415 research outputs found
Measurements of the production cross-section for a Z boson in association with b- or c-jets in proton–proton collisions at s=13 TeV with the ATLAS detector
This paper presents a measurement of the production cross-section of a Z boson in association with b- or c-jets, in proton–proton collisions at s=13 TeV with the ATLAS experiment at the Large Hadron Collider using data corresponding to an integrated luminosity of 140 fb-1. Inclusive and differential cross-sections are measured for events containing a Z boson decaying into electrons or muons and produced in association with at least one b-jet, at least one c-jet, or at least two b-jets with transverse momentum pT>20 GeV and rapidity |y|<2.5. Predictions from several Monte Carlo generators based on next-to-leading-order matrix elements interfaced with a parton-shower simulation, with different choices of flavour schemes for initial-state partons, are compared with the measured cross-sections. The results are also compared with novel predictions, based on infrared and collinear safe jet flavour dressing algorithms. Selected Z+≥1c-jet observables, optimized for sensitivity to intrinsic-charm, are compared with benchmark models with different intrinsic-charm fractions
Valorization of Apple Pomace Via Single Cell Oil Production Using Oleaginous Yeast Rhodosporidium toruloides
© 2022, The Author(s), under exclusive licence to Springer Nature B.V.Apple pomace was used as a sole raw material for single cell oil (SCO) production by the oleaginous yeast Rhodosporidium toruloides DSM 4444. Preliminary studies with glucose medium revealed 100 mL of working volume in 500 mL Erlenmeyer flask as the most efficient in terms of lipid content. Thus, apple pomace hydrolysate was tested in six different conditions using 100 mL medium. The detoxified hydrolysate without chemical supplement (D medium) was found to be the most viable medium by 47.5 ± 2.47% lipid on dry cell basis (w/w). Apple pomace hydrolysate was also proven effective for SCO productions in bench-top fermenter (1 L working volume) under controlled temperature (25 °C), pH (5.0), and aeration (1vvm) by 40.1 ± 5.51% (w/w) lipid content. The same medium resulted in 50.9% (w/w) lipid on a dry cell basis in 30 L industrial-type bioreactor with 10 L of working volume, without exact control of temperature and pH. The results confirm that apple pomace is a prosperous raw material for SCO production in flask and fermenter scales. Graphical Abstract: [Figure not available: see fulltext.]
A precise measurement of the Z-boson double-differential transverse momentum and rapidity distributions in the full phase space of the decay leptons with the ATLAS experiment at s=8 TeV
This paper presents for the first time a precise measurement of the production properties of the Z boson in the full phase space of the decay leptons. This is in contrast to the many previous precise unfolded measurements performed in the fiducial phase space of the decay leptons. The measurement is obtained from proton–proton collision data collected by the ATLAS experiment in 2012 at s=8 TeV at the LHC and corresponding to an integrated luminosity of 20.2 fb-1. The results, based on a total of 15.3 million Z-boson decays to electron and muon pairs, extend and improve a previous measurement of the full set of angular coefficients describing Z-boson decay. The double-differential cross-section distributions in Z-boson transverse momentum pT and rapidity y are measured in the pole region, defined as 80<100 GeV, over the range |y|<3.6. The total uncertainty of the normalised cross-section measurements in the peak region of the pT distribution is dominated by statistical uncertainties over the full range and increases as a function of rapidity from 0.5–1.0% for |y|<2.0 to 2-7% at higher rapidities. The results for the rapidity-dependent transverse momentum distributions are compared to state-of-the-art QCD predictions, which combine in the best cases approximate N4LL resummation with N3LO fixed-order perturbative calculations. The differential rapidity distributions integrated over pT are even more precise, with accuracies from 0.2–0.3% for |y|<2.0 to 0.4–0.9% at higher rapidities, and are compared to fixed-order QCD predictions using the most recent parton distribution functions. The agreement between data and predictions is quite good in most cases
Erratum to: Observation of four-top-quark production in the multilepton final state with the ATLAS detector (Eur. Phys. J. C, (2023), 83, (496), 10.1140/epjc/s10052-023-11573-0)
Corrections to two figures, one table and the corresponding numbers in the text are noted for the paper. Systematic uncertainties arising from the comparison of the nominal tt ̄tt ̄ simulation with alternative samples generated with Sherpa and with MadGraph5_aMC@NLO+Herwig7 were not applied when deriving limits on the top-quark Yukawa coupling, Higgs oblique parameter and EFT operators. This affects Figs. 8 and 9, and Table 8. (Figure presented.) (Figure presented.) (Table presented.) Two-dimensional negative log-likelihood contours for |κtcos(α)| versus |κtsin(α)| at 68% and 95%, where κt is the top-Higgs Yukawa coupling strength parameter and α is the mixing angle between the CP-even and CP-odd components. The gradient-shaded area represents the observed likelihood value as a function of κt and α. Both the tt ̄tt ̄ signal and tt ̄H background yields in each fitted bin are parameterised as a function of κt and α. The blue cross shows the SM expectation, while the black cross shows the best fit value The negative log-likelihood values as a function of the Higgs oblique parameter H^. The solid line represents the observed likelihood while the dashed line corresponds to the expected one. The dashed region shows the non-unitary regime Expected and observed 95% CL intervals on EFT coupling parameters assuming one EFT parameter variation in the fit Operators Expected Ci/Λ2 [TeV -2] Observed Ci/Λ2 [TeV -2] OQQ1 [-2.5,3.2] [-4.0,4.5] OQt1 [-2.6,2.1] [-3.8,3.4] Ott1 [-1.2,1.4] [-1.9,2.1] OQt8 [-4.3,5.1] [-6.9,7.6] The changes in the text are noted for Sects. 9.1, 9.2 and 10. In Sect. 9.1, for the case when the tt ̄tt ̄ and tt ̄H yields in each bin of the GNN distribution are parameterised as a function of κt and α and fixing the top-quark Yukawa coupling to be CP-even only, the observed limit is |κt|<1.9 instead of |κt|<1.8. If the tt ̄H background yields are not parametrised, whilst the normalisation of the tt ̄H background is treated as a free parameter of the fit, the observed (expected) limit is |κt|<2.3 (1.9) instead of |κt|<2.2 (1.8). In Sect. 9.2, the upper limits on the absolute values of the coefficients (|Ci/Λ2|) of OQQ1, OQt1, Ott1 and OQt8 assuming only the linear terms are 6.6, 4.0, 2.8 and 10.8 TeV -2, respectively, at 95% CL instead of 5.3, 3.3, 2.4 and 8.8 TeV -2. In Sect. 9.2, the observed (expected) upper limit on the H^ parameter is 0.23 (0.11) at 95% CL instead of 0.20 (0.12). The published expected upper limit of 0.12 was a mistake in the text and should have been 0.1 corresponding to the likelihood scan in Fig. 9. The observed limit is weaker than the largest value of this parameter equal to 0.2 that preserves unitarity in the perturbative theory. In Sect. 10, assuming a pure CP-even coupling (α=0), the observed upper limit on |κt|=|yt/ytSM| at 95% CL is 1.9 instead of 1.8. Assuming one operator taking effect at a time, the observed constraints on the coefficients (Ci/Λ2) of OQQ1, OQt1, Ott1 and OQt8 are [-4.0,4.5], [-3.8,3.4], [-1.9,2.1] and [-6.9,7.6] TeV -2, respectively. An observed upper limit at 95% CL of 0.23 is obtained for the Higgs oblique parameter that is weaker than the largest value that preserves unitarity in the perturbative theory. In Sect. 9.1, for the case when the tt ̄tt ̄ and tt ̄H yields in each bin of the GNN distribution are parameterised as a function of κt and α and fixing the top-quark Yukawa coupling to be CP-even only, the observed limit is |κt|<1.9 instead of |κt|<1.8. If the tt ̄H background yields are not parametrised, whilst the normalisation of the tt ̄H background is treated as a free parameter of the fit, the observed (expected) limit is |κt|<2.3 (1.9) instead of |κt|<2.2 (1.8). In Sect. 9.2, the upper limits on the absolute values of the coefficients (|Ci/Λ2|) of OQQ1, OQt1, Ott1 and OQt8 assuming only the linear terms are 6.6, 4.0, 2.8 and 10.8 TeV -2, respectively, at 95% CL instead of 5.3, 3.3, 2.4 and 8.8 TeV -2. In Sect. 9.2, the observed (expected) upper limit on the H^ parameter is 0.23 (0.11) at 95% CL instead of 0.20 (0.12). The published expected upper limit of 0.12 was a mistake in the text and should have been 0.1 corresponding to the likelihood scan in Fig. 9. The observed limit is weaker than the largest value of this parameter equal to 0.2 that preserves unitarity in the perturbative theory. In Sect. 10, assuming a pure CP-even coupling (α=0), the observed upper limit on |κt|=|yt/ytSM| at 95% CL is 1.9 instead of 1.8. Assuming one operator taking effect at a time, the observed constraints on the coefficients (Ci/Λ2) of OQQ1, OQt1, Ott1 and OQt8 are [-4.0,4.5], [-3.8,3.4], [-1.9,2.1] and [-6.9,7.6] TeV -2, respectively. An observed upper limit at 95% CL of 0.23 is obtained for the Higgs oblique parameter that is weaker than the largest value that preserves unitarity in the perturbative theory
Measurement of the production cross-section of J/ψ and ψ(2S) mesons in pp collisions at √s=13 TeV with the ATLAS detector
Measurements of the differential production cross-sections of prompt and non-prompt J/ψ and ψ(2S) mesons with transverse momenta between 8 and 360 GeV and rapidity in the range |y|<2 are reported. Furthermore, measurements of the non-prompt fractions of J/ψ and ψ(2S), and the prompt and non-prompt ψ(2S)-to-J/ψ production ratios, are presented. The analysis is performed using 140 fb-1 of s=13 TeV pp collision data recorded by the ATLAS detector at the LHC during the years 2015–2018
Development of an agglomerated cape gooseberry (Physalis peruviana L.) product with instantaneous characteristics and potential antioxidant effect
ilustraciones. diagramas, tablasLa uchuva (Physalis peruviana L.), es una fruta exótica de la región Andina, la cual presenta una demanda creciente debido a que posee características aromáticas y propiedades nutricionales favoreciendo su uso como alimento funcional. Colombia está entre los principales productores y exportadores de fruta exótica del mundo, principalmente gulupa y uchuva, por consiguiente, es la quinta fruta con mayor mercado después del banano en términos de exportación. La generación de nuevos productos, con sabores innovadores y con mejores características fisicoquímicas ha permitido el desarrollo y la implementación de nuevas metodologías para su obtención. Una alternativa a este contexto es el secado de la pulpa con el fin de obtener un producto en polvo, conservando las propiedades de la fruta. Algunos métodos de secado resultan inapropiados por afectar fuertemente las características sensoriales y las propiedades nutricionales de las frutas. El secado por aspersión, es un método usado en pulpas de frutas que son sensibles al calor, siendo sus principales ventajas el alto rendimiento y la reducción del daño térmico. El objetivo de la investigación fue desarrollar un producto aglomerado de uchuva (Physalis peruviana L.) con características instantáneas y potencial efecto antioxidante, contribuyendo a mejorar la competitividad de la agrocadena. En este contexto, la investigación se planteó en tres etapas: En la 1ª etapa se realizó la evaluación de la influencia del proceso de hidrólisis enzimática sobre la estabilidad fisicoquímica de un sistema coloidal a base de pulpa, piel y semilla de uchuva (CSU), con fines a ser utilizado en secado por aspersión. La pulpa con semilla y piel fue homogenizada inicialmente por cizalla en un sistema rotor-estator a 10000 rpm durante 10 minutos y para la evaluación enzimática, se empleó el complejo multienzimático Viscozyme L y se utilizó un diseño factorial completamente aleatorizado, considerando las variables independientes: concentración de enzima [Enzima] (50, 125 y 200 ppm) y tiempo de hidrólisis (TH) (0, 30, 60, 90 y 120 minutos), y las variables dependientes: viscosidad (), potencial zeta (ζ), tamaño de partícula (percentiles D10, D50 y D90), Span, índice de absorción espectral (R) y sólidos solubles (SS). La [Enzima] tuvo un efecto significativo (p < 0.05) sobre la μ, SS, D50, D90 y R, el TH sobre la μ, SS y D10; además, existe un efecto de la interacción [Enzima]-HT sobre el aumento de la μ y los SS. La optimización de la formulación presentó una deseabilidad del 74.2%, con una [Enzima] = 78.5 ppm y TH = 120 minutos; siendo las variables dependientes calculadas por un modelo cuadrático: µ = 356.9 cP, SS = 15.5, = -18.5 mV, D10 = 3.2 m, D50 = 118.2 m; D90 = 480.8 m; Span = 4.1, R = 0.605. La combinación de procesos de homogenización por cizalla y el tratamiento enzimático aplicado, contribuyeron a la obtención de sistema coloidal estable fisicoquímicamente, sin embargo, se pretendía obtener una mayor reducción de tamaños de partícula, lo cual se logra mediante un proceso de homogenización de alta presión y adición de hidrocoloides que favorecieron la estabilidad de la suspensión. En la 2ª etapa se planteó la evaluación del proceso de secado por aspersión y la composición de la alimentación sobre los atributos de calidad de las microcápsulas de uchuva. El secado por aspersión operó en condiciones subatmosféricas a 0.37 kPa (1.5” H2O) y utilizando el equipo Vibrasec SA, referencia PASLAB1.5, con una capacidad de evaporación de 1.5L/h. El proceso de secado por aspersión se optimizó utilizando la metodología de superficie de respuesta, con un diseño experimental central compuesto cara centrada, teniendo en cuanta las variables independientes: goma arábiga (AG) (1 - 3%), maltodextrina (MD) (9.5 – 13.5%), temperatura de entrada de aire (TEA) (130-160°C), temperatura del aire de salida (TSA) (75-85°C) y velocidad del disco atomizador (VDA) (18000-22000 rpm), las variables dependientes evaluadas fueron: humedad (Xw), solubilidad (S), higroscopicidad (H), humectabilidad (Hu), coordenadas de color L* y b*, fenoles totales (FT), capacidad antioxidante (DPPH y ABTS) y rendimiento (Y). La optimización experimental de múltiples respuestas presentó una deseabilidad del 68.4%, definiendo las variables independientes: GA = 2.2%, MD = 10.1%, TEA = 160 °C, TSA = 77.8 °C y VDA = 21450 rpm, y las variables dependientes: Xw = 2.7±0.1%,.S = 86.2±2.3%, H = 16.2±0.0%, Hu = 4.0±013 s, L* = 43.9±0.1, b* = 35.7±0.9, TP = 284.2±1.8 mg AGE/100 g bs, DPPH = 99.8±2.5 mg TE/100 g bs, ABTS = 158.5±0.1 mg TE/100 g bs y Y = 56.1±1.6%. El secado por aspersión como proceso de microencapsulación del extracto de uchuva, fue una tecnología efectiva que permitió la obtención microcápsulas de uchuva con excelentes atributos de calidad. En el proceso se dio un mayor aprovechamiento de la estructura de la uchuva (pulpa, semilla y cáscara), que otorgó un alto contenido de solidos de uchuva al producto obtenido. En la 3ª etapa se evaluó el sistema de aglomeración por lecho fluidizado, el cual se optimizó utilizando la metodología de superficie de respuesta, con diseño experimental central compuesto cara centrada, teniendo en cuenta las variables independientes: temperatura del aire de fluidización (T) (50 – 70 °C), presión de atomización de la solución ligante (P) (1.0 – 2.0 bar) y tiempo de aglomeración (t) (20 – 40 min), y como variables dependientes: humedad (Xw), solubilidad (S), humectabilidad (Hu), higroscopicidad (H), densidad aparente (a), índice de Carr (IC), relación de Hausner (RH), tamaño de partícula D[4,3], fenoles totales (FT), flavonoides totales (FLT), capacidad antioxidante (DPPH y ABTS), vitamina C (Vit.C), -caroteno (-car) y el rendimiento (Y). La optimización experimental de múltiples repuestas presentó una deseabilidad del 63.8%, definiendo las variables independientes: T = 68.4 °C, P = 1.1 bar, t = 36.5 min, y las variables dependientes: Xw (4.3±0.1%), S (80.5±0.8%), H (14.4±0.5%), Hu (2.3±0.1 s), a (0.588±0.021 g/mL), IC (11.9 ± 2.5%), RH (1.11±0.02), D[4,3] (136.0 2.2 µm), FT (366.7±2.5 mg AGE/100 g bs), FLT (26.5±0.9 mg QE/100 g bs), DPPH (163.5±2.6 mg TE/100 g bs) y ABTS (133.0±1.1 mg TE/100 g bs), Vit.C (42.2±2.5 mg/100 g bs), -car (72.4±2.1 mg/100 g bs) y Y (62.5±3.3%). El proceso de aglomeración por lecho fluidizado del polvo de uchuva, fue efectivo, resultando en la mejora de las propiedades físicas relacionadas con las características funcionales de instantanización y fluidez. (Texto tomado de la fuente)The cape gooseberry (Physalis peruviana L.) is an exotic fruit from the Andean region, growing demand due to its aromatic characteristics and nutritional properties that favor its use as a functional food. Colombia is among the primary producers and exporters of exotic fruit globally, mainly purple passion fruit and cape gooseberry, and is, therefore, the fifth fruit with the largest market after bananas in terms of exports. The generation of new products with innovative flavors and better physicochemical characteristics has allowed the development and implementation of new methodologies. An alternative to this context is the drying of the pulp to obtain a powdered product, preserving the properties of the fruit. Some drying methods are inappropriate because they strongly affect its sensory characteristics and nutritional properties. Spray drying is a method used for fruit pulps that are sensitive to heat, its main advantages being high yield and reduction of thermal damage. The objective of the research was to develop an agglomerated cape gooseberry (Physalis peruviana L.) product with instantaneous characteristics and potential antioxidant effect, contributing to improving the competitiveness of the agribusiness chain. In this context, the research was carried out in three stages: In the first stage, the influence of the enzymatic hydrolysis process on the physicochemical stability of a colloidal system based on cape gooseberry pulp, skin, and seed (CSU), is to be used in spray drying, was evaluated. The pulp with seed and skin was initially homogenized by shearing in a rotor-stator system at 10000 rpm for 10 minutes. For the enzymatic evaluation, the multi-enzyme complex Viscozyme L and a completely randomized factorial design were used, considering the independent variables: [Enzyme] enzyme concentration (50, 125, and 200 ppm) and hydrolysis time (HT) (0, 30, 60, 90 and 120 minutes), and the dependent variables: viscosity (μ), zeta potential (ζ), particle size (percentiles D10, D50, and D90), Span, spectral absorption index (R) and soluble solids (SS). Enzyme] had a significant effect (p <0.05) on μ, SS, D50, D90 and R, HT on μ, SS and D10; furthermore, there is an effect of [Enzyme]-HT interaction on the increase of μ and SS. The formulation optimization presented a desirability of 74.2%, with [Enzyme] = 78.5 ppm and TH = 120 min; being the dependent variables calculated by a quadratic model: µ = 356.9 cP, SS = 15.5, ζ = -18.5 mV, D10 = 3.2 μm, D50 = 118.2 μm; D90 = 480.8 μm; Span = 4.1, R = 0.605. The combination of shear homogenization processes and the enzymatic treatment applied contributed to obtaining a physicochemically stable colloidal system; however, it was intended to reduce particle size, which is achieved through a high-pressure homogenization process and addition of hydrocolloids that favored the stability of the suspension. In the second stage, the evaluation of the spray drying process and the composition of the feed on the quality attributes of the cape gooseberry microcapsules was proposed. The spray drying process operated under subatmospheric conditions at 0.37 kPa (1.5" H2O) and using the Vibrasec SA equipment, reference PASLAB1.5, with an evaporation capacity of 1.5L/h. The spray drying process was optimized using the response surface methodology, with a face-centered central composite experimental design, taking into account the independent variables: gum arabic (GA) (1 - 3%), maltodextrin (MD) (9.5 - 13. 5%), air inlet temperature (AIT) (130 - 160°C), air outlet temperature (AOT) (75-85°C) and atomizing disk speed (ADS) (18000-22000 rpm), the dependent variables evaluated were: moisture (Xw), solubility (S), hygroscopicity (H), wettability (We), color coordinates L* and b*, total phenols (TP), antioxidant capacity (DPPH and ABTS) and yield (Y). The experimental optimization of multiple responses presented a desirability of 68.4%, defining the independent variables: GA = 2.2%, MD = 10.1%, AIT = 160 °C, AOT = 77.8 °C and ADS = 21450 rpm, and the dependent variables: Xw = 2.7±0.1%, S = 86.2±2.3%, H = 16.2±0.0%, We = 4.0±013 s, L* = 43.9±0.1, b* = 35.7±0.9, TP = 284.2±1.8 mg GAE/100 g bs, DPPH = 99.8±2.5 mg TE/100 g bs, ABTS = 158.5±0.1 mg TE/100 g bs and Y = 56.1±1.6%. Spray drying is a process of microencapsulation of cape gooseberry extract was an effective technology that allowed obtaining cape gooseberry microcapsules with excellent quality attributes. In the process, greater use was made of the structure of the cape gooseberry (pulp, seed, and peel), which gave a high content of cape gooseberry solids to the product obtained. In the third stage, the fluidized bed agglomeration system was evaluated, which was optimized using the response surface methodology, with face-centered central composite experimental design, taking into account the independent variables: fluidization air temperature (T) (50 - 70 °C), binder solution atomization pressure (P) (1.0 - 2. 0 bar) and agglomeration time (t) (20 - 40 min), and as dependent variables: moisture (Xw), solubility (S), wettability (We), hygroscopicity (H), bulk density (ρa), Carr's index (CI), Hausner's ratio (RH), particle size D[4,3], total phenols (TP), total flavonoids (TFL), antioxidant capacity (DPPH and ABTS), vitamin C (Vit.C), β-carotene (β-car) and yield (Y). The multiple-response experimental optimization presented a desirability of 63.8%, defining the independent variables: T = 68.4 °C, P = 1.1 bar, t = 36.5 min, and the dependent variables: Xw (4.3±0.1%), S (80.5±0.8%), H (14.4±0.5%), We (2.3±0.1 s), ρa (0.588±0.021 g/mL), CI (11.9±2.5%), RH (1.11±0.02), D[4,3] (136.0±2.2 µm), TP (366.7±2.5 mg GAE/100 g db), TFL (26.5±0.9 mg QE/100 g db), DPPH (163.5±2.6 mg TE/100 g db) and ABTS (133.0±1.1 mg TE/100 g db), Vit.C (42.2±2.5 mg/100 g db), β-car (72.4±2.1 mg/100 g db) and Y (62.5±3.3%). The fluidized bed agglomeration process of cape gooseberry powder was effective, resulting in improved physical properties related to the functional characteristics of instantaneousness and flowability.PROEXCAR SASMaestríaMagíster en Ciencia y Tecnología de AlimentosÁrea Curricular en Ingeniería Agrícola y Alimento
Corylus avellana L. Husks an Underutilized Waste but a Valuable Source of Polyphenols
[EN] Bioactive potential of hazelnut husks was determined as a function of their cultivar source and extraction solvent. Hazelnut husks from four hazelnut cultivars (Butler, Grada de Viseu, Lansing and Morell) were picked in a hazelnut orchard at harvest and extracted with five solvents with different polarity: water, methanol, acetone, ethyl acetate and hexane. Phenolics were identified by HPLC-DAD and antioxidant activity was determined by three complementary methods: DPPH, FRAP and inhibition of lipid peroxidation. A total of 11 phenolics were identified in studied cultivars and grouped in five main classes namely, ellagitannin (ellagic acid), benzoic acids (gallic acid, protocatechuic acid and vanillic acid), flavonols (kaempferol-3,7-O-diglucoside, kaempferol-3-O-[6-acetylglucoside]-7-O-glucoside, kaempferol-3-O-[6acetylglucoside]-7-O-rhamnoside and quercetin-3-O-rutinoside), flavone (luteolin-7-O-rutinoside) and flavan-3-ol (epicatechin). Cultivar and extraction solvent influenced significantly (p < 0.001) the extraction yield. 'Grada de Viseu' husks presented the highest content of individual phenolics identified, particularly in methanol extracts whilst 'Lansing' showed the lowest levels. Similar pattern was found for antioxidant activities. Methanolic husk extracts exhibited the greatest antioxidant potentials followed by water and acetone. The valorization of hazelnuts by-products gives an important contribution for the isolation and purification of bioactive molecules that can be used for both medicinal and industrial purposes.The author Sandra Cabo acknowledges the financial support by the Portuguese Foundation for Science and Technology (FCT) (PB/BD/113615/2015) under the Doctoral Programme "Agricultural Production Chains-from fork to farm" (PD/00122/2012). The authors also acknowledge the financial support provided by National Funds from FCT, under the project UID/AGR/04033/2019. The authors acknowledge the financial support of INTERACT project "Integrative Research in Environment, Agro-Chains and Technology", no. NORTE-01-0145-FEDER-000017, in its line of research entitled ISAC, co-financed by the European Regional Development Fund (ERDF) through NORTE 2020 (North Regional Operational Program 2014/2020) and Project IBERPHENOL, Project Number 0377_IBERPHENOL_6_E, co-financed by European Regional Development Fund (ERDF) through POCTEP 2014-2020.Cabo, S.; Aires, A.; Carvalho, R.; Pascual-Seva, N.; Silva, AP.; Gonçalves, B. (2021). Corylus avellana L. Husks an Underutilized Waste but a Valuable Source of Polyphenols. Waste and Biomass Valorization. 12(7):3629-3644. https://doi.org/10.1007/s12649-020-01246-4S36293644127Molnar, T.J., Goffreda, J.C., Funk, C.R.: Developing hazelnuts for the eastern United States. Acta Hortic. 686, 609–618 (2005)Lopez-Calleja, I.M., Cruz, S.D., La Pegels, N., Gonzalez, I., Garcia, T., Martin, R.: High resolution TaqMan real-time PCR approach to detect hazelnut DNA encoding for ITS rDNA in foods. Food Chem. 141, 1872–1880 (2005)Shahidi, F., Alasalvar, C., Liyana-Pathirana, C.M.: Antioxidant phytochemicals in hazelnut kernel (Corylus avellana L.) and hazelnut byproducts. J. Agric. Food Chem. 55, 1212–1220 (2007)Bacchetta, L., Rovira, M., Tronci, C., Aramini, M., Drogoudi, P., Silva, A.P., Solar, A., Avanzato, D., Botta, R., Valentini, N., Boccacci, P.: A multidisciplinary approach to enhance the conservation and use of hazelnut Corylus avellana L. genetic resources. Genet. Resour. Crop Evol. 62, 649–663 (2005)FAO. Agricultural Production Crops—Hazelnut. Food and Agriculture Organization of the United Nations. Access online: https://faostat.fao.org. (2016)Uzuner, S., Cekmecelioglu, D.: Hydrolysis of hazelnut shells as a carbon source for bioprocessing applications and fermentation. Int. J. Food Eng. 10, 799–808 (2014)Çöpür, Y., Güler, C., Akgül, M., Taşçioǧlu, C.: Some chemical properties of hazelnut husk and its suitability for particleboard production. Build. Environ. 42, 2568–2572 (2007)Guney, M.S.: Utilization of hazelnut husk as biomass. Sustain. Energy Technol. Assess. 4, 72–77 (2013)Masullo, M., Cerulli, A., Mari, A., de Souza, S.C.C., Pizza, C., Piacente, S.: LC-MS profiling highlights hazelnut (Nocciola di Giffoni PGI) shells as a byproduct rich in antioxidant phenolics. Food Res. Int. 101, 180–187 (2017)Yuan, B., Lu, M., Eskridge, K.M., Isom, L.D., Hanna, M.A.: Extraction, identification, and quantification of antioxidant phenolics from hazelnut (Corylus avellana L.) shells. Food Chem. 244, 7–15 (2018)Li, A.N., Li, S., Zhang, Y.J., Xu, X.R., Chen, Y.M., Li, H.B.: Resources and biological activities of natural polyphenols. Nutrients 6, 6020–6047 (2014)Li, F., Li, S., Li, H.B., Deng, G.F., Ling, W.H., Wu, S., Xu, X.R., Chen, F.: Antiproliferative activity of peels, pulps and seeds of 61 fruits. J. Funct. Foods 5, 1298–1309 (2013)Bouayed, J., Bohn, T.: Exogenous antioxidants—double-edged swords in cellular redox state: health beneficial effects at physiologic doses versus deleterious effects at high doses. Oxid. Med. Cell Longev. 3, 228–237 (2010)Ignat, I., Volf, I., Popa, V.I.: A critical review of methods for characterisation of polyphenolic compounds in fruits and vegetables. Food Chem. 126, 1821–1835 (2011)Kottek, M., Grieser, J., Beck, C., Rudolf, B., Rubel, F.: World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 15(3), 259–263 (2006)John, K.M.M., Harnly, J., Luthri, D.: Influence of direct and sequential extraction methodology on metabolic profiling. J. Chromatogr. B 1073, 34–42 (2018)Singleton, V.L., Rossi, J.A.: Colorometry of total phenolics with phosphomolybdic-phosphotungstic acid reagents. Am. J. Enol. Vitic. 16, 144–158 (1965)Dewanto, V., Wu, X., Adom, K.K., Liu, R.H.: Thermal processing enhances the nutritional value of tomatoes by increasing total antioxidant activity. J. Agric. Food Chem. 50, 3010–3014 (2002)Lichtenthaler, H.K., Wellburn, A.R.: Determination of total carotenoids and chlorophylls a and b of leaf in different solvents. Biol. Soc. Trans. 11, 591–592 (1983)Aires, A., Carvalho, R., Rosa, E.A.S., Saavedra, M.J.: Phytochemical characterization and antioxidant properties of organic baby-leaf watercress produced under organic production system. CyTA-J. Food. 11, 343–351 (2013)Siddhraju, P., Becker, K.: Antioxidant properties of various solvents extracts of total phenolic constituents from three different agroclimatic origins of drumstick tree (Moringa oleifera Lam) leaves. J. Agric. Food Chem. 51, 2144–2155 (2003)Benzie, I.F.F., Strain, J.J.: The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: the FRAP assay. Anal. Biochem. 239, 70–76 (1996)Ruberto, G., Baratta, M.T., Deans, S.G., Dorman, H.J.D.: Antioxidant and antimicrobial activity of Foeniculum vulgare and Crithmum maritimum essential oils. Planta Med. 66, 687–693 (2000)Shaidi, F., Alasalvar, C., Liyana-Pathirana, C.M.: Antioxidant phytochemicals in hazelnut kernel (Corylus avellana L.) and hazelnut byproducts. J. Agric. Food Chem. 55, 1212–1220 (2007)Rusu, M.E., Fizeșan, I., Pop, A., Gheldiu, A.-M., Mocan, A., Crișan, G., Vlase, L., Loghin, F., Popa, D.-S., Tomuta, I.: Enhanced recovery of antioxidant compounds from hazelnut (Corylus avellana L.) involucre based on extraction optimization: phytochemical profile and biological activities. Antioxidants 8, 460 (2019)Boulekbache-Makhlouf, L., Medouni, L., Medouni-Adrar, S., Arkoub, L., Madani, K.: Effect of solvents extraction on phenolic content and antioxidant activity of the byproduct of eggplant. Ind. Crops Prod. 49, 668–674 (2013)Fanali, C., Tripodo, G., Russo, M., Della, P.S., Pasqualetti, V., De Gara, L.: Effect of solvent on the extraction of phenolic compounds and antioxidant capacity of hazelnut kernel. Electrophoresis 39(13), 1683–1691 (2018)Aires, A.: Phenolics in foods: extraction, analysis and measurements. In: Soto-Hernandez, M., Tenango, M.P., Rosario Garcia-Mateos, M. (eds.) Phenolic Compounds—Natural Sources, Importance and Applications, pp. 61–88. IntechOpen, London, SE19SG-United Kingdom. ISBN 978-953-51-2958-5 (2017)Nobossé, P., Fombang, E.N., Mbofung, C.M.F.: Effects of age and extraction solvent on phytochemical content and antioxidant activity of fresh Moringa oleifera L. leaves. Food Sci. Nutr. 6, 2188–2198 (2018)Elfalleh, W., Kirkan, B., Sarikurkcu, C.: Antioxidant potential and phenolic composition of extracts from Stachys tmolea: an endemic plant from Turkey. Ind. Crops Prod. 27, 212–216 (2019)Chang, Y., Chou, D.-S., Sheu, J.-R., Chen, W.-F., Lin, K.-H., Hsieh, C.-Y., Lin, L.-J., Chang, C.-C.: Novel bioactivity of ellagic acid in inhibiting human platelet activation. Evid. Based Complement. Altern. Med. 2013, 1–9 (2013)Farbood, Y., Sarkaki, A., Dianat, M., Khodadadi, A., Haddad, M.K., Mashhadizadeh, S.: Ellagic acid prevents cognitive and hippocampal long-term potentiation deficits and brain inflammation in rat with traumatic brain injury. Life Sci. 124, 120–127 (2015)Punithavathi, V.R., Prince, P.S.M., Kumar, R., Selvakumari, J.: Antihyperglycaemic antilipid peroxidative and antioxidant effects of gallic acid on streptozotocin induced diabetic Wistar rats. Eur. J. Pharmacol. 650, 465–471 (2011)Huang, W.W., Tsai, S.C., Peng, S.F., Lin, M.W., Chiang, J.H., Chiu, Y.J., Fushiya, S., Tseng, M.T., Yang, J.S.: Kaempferol induces autophagy through AMPK and AKT signalling molecules and causes G 2/M arrest via downregulation of CDK1/cyclin B in SK-HEP-1 human hepatic cancer cells. Int. J. Oncol. 42, 2069–2077 (2013)Kashafi, E., Moradzadeh, M., Mohamadkhani, A., Erfanian, S.: Kaempferol increases apoptosis in human cervical cancer HeLa cells via PI3K/AKT and telomerase pathways. Biomed. Pharmacother. 89, 573–577 (2017)Labbé, D.P., Zadra, G., Ebot, E.M., Mucci, L.A., Kantoff, P.W., Loda, M., Brown, M.: Role of diet in prostate cancer: the epigenetic link. Oncogene 34, 4683–4691 (2015)Yap, S.: Reversing breast cancer in a premenopausal woman: a case for phyto-nutritional therapy. Int. J. Biotechnol. Wellness Ind. 4, 25–39 (2015)Esposito, T., Sansone, F., Franceschelli, S., Del Gaudio, P., Picerno, P., Aquino, R.P., Mencherini, T.: Hazelnut (Corylus avellana L.) shells extract: phenolic composition, antioxidant effect and cytotoxic activity on human cancer cell lines. Int. J. Mol. Sci. 18, 392 (2017)Tungmunnithum, D., Thongboonyou, A., Pholboon, A., Yangsabai, A.: Flavonoids and other phenolic compounds from medicinal plants for pharmaceutical and medical aspects: an overview. Medicines (Basel, Switzerland) 5, 93 (2018
Search for Majorana neutrinos in same-sign WW scattering events from pp collisions at s√=13 TeV
A search for Majorana neutrinos in same-sign WW scattering events is presented. The analysis uses s√=13 TeV proton–proton collision data with an integrated luminosity of 140 fb−1 recorded during 2015–2018 by the ATLAS detector at the Large Hadron Collider. The analysis targets final states including exactly two same-sign muons and at least two hadronic jets well separated in rapidity. The modelling of the main backgrounds, from Standard Model same-sign WW scattering and WZ production, is constrained with data in dedicated signal-depleted control regions. The distribution of the transverse momentum of the second-hardest muon is used to search for signals originating from a heavy Majorana neutrino with a mass between 50 GeV and 20 TeV. No significant excess is observed over the background expectation. The results are interpreted in a benchmark scenario of the Phenomenological Type-I Seesaw model. In addition, the sensitivity to the Weinberg operator is investigated. Upper limits at the 95% confidence level are placed on the squared muon-neutrino–heavy-neutrino mass-mixing matrix element |VμN|2 as a function of the heavy Majorana neutrino’s mass mN, and on the effective μμ Majorana neutrino mass |mμμ|
Precision luminosity measurement in proton–proton collisions at √s=13TeV in 2015 and 2016 at CMS
(…) the Secretaría de Estado de Investigación, Desarrollo, e Innovación, Programa Consolider-Ingenio 2010, Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020, research Project No. IDI-2018-000174 del Principado de Asturias, and Fondo Europeo de Desarrollo Regional, Spain. Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 765710 and 824093 (European Union); the Programa María de Maeztu and the Programa Severo Ochoa del Principado de Asturias (…)Sirunyan AM, Tumasyan A, Adam W, Andrejkovic JW, Bergauer T, Chatterjee S, Dragicevic M, Valle AED, Frühwirth R, Jeitler M, Krammer N, Lechner L, Liko D, Mikulec I, Pitters FM, Schieck J, Schöfbeck R, Spanring M, Templ S, Waltenberger W, Wulz CE, Chekhovsky V, Litomin A, Makarenko V, Darwish MR, De Wolf EA, Janssen X, Kello T, Lelek A, Sfar HR, Van Mechelen P, Van Putte S, Van Remortel N, Blekman F, Bols ES, D'Hondt J, De Clercq J, Delcourt M, Lowette S, Moortgat S, Morton A, Müller D, Sahasransu AR, Tavernier S, Van Doninck W, Van Mulders P, Beghin D, Bilin B, Clerbaux B, De Lentdecker G, Favart L, Grebenyuk A, Kalsi AK, Lee K, Mahdavikhorrami M, Makarenko I, Moureaux L, Pétré L, Popov A, Postiau N, Starling E, Thomas L, Bemden MV, Vander Velde C, Vanlaer P, Vannerom D, Wezenbeek L, Cornelis T, Dobur D, Gruchala M, Mestdach G, Niedziela M, Roskas C, Skovpen K, Tytgat M, Verbeke W, Vermassen B, Vit M, Bethani A, Bruno G, Bury F, Caputo C, David P, Delaere C, Donertas IS, Giammanco A, Lemaitre V, Mondal K, Prisciandaro J, Taliercio A, Teklishyn M, Vischia P, Wertz S, Wuyckens S, Alves GA, Hensel C, Moraes A, Júnior WLA, Filho MBF, Malbouisson HB, Carvalho W, Chinellato J, Da Costa EM, Da Silveira GG, De Jesus Damiao D, De Souza SF, Figueiredo DM, Herrera CM, Amarilo KM, Mundim L, Nogima H, Teles PR, Rosas LJS, Santoro A, Silva Do Amaral SM, Sznajder A, Thiel M, Da Silva De Araujo FT, Pereira AV, Bernardes CA, Calligaris L, Tomei TRFP, Gregores EM, Lemos DS, Mercadante PG, Novaes SF, Padula SS, Aleksandrov A, Antchev G, Atanasov I, Hadjiiska R, Iaydjiev P, Misheva M, Rodozov M, Shopova M, Sultanov G, Dimitrov A, Ivanov T, Litov L, Pavlov B, Petkov P, Petrov A, Cheng T, Fang W, Guo Q, Javaid T, Mittal M, Wang H, Yuan L, Ahmad M, Bauer G, Dozen C, Hu Z, Martins J, Wang Y, Yi K, Chapon E, Chen GM, Chen HS, Chen M, Kapoor A, Leggat D, Liao H, Liu ZA, Sharma R, Spiezia A, Tao J, Thomas-Wilsker J, Wang J, Zhang H, Zhang S, Zhao J, Agapitos A, Ban Y, Chen C, Huang Q, Levin A, Li Q, Lu M, Lyu X, Mao Y, Qian SJ, Wang D, Wang Q, Xiao J, You Z, Gao X, Okawa H, Xiao M, Avila C, Cabrera A, Florez C, Fraga J, Sarkar A, Delgado MAS, Jaramillo J, Guisao JM, Ramirez F, Alvarez JDR, González CAS, Arbelaez NV, Giljanovic D, Godinovic N, Lelas D, Puljak I, Antunovic Z, Kovac M, Sculac T, Brigljevic V, Ferencek D, Majumder D, Roguljic M, Starodumov A, Susa T, Attikis A, Erodotou E, Ioannou A, Kole G, Kolosova M, Konstantinou S, Mousa J, Nicolaou C, Ptochos F, Razis PA, Rykaczewski H, Saka H, Finger M, Finger M Jr, Kveton A, Ayala E, Jarrin EC, Zeid SA, Khalil S, Salama E, Mahmoud MA, Mohammed Y, Bhowmik S, De Oliveira ACA, Dewanjee RK, Ehataht K, Kadastik M, Pata J, Raidal M, Veelken C, Eerola P, Forthomme L, Kirschenmann H, Osterberg K, Voutilainen M, Brücken E, Garcia F, Havukainen J, Karimäki V, Kim MS, Kinnunen R, Lampén T, Lassila-Perini K, Lehti S, Lindén T, Siikonen H, Tuominen E, Tuominiemi J, Luukka P, Petrow H, Tuuva T, Amendola C, Besancon M, Couderc F, Dejardin M, Denegri D, Faure JL, Ferri F, Ganjour S, Givernaud A, Gras P, de Monchenault GH, Jarry P, Lenzi B, Locci E, Malcles J, Rander J, Rosowsky A, Sahin MÖ, Savoy-Navarro A, Titov M, Yu GB, Ahuja S, Beaudette F, Bonanomi M, Perraguin AB, Busson P, Charlot C, Davignon O, Diab B, Falmagne G, Ghosh S, de Cassagnac RG, Hakimi A, Kucher I, Lobanov A, Nguyen M, Ochando C, Paganini P, Rembser J, Salerno R, Sauvan JB, Sirois Y, Zabi A, Zghiche A, Agram JL, Andrea J, Apparu D, Bloch D, Bourgatte G, Brom JM, Chabert EC, Collard C, Darej D, Fontaine JC, Goerlach U, Grimault C, Bihan AL, Van Hove P, Asilar E, Beauceron S, Bernet C, Boudoul G, Camen C, Carle A, Chanon N, Contardo D, Depasse P, El Mamouni H, Fay J, Gascon S, Gouzevitch M, Ille B, Jain S, Laktineh IB, Lattaud H, Lesauvage A, Lethuillier M, Mirabito L, Shchablo K, Torterotot L, Touquet G, Vander Donckt M, Viret S, Khvedelidze A, Tsamalaidze Z, Feld L, Klein K, Lipinski M, Meuser D, Pauls A, Rauch MP, Schulz J, Teroerde M, Eliseev D, Erdmann M, Fackeldey P, Fischer B, Ghosh S, Hebbeker T, Hoepfner K, Keller H, Mastrolorenzo L, Merschmeyer M, Meyer A, Mocellin G, Mondal S, Mukherjee S, Noll D, Novak A, Pook T, Pozdnyakov A, Rath Y, Reithler H, Roemer J, Schmidt A, Schuler SC, Sharma A, Wiedenbeck S, Zaleski S, Dziwok C, Flügge G, Ahmad WH, Hlushchenko O, Kress T, Nowack A, Pistone C, Pooth O, Roy D, Sert H, Stahl A, Ziemons T, Petersen HA, Martin MA, Asmuss P, Babounikau I, Baxter S, Behnke O, Martínez AB, Anuar AAB, Borras K, Botta V, Brunner D, Campbell A, Cardini A, Connor P, Rodríguez SC, Danilov V, Defranchis MM, Didukh L, Eckerlin G, Eckstein D, Banos LIE, Gallo E, Geiser A, Giraldi A, Grohsjean A, Guthoff M, Harb A, Jafari A, Jomhari NZ, Jung H, Kasem A, Kasemann M, Kaveh H, Kleinwort C, Knolle J, Krücker D, Lange W, Lenz T, Leonard J, Lidrych J, Lipka K, Lohmann W, Madlener T, Mankel R, Melzer-Pellmann IA, Metwally J, Meyer AB, Meyer M, Mnich J, Mussgiller A, Myronenko V, Otarid Y, Adán DP, Pitzl D, Raspereza A, Lopes BR, Rübenach J, Saggio A, Saibel A, Savitskyi M, Scheurer V, Schwanenberger C, Singh A, Ricardo RES, Tonon N, Turkot O, Vagnerini A, Van De Klundert M, Walsh R, Walter D, Wen Y, Wichmann K, Wissing C, Wuchterl S, Zlebcik R, Aggleton R, Bein S, Benato L, Benecke A, De Leo K, Dreyer T, Eich M, Feindt F, Fröhlich A, Garbers C, Garutti E, Gunnellini P, Haller J, Hinzmann A, Karavdina A, Kasieczka G, Klanner R, Kogler R, Kutzner V, Lange J, Lange T, Malara A, Nigamova A, Rodriguez KJP, Rieger O, Schleper P, Schröder M, Schwandt J, Schwarz D, Sonneveld J, Stadie H, Steinbrück G, Tews A, Vormwald B, Zoi I, Bechtel J, Berger T, Butz E, Caspart R, Chwalek T, De Boer W, Dierlamm A, Droll A, El Morabit K, Faltermann N, Flöh K, Giffels M, Gosewisch JO, Gottmann A, Hartmann F, Heidecker C, Husemann U, Katkov I, Keicher P, Koppenhöfer R, Maier S, Mallows S, Metzler M, Mitra S, Müller T, Musich M, Neukum M, Quast G, Rabbertz K, Rauser J, Savoiu D, Schäfer D, Schnepf M, Seith D, Shvetsov I, Simonis HJ, Ulrich R, Van Der Linden J, Von Cube RF, Wassmer M, Weber M, Wieland S, Wolf R, Wozniewski S, Wunsch S, Anagnostou G, Asenov P, Daskalakis G, Geralis T, Kyriakis A, Loukas D, Stakia A, Diamantopoulou M, Karasavvas D, Karathanasis G, Kontaxakis P, Koraka CK, Manousakis-Katsikakis A, Panagiotou A, Papavergou I, Saoulidou N, Theofilatos K, Tziaferi E, Vellidis K, Vourliotis E, Bakas G, Kousouris K, Papakrivopoulos I, Tsipolitis G, Zacharopoulou A, Evangelou I, Foudas C, Gianneios P, Katsoulis P, Kokkas P, Manthos N, Papadopoulos I, Strologas J, Csanad M, Gadallah MMA, Lökös S, Major P, Mandal K, Mehta A, Pasztor G, Rádl AJ, Surányi O, Veres GI, Bartók M, Bencze G, Hajdu C, Horvath D, Sikler F, Veszpremi V, Vesztergombi G, Czellar S, Karancsi J, Molnar J, Szillasi Z, Teyssier D, Raics P, Trocsanyi ZL, Ujvari B, Csorgo T, Nemes F, Novak T, Choudhury S, Komaragiri JR, Kumar D, Panwar L, Tiwari PC, Bahinipati S, Dash D, Kar C, Mal P, Mishra T, Bindhu VKMN, Nayak A, Saha P, Sur N, Swain SK, Bansal S, Beri SB, Bhatnagar V, Chaudhary G, Chauhan S, Dhingra N, Gupta R, Kaur A, Kaur S, Kumari P, Meena M, Sandeep K, Singh JB, Virdi AK, Ahmed A, Bhardwaj A, Choudhary BC, Garg RB, Gola M, Keshri S, Kumar A, Naimuddin M, Priyanka P, Ranjan K, Shah A, Bharti M, Bhattacharya R, Bhattacharya S, Bhowmik D, Dutta S, Gomber B, Maity M, Nandan S, Palit P, Rout PK, Saha G, Sahu B, Sarkar S, Sharan M, Singh B, Thakur S, Behera PK, Behera SC, Kalbhor P, Muhammad A, Pradhan R, Pujahari PR, Sharma A, Sikdar AK, Dutta D, Jha V, Kumar V, Mishra DK, Naskar K, Netrakanti PK, Pant LM, Shukla P, Aziz T, Dugad S, Mohanty GB, Sarkar U, Banerjee S, Bhattacharya S, Chudasama R, Guchait M, Karmakar S, Kumar S, Majumder G, Mazumdar K, Mukherjee S, Roy D, Dube S, Kansal B, Pandey S, Rane A, Rastogi A, Sharma S, Bakhshiansohi H, Zeinali M, Chenarani S, Etesami SM, Khakzad M, Najafabadi MM, Felcini M, Grunewald M, Abbrescia M, Aly R, Aruta C, Colaleo A, Creanza D, De Filippis N, De Palma M, Di Florio A, Di Pilato A, Elmetenawee W, Fiore L, Gelmi A, Gul M, Iaselli G, Ince M, Lezki S, Maggi G, Maggi M, Margjeka I, Mastrapasqua V, Merlin JA, My S, Nuzzo S, Pompili A, Pugliese G, Ranieri A, Selvaggi G, Silvestris L, Simone FM, Venditti R, Verwilligen P, Abbiendi G, Battilana C, Bonacorsi D, Borgonovi L, Braibant-Giacomelli S, Brigliadori L, Campanini R, Capiluppi P, Castro A, Cavallo FR, Ciocca C, Cuffiani M, Dallavalle GM, Diotalevi T, Fabbri F, Fanfani A, Fontanesi E, Giacomelli P, Giommi L, Grandi C, Guiducci L, Iemmi F, Meo SL, Marcellini S, Masetti G, Navarria FL, Perrotta A, Primavera F, Rossi AM, Rovelli T, Siroli GP, Tosi N, Albergo S, Costa S, Mattia AD, Potenza R, Tricomi A, Tuve C, Barbagli G, Cassese A, Ceccarelli R, Ciulli V, Civinini C, D'Alessandro R, Fiori F, Focardi E, Latino G, Lenzi P, Lizzo M, Meschini M, Paoletti S, Seidita R, Sguazzoni G, Viliani L, Benussi L, Bianco S, Piccolo D, Bozzo M, Ferro F, Mulargia R, Robutti E, Tosi S, Benaglia A, Brivio F, Cetorelli F, Ciriolo V, De Guio F, Dinardo ME, Dini P, Gennai S, Ghezzi A, Govoni P, Guzzi L, Malberti M, Malvezzi S, Massironi A, Menasce D, Monti F, Moroni L, Paganoni M, Pedrini D, Ragazzi S, de Fatis TT, Valsecchi D, Zuolo D, Buontempo S, Carnevali F, Cavallo N, De Iorio A, Fabozzi F, Iorio AOM, Lista L, Meola S, Paolucci P, Rossi B, Sciacca C, Azzi P, Bacchetta N, Bisello D, Bortignon P, Bragagnolo A, Carlin R, Checchia P, De Castro Manzano P, Dorigo T, Gasparini F, Gasparini U, Hoh SY, Layer L, Margoni M, Meneguzzo AT, Presilla M, Ronchese P, Rossin R, Simonetto F, Strong G, Tosi M, Yarar H, Zanetti M, Zotto P, Zucchetta A, Zumerle G, Aime' C, Braghieri A, Calzaferri S, Fiorina D, Montagna P, Ratti SP, Re V, Ressegotti M, Riccardi C, Salvini P, Vai I, Vitulo P, Bilei GM, Ciangottini D, Fanò L, Lariccia P, Mantovani G, Mariani V, Menichelli M, Moscatelli F, Piccinelli A, Rossi A, Santocchia A, Spiga D, Tedeschi T, Azzurri P, Bagliesi G, Bertacchi V, Bianchini L, Boccali T, Bossini E, Castaldi R, Ciocci MA, Dell'Orso R, Domenico MRD, Donato S, Giassi A, Grippo MT, Ligabue F, Manca E, Mandorli G, Messineo A, Palla F, Ramirez-Sanchez G, Rizzi A, Rolandi G, Chowdhury SR, Scribano A, Shafiei N, Spagnolo P, Tenchini R, Tonelli G, Turini N, Venturi A, Verdini PG, Cavallari F, Cipriani M, Re DD, Marco ED, Diemoz M, Longo E, Meridiani P, Organtini G, Pandolfi F, Paramatti R, Quaranta C, Rahatlou S, Rovelli C, Santanastasio F, Soffi L, Tramontano R, Amapane N, Arcidiacono R, Argiro S, Arneodo M, Bartosik N, Bellan R, Bellora A, Antequera JB, Biino C, Cappati A, Cartiglia N, Cometti S, Costa M, Covarelli R, Demaria N, Kiani B, Legger F, Mariotti C, Maselli S, Migliore E, Monaco V, Monteil E, Monteno M, Obertino MM, Ortona G, Pacher L, Pastrone N, Pelliccioni M, Angioni GLP, Ruspa M, Salvatico R, Shchelina K, Siviero F, Sola V, Solano A, Soldi D, Staiano A, Tornago M, Trocino D, Belforte S, Candelise V, Casarsa M, Cossutti F, Da Rold A, Ricca GD, Sorrentino G, Vazzoler F, Dogra S, Huh C, Kim B, Kim DH, Kim GN, Lee J, Lee SW, Moon CS, Oh YD, Pak SI, Radburn-Smith BC, Sekmen S, Yang YC, Kim H, Moon DH, Kim TJ, Park J, Cho S, Choi S, Go Y, Hong B, Lee K, Lee KS, Lim J, Park J, Park SK, Yoo J, Goh J, Gurtu A, Kim HS, Kim Y, Almond J, Bhyun JH, Choi J, Jeon S, Kim J, Kim JS, Ko S, Kwon H, Lee H, Lee S, Oh BH, Oh M, Oh SB, Seo H, Yang UK, Yoon I, Jeon D, Kim JH, Ko B, Lee JSH, Park IC, Roh Y, Song D, Watson IJ, Ha S, Yoo HD, Choi Y, Jeong Y, Lee H, Lee Y, Yu I, Beyrouthy T, Maghrbi Y, Veckalns V, Ambrozas M, Juodagalvis A, Rinkevicius A, Tamulaitis G, Vaitkevicius A, Abdullah WATW, Yusli MN, Zolkapli Z, Benitez JF, Hernandez AC, Quijada JAM, Palomo LV, Ayala G, Castilla-Valdez H, De La Cruz-Burelo E, La Cruz IH, Lopez-Fernandez R, Herrera CAM, Navarro DAP, Sanchez-Hernandez A, Moreno SC, Barrera CO, Ramirez-Garcia M, Valencia FV, Pedraza I, Ibarguen HAS, Estrada CU, Mijuskovic J, Raicevic N, Krofcheck D, Bheesette S, Butler APH, Butler PH, Lokhovitskiy A, Lujan P, Ahmad A, Asghar MI, Awais A, Awan MIM, Hoorani HR, Khan WA, Shah MA, Shoaib M, Waqas M, Avati V, Grzanka L, Malawski M, Bialkowska H, Bluj M, Boimska B, Frueboes T, Górski M, Kazana M, Szleper M, Traczyk P, Zalewski P, Bunkowski K, Doroba K, Kalinowski A, Konecki M, Krolikowski J, Walczak M, Araujo M, Bargassa P, Bastos D, Boletti A, Faccioli P, Gallinaro M, Hollar J, Leonardo N, Niknejad T, Seixas J, Toldaiev O, Varela J, Afanasiev S, Budkouski D, Bunin P, Gavrilenko M, Golutvin I, Gorbunov I, Kamenev A, Karjavine V, Lanev A, Malakhov A, Matveev V, Palichik V, Perelygin V, Savina M, Seitova D, Shalaev V, Shmatov S, Shulha S, Smirnov V, Teryaev O, Voytishin N, Zarubin A, Zhizhin I, Gavrilov G, Golovtcov V, Ivanov Y, Kim V, Kuznetsova E, Murzin V, Oreshkin V, Smirnov I, Sosnov D, Sulimov V, Uvarov L, Volkov S, Vorobyev A, Andreev Y, Dermenev A, Gninenko S, Golubev N, Karneyeu A, Kirsanov M, Krasnikov N, Pashenkov A, Pivovarov G, Tlisov D, Toropin A, Epshteyn V, Gavrilov V, Lychkovskaya N, Nikitenko A, Popov V, Safronov G, Spiridonov A, Stepennov A, Toms M, Vlasov E, Zhokin A, Aushev T, Bychkova O, Danilov M, Parygin P, Popova E, Rusinov V, Andreev V, Azarkin M, Dremin I, Kirakosyan M, Terkulov A, Belyaev A, Boos E, Dubinin M, Dudko L, Ershov A, Gribushin A, Kaminskiy A, Klyukhin V, Kodolova O, Lokhtin I, Obraztsov S, Petrushanko S, Savrin V, Blinov V, Dimova T, Kardapoltsev L, Ovtin I, Skovpen Y, Azhgirey I, Bayshev I, Kachanov V, Kalinin A, Konstantinov D, Petrov V, Ryutin R, Sobol A, Troshin S, Tyurin N, Uzunian A, Volkov A, Babaev A, Okhotnikov V, Sukhikh L, Borchsh V, Ivanchenko V, Tcherniaev E, Adzic P, Dordevic M, Milenovic P, Milosevic J, Milosevic V, Aguilar-Benitez M, Maestre JA, Fernández AÁ, Bachiller I, Luna MB, Bedoya CF, Montoya CAC, Cepeda M, Cerrada M, Colino N, De La Cruz B, Peris AD, Ramos JPF, Flix J, Fouz MC, Lopez OG, Lopez SG, Hernandez JM, Josa MI, Holgado JL, Moran D, Tobar ÁN, Yzquierdo AP, Pelayo JP, Redondo I, Romero L, Navas SS, Soares MS, Gómez LU, Willmott C, de Trocóniz JF, Reyes-Almanza R, Gonzalez BA, Cuevas J, Erice C, Menendez JF, Folgueras S, Caballero IG, Cortezon EP, Álvarez CR, Sau JR, Bouza VR, Trapote A, Cifuentes JAB, Cabrillo IJ, Calderon A, Quero BC, Campderros JD, Fernandez M, Madrazo CF, Manteca PJF, Alonso AG, Gomez G, Rivero CM, Arbol PMRD, Matorras F, Gomez JP, Prieels C, Ricci-Tam F, Rodrigo T, Ruiz-Jimeno A, Scodellaro L, Trevisani N, Vila I, Garcia JMV, Jayananda MK, Kailasapathy B, Sonnadara DUJ, Wickramarathna DDC, Dharmaratna WGD, Liyanage K, Perera N, Wickramage N, Aarrestad TK, Abbaneo D, Alimena J, Auffray E, Auzinger G, Baechler J, Baillon P, Ball AH, Barney D, Bendavid J, Beni N, Bianco M, Bocci A, Brondolin E, Camporesi T, Garrido MC, Cerminara G, Chhibra SS, Cristella L, d'Enterria D, Dabrowski A, Daci N, David A, De Roeck A, Deile M, Maria RD, Dobson M, Dünser M, Dupont N, Elliott-Peisert A, Emriskova N, Fallavollita F, Fasanella D, Fiorendi S, Florent A, Franzoni G, Fulcher J, Funk W, Giani S, Gigi D, Gill K, Glege F, Gouskos L, Haranko M, Hegeman J, Iiyama Y, Innocente V, James T, Janot P, Kaspar J, Kieseler J, Komm M, Kratochwil N, Lange C, Laurila S, Lecoq P, Long K, Lourenço C, Malgeri L, Mallios S, Mannelli M, Meijers F, Mersi S, Meschi E, Moortgat F, Mulders M, Orfanelli S, Orsini L, Pantaleo F, Pape L, Perez E, Peruzzi M, Petrilli A, Petrucciani G, Pfeiffer A, Pierini M, Qu H, Quast T, Rabady D, Racz A, Rieger M, Rovere M, Sakulin H, Salfeld-Nebgen J, Scarfi S, Schäfer C, Schwick C, Selvaggi M, Sharma A, Silva P, Snoeys W, Sphicas P, Summers S, Tavolaro VR, Treille D, Tsirou A, Tsrunchev P, Onsem GPV, Verzetti M, Wanczyk J, Wozniak KA, Zeuner WD, Caminada L, Ebrahimi A, Erdmann W, Horisberger R, Ingram Q, Kaestli HC, Kotlinski D, Langenegger U, Missiroli M, Rohe T, Androsov K, Backhaus M, Berger P, Calandri A, Chernyavskaya N, De Cosa A, Dissertori G, Dittmar M, Donegà M, Dorfer C, Eble F, Gadek T, Espinosa TAG, Grab C, Hits D, Lustermann W, Lyon AM, Manzoni RA, Perez CM, Meinhard MT, Micheli F, Nessi-Tedaldi F, Niedziela J, Pauss F, Perovic V, Perrin G, Pigazzini S, Ratti MG, Reichmann M, Reissel C, Reitenspiess T, Ristic B, Ruini D, Becerra DAS, Schönenberger M, Stampf V, Steggemann J, Wallny R, Zhu DH, Amsler C, Botta C, Brzhechko D, Canelli MF, De Wit A, Burgo RD, Heikkilä JK, Huwiler M, Jofrehei A, Kilminster B, Leontsinis S, Macchiolo A, Meiring P, Mikuni VM, Molinatti U, Neutelings I, Rauco G, Reimers A, Robmann P, Cruz SS, Schweiger K, Takahashi Y, Adloff C, Kuo CM, Lin W, Roy A, Sarkar T, Yu SS, Ceard L, Chang P, Chao Y, Chen KF, Chen PH, Hou WS, Li YY, Lu RS, Paganis E, Psallidas A, Steen A, Yazgan E, Yu PR, Asavapibhop B, Asawatangtrakuldee C, Srimanobhas N, Boran F, Damarseckin S, Demiroglu ZS, Dolek F, Dumanoglu I, Eskut E, Gokbulut G, Guler Y, Guler EG, Hos I, Isik C, Kangal EE, Kara O, Topaksu AK, Kiminsu U, Onengut G, Ozdemir K, Polatoz A, Simsek AE, Tali B, Tok UG, Turkcapar S, Zorbakir IS, Zorbilmez C, Isildak B, Karapinar G, Ocalan K, Yalvac M, Akgun B, Atakisi IO, Cekmecelioglu YC, Gülmez E, Kaya M, Kaya O, Özçelik Ö, Tekten S, Yetkin EA, Cakir A, Cankocak K, Komurcu Y, Sen S, Sen FA, Cerci S, Kaynak B, Ozkorucuklu S, Cerci DS, Grynyov B, Levchuk L, Bhal E, Bologna S, Brooke JJ, Bundock A, Clement E, Cussans D, Flacher H, Goldstein J, Heath GP, Heath HF, Kreczko L, Krikler B, Paramesvaran S, Sakuma T, Nasr-Storey SSE, Smith VJ, Stylianou N, Taylor J, Titterton A, Bell KW, Belyaev A, Brew C, Brown RM, Cockerill DJA, Ellis KV, Harder K, Harper S, Linacre J, Manolopoulos K, Newbold DM, Olaiya E, Petyt D, Reis T, Schuh T, Shepherd-Themistocleous CH, Thea A, Tomalin IR, Williams T, Bainbridge R, Bloch P, Bonomally S, Borg J, Breeze S, Buchmuller O, Cepaitis V, Chahal GS, Colling D, Dauncey P, Davies G, Negra MD, Fayer S, Fedi G, Hall G, Hassanshahi MH, Iles G, Langford J, Lyons L, Magnan AM, Malik S, Martelli A, Nash J, Palladino V, Pesaresi M, Raymond DM, Richards A, Rose A, Scott E, Seez C, Shtipliyski A, Tapper A, Uchida K, Virdee T, Wardle N, Webb SN, Winterbottom D, Zecchinelli AG, Cole JE, Khan A, Kyberd P, Mackay CK, Reid ID, Teodorescu L, Zahid S, Abdullin S, Brinkerhoff A, Caraway B, Dittmann J, Hatakeyama K, Kanuganti AR, McMaster B, Pastika N, Sawant S, Smith C, Sutantawibul C, Wilson J, Bartek R, Dominguez A, Uniyal R, Hernandez AMV, Buccilli A, Charaf O, Cooper SI, Croce DD, Gleyzer SV, Henderson C, Perez CU, Rumerio P, West C, Akpinar A, Albert A, Arcaro D, Cosby C, Demiragli Z, Gastler D, Rohlf J, Salyer K, Sperka D, Spitzbart D, Suarez I, Tsatsos A, Yuan S, Zou D, Benelli G, Burkle B, Coubez X, Cutts D, Duh YT, Hadley M, Heintz U, Hogan JM, Laird E, Landsberg G, Lau KT, Lee J, Luo J, Narain M, Sagir S, Usai E, Wong WY, Yan X, Yu D, Zhang W, Brainerd C, Breedon R, De La Barca Sanchez MC, Chertok M, Conway J, Cox PT, Erbacher R, Jensen F, Kukral O, Lander R, Mulhearn M, Pellett D, Regnery B, Taylor D, Tripathi M, Yao Y, Zhang F, Bachtis M, Cousins R, Dasgupta A, Datta A, Hamilton D, Hauser J, Ignatenko M, Iqbal MA, Lam T, Mccoll N, Nash WA, Regnard S, Saltzberg D, Schnaible C, Stone B, Valuev V, Burt K, Chen Y, Clare R, Gary JW, Hanson G, Karapostoli G, Long OR, Manganelli N, Negrete MO, Si W, Wimpenny S, Zhang Y, Branson JG, Chang P, Cittolin S, Cooperstein S, Deelen N, Duarte J, Gerosa R, Giannini L, Gilbert D, Guiang J, Kansal R, Krutelyov V, Lee R, Letts J, Masciovecchio M, May S, Padhi S, Pieri M, Narayanan BVS, Sharma V, Tadel M, Vartak A, Würthwein F, Xiang Y, Yagil A, Amin N, Campagnari C, Citron M, Dorsett A, Dutta V, Incandela J, Kilpatrick M, Marsh B, Mei H, Ovcharova A, Quinnan M, Richman J, Sarica U, Stuart D, Wang S, Bornheim A, Cerri O, Dutta I, Lawhorn JM, Lu N, Mao J, Newman HB, Ngadiuba J, Nguyen TQ, Spiropulu M, Vlimant JR, Wang C, Xie S, Zhang Z, Zhu RY, Alison J, Andrews MB, Ferguson T, Mudholkar T, Paulini M, Vorobiev I, Cumalat JP, Ford WT, MacDonald E, Patel R, Perloff A, Stenson K, Ulmer KA, Wagner SR, Alexander J, Cheng Y, Chu J, Cranshaw DJ, Mcdermott K, Monroy J, Patterson JR, Quach D, Reichert J, Ryd A, Sun W, Tan SM, Tao Z, Thom J, Wittich P, Zientek M, Albrow M, Alyari M, Apollinari G, Apresyan A, Apyan A, Banerjee S, Bauerdick LAT, Beretvas A, Berry D, Berryhill J, Bhat PC, Burkett K, Butler JN, Canepa A, Cerati GB, Cheung HWK, Chlebana F, Cremonesi M, Petrillo KFD, Elvira VD, Freeman J, Gecse Z, Gray L, Green D, Grünendahl S, Gutsche O, Harris RM, Heller R, Herwig TC, Hirschauer J, Jayatilaka B, Jindariani S, Johnson M, Joshi U, Klabbers P, Klijnsma T, Klima B, Kortelainen MJ, Kwok KHM, Lammel S, Lincoln D, Lipton R, Liu T, Lykken J, Madrid C, Maeshima K, Mantilla C, Mason D, McBride P, Merkel P, Mrenna S, Nahn S, O'Dell V, Papadimitriou V, Pedro K, Pena C, Prokofyev O, Ravera F, Hall AR, Ristori L, Schneider B, Sexton-Kennedy E, Smith N, Soha A, Spiegel L, Stoynev S, Strait J, Taylor L, Tkaczyk S, Tran NV, Uplegger L, Vaandering EW, Weber HA, Woodard A, Acosta D, Avery P, Bourilkov D, Cadamuro L, Cherepanov V, Errico F, Field RD, Guerrero D, Joshi BM, Kim M, Konigsberg J, Korytov A, Lo KH, Matchev K, Menendez N, Mitselmakher G, Rosenzweig D, Shi K, Sturdy J, Wang J, Yigitbasi E, Zuo X, Adams T, Askew A, Diaz D, Habibullah R, Hagopian S, Hagopian V, Jo
Evaluación de microorganismos y sustratos obtenidos a partir de residuos orgánicos para la producción de celulasas
The necessity of reducing enzyme production costs and their wide use in several industrial sectors, have increased the interest on agro-industrial wastes valorization as substrates for the obtention of these bioproducts. Given that agricultural wastes are both a source of cellulose and cellulolytic microorganisms, the purpose of this study was the selection of previously isolated cellulolytic bacteria from wastes generated in marketplaces and, the evaluation of media formulated from this waste. 11 bacterial strains were grown in Mandel’s broth for 72 hours evaluating their cellulolytic activity at 30 and 50 ºC. To formulate the culture media, the cellulose, nitrogen and total organic carbon content in corn cob leaves and legume seed pods collected in a marketplace was determined. Three types of media were made using cellulose, sourced from waste, supplemented with peptone, ammonium sulfate and urea: the last three added as Nitrogen source. Medium A was formulated with chopped and dehydrated wastes. Medium B had the same treatment than medium A plus a liquefy step. Medium C was made with un-dehydrated and liquefied waste. From the 5 selected cellulolytic strains, C6M2 was cultured at 37 ºC on each of the three media and the enzyme activity was monitored for 96 hours of fermentation. Cellulase production was achieved in media A and B. Medium A presented higher production (19,82 ± 3,0 U/mL). On the other hand, no cellulolytic activity was evidenced in medium C. The corn cob leaves and legume seed pods, chopped and dehydrated, allow the cellulase production using the bacterium strain C6M2.La necesidad de reducir los costos de producción de las enzimas y su amplia utilización en diferentes sectores industriales, ha incrementado el interés en la valorización de residuos agroindustriales como sustratos para la obtención de estos bioproductos. Los residuos agrícolas son una fuente tanto de celulosa como de microorganismos productores de celulasas, por lo que este estudio tuvo como propósito la selección de bacterias celulolíticas aisladas previamente de residuos generados en plazas de mercado y la evaluación de medios formulados a partir de estos. 11 cepas bacterianas fueron cultivadas en caldo Mandels durante 72 horas, evaluando su actividad celulolítica a 30 y 50 ºC. Para la formulación de medios de cultivo se determinó el contenido de celulosa, nitrógeno y carbono orgánico total de los ameros de mazorca y vainas de leguminosas recolectados en una plaza de mercado. Se elaboraron tres medios de cultivo utilizando los residuos como fuente de celulosa y suplementándolos con peptona, sulfato de amonio y urea como fuente de nitrógeno. El medio A se formuló con residuos troceados y deshidratados, en el medio B estos tuvieron el mismo tratamiento adicionando un paso de licuado y para el medio C se utilizaron residuos licuados sin deshidratar. De las 5 cepas celulolíticas seleccionadas, C6M2 fue cultivada a 37 ºC en los tres medios y la actividad enzimática fue monitoreada durante las 96 horas de fermentación. En los medios A y B se evidenció la producción de celulasas, siendo A el que presentó una mayor actividad (19,82 ± 3,0 U/mL), mientras que en el medio C no se evidenció actividad celulolítica. En conclusión, la cepa bacteriana seleccionada C6M2 es capaz de producir celulasas en medios de cultivo formulados con ameros de mazorca y vainas de leguminosas troceados y deshidratados
- …
