An experiment was conducted to determine whether pregnancy rates following the transfer of in vitro-produced embryos to heat-stressed cows could be improved by 1) culturing embryos in the presence of IGF-I and 2) treating recipients with GnRH. Lactating Holstein cows (n = 260) were synchronized using a timed ovulation protocol. Embryos were produced in vitro and cultured with or without 100 ng/mL of IGF-I. On d 7 after anticipated ovulation (d 0), a single embryo was transferred to all recipients with a palpable corpus luteum (n = 210). A subset of recipients (n = 164) was injected with either GnRH or placebo on d 11. Plasma progesterone concentrations on d 0 and 7 were used to determine the synchrony of recipients. Pregnancy was diagnosed at d 53 and 81 by rectal palpation. Among all recipients, transfer of IGF-I-treated embryos increased pregnancy rate at d 53 (P < 0.05) and tended to increase pregnancy rate at d 81 (P < 0.06). Calving rate also tended to be higher for recipients that received IGF-I-treated embryos (P < 0.07). Among the subset of synchronized recipients (n = 190), pregnancy rate at d 53 and d 81 and calving rate were higher (P < 0.05) for IGF-I-treated embryos. The GnRH tended to increase pregnancy rate at d 53 for all recipients (P < 0.08) and the subset of synchronized recipients (P < 0.10). There were no effects of GnRH (P > 0.10) for pregnancy rate at d 81 and calving rate. The overall proportion of male calves was 64.3%. There was no effect (P > 0.10) of embryo treatment or GnRH on the birth weight or sex ratio of calves. Results of this experiment indicate that treatment of embryos with IGF-I can improve pregnancy and calving rates following transfer of in vitro-produced embryos. Further research is necessary to determine whether the treatment of recipients with GnRH is a practical approach to increase pregnancy rates following in vitro embryo transfer.

Automatic registration of multimodal images involves algorithmically estimating the coordinate transformation required to align the data sets. Most existing methods in the literature are unable to cope with registration of image pairs with large nonoverlapping field of view (FOV). We propose a robust algorithm, based on matching dominant local frequency image representations, which can cope with image pairs with large nonoverlapping FOV. The local frequency representation naturally allows for processing the data at different scales/resolutions, a very desirable property from a computational efficiency view point. Our algorithm involves minimizing-over all rigid/affine transformations--the integral of the squared error (ISE or L2 E) between a Gaussian model of the residual and its true density function. The residual here refers to the difference between the local frequency representations of the transformed (by an unknown transformation) source and target data. We present implementation results for image data sets, which are misaligned magnetic resonance (MR) brain scans obtained using different image acquisition protocols as well as misaligned MR-computed tomography scans. We experimently show that our L2E-based scheme yields better accuracy over the normalized mutual information.

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