Decrease and recovery of integrated information Φ during anesthesia and sleep on human functional magnetic resonance imaging.

Integrated information theory (IIT) offers an axiomatic framework based on phenomenological properties, allowing the quantification and characterization of consciousness through a measure known as Φ. According to IIT, Φ reflects the level of consciousness and is expected to decrease with loss of consciousness, although empirical data supporting this claim remain limited. In this study, we analyzed two functional magnetic resonance imaging (fMRI) datasets acquired during anesthesia (propofol-induced) and natural sleep to determine whether Φ changes with the loss and recovery of consciousness.

Exploring complex and integrated information during sleep.

The Integrated Information Theory is a theoretical framework that aims to elucidate the nature of consciousness by postulating that it emerges from the integration of information within a system, and that the degree of consciousness depends on the extent of information integration within the system. When consciousness is lost, the core complex of consciousness proposed by the Integrated Information Theory disintegrates, and Φ measures, which reflect the level of integrated information, are expected to diminish. This study examined the predictions of the Integrated Information Theory using the global brain network acquired via functional magnetic resonance imaging during various tasks and sleep.

Complex of global functional network as the core of consciousness.

Finding the neural basis of consciousness is challenging, and the distribution location of the core of consciousness remains inconclusive. Integrated information theory (IIT) argues that the posterior part of the brain is the hot zone of consciousness, especially phenological consciousness. The IIT has proposed a "main complex", a set of elements determined such that the information loss in a hierarchical partition approach is the largest among those of any other supersets and subsets, as the core of consciousness in a dynamic system.

Neural substrates of brand equity: applying a quantitative meta-analytical method for neuroimage studies.

Although the concept of brand equity has been investigated using various approaches, a comprehensive neural basis for brand equity remains unclear. The default mode network (DMN) as a mental process might influence brand equity related consumers' decision-making, as reported in the marketing literature. While studies on the overlapping regions between the DMN and value-based decision-making related brain regions have been reported in neuroscience literature, relationships between the DMN and a neural mechanism of brand equity have not been clarified.

Extended Invariant Information Clustering Is Effective for Leave-One-Site-Out Cross-Validation in Resting State Functional Connectivity Modeling.

Herein, we propose a new deep neural network model based on invariant information clustering (IIC), proposed by Ji et al., to improve the modeling performance of the leave-one-site-out cross-validation (LOSO-CV) for a multi-source dataset. Our Extended IIC (EIIC) is a type of contrastive learning; however, unlike the original IIC, it is characterized by transfer learning with labeled data pairs, but without the need for a data augmentation technique.

Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions.

Natural aldolase enzymes and created retro-aldolase protein catalysts often catalyze both aldol and retro-aldol reactions depending on the concentrations of the reactants and the products. Here, we report that the directionality of protein catalysts can be altered by replacing one amino acid. The protein catalyst derived from a scaffold of a previously reported retro-aldolase catalyst, catalyzed aldol reactions more efficiently than the previously reported retro-aldolase catalyst.

Task-induced brain functional connectivity as a representation of schema for mediating unsupervised and supervised learning dynamics in language acquisition.

Introduction: Based on the schema theory advanced by Rumelhart and Norman, we shed light on the individual variability in brain dynamics induced by hybridization of learning methodologies, particularly alternating unsupervised learning and supervised learning in language acquisition. The concept of "schema" implies a latent knowledge structure that a learner holds and updates as intrinsic to his or her cognitive space for guiding the processing of newly arriving information.

Methods: We replicated the cognitive experiment of Onnis and Thiessen on implicit statistical learning ability in language acquisition but included additional factors of prosodic variables and explicit supervised learning.

Evaluation of Task fMRI Decoding With Deep Learning on a Small Sample Dataset.

Recently, several deep learning methods have been applied to decoding in task-related fMRI, and their advantages have been exploited in a variety of ways. However, this paradigm is sometimes problematic, due to the difficulty of applying deep learning to high-dimensional data and small sample size conditions. The difficulties in gathering a large amount of data to develop predictive machine learning models with multiple layers from fMRI experiments with complicated designs and tasks are well-recognized.

Neural Substrates of Brand Love: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies.

Brand love is a critical concept for building a relationship between brands and consumers because falling in love with a brand can lead to strong brand loyalty. Despite the importance of marketing strategies, however, the underlying neural mechanisms of brand love remain unclear. The present study used an activation likelihood estimation meta-analysis method to investigate the neural correlates of brand love and compared it with those of maternal and romantic love.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns.

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution).

Neural basis of language switching in the brain: fMRI evidence from Korean-Chinese early bilinguals.

Using fMRI, we conducted two types of property generation task that involved language switching, with early bilingual speakers of Korean and Chinese. The first is a more conventional task in which a single language (L1 or L2) was used within each trial, but switched randomly from trial to trial. The other consists of a novel experimental design where language switching happens within each trial, alternating in the direction of the L1/L2 translation required.

Decoding semantics across fMRI sessions with different stimulus modalities: a practical MVPA study.

Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task.

Development of an immunochromatographic strip for simple detection of penicillin-binding protein 2'.

Infections with methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus (MR-CNS) are a serious problem in hospitals because these bacteria produce penicillin-binding protein 2' (PBP2' or PBP2a), which shows low affinity to β-lactam antibiotics. Furthermore, the bacteria show resistance to a variety of antibiotics. Identification of these pathogens has been carried out mainly by the oxacillin susceptibility test, which takes several days to produce a reliable result.

Trends of beta-lactam antibiotic susceptibility in blood-borne methicillin-resistant Staphylococcus aureus (MRSA) and their linkage to the staphylococcal cassette chromosome mec (SCCmec) type.

We investigated trends of beta-lactam antibiotic susceptibility in a total of 218 strains of blood-borne methicillin-resistant Staphylococcus aureus (MRSA) isolated from 1978 through 2002 at a middle-size geriatric hospital in Tokyo; the strains were classified by the MRSA marker, staphylococcal cassette chromosome mec (SCCmec). The minimum growth inhibitory concentration (MIC) of cloxacillin at which 50% of the strains were inhibited (MIC50) was 2 microg/ml in the strains isolated in 1978-1984 and 32 to 64 microg/ml in the strains isolated subsequently. Similarly, the MIC50 values of cefazolin and imipenem in the 1978-1984 isolates were 16 and View Article and Find Full Text PDF

Trends in the gentamicin and arbekacin susceptibility of methicillin-resistant Staphylococcus aureus and the genes encoding aminoglycoside-modifying enzymes.

It is generally accepted that methicillin-resistant Staphylococcus aureus (MRSA) is also resistant to aminoglycoside antibiotics. We investigated trends of gentamicin and arbekacin susceptibilities and the prevalence of the genes encoding aminoglycoside-modifying enzymes (AMEs) for a total of 218 strains of MRSA isolated from blood specimens obtained from 1978 through 2002 in one hospital. The minimum inhibitory concentrations of gentamicin at which 50% of the strains were inhibited (MIC(50)) were > or =128 and 32 microg/ml for isolates obtained from 1978 to 1984 and from 1985 to 1989, respectively, and 0.

Preliminary crystallographic analysis of the antibiotic discharge outer membrane lipoprotein OprM of Pseudomonas aeruginosa with an exceptionally long unit cell and complex lattice structure.

Crystals of the drug-discharge outer membrane protein OprM (MW = 50.9 kDa) of the MexAB-OprM multidrug transporter of Pseudomonas aeruginosa have been grown at 293 K in the presence of 2-methyl-2,4-propanediol and a combination of surfactants. The crystal belonged to space group R32, with unit-cell parameters a = b = 85.

Multidrug transporter MexB of Pseudomonas aeruginosa: overexpression, purification, and initial structural characterization.

Structural and functional characterization of the multidrug transporter, MexB, of Pseudomonas aeruginosa is significantly restricted due to a low yield of approximately 0.1 mg/L of culture from natural sources. To facilitate structural studies of this medically important transporter protein, we developed a large-scale system for expression of the genetically engineered recombinant, MexB, in the Escherichia coli cell.

Forceful large-scale expression of "problematic" membrane proteins.

We developed an Escherichia coli expression system for overproduction of a highly toxic membrane protein that is impossible to overexpress by traditionally used approaches. The method is based on combination of the genetic modifications of a bicistronic expression plasmid, stabilization of a synthesized protein, and selection of a compatible expression host. This enabled us to enhance the expression level of a toxic membrane protein 30-50 times compared with expression in the native state and to obtain 3-5mg of a highly purified functionally active protein per liter of culture.

Crystal structure of the drug discharge outer membrane protein, OprM, of Pseudomonas aeruginosa: dual modes of membrane anchoring and occluded cavity end.

The OprM lipoprotein of Pseudomonas aeruginosa is a member of the MexAB-OprM xenobiotic-antibiotic transporter subunits that is assumed to serve as the drug discharge duct across the outer membrane. The channel structure must differ from that of the porin-type open pore because the protein facilitates the exit of antibiotics but not the entry. For better understanding of the structure-function linkage of this important pump subunit, we studied the x-ray crystallographic structure of OprM at the 2.

Role of the membrane fusion protein in the assembly of resistance-nodulation-cell division multidrug efflux pump in Pseudomonas aeruginosa.

The tripartite xenobiotic-antibiotic transporter of Pseudomonas aeruginosa consists of the inner membrane transporter (e.g., MexB, MexY), the periplasmic membrane-fusion-protein (e.

Crystal structure of the membrane fusion protein, MexA, of the multidrug transporter in Pseudomonas aeruginosa.

The MexAB-OprM efflux pump of Pseudomonas aeruginosa is central to multidrug resistance of this organism, which infects immunocompromised hospital patients. The MexA, MexB, and OprM subunits were assumed to function as the membrane fusion protein, the body of the transporter, and the outer membrane channel protein, respectively. For better understanding of this important xenobiotic transporter, we show the x-ray crystallographic structure of MexA at a resolution of 2.

Mutations affecting DNA-binding activity of the MexR repressor of mexR-mexA-mexB-oprM operon expression.

We have isolated 25 MexR mutants that retained their dimerizing ability but were unable to bind mexOP DNA. Surprisingly, 20 mutations were located in the hydrophobic core region at alpha4, W1, alpha2, alpha3, and beta2, and only 3 were in positively charged residues. These results verified that DNA binding is mediated by distinct regions of MexR and showed the importance of the hydrophobic core region of the DNA-binding domain.