Two theories of origin of the land-plant sporophyte: Which is left standing?

Questions concerning the two competing theories of the development of alternating generations in land plants, the homologous theory and the antithetic theory, have never been fully resolved. In the majority of recent accounts there appears to have been increasing de facto support (if one considers the ontogenetic processes and phylogenetic consequences discussed) for the antithetic theory. However, this preference is usually not plainly stated (as such) in these discussions, and some support has also continued for the homologous theory. The crux of both theories (homologous and antithetic) centers upon how the sporophyte may have originated in the life cycle. One problem with the homologous theory is that it is not made explicit how the development of a dependent sporophyte could have occurred in the life cycle (when the precedent organisms are considered to have had free-living, putatively similar, gametophytes and sporophytes). The antithetic theory, by contrast, offers a definite ontogenetic mechanism or process (retention of the zygote on the gametophyte, delay of zygotic meiosis, with zygotic mitoses occurring first) by which a dependent sporophyte might have originated and persisted, in the context of a life cycle formerly lacking a sporophyte generation. Also, a review of a variety of evidence (morphological, cytological, biochemical, etc.) would appear to lend more support to the antithetic theory than to the homologous theory. In discussing types of algae now known to be most clearly related to land plants (i.e., charophytes, particularly advanced forms), the type of life cycle exhibited by these particular algae (haplontic, with zygotic meiosis; no sporophyte present) suggests that only an antithetic origin of the sporophyte in land plants is actually feasible.     

Partial characterization of protein kinase-catalyzed phosphorylation of low molecular weight proteins in purified preparations of pigeon heart sarcolemma and sarcoplasmic reticulum

Pigeon heart microsomes contain three minor size protein kinase substrates of minimal molecular weights of 22 000, 15 000, and 11 500, as estimated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. When the microsomes were partially loaded with calcium oxalate and subjected to rate zonal and isopynic centrifugations in sucrose density gradient columns, the 22 000 and the 15 000 dalton proteins settled in the heaviest fraction, which was composed mainly of vesicles of sarcoplasmic reticular membranes; the 11 500 dalton protein was concentrated in the lightest fractions, which consisted chiefly of vesicles of sarcolemmal origin. During incubation of the membrane fractions with Mg[γ-³²P]ATP significant amounts of ³²P were incorporated into all these proteins. Incorporation of ³²P into the 15 000 dalton protein was moderately and ³²P incorporation into the 22 000 dalton protein was markedly enhanced in the presence of exogenous soluble cyclic AMP-dependent protein kinase and cyclic AMP. The phosphorylation of the three proteins was virtually unaffected by CA²⁺ concentrations up to 0.1 mM and by ethyleneglycol-bis(β-aminoethylether)-N,N′-tetraacetic acid in the absence of added Ca²⁺.Phosphorylation of the 22 000 and the 11 500 dalton proteins occurred mainly at serine residues. In the 15 000 dalton protein threonine residues were the main site of endogenous phosphorylation. Nearly equal amounts of [³²P]-phosphate were incorporated into threonine and serine residues of this protein when phosphorylation was supported by exogenous cyclic AMP-dependent protein kinase and cyclic AMP.The 15 000 dalton protein could be removed from its membrane attachment by extraction with an acidic chloroform/methanol mixture. This step opens the way for the purification of this membrane-bound protein kinase substrate.     

Population Level Inference for Multivariate MEG Analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation.