276 research outputs found

    In vitro dissolution characteristics of patent, generic and similar brands of naproxen in various dissolution media

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    Purpose: To investigate the dissolution properties of various brands of naproxen in four dissolution media in order to forecast their biological availability. Methods: Dissolution tests were carried out in a dissolution tester with 48 tablets of different naproxen brands in 900 mL of 0.1 M phosphate buffer, pH 7.4. Subsequently, the medium was modified with 600 mL of buffer plus 300 mL of cola drink, grapefruit or milk. Each sample was taken and brought to a concentration approximating that of a reference solution. Absorbance at 332 nm was determined and the dissolution, Q, was calculated (Q values ≥ 80.0 ± 5 % were acceptable). Results: Dissolution in buffer was > 85 %. In cola drink, it was < 80 %, while in grapefruit juice, it was in the range of 7 - 68 %. Using 2-way ANOVA, these media and the three naproxen brands showed significant differences (F = 68.90, p = 0.0000; F = 23.18, p = 0.0000). With Fisher's LSD test, two of these media contributed consistently to dissolution, and the three drug brands showed statistically different dissolution profiles (p ≤ 0.05). Conclusion: Caution must be exercised cola drink, grapefruit juice and milk are used to administered naproxen as the biological availability of the drug may be altered

    Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy

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    Methane (CH) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH. To address this limitation, we developed novel CH prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH production (g CH/animal·d, ANIM-B models) and CH yield (g CH/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin’s concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH emissions from sheep, providing valuable insights for future research and mitigation strategies.Te authors gratefully acknowledge funding for this project from the USDA National Institute of Food and Agriculture (Award number: 2014-67003-21979). Te animal and microbial data originated from a study funded by the Pastoral Greenhouse Gas Research Consortium (www.pggrc.co.nz)

    Easily Multiplexable Immunoplatform to Assist Heart Failure Diagnosis through Amperometric Determination of Galectin-3

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    This work reports the first electrochemical immunoassay involving magnetic microbeads (MBs) for the determination of galectin-3 (Gal-3), a β-galactosidase-binding lectin that acts as mediator of heart failure (HF). MBs-captured sandwich-type immune complexes and amperometric detection at disposable screen-printed carbon electrodes were used. The immunoplatform showed a detection limit of 8.3 pg mL−1, good reproducibility, and excellent selectivity. The endogenous concentration of Gal-3 in human plasma from HF patients was determined with results in agreement with those obtained using ELISA. The multiplexing feasibility of the developed immunoplatform was demonstrated for the simultaneous determination of Gal-3 and N-terminal pro-brain natriuretic peptide (NT-proBNP).Fil: Piguillem Palacios, Sofía Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina. Universidad Complutense de Madrid; EspañaFil: María Gamella. Universidad Complutense de Madrid; EspañaFil: García de Frutos, Pablo. INSTITUTO DE INVESTIGACIONES BIOMEDICAS AUGUST PI I SUNYER (IDIBAPS);Fil: Batlle, Montserrat. No especifíca;Fil: Yáñez Sedeño, Paloma. Universidad Complutense de Madrid; EspañaFil: Messina, Germán Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; ArgentinaFil: Fernández Baldo, Martín Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; ArgentinaFil: Campuzano, Susana. Universidad Complutense de Madrid; EspañaFil: Pedrero, María. Universidad Complutense de Madrid; EspañaFil: Pingarrón, José M.. Universidad Complutense de Madrid; Españ

    Ayotzinapa y la crisis del estado neoliberal mexicano

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    ¿Qué pasó en Ayotzinapa? Es la pregunta que surgió el 26 de septiembre de 2014, que no encuentra una respuesta satisfactoria pese a la intervención de actores de distintas instancias, niveles y nacionalidades, y al esbozo de múltiples hipótesis sobre los enfrentamientos registrados en Iguala, Guerrero, que derivaron en la muerte de varias personas y la desaparición de 43 estudiantes de la Normal Rural “Isidro Burgos”, en una tragedia que evidenció la crisis que atraviesa el estado mexicano y que afecta a todo el país. A partir de lo acontecido en Ayotzinapa y con base en la teoría general de los campos de Pierre Bourdieu y su propuesta de análisis teórico metodológico sobre el estado, en esta obra se realiza un análisis de la práctica sistemática y generalizada de las desapariciones forzadas en México, con el fin de ofrecer otra manera de comprender el entretejido político–económico–social que hace posible este grave fenómeno, que desgarra tanto a familias como a la comunidad. La herida abierta por Ayotzinapa sangra y el objetivo último de este libro es contribuir a evitar que se cierre en tanto no se responda la interrogante de qué pasó ahí y que crímenes de lesa humanidad como este sigan aconteciendo en México.ITESO, A.C

    A Potassium Metal-Organic Framework based on Perylene- 3,4,9,10-tetracarboxylate as Sensing Layer for Humidity Actuators

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    We have synthesized a novel three-dimensional metal-organic-framework (MOF) based on the perylene-3,4,9,10-tetracarboxylate linker and potassium as metallic centre. We report the formation of this K-based MOF using conventional routes with water as solvent. This material displays intense green photoluminescence at room temperature, and displays an aggregation dependent quenching. Correlation of the optical properties with the crystalline packing was confirmed by DFT calculations. We also demonstrate its potential to build humidity actuators with a reversible and reproducible response, with a change of 5 orders of magnitudes in its impedance at about 40% relative humidity (RH). This 3D-MOF is based on an interesting perylene derivative octadentate ligand, a moiety with interesting fluorescent properties and known component in organic semiconductors. To the best of our knowledge, this is the first time to build such a printed and flexible actuator towards humidity with a reversible response, enabling precise humidity threshold monitoring.This work was supported by the Junta de Andalucía (FQM-1484, and FQM-195). Red Guipuzcoana de Ciencia, Tecnología e Innovación (OF188/2017) and University of the Basque Country (GIU14/01, EHUA16/32). BB acknowledges funding by RyC-2012–10381 contract and computational resources provided by the RES and Alhambra supercomputing facilities. This work was also supported by the German Research Foundation (DFG) and the Technical University of Munich within the Open Access Publishing Funding Programme

    The effect of agitation speed, enzyme loading and substrate concentration on enzymatic hydrolysis of cellulose from brewer’s spent grain

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    Brewer’s spent grain components (cellulose, hemicellulose and lignin) were fractionated in a two-step chemical pretreatment process using dilute sulfuric acid and sodium hydroxide solutions. The cellulose pulp produced was hydrolyzed with a cellulolytic complex, Celluclast 1.5 L, at 45 ºC to convert the cellulose into glucose. Several conditions were examined: agitation speed (100, 150 and 200 rpm), enzyme loading (5, 25 and 45 FPU/g substrate), and substrate concentration (2, 5 and 8% w/v), according to a 2 3 full factorial design aiming to maximize the glucose yield. The obtained results were interpreted by analysis of variance and response surface methodology. The optimal conditions for enzymatic hydrolysis of brewer’s spent grain were identified as 100 rpm, 45 FPU/g and 2% w/v substrate. Under these conditions, a glucose yield of 93.1% and a cellulose conversion (into glucose and cellobiose) of 99.4% was achieved. The easiness of glucose release from BSG makes this substrate a raw material with great potential to be used in bioconversion processes.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo), Brazil. Novozymes ( FAPESP )Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

    Prediction of enteric methane production, yield and intensity of beef cattle using an intercontinental database

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    Enteric methane (CH4) production attributable to beef cattle contributes to global greenhouse gas emissions. Reliably estimating this contribution requires extensive CH4 emission data from beef cattle under different management conditions worldwide. The objectives were to: 1) predict CH4 production (g d¬-1 animal-1), yield [g (kg dry matter intake; DMI)-1] and intensity [g (kg average daily gain)-1] using an intercontinental database (data from Europe, North America, Brazil, Australia and South Korea); 2) assess the impact of geographic region, and of higher- and lower-forage diets. Linear models were developed by incrementally adding covariates. A K-fold cross-validation indicated that a CH4 production equation using only DMI that was fitted to all available data had a root mean square prediction error (RMSPE; % of observed mean) of 31.2%. Subsets containing data with ≥ 25% and ≤ 18% dietary forage contents had an RMSPE of 30.8 and 34.2%, with the all-data CH4 production equation, whereas these errors decreased to 29.3 and 28.4%, respectively, when using CH4 prediction equations fitted to these subsets. The RMSPE of the ≥ 25% forage subset further decreased to 24.7% when using multiple regression. Europe- and North America-specific subsets predicted by the best performing ≥ 25% forage multiple regression equation had RMSPE of 24.5 and 20.4%, whereas these errors were 24.5 and 20.0% with region-specific equations, respectively. The developed equations had less RMSPE than extant equations evaluated for all data (22.5 vs. 23.2%), for higher-forage (21.2 vs. 23.1%), but not for the lower-forage subsets (28.4 vs. 27.9%). Splitting the dataset by forage content did not improve CH4 yield or intensity predictions. Predicting beef cattle CH4 production using energy conversion factors, as applied by the Intergovernmental Panel on Climate Change, indicated that adequate forage content-based and region-specific energy conversion factors improve prediction accuracy and are preferred in national or global inventories

    Pseudomonas aeruginosa Bloodstream Infections in Patients with Cancer: Differences between Patients with Hematological Malignancies and Solid Tumors

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    Objectives: To assess the clinical features and outcomes of Pseudomonas aeruginosa bloodstream infection (PA BSI) in neutropenic patients with hematological malignancies (HM) and with solid tumors (ST), and identify the risk factors for 30-day mortality. Methods: We performed a large multicenter, retrospective cohort study including onco-hematological neutropenic patients with PA BSI conducted across 34 centers in 12 countries (January 2006-May 2018). Episodes occurring in hematologic patients were compared to those developing in patients with ST. Risk factors associated with 30-day mortality were investigated in both groups. Results: Of 1217 episodes of PA BSI, 917 occurred in patients with HM and 300 in patients with ST. Hematological patients had more commonly profound neutropenia (0.1 x 10(9) cells/mm) (67% vs. 44.6%; p < 0.001), and a high risk Multinational Association for Supportive Care in Cancer (MASCC) index score (32.2% vs. 26.7%; p = 0.05). Catheter-infection (10.7% vs. 4.7%; p = 0.001), mucositis (2.4% vs. 0.7%; p = 0.042), and perianal infection (3.6% vs. 0.3%; p = 0.001) predominated as BSI sources in the hematological patients, whereas pneumonia (22.9% vs. 33.7%; p < 0.001) and other abdominal sites (2.8% vs. 6.3%; p = 0.006) were more common in patients with ST. Hematological patients had more frequent BSI due to multidrug-resistant P. aeruginosa (MDRPA) (23.2% vs. 7.7%; p < 0.001), and were more likely to receive inadequate initial antibiotic therapy (IEAT) (20.1% vs. 12%; p < 0.001). Patients with ST presented more frequently with septic shock (45.8% vs. 30%; p < 0.001), and presented worse outcomes, with increased 7-day (38% vs. 24.2%; p < 0.001) and 30-day (49% vs. 37.3%; p < 0.001) case-fatality rates. Risk factors for 30-day mortality in hematologic patients were high risk MASCC index score, IEAT, pneumonia, infection due to MDRPA, and septic shock. Risk factors for 30-day mortality in patients with ST were high risk MASCC index score, IEAT, persistent BSI, and septic shock. Therapy with granulocyte colony-stimulating factor was associated with survival in both groups. Conclusions: The clinical features and outcomes of PA BSI in neutropenic cancer patients showed some differences depending on the underlying malignancy. Considering these differences and the risk factors for mortality may be useful to optimize their therapeutic management. Among the risk factors associated with overall mortality, IEAT and the administration of granulocyte colony-stimulating factor were the only modifiable variables
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