoids tapering

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    BackgroundInferential statistical methods failed in identifying reliable biomarkers and risk factors for relapsing giant cell arteritis (GCA) after glucocorticoids (GCs) tapering. A ML approach allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome. ObjectiveThe objective of the study was to assess whether ML algorithms can predict GCA relapse after GCs tapering. MethodsGCA patients who underwent GCs therapy and regular follow-up visits for at least 12 months, were retrospectively analyzed and used for implementing 3 ML algorithms, namely, Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The outcome of interest was disease relapse within 3 months during GCs tapering. After a ML variable selection method, based on a XGBoost wrapper, an attribute core set was used to train and test each algorithm using 5-fold cross-validation. The performance of each algorithm in both phases was assessed in terms of accuracy and area under receiver operating characteristic curve (AUROC). ResultsThe dataset consisted of 107 GCA patients (73 women, 68.2%) with mean age ( +/- SD) 74.1 ( +/- 8.5) years at presentation. GCA flare occurred in 40/107 patients (37.4%) within 3 months after GCs tapering. As a result of ML wrapper, the attribute core set with the least number of variables used for algorithm training included presence/absence of diabetes mellitus and concomitant polymyalgia rheumatica as well as erythrocyte sedimentation rate level at GCs baseline. RF showed the best performance, being significantly superior to other algorithms in accuracy (RF 71.4% vs LR 70.4% vs DT 62.9%). Consistently, RF precision (72.1%) was significantly greater than those of LR (62.6%) and DT (50.8%). Conversely, LR was superior to RF and DT in recall (RF 60% vs LR 62.5% vs DT 47.5%). Moreover, RF AUROC (0.76) was more significant compared to LR (0.73) and DT (0.65). ConclusionsRF algorithm can predict GCA relapse after GCs tapering with sufficient accuracy. To date, this is one of the most accurate predictive modelings for such outcome. This ML method represents a reproducible tool, capable of supporting clinicians in GCA patient management

    Mediterranean diet impact on cardiovascular diseases: a narrative review

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    : Cardiovascular disease (CVD) accounts for more than 17 million deaths per year worldwide. It has been estimated that the influence of lifestyle on CVD mortality amounts to 13.7% for smoking, 13.2% for poor diet, and 12% for inactive lifestyle. These results deeply impact both the healthy status of individuals and their skills in working. The impact of CVD on productivity loss accounts for the 24% in total costs for CVD management.Mediterranean diet (MedD) can positively impact on natural history of CVD. It is characterized by a relatively high consumption of inexpensive and genuine food such as cereals, vegetables, legumes, nuts, fish, fresh fruits, and olive oil as the principal source of fat, low meat consumption and low-to-moderate consumption of milk, dairy products, and wine.Its effects on cardiovascular health are related to the significant improvements in arterial stiffness. Peripheral artery disease, coronary artery disease, and chronic heart failure are all positively influenced by the MedD. Furthermore, MedD lowers the risk of sudden cardiac death due to arrhythmias.The present narrative review aims to analyze the effects of MedD on CVD

    Wastewater-based epidemiology for early warning of SARS-COV-2 circulation: A pilot study conducted in Sicily, Italy

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    There is increasing evidence of the use of wastewater-based epidemiology to integrate conventional monitoring assessing disease symptoms and signs of viruses in a specific territory. We present the results of SARS-CoV-2 environmental surveillance activity in wastewater samples collected between September 2020 and July 2021 in 9 wastewater treatment plants (WTPs) located in central and western Sicily, serving over 570,000 residents. The presence of SARS-CoV-2, determined in 206 wastewater samples using RT-qPCR assays, was correlated with the notified and geo-referenced cases on the areas served by the WTPs in the same study period. Overall, 51% of wastewater samples were positive. Samples were correlated with 33,807 SARS-CoV-2 cases, reported in 4 epidemic waves, with a cumulative prevalence of 5.9% among Sicilian residents. The results suggest that the daily prevalence of SARS-CoV-2 active cases was statistically significant and higher in areas with SARS-CoV-2 positive wastewater samples. According to these findings, the proposed method achieves a good sensitivity profile (78.3%) in areas with moderate or high viral circulation (≥133 cases/100,000 residents) and may represent a useful tool in the management of epidemics based on an environmental approach, although it is necessary to improve the accuracy of the process

    Mediterranean monitoring and forecasting operational system for Copernicus Marine Service

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    The MEDiterranean Monitoring and Forecasting Center (Med-MFC) is part of the Copernicus Marine Environment Monitoring Service (CMEMS, http://marine.copernicus.eu/), provided on an operational mode by Mercator Ocean in agreement with the European Commission. Specifically, Med MFC system provides regular and systematic information about the physical state of the ocean and marine ecosystems for the Mediterranean Sea. The Med-MFC service started in May 2015 from the pre-operational system developed during the MyOcean projects, consolidating the understanding of regional Mediterranean Sea dynamics, from currents to biogeochemistry to waves, interfacing with local data collection networks and guaranteeing an efficient link with other Centers in Copernicus network. The Med-MFC products include analyses, 10 days forecasts and reanalysis, describing currents, temperature, salinity, sea level and pelagic biogeochemistry. Waves products will be available in MED-MFC version in 2017. The consortium, composed of INGV (Italy), HCMR (Greece) and OGS (Italy) and coordinated by the Euro-Mediterranean Centre on Climate Change (CMCC, Italy), performs advanced R&D activities and manages the service delivery. The Med-MFC infrastructure consists of 3 Production Units (PU), for Physics, Biogechemistry and Waves, a unique Dissemination Unit (DU) and Archiving Unit (AU) and Backup Units (BU) for all principal components, guaranteeing a resilient configuration of the service and providing and efficient and robust solution for the maintenance of the service and delivery. The Med-MFC includes also an evolution plan, both in terms of research and operational activities, oriented to increase the spatial resolution of products, to start wave products dissemination, to increase temporal extent of the reanalysis products and improving ocean physical modeling for delivering new products. The scientific activities carried out in 2015 concerned some improvements in the physical, biogeochemical and wave components of the system. Regarding the currents, new grid-point EOFs have been implemented in the Med-MFC assimilation system; the climatological CMAP precipitation was replaced by the ECMWF daily precipitation; reanalysis time-series have been increased by one year. Regarding the biogeochemistry, the main scientific achievement is related to the implementation of the carbon system in the Med-MFC biogeochemistry model system already available. The new model is able to reproduce the principal spatial patterns of the carbonate system variables in the Mediterranean Sea. Further, a key result consists of the calibration of the new variables (DIC and alkalinity), which serves to the estimation of the accuracy of the new products to be released in the next version of the system (i.e. pH and pCO2 at surface). Regarding the waves, the system has been validated against in-situ and satellite observations. For example, a very good agreement between model output and in-situ observations has been obtained at offshore and/or well-exposed wave buoys in the Mediterranean Sea.PublishedVienna3SR. AMBIENTE - Servizi e ricerca per la Societ
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