A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Deciphering a neural code for vision

Deciphering the information that eyes, ears, and other sensory organs transmit to the brain is important for understanding the neural basis of behavior. Recordings from single sensory nerve cells have yielded useful insights, but single neurons generally do not mediate behavior; networks of neurons do. Monitoring the activity of all cells in a neural network of a behaving animal, however, is not yet possible. Taking an alternative approach, we used a realistic cell-based model to compute the ensemble of neural activity generated by one sensory organ, the lateral eye of the horseshoe crab, Limulus polyphemus. We studied how the neural network of this eye encodes natural scenes by presenting to the model movies recorded with a video camera mounted above the eye of an animal that was exploring its underwater habitat. Model predictions were confirmed by simultaneously recording responses from single optic nerve fibers of the same animal. We report here that the eye transmits to the brain robust “neural images” of objects having the size, contrast, and motion of potential mates. The neural code for such objects is not found in ambiguous messages of individual optic nerve fibers but rather in patterns of coherent activity that extend over small ensembles of nerve fibers and are bound together by stimulus motion. Integrative properties of neurons in the first synaptic layer of the brain appear well suited to detecting the patterns of coherent activity. Neural coding by this relatively simple eye helps explain how horseshoe crabs find mates and may lead to a better understanding of how more complex sensory organs process information.

Three-dimensional structure of poliovirus receptor bound to poliovirus

Poliovirus initiates infection by binding to its cellular receptor (Pvr). We have studied this interaction by using cryoelectron microscopy to determine the structure, at 21-Å resolution, of poliovirus complexed with a soluble form of its receptor (sPvr). This density map aided construction of a homology-based model of sPvr and, in conjunction with the known crystal structure of the virus, allowed delineation of the binding site. The virion does not change significantly in structure on binding sPvr in short incubations at 4°C. We infer that the binding configuration visualized represents the initial interaction that is followed by structural changes in the virion as infection proceeds. sPvr is segmented into three well-defined Ig-like domains. The two domains closest to the virion (domains 1 and 2) are aligned and rigidly connected, whereas domain 3 diverges at an angle of ≈60°. Two nodules of density on domain 2 are identified as glycosylation sites. Domain 1 penetrates the “canyon” that surrounds the 5-fold protrusion on the capsid surface, and its binding site involves all three major capsid proteins. The inferred pattern of virus–sPvr interactions accounts for most mutations that affect the binding of Pvr to poliovirus.

Duplication and functional divergence in the chalcone synthase gene family of Asteraceae: evolution with substrate change and catalytic simplification.

Plant-specific polyketide synthase genes constitute a gene superfamily, including universal chalcone synthase [CHS; malonyl-CoA:4-coumaroyl-CoA malonyltransferase (cyclizing) (EC 2.3.1.74)] genes, sporadically distributed stilbene synthase (SS) genes, and atypical, as-yet-uncharacterized CHS-like genes. We have recently isolated from Gerbera hybrida (Asteraceae) an unusual CHS-like gene, GCHS2, which codes for an enzyme with structural and enzymatic properties as well as ontogenetic distribution distinct from both CHS and SS. Here, we show that the GCHS2-like function is encoded in the Gerbera genome by a family of at least three transcriptionally active genes. Conservation within the GCHS2 family was exploited with selective PCR to study the occurrence of GCHS2-like genes in other Asteraceae. Parsimony analysis of the amplified sequences together with CHS-like genes isolated from other taxa of angiosperm subclass Asteridae suggests that GCHS2 has evolved from CHS via a gene duplication event that occurred before the diversification of the Asteraceae. Enzyme activity analysis of proteins produced in vitro indicates that the GCHS2 reaction is a non-SS variant of the CHS reaction, with both different substrate specificity (to benzoyl-CoA) and a truncated catalytic profile. Together with the recent results of Durbin et al. [Durbin, M. L., Learn, G. H., Jr., Huttley, G. A. & Clegg, M. T. (1995) Proc. Natl. Acad. Sci. USA 92, 3338-3342], our study confirms a gene duplication-based model that explains how various related functions have arisen from CHS during plant evolution.