Construcción de sistemas basados en redes de conocimiento para la gestión

Las Tecnologías de la Información no constituyen un fin en sí mismo, son un medio, sin duda un medio particular que afecta nuestra manera de pensar y constituye uno de los caminos para mejorar la calidad de la Investigación. Dentro de este contexto, nos corresponde como investigadores la generación de las ideas, el diseño de las experiencias, la aplicación y la reflexión evaluativa que aporte conocimiento para el mejoramiento de la acción. En este sentido, el Análisis de Redes de Conocimiento ha pasado de ser una metáfora sugerente para constituirse en un enfoque analítico y un paradigma, con sus principios teóricos, métodos de software para el análisis y líneas de investigación. Los Modelos propios surgidos de nuestras investigaciones anteriores y aplicados luego en cada Relevamiento, Análisis, Diseño e Implementación de las Organizaciones abordadas, nos develaron una hipótesis superadora: no solo podíamos construir la Red de Conocimiento para la Gestión, sino que se daban las condiciones para incorporar las propiedades específicas del tema abordado. Esto nos permitirá configurar los escenarios para implementar Sistemas que dan el sustento necesario para el control de las Operaciones, la gestión de trazabilidad, el acompañamiento Táctico y apoyo Estratégico a partir de los cambios de Estados y las relaciones entre las Tareas Estándares de una Red de Conocimiento para la Gestión.Eje: Innovación en Sistemas de Software.Red de Universidades con Carreras en Informática (RedUNCI

Tunable Collagen I Hydrogels for Engineered Physiological Tissue Micro-Environments

<div><p>Collagen I hydrogels are commonly used to mimic the extracellular matrix (ECM) for tissue engineering applications. However, the ability to design collagen I hydrogels similar to the properties of physiological tissues has been elusive. This is primarily due to the lack of quantitative correlations between multiple fabrication parameters and resulting material properties. This study aims to enable informed design and fabrication of collagen hydrogels in order to reliably and reproducibly mimic a variety of soft tissues. We developed empirical predictive models relating fabrication parameters with material and transport properties. These models were obtained through extensive experimental characterization of these properties, which include compression modulus, pore and fiber diameter, and diffusivity. Fabrication parameters were varied within biologically relevant ranges and included collagen concentration, polymerization pH, and polymerization temperature. The data obtained from this study elucidates previously unknown fabrication-property relationships, while the resulting equations facilitate informed <i>a priori</i> design of collagen hydrogels with prescribed properties. By enabling hydrogel fabrication by design, this study has the potential to greatly enhance the utility and relevance of collagen hydrogels in order to develop physiological tissue microenvironments for a wide range of tissue engineering applications.</p></div

Supplementary Video 2 from The stentable <i>in vitro</i> artery: an instrumented platform for endovascular device development and optimization

<b>3D cell morphology in the <i>in vitro</i> artery.</b> Cell nuclei are shown in blue (DAPI) while actin is shown in red (phalloidin). Z position is as shown in Figure 1a, with <i>z</i>=0 at the centerline of the <i>in vitro</i> artery, 0<<i>z</i><1.5 within the channel lumen, <i>z</i>=1.5 at the wall, and <i>z</i>>1.5 within the collagen hydrogel. Scale bar is 500 µm. Slice resolution is 12.5 µm

Fabrication parameters varied in experiments.

<p>Fabrication parameters varied in experiments.</p

Pore and fiber diameter of collagen hydrogels.

<p>Blue symbols with dashed lines represent hydrogels polymerized at 23°C while red symbols with solid lines represent hydrogels polymerized at 37°C. Data shown are mean + SE with N = 12. Significance was calculated for pH-averaged groups. At each concentration, the difference between means at T = 23°C and T = 37°C is significant at p<0.0001 for both pore diameter and fiber diameter.</p

Sensitivity of key hydrogel material properties to fabrication parameters.

<p>Sensitivities are obtained from the multiple regression coefficients, normalized to the largest coefficient in each model. The R² of the multivariate fit is indicated for each property. Analysis was performed on transformed (nondimensionalized) parameters. Only factors with p<0.01 (ANOVA) are shown.</p

Kinetics of collagen hydrogel polymerization.

<p>Blue square symbols with dashed lines represent hydrogels polymerized at 23°C while red triangle symbols with solid lines represent hydrogels polymerized at 37°C. As the effect of pH was statistically non-significant (p>0.05), data is averaged over all three pH groups. Data shown are mean + SE with N = 6–12. Significance was calculated for pH-averaged groups: temperature means comparison is indicated with # while concentration means comparison is indicated with *. At 37°C (solid red lines), concentration had no significant effect on either polymerization half-time or polymerization lag time.</p

Fiber structure images obtained from confocal reflectance.

<p>Images shown are for hydrogels polymerized at pH 7.4. Scale bar 25 μm.</p

Representative FRAP image sequence.

<p>Data shown is for 40 kDa dextran in 10 mg/ml collagen hydrogel polymerized at pH 7.4 and 23°C. Left to right: Prebleach; t = 0 s, t = 6 s, t = 12 s, t = 18 s. Scale bar 50 μm.</p

Rate of diffusion of dextran in collagen hydrogels.

<p>Blue square symbols with dashed lines represent hydrogels polymerized at 23°C while red triangle symbols with solid lines represent hydrogels polymerized at 37°C. Data shown are mean + SE with N = 72. Each measurement is averaged over pH and concentration. Significance was calculated for pH- and concentration-averaged groups: temperature means comparison is indicated with # while hydrodynamic radius means comparison is indicated with *.</p