Jelly-like Microbial Mats over Subsurface Fields of Gas Hydrates at the St. Petersburg Methane Seep (Central Baikal)

Jelly-like microbial mat samples were collected from benthic surfaces at the St. Petersburg methane seep located in Central Baikal. The concentrations of certain ions, specifically chloride, bromide, sulphate, acetate, iron, calcium, and magnesium, were 2–40 times higher in the microbial mats than those in the pore and bottom water. A large number of diatom valves, cyanobacteria, and filamentous, rod-shaped and coccal microorganisms were found in the samples of bacterial mats using light, epifluorescence and scanning microscopy.Comparative analysis of a 16S rRNA gene fragment demonstrated the presence of bacteria and archaea belonging to the following classes and phyla: Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Verrucomicrobia, Cytophaga-Flavobacteria-Bacteroidetes, Cyanobacteria, and Euryarchaeota. The chemical composition and phylogenetic structure of the microbial community showed that the life activity of the mat occurs due to methane and its derivatives involved. Values of δ¹³C for the microbial mats varied from ?73.6‰ to ?65.8‰ and for animals from ?68.9‰ to ?36.6‰. Functional genes of the sequential methane oxidation (pmoA and mxaF) and different species of methanotrophic bacteria inhabiting cold ecosystems were recorded in the total DNA. Like in other psychroactive communities, the destruction of organic substances forming formed as a result of methanotrophy, terminates at the stage of acetate formation in the microbial mats of Lake Baikal (1,400 m depth). Its further transformation is limited by hydrogen content and carried out in the subsurface layers of sediments.     

Site-directed mutagenesis of cysteine residues of <Emphasis Type="Italic">Luciola mingrelica</Emphasis> firefly luciferase

Single mutants (C62S, C62V, C86S, C146S, C164S), double mutants (C62/146S, C62/164S, C86/146S, C146/164S), and triple mutant C62/146/164S of the Luciola mingrelica firefly luciferase carrying C-terminal His6-tag were obtained on the basis of plasmid pETL7 by site-directed mutagenesis. Bioluminescence and fluorescence spectra were not altered by the introduced mutations. In the case of mutants C86S, C86/146S, C62/164S, and the triple mutant C62/146/164S, the K _m^ATP and K_m^LH₂ K_m^{LH_2 } values were increased by a factor of ∼1.5–1.9. Their expression level, specific activity, and thermal stability were significantly decreased. The other mutations had almost no effect on the K _m^ATP and K_m^LH₂ K_m^{LH_2 } values, specific activity, and thermal stability of the enzyme. Thermal stability of the C146S mutant was increased by a factor of ∼2 and 1.3 at 37 and 42°C, respectively. The possible mechanism of the influence of these mutations on properties and structure of the enzyme is discussed.     

Inferring on the Intentions of Others by Hierarchical Bayesian Learning

Inferring on others'' (potentially time-varying) intentions is a fundamental problem during many social transactions. To investigate the underlying mechanisms, we applied computational modeling to behavioral data from an economic game in which 16 pairs of volunteers (randomly assigned to “player” or “adviser” roles) interacted. The player performed a probabilistic reinforcement learning task, receiving information about a binary lottery from a visual pie chart. The adviser, who received more predictive information, issued an additional recommendation. Critically, the game was structured such that the adviser''s incentives to provide helpful or misleading information varied in time. Using a meta-Bayesian modeling framework, we found that the players'' behavior was best explained by the deployment of hierarchical learning: they inferred upon the volatility of the advisers'' intentions in order to optimize their predictions about the validity of their advice. Beyond learning, volatility estimates also affected the trial-by-trial variability of decisions: participants were more likely to rely on their estimates of advice accuracy for making choices when they believed that the adviser''s intentions were presently stable. Finally, our model of the players'' inference predicted the players'' interpersonal reactivity index (IRI) scores, explicit ratings of the advisers'' helpfulness and the advisers'' self-reports on their chosen strategy. Overall, our results suggest that humans (i) employ hierarchical generative models to infer on the changing intentions of others, (ii) use volatility estimates to inform decision-making in social interactions, and (iii) integrate estimates of advice accuracy with non-social sources of information. The Bayesian framework presented here can quantify individual differences in these mechanisms from simple behavioral readouts and may prove useful in future clinical studies of maladaptive social cognition.     

Structure of actinoidins A and B

The sequence of the amino acid residues in the peptide chain of aglycone was shown on the basis of the data concerning the splitting of actinoidin aglycon and the products of its partial acid hydrolysis by various methods. It was found that the free COOH-group of actinoidin belonged to he glycine residue of the dioxyphenyl nucleus of actinoidinic amino acid. The site of the actinosamine attachment to aglycon was determined. The final structure of actinoidins A and B is suggested.     

Generative embedding for model-based classification of fMRI data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in 'hidden' physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups.     

Characterization of urokinase type plasminogen activator modified by phenylglyoxal

A chemical modification of single-chain urokinase-type plasminogen activator (scu-PA) with phenylglyoxal under mild conditions resulted in the scu-PA derivatives with various numbers of the modified Arg residues. The study of properties of the resulting derivatives demonstrated that the modification of 4-12 Arg residues did not cause any loss of the activator, fibrinolytic, and potential amidase activities of the activator. The scu-PA with four modified Arg residues was found to be the most stable derivative in human blood plasma; it causes a more efficient lysis of plasma clots than the native activator. Three of four modified Arg residues are supposed to be within the 178RRHRGGS184 cluster, which was localized in the superficial loop of the scu-PA globule and was shown to interact with the complementary series of negatively charged residues in the molecule of the main plasma inhibitor PAI-1. The neutralization of positively charged Arg residues in this cluster decreases the affinity of scu-PA and the double chain urokinase-type plasminogen activator for PAI-1, which results in an enhancement of the stability in plasma and the fibrinolytic efficiency of the activator. The English version of the paper: Russian Journal of Bioorganic Chemistry, 2002, vol. 28, no. 4; see also http://www.maik.ru.     

Micromechanical tests of adhesion dynamics between neutrophils and immobilized ICAM-1

Strong, integrin-mediated adhesion of neutrophils to endothelium during inflammation is a dynamic process, requiring a conformational change in the integrin molecule to increase its affinity for its endothelial counterreceptors. To avoid general activation of the cell, Mg(2+) was used to induce the high-affinity integrin conformation, and micromechanical methods were used to determine adhesion probability to beads coated with the endothelial ligand ICAM-1. Neutrophils in Mg(2+) bind to the beads with much greater frequency and strength than in the presence of Ca(2+). An increase in adhesion strength and frequency was observed with both increasing temperature and contact duration (from 2 s to 1 min, 21 or 37 degrees C). The dependence of adhesion probability on contact time or receptor density yielded estimates of the effective reverse rate constant, k(r), and the equilibrium association constant, K(a), for binding of neutrophils to ICAM-1 coated surfaces in Mg(2+): k(r) approximately 0.7 s(-1) and the product K(a)rho(c) approximately 2.4 x 10(-4), where rho(c) is the density of integrin on the cell surface.     

Quantitative amino acid makeup and the characteristics of the amino groups of ristomycin and the products of its partial acid hydrolysis]

The quantitative amino acid composition of ristomycin A, a glycopeptide antibiotic, peptides I-IV (from partial acid hydrolysis of the antibiotic) and their dinitrophenylic derivatives was determined. It was shown that both ristomycin and free peptides I-IV contained one residue of ristomycinic acid and one residue of actinoidinic acid, diamino-dicarbonic amino acids of the glycylphenolic type. Peptides I-IV had close molecular weights, i.e. 1100-1200 and differed from each other in the gradually increasing numbers of NH2- and COON- groups, from one in peptide I to four in peptide IV. The quantitative amino acid analysis of the dinitrophenylic derivatives of ristomycin and peptides I-IV showed that the free NH2-group in peptide I belonged to ristomycinic acid, the same as in the antibiotic, while in peptides III-IV at least one of the free NH2-groups belonged to ristomycinic acid and the other belonged to actinoidinic acid.