Coalescent estimates of HIV-1 generation time in vivo

The generation time of HIV Type 1 (HIV-1) in vivo has previously been estimated using a mathematical model of viral dynamics and was found to be on the order of one to two days per generation. Here, we describe a new method based on coalescence theory that allows the estimate of generation times to be derived by using nucleotide sequence data and a reconstructed genealogy of sequences obtained over time. The method is applied to sequences obtained from a long-term nonprogressing individual at five sampling occasions. The estimate of viral generation time using the coalescent method is 1.2 days per generation and is close to that obtained by mathematical modeling (1.8 days per generation), thus strengthening confidence in estimates of a short viral generation time. Apart from the estimation of relevant parameters relating to viral dynamics, coalescent modeling also allows us to simulate the evolutionary behavior of samples of sequences obtained over time.

Determining RNA solution structure by segmental isotopic labeling and NMR: application to Caenorhabditis elegans spliced leader RNA 1.

Recent developments in multidimensional heteronuclear NMR spectroscopy and large-scale synthesis of uniformly 13C- and 15N-labeled oligonucleotides have greatly improved the prospects for determination of the solution structure of RNA. However, there are circumstances in which it may be advantageous to label only a segment of the entire RNA chain. For example, in a larger RNA molecule the structural question of interest may reside in a localized domain. Labeling only the corresponding nucleotides simplifies the spectrum and resonance assignments because one can filter proton spectra for coupling to 13C and 15N. Another example is in resolving alternative secondary structure models that are indistinguishable in imino proton connectivities. Here we report a general method for enzymatic synthesis of quantities of segmentally labeled RNA molecules required for NMR spectroscopy. We use the method to distinguish definitively two competing secondary structure models for the 5' half of Caenorhabditis elegans spliced leader RNA by comparison of the two-dimensional [15N] 1H heteronuclear multiple quantum correlation spectrum of the uniformly labeled sample with that of a segmentally labeled sample. The method requires relatively small samples; solutions in the 200-300 microM concentration range, with a total of 30 nmol or approximately 40 micrograms of RNA in approximately 150 microliters, give strong NMR signals in a short accumulation time. The method can be adapted to label an internal segment of a larger RNA chain for study of localized structural problems. This definitive approach provides an alternative to the more common enzymatic and chemical footprinting methods for determination of RNA secondary structure.

Invariance between subjects of brain wave representations of language

In three experiments, electric brain waves of 19 subjects were recorded under several different experimental conditions for two purposes. One was to test how well we could recognize which sentence, from a set of 24 or 48 sentences, was being processed in the cortex. The other was to study the invariance of brain waves between subjects. As in our earlier work, the analysis consisted of averaging over trials to create prototypes and test samples, to both of which Fourier transforms were applied, followed by filtering and an inverse transformation to the time domain. A least-squares criterion of fit between prototypes and test samples was used for classification. In all three experiments, averaging over subjects improved the recognition rates. The most significant finding was the following. When brain waves were averaged separately for two nonoverlapping groups of subjects, one for prototypes and the other for test samples, we were able to recognize correctly 90% of the brain waves generated by 48 different sentences about European geography.

Direct molecular level measurements of the electrostatic properties of a protein surface

In this work, we used direct measurements with the surface force apparatus to determine the pH-dependent electrostatic charge density of a single binding face of streptavidin. Mean field calculations have been used with considerable success to model electrostatic potential fields near protein surfaces, but these models and their inherent assumptions have not been tested directly at the molecular level. Using the force apparatus and immobilized, oriented monolayers of streptavidin, we measured a pI of 5–5.5 for the biotin-binding face of the protein. This differs from the pI of 6.3 for the soluble protein and confirms that we probed the local electrostatic features of the macromolecule. With finite difference solutions of the linearized Poisson–Boltzmann equation, we then calculated the pH-dependent charge densities adjacent to the same face of the protein. These calculated values agreed quantitatively with those obtained by direct force measurements. Although our study focuses on the pH-dependence of surface electrostatics, this direct approach to probing the electrostatic features of proteins is applicable to investigations of any perturbations that alter the charge distribution of the surfaces of immobilized molecules.

Invariance of brain-wave representations of simple visual images and their names

In two experiments, electric brain waves of 14 subjects were recorded under several different conditions to study the invariance of brain-wave representations of simple patches of colors and simple visual shapes and their names, the words blue, circle, etc. As in our earlier work, the analysis consisted of averaging over trials to create prototypes and test samples, to both of which Fourier transforms were applied, followed by filtering and an inverse transformation to the time domain. A least-squares criterion of fit between prototypes and test samples was used for classification. The most significant results were these. By averaging over different subjects, as well as trials, we created prototypes from brain waves evoked by simple visual images and test samples from brain waves evoked by auditory or visual words naming the visual images. We correctly recognized from 60% to 75% of the test-sample brain waves. The general conclusion is that simple shapes such as circles and single-color displays generate brain waves surprisingly similar to those generated by their verbal names. These results, taken together with extensive psychological studies of auditory and visual memory, strongly support the solution proposed for visual shapes, by Bishop Berkeley and David Hume in the 18th century, to the long-standing problem of how the mind represents simple abstract ideas.

Brain wave recognition of words

Electrical and magnetic brain waves of seven subjects under three experimental conditions were recorded for the purpose of recognizing which one of seven words was processed. The analysis consisted of averaging over trials to create prototypes and test samples, to both of which Fourier transforms were applied, followed by filtering and an inverse transformation to the time domain. The filters used were optimal predictive filters, selected for each subject and condition. Recognition rates, based on a least-squares criterion, varied widely, but all but one of 24 were significantly different from chance. The two best were above 90%. These results show that brain waves carry substantial information about the word being processed under experimental conditions of conscious awareness.

Brain-wave recognition of sentences

Electrical and magnetic brain waves of two subjects were recorded for the purpose of recognizing which one of 12 sentences or seven words auditorily presented was processed. The analysis consisted of averaging over trials to create prototypes and test samples, to each of which a Fourier transform was applied, followed by filtering and an inverse transformation to the time domain. The filters used were optimal predictive filters, selected for each subject. A still further improvement was obtained by taking differences between recordings of two electrodes to obtain bipolar pairs that then were used for the same analysis. Recognition rates, based on a least-squares criterion, varied, but the best were above 90%. The first words of prototypes of sentences also were cut and pasted to test, at least partially, the invariance of a word’s brain wave in different sentence contexts. The best result was above 80% correct recognition. Test samples made up only of individual trials also were analyzed. The best result was 134 correct of 288 (47%), which is promising, given that the expected recognition number by chance is just 24 (or 8.3%). The work reported in this paper extends our earlier work on brain-wave recognition of words only. The recognition rates reported here further strengthen the case that recordings of electric brain waves of words or sentences, together with extensive mathematical and statistical analysis, can be the basis of new developments in our understanding of brain processing of language.

Syntax processing by auditory cortical neurons in the FM–FM area of the mustached bat Pteronotus parnellii

Syntax denotes a rule system that allows one to predict the sequencing of communication signals. Despite its significance for both human speech processing and animal acoustic communication, the representation of syntactic structure in the mammalian brain has not been studied electrophysiologically at the single-unit level. In the search for a neuronal correlate for syntax, we used playback of natural and temporally destructured complex species-specific communication calls—so-called composites—while recording extracellularly from neurons in a physiologically well defined area (the FM–FM area) of the mustached bat’s auditory cortex. Even though this area is known to be involved in the processing of target distance information for echolocation, we found that units in the FM–FM area were highly responsive to composites. The finding that neuronal responses were strongly affected by manipulation in the time domain of the natural composite structure lends support to the hypothesis that syntax processing in mammals occurs at least at the level of the nonprimary auditory cortex.