917 research outputs found

    Comparative adsorption of tetracycline onto unmodified and NaOH-modified silicomanganese fumes: kinetic and process modeling

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    Silicomanganese fumes (SMF) are industrial waste and a potential low-cost adsorbent for the removal of contaminants from water. In this study, the adsorption performance of SMF and NaOH-modified SMF (SMF-Na) for the removal of tetracycline (TC) from an aqueous solution was investigated. The characterization results showed the presence of functional groups (SiO2, -OH and C-O-C), a considerably higher surface area of the SMF-Na (142.59 m2 g−1) compared to the SMF (7.73 m2 g−1). The TC adsorption was favored under acidic conditions (pH 2–3) and increased with an increasing amount of adsorbent. The adsorption equilibrium was achieved in 360 min, and the presence of Na+ ions insignificantly influenced the TC adsorption. The Avrami model fitted better to the kinetic data with R2 = 0.995. The isothermal data was well represented by the Redlich-Peterson and Langmuir model. The maximum monolayer adsorption capacity of SMF and SMF-Na was 117 and 129 mg g−1, respectively. The thermodynamic results confirmed that the TC adsorption was endothermic and predominantly governed by physical forces. The removal of TC onto SMF and SMF-Na was maintained above 90 % even after five regeneration cycles The results suggested that SMF-Na is a promising alternative adsorbent for the removal of tetracycline antibiotics from wastewater streams

    Cardiovascular Side Effects of Anthracyclines and HER2 Inhibitors among Patients with Breast Cancer: A Multidisciplinary Stepwise Approach for Prevention, Early Detection, and Treatment

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    : Cardiovascular (CV) diseases (CVD) are a major cause of long-term morbidity and mortality affecting life expectancy amongst cancer survivors. In recent years, because of the possibility of early diagnosis and the increased efficacy of neo-adjuvant and adjuvant systemic treatments (targeting specific molecular pathways), the high percentage of survival from breast cancer led CVD to become the first cause of death among survivors. Therefore, it is mandatory to adopt cardioprotective strategies to minimize CV side effects and CVD in general in breast cancer patients. Cancer therapeutics-related cardiac dysfunction (CTRCD) is a common group of side effects of chemotherapeutics widely employed in breast cancer (e.g., anthracycline and human epidermal growth factor receptor 2 inhibitors). The aim of the present manuscript is to propose a pragmatic multidisciplinary stepwise approach for prevention, early detection, and treatment of cardiotoxicity in patients with breast cancer

    Improved calorimetric particle identification in NA62 using machine learning techniques

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    International audienceMeasurement of the ultra-rare K+π+νν {K}^{+}\to {\pi}^{+}\nu \overline{\nu} decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2 × 105^{−5} for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 105^{−5}

    Electrospun hybrid TiO<inf>2</inf>/humic substance PHBV films for active food packaging applications

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    Sustainable packaging materials can play a key role in minimizing the environmental footprint of packaged food by preserving its quality and avoiding environmental persistence of plastic waste. Waste to wealth approach can cope with these major challenges by providing for bioavailable active compounds from waste residues. To this regard, humic substances (HS), derived from biowaste oxidative processes, exhibit intrinsic antioxidant and antimicrobial features, which can be significantly boosted by molecular combination with an inorganic nanostructured phase. Herein, this approach has been integrated with the electrospinning technology to design composite films made of electrospun biodegradable and bioderived polymers filled with nanostructured hybrid HS based materials. Therefore, electrospun composites made by including hybrid TiO2_HS nanostructures into PHBV matrix were first produced and then converted into homogeneous and continuous films to obtain an active layer which will be part of a multilayer food packaging solution. These were characterized in terms of morphology, thermal, crystallinity, optical, mechanical and barrier properties as well as antimicrobial performance against Staphylococcus aureus and Escherichia coli, two main strains of food pathogens. The results suggested that the combination of hybrid nanomaterials with electrospinning methodology is a promising and sustainable approach to convert biowaste into multifunctional materials for active packaging.The authors thank the Verde Vita company (s.r.l.) for providing the compost from which the humic substance HS used in this work was extracted. The authors wish to thank the European Union POC Ricerca e Innovazione 2014–2020, Azione I.1 “Dottorati Innovativi con caratterizzazione Industriale”) for funding a XXXV Cycle Ph.D. grant to Dr. Virginia Venezia. The collaboration with this company is foreseen as part of the activity scheduled in the POC doctoral project. The authors would also like to thank the Spanish Ministry of Science and Innovation, project PID2021-128749OB-C31 for financial support.Peer reviewedPID2021-128749OB-C3

    Acute Heart Failure: Diagnostic-Therapeutic Pathways and Preventive Strategies-A Real-World Clinician's Guide

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    : Acute heart failure (AHF) is the most frequent cause of unplanned hospital admission in patients of >65 years of age and it is associated with significantly increased morbidity, mortality, and healthcare costs. Different AHF classification criteria have been proposed, mainly reflecting the clinical heterogeneity of the syndrome. Regardless of the underlying mechanism, peripheral and/or pulmonary congestion is present in the vast majority of cases. Furthermore, a marked reduction in cardiac output with peripheral hypoperfusion may occur in most severe cases. Diagnosis is made on the basis of signs and symptoms, laboratory, and non-invasive tests. After exclusion of reversible causes, AHF therapeutic interventions mainly consist of intravenous (IV) diuretics and/or vasodilators, tailored according to the initial hemodynamic status with the addition of inotropes/vasopressors and mechanical circulatory support if needed. The aim of this review is to discuss current concepts on the diagnosis and management of AHF in order to guide daily clinical practice and to underline the unmet needs. Preventive strategies are also discussed

    Improved calorimetric particle identification in NA62 using machine learning techniques

    No full text
    International audienceMeasurement of the ultra-rare K+π+νν {K}^{+}\to {\pi}^{+}\nu \overline{\nu} decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2 × 105^{−5} for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 105^{−5}

    Improved calorimetric particle identification in NA62 using machine learning techniques

    No full text
    Measurement of the ultra-rare K+π+ννˉK^+\to\pi^+\nu\bar\nu decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2×1051.2\times 10^{-5} for a pion identification efficiency of 75% in the momentum range of 15-40 GeV/cc. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10510^{-5}.Measurement of the ultra-rare K+π+ννˉK^+\to\pi^+\nu\bar\nu decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2×1051.2\times 10^{-5} for a pion identification efficiency of 75% in the momentum range of 15-40 GeV/cc. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10510^{-5}

    Multifrequency studies of the peculiar quasar 4C+21.35 during the 2010 flaring activity

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    The discovery of rapidly variable Very High Energy ( VHE; E &gt; 100 GeV). - ray emission from 4C + 21.35 ( PKS 1222+ 216) by MAGIC on 2010 June 17, triggered by the high activity detected by the Fermi Large Area Telescope ( LAT) in high energy ( HE; E &gt; 100 MeV). - rays, poses intriguing questions on the location of the. - ray emitting region in this flat spectrum radio quasar. We present multifrequency data of 4C + 21.35 collected from centimeter to VHE during 2010 to investigate the properties of this source and discuss a possible emission model. The first hint of detection at VHE was observed by MAGIC on 2010 May 3, soon after a gamma- ray flare detected by Fermi-LAT that peaked on April 29. The same emission mechanism may therefore be responsible for both the HE and VHE emission during the 2010 flaring episodes. Two optical peaks were detected on 2010 April 20 and June 30, close in time but not simultaneous with the two gamma- ray peaks, while no clear connection was observed between the X-ray and gamma- ray emission. An increasing flux density was observed in radio and mm bands from the beginning of 2009, in accordance with the increasing gamma- ray activity observed by Fermi-LAT, and peaking on 2011 January 27 in the mm regime ( 230 GHz). We model the spectral energy distributions ( SEDs) of 4C + 21.35 for the two periods of the VHE detection and a quiescent state, using a one-zone model with the emission coming from a very compact region outside the broad line region. The three SEDs can be fit with a combination of synchrotron self-Compton and external Compton emission of seed photons from a dust torus, changing only the electron distribution parameters between the epochs. The fit of the optical/UV part of the spectrum for 2010 April 29 seems to favor an inner disk radius of &lt; six gravitational radii, as one would expect from a prograde-rotating Kerr black hole.</p

    Hydrogels from the assembly of SAA/elastin-inspired peptides reveal non-canonical nanotopologies

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    Peptide-based hydrogels are of great interest in the biomedical field, according to their biocompatibility, simple structure, and tunable properties via sequence modification. In recent years multicomponent assembly of peptides has expanded the possibilities to produce more versatile hydrogels, by blending gelating peptides with different types of peptides to add new features. In the present study assembly of gelating P5 peptide, SFFSF, blended with P21 peptide, SFFSFGVPGVGVPGVGSFFSF an elastin-inspired peptides or alternatively with FF dipeptide, was investigated by oscillatory rheology and different microscopy techniques in order to shed light on the nanotopologies formed by the self-assembled peptide mixtures. Our data show that, depending on the added peptides, cooperative or disruptive assembly can be observed giving rise to distinct nanotopologies to which correspond different mechanical properties that could be exploited to fabricate materials of desired properties
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