138 research outputs found
Recent advances in supercritical fluid dyeing
Supercritical fluid dyeing is a promising technology that was first proposed in the 1980s to overcome the high energy demand and water consumption of conventional textile coloration. This review covers its advances from 2014 to the present, from the successful industrial implementation of supercritical fluid dyeing of polyethylene terephthalate to the most recent results obtained for the dyeing of other synthetic and natural textiles. Specific attention is also dedicated to the most innovative applications of supercritical fluid dyeing such as the functionalisation of textile and non-textile substrates, which may give rise to the development of other sustainable processes or novel advanced materials in the near future
Tranexamic acid-loaded mesoporous silica microspheres as a hemostatic material
Bleeding management is considered essential for saving life both in the military and civilian field. There is still a need to develop topical hemostats that can stop bleeding and be used easily in the trauma sites. The aim of this work is to develop a hemostat based on mesoporous silica particles with large pores for bleeding control. Mesoporous silica microspheres (MSM) with particle size of 1.5 − 5 µm and pores diameter of 25 nm have been successfully synthesized and, for the first time, loaded with tranexamic acid (TXA) with a content of 4.7%w/w. The hemostatic activity of both the pure material and TXA-loaded material (TXA@MSM) was investigated. It was found that the blood clotting time was significantly shortened by both systems with respect to control. A hemolysis assay was performed to evaluate the hemolytic activity of MSM, and the result indicated that the material was blood compatible. A preliminary TXA in vitro release test was performed, showing the complete release of TXA from the carrier within one hour. Considering the above results, TXA@MSM can be considered a promising material for the development of new hemostats
Supercritical solvent impregnation of different drugs in mesoporous nanostructured zno
Supercritical solvent impregnation (SSI) is a green unconventional technique for preparing amorphous drug formulations. A mesoporous nanostructured ZnO (mesoNsZnO) carrier with 8-nm pores, spherical-nanoparticle morphology, and an SSA of 75 m2/g has been synthesized and, for the first time, subjected to SSI with poorly water-soluble drugs. Ibuprofen (IBU), clotrimazole (CTZ), and hydrocortisone (HC) were selected as highly, moderately, and poorly CO2-soluble drugs. Powder X-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, nitrogen adsorption analysis, and ethanol extraction coupled with ultraviolet spectroscopy were employed to characterize the samples and quantify drug loading. Successful results were obtained with IBU and CTZ while HC loading was negligible, which could be related to different solubilities in CO2, drug size, and polarity. Successful SSI resulted in amorphous multilayer confinement of the drug. The mesoNsZnO-IBU system showed double drug loading than the mesoNsZnO-CTZ one, with a maximum uptake of 0.24 g/g. Variation of contact time during SSI of the mesoNsZnO-IBU system showed that drug loading triplicated between 3 and 8 h with an additional 30% increment between 8 h and 24 h. SSI did not affect the mesoNsZnO structure, and the presence of the adsorbed drug reduced the chemisorption of CO2 on the carrier surface
Procesamiento eficiente de grafos masivos para aplicaciones en redes sociales
Las redes sociales digitales se han convertido sin dudas en una de las aplicaciones más populares de Internet y atraen a millones de usuarios que, de forma implÃcita, generan estructuras con propiedades emergentes que surgen del comportamiento global.
Existen diversos problemas interesantes a resolver como la formación de comunidades, la recomendación de enlaces y el estudio de la polarización de opiniones. En todos los casos, resulta motivador tanto el proceso de formación como el estudio de algoritmos eficientes para el procesamiento. Estos problemas se pueden abordar estudiando el grafo subyacente, el contenido de las publicaciones o combinaciones de ambos.
En este trabajo se proponen diversas lÃneas de investigación sobre los temas mencionados, con aplicaciones a grafos masivos y problemas reales. Se abordan tanto problemas algorÃtmicos en cuanto a la eficiencia como las interacciones entre usuarios y diferentes escenarios.Eje: Bases de Datos y MinerÃa de Datos.Red de Universidades con Carreras en Informátic
Procesamiento eficiente de grafos masivos para aplicaciones en redes sociales
Las redes sociales digitales se han convertido sin dudas en una de las aplicaciones más populares de Internet y atraen a millones de usuarios que, de forma implÃcita, generan estructuras con propiedades emergentes que surgen del comportamiento global.
Existen diversos problemas interesantes a resolver como la formación de comunidades, la recomendación de enlaces y el estudio de la polarización de opiniones. En todos los casos, resulta motivador tanto el proceso de formación como el estudio de algoritmos eficientes para el procesamiento. Estos problemas se pueden abordar estudiando el grafo subyacente, el contenido de las publicaciones o combinaciones de ambos.
En este trabajo se proponen diversas lÃneas de investigación sobre los temas mencionados, con aplicaciones a grafos masivos y problemas reales. Se abordan tanto problemas algorÃtmicos en cuanto a la eficiencia como las interacciones entre usuarios y diferentes escenarios.Eje: Bases de Datos y MinerÃa de Datos.Red de Universidades con Carreras en Informátic
Procesamiento eficiente de grafos masivos para aplicaciones en redes sociales
Las redes sociales digitales se han convertido sin dudas en una de las aplicaciones más populares de Internet y atraen a millones de usuarios que, de forma implÃcita, generan estructuras con propiedades emergentes que surgen del comportamiento global.
Existen diversos problemas interesantes a resolver como la formación de comunidades, la recomendación de enlaces y el estudio de la polarización de opiniones. En todos los casos, resulta motivador tanto el proceso de formación como el estudio de algoritmos eficientes para el procesamiento. Estos problemas se pueden abordar estudiando el grafo subyacente, el contenido de las publicaciones o combinaciones de ambos.
En este trabajo se proponen diversas lÃneas de investigación sobre los temas mencionados, con aplicaciones a grafos masivos y problemas reales. Se abordan tanto problemas algorÃtmicos en cuanto a la eficiencia como las interacciones entre usuarios y diferentes escenarios.Eje: Bases de Datos y MinerÃa de Datos.Red de Universidades con Carreras en Informátic
Algoritmos de aprendizaje automático para respuestas en tiempo real sobre entornos masivos de datos
En la actualidad existen incontables fuentes de información en tiempo real que provienen de redes de sensores, plataformas de observación del tiempo, mediciones de gases, observación de la tierra desde plataformas satelitales, ciudades inteligentes, entre un sin número de instrumentos que censan y transmiten datos. A su vez hay una creciente demanda por el desarrollo de herramientas para poder extraer conocimiento a partir de esos grandes repositorios de datos. El aprendizaje automático es un área de la inteligencia artificial donde sus métodos contribuyen en el proceso de descubrimiento de conocimiento para la toma de decisiones inteligentes.
Las demandas para la extracción de conocimiento en entornos de Big Data ha acrecentado el interés por la utilización de técnicas tradicionales de aprendizaje automático en distintos problemas de repositorios masivos de datos y también en entornos de flujos (o streaming) de datos donde muchas veces no es posible su almacenamiento, pero se requiere tomar decisiones en tiempo real conforme se leen los datos.Eje: Bases de Datos y MinerÃa de Datos.Red de Universidades con Carreras en Informátic
Cyclodextrin Complexes of Reduced Bromonoscapine in Guar Gum Microspheres Enhance Colonic Drug Delivery
Here, we report improved solubility and enhanced colonic delivery of reduced bromonoscapine (Red-Br-Nos), a cyclic ether brominated analogue of noscapine, upon encapsulation of its cyclodextrin (CD) complexes in bioresponsive guar gum microspheres (GGM). Phase−solubility analysis suggested that Red-Br-Nos complexed with β-CD and methyl-β-CD in a 1:1 stoichiometry, with a stability constant (Kc) of 2.29 × 103 M−1 and 4.27 × 103 M−1. Fourier transforms infrared spectroscopy indicated entrance of an O−CH2 or OCH3−C6H4−OCH3 moiety of Red-Br-Nos in the β-CD or methyl-β- CD cavity. Furthermore, the cage complex of Red-Br-Nos with β-CD and methyl-β-CD was validated by several spectral techniques. Rotating frame Overhauser enhancement spectroscopy revealed that the Ha proton of the OCH3−C6H4−OCH3 moiety was closer to the H5 proton of β-CD and the H3 proton of the methyl-β-CD cavity. The solubility of Red-Br-Nos in phosphate buffer saline (PBS, pH ∼ 7.4) was improved by ∼10.7-fold and ∼21.2-fold when mixed with β-CD and methyl-β-CD, respectively. This increase in solubility led to a favorable decline in the IC50 by ∼2-fold and ∼3-fold for Red-Br-Nos−β-CD-GGM and Red-Br-Nos−methyl-β-CD-GGM formulations respectively, compared to free Red-Br-Nos−β-CD and Red-Br-Nos−methyl-β-CD in human colon HT-29 cells. GGM-bearing drug complex formulations were found to be highly cytotoxic to the HT-29 cell line and further effective with simultaneous continuous release of Red-Br-Nos from microspheres. This is the first study to showing the preparation of drug-complex loaded GGMS for colon delivery of Red-Br-Nos that warrants preclinical assessment for the effective management of colon cancer
An integrated cell atlas of the lung in health and disease
Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1 + profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas. </p
Aplicação de modelos não-lineares para descrever a evolução de caracterÃsticas de crescimento e carcaça em bovinos da raça Hereford
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