Publications by authors named "J P Geibel"

Article Synopsis
  • - In xenotransplantation research, genetically modified pigs are crucial, with traditional methods like somatic cell nuclear transfer being lengthy and complex, prompting the need for more efficient gene editing techniques.
  • - The study explores the use of CRISPR/Cas9 and different delivery methods (electroporation vs. microinjection) to edit genes in pig zygotes, aiming to create triple-knock-out embryos targeting key porcine xenoantigens.
  • - Results showed that higher voltage during electroporation improved gene editing efficiency without significantly affecting embryo development, but mosaicism remained a common issue across all methods, highlighting the need for further optimization in genome editing approaches.
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The effective planning and allocation of resources in modern breeding programs is a complex task. Breeding program design and operational management have a major impact on the success of a breeding program and changing parameters such as the number of selected/phenotyped/genotyped individuals in the breeding program will impact genetic gain, genetic diversity, and costs. As a result, careful assessment and balancing of design parameters is crucial, taking into account the trade-offs between different breeding goals and associated costs.

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Additive manufacturing (3D printing) has been deployed across multiple platforms to fabricate bioengineered tissues. We demonstrate the use of a Thermal Inkjet Pipette System (TIPS) for targeted delivery of cells onto manufactured substrates to design bio-bandages. Two cell lines - HEK 293 (kidney) and K7M2 wt (bone) - were applied using TIPS.

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In recent years, breeding programs have increased significantly in size and complexity, with various highly interdependent parameters and many contrasting breeding goals. As a result, resource allocation in these programs has become more complex, and deriving an optimal breeding strategy has become increasingly challenging. To address this, a common practice is to reduce the optimization problem to a set of scenarios that differ only in a few parameters and can therefore be analyzed in detail.

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Background: This paper highlights the relationships between economic weights, genetic progress, and phenotypic progress in genomic breeding programs that aim at generating genetic progress in complex, i.e., multi-trait, breeding objectives via a combination of estimated breeding values for different trait complexes.

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