PubMed · 14372626
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P BURTIN. 1954. [Immunochemical diffusion methods in a gelatinous medium].. https://pubmed.ncbi.nlm.nih.gov/14372626/
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Tomato was one of the first crops for which a genetic transformation system was reported involving regeneration by organogenesis from Agrobacterium-transformed explants. Since the initial reports, various factors have been studied that affect the efficiency of tomato transformation and the technique has been useful for the isolation and identification of many genes involved in plant disease resistance, morphology and development. In this method, cotyledon explants from in vitro-grown seedlings are precultured overnight on a tobacco suspension feeder layer. The explants are then inoculated with Agrobacterium and returned to the feeder layer for a 2-d period of cocultivation. After cocultivation, the explants are transferred to an MS-based selective regeneration medium containing zeatin. Regenerated shoots are then rooted on a separate selective medium. This protocol has been used with several tomato cultivars and routinely yields transformation efficiencies of 10-15%.
OBJECTIVE: It is now widely accepted that increasing the number of replacement embryos (>3 embryos per embryo transfer [ET]) is associated with an increased risk of multiple pregnancies. While embryo reduction is often proposed when there is a high risk of multiple pregnancies, it is a difficult decision for the couple. For this reason, different studies have focused on single embryo transfer, more precisely blastocyst transfer. The aim of the study is to confirm that phosphate-free culture media can be used to generate greater quality embryos. METHODS AND RESULTS: We carried out a study to compare the efficacy of human tubal fluid (HTF) versus preimplantation stage one (P1) as culture media for assisted reproductive therapy (ART). In 109 nonselected patients, we obtained an embryo fertilization rate with HTF and P1 culture media of 58.6 and 62.5% (P = 0.003), respectively. After 48 and 72 h, the morphology was similar for both P1 and HTF embryos in most patients. However, in the same patients, when HTF embryo quality was low (15.4%), P1 embryo quality was significantly higher 68.7% (P = 0.002). Some embryos were transferred at 48 h and some at 72 h after retrieval, in a randomized manner. We transferred a maximum of up to three embryos per ET. The implantation rate was significantly different; at 48 h, it was 6.8 and 12.2% for HTF and P1, respectively (P = 0.02). The pregnancy rate was 17.1% for HTF embryos and 23.7% for P1 embryos (P = 0.02). CONCLUSIONS: Therefore, we observed a significant difference between P1 and HTF in the fertilization rate, in embryo quality, in implantation rate and in pregnancy rate. But the most important difference between this study and others is that every patient was the control of herself, so we eliminated every variable.
Many variables and their interactions can affect a biotechnological process. Testing a large number of variables and all their possible interactions is a cumbersome task and its cost can be prohibitive. Several screening strategies, with a relatively low number of experiments, can be used to find which variables have the largest impact on the process and estimate the magnitude of their effect. One approach for process screening is the use of experimental designs, among which fractional factorial and Plackett-Burman designs are frequent choices. Other screening strategies involve the use of artificial neural networks (ANNs). The advantage of ANNs is that they have fewer assumptions than experimental designs, but they render black-box models (i.e., little information can be extracted about the process mechanics). In this paper, we simulate a biotechnological process (fed-batch growth of baker's yeast) to analyze and compare the effect of random experimental errors of different magnitudes and statistical distributions on experimental designs and ANNs. Except for the situation in which the error has a normal distribution and the standard deviation is constant, it was not possible to determine a clear-cut rule for favoring one screening strategy over the other. Instead, we found that the data can be better analyzed using both strategies simultaneously.