Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes

The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.

The right hippocampus leads the bilateral integration of gamma-parsed lateralized information

It is unclear whether the two hippocampal lobes convey similar or different activities and how they cooperate. Spatial discrimination of electric fields in anesthetized rats allowed us to compare the pathway-specific field potentials corresponding to the gamma-paced CA3 output (CA1 Schaffer potentials) and CA3 somatic inhibition within and between sides. Bilateral excitatory Schaffer gamma waves are generally larger and lead from the right hemisphere with only moderate covariation of amplitude, and drive CA1 pyramidal units more strongly than unilateral waves. CA3 waves lock to the ipsilateral Schaffer potentials, although bilateral coherence was weak. Notably, Schaffer activity may run laterally, as seen after the disruption of the connecting pathways. Thus, asymmetric operations promote the entrainment of CA3-autonomous gamma oscillators bilaterally, synchronizing lateralized gamma strings to converge optimally on CA1 targets. The findings support the view that interhippocampal connections integrate different aspects of information that flow through the left and right lobes.

Analysis of the genome content of Lactococcus garvieae by genomic interspecies microarray hybridization

BACKGROUND Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH) experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. RESULTS The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of >or= 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258) have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. CONCLUSIONS In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.