Use of designer nucleases for targeted gene and genome editing in plants

The ability to efficiently inactivate or replace genes in model organisms allowed a rapid expansion of our understanding of many of the genetic, biochemical, molecular and cellular mechanisms that support life. With the advent of new techniques for manipulating genes and genomes that are applicable not only to single-celled organisms, but also to more complex organisms such as animals and plants, the speed with which scientists and biotechnologists can expand fundamental knowledge and apply that knowledge to improvements in medicine, industry and agriculture is set to expand in an exponential fashion. At the heart of these advancements will be the use of gene editing tools such as zinc finger nucleases, modified meganucleases, hybrid DNA/ RNA oligonucleotides, TAL effector nucleases and modified CRISPR/Cas9. Each of these tools has the ability to precisely target one specific DNA sequence within a genome and (except for DNA/ RNA oligonucleotides) to create a double-stranded DNA break. DNA repair to such breaks sometimes leads to gene knockouts or gene replacement by homologous recombination if exogenously supplied homologous DNA fragments are made available. Genome rearrangements are also possible to engineer. Creation and use of such genome rearrangements, gene knockouts and gene replacements by the plant science community is gaining significant momentum. To document some of this progress and to explore the technology’s longer term potential, this review highlights present and future uses of designer nucleases to greatly expedite research with model plant systems and to engineer genes and genomes in major and minor crop species for enhanced food production

Procesamiento de imágenes biomédicas

Este texto electrónico está pensado para apoyar los recursos de procesamiento de imágenes del posgrado en Ingeniería Biomédica. Se basa en la experiencia de más de diez años de impartir cursos en los niveles de educación continua, licenciatur y posgrado en la Universidad Autónoma Metropolitana, Iztapalapa, México; la Universidad Tecnológica de Compiege, Frnacia; y la Universidad Nacional de Entre Ríos, Argentina. Es un curso introductorio que se puede impartir en los primeros años de un posgrado o incluso en licenciatura. Aun cuando su enfoque se orienta a las imágenes biomédicas, puede emplearse como texto para cualquier tipo de imágenes, ya sean de percepción remota, de microscopía o de biotecnología. Los temas tratados abarcan la percepción de imágenes, los diversos tipos de procesamientos posibles, el filtrado, la segmentación, la morfología, la compresión de imágenes y las aplicaciones

Assisted quantification of abdominal adipose tissue based on magnetic resonance images

An assisted method to segment Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT) from Magnetic Resonance Imaging (MRI) slices is presented. The segmentation process, called shape-based segmentation, consists in three main steps: 1) to draw a series of closed curves at different slices that separates the abdominal structures of interest, 2) to generate a 3D model from the closed curves for each abdominal structure by using shape-based interpolation and 3) to apply a segmentation algorithm to define the adipose tissue. The 3D models considerably simplify the problem since the abdominal structures are separated, and in turn, this reduces the possibility of large segmentation errors. In addition, a fully automatic segmentation procedure was also implemented. Twenty slices of MRI at the abdominal region for each of twelve subjects were analysed. The results of the shape-based and automatic segmentation were compared with the expert segmentation carried out in the slice located at the umbilicus level. Correlation Coefficient (CC) and volume error (VE) were used as performance measures. The comparison between the expert and shape-based segmentation for SAT yielded results of CC= 0.974 and VE=-0.01 ± 5.8 cm3, while for VAT the performance indexes were CC= 0.993 and VE= 0.9 ± 1.8 cm3. The results suggest that the shape-based segmentation provides an accurate and simple assessment of the abdominal adiposity with minimal human intervention and it could be used as a simple tool in clinics