Stable Neural Population Dynamics in the Regression Subspace for Continuous and Categorical Task Parameters in Monkeys.

Neural population dynamics provide a key computational framework for understanding information processing in the sensory, cognitive, and motor functions of the brain. They systematically depict complex neural population activity, dominated by strong temporal dynamics as trajectory geometry in a low-dimensional neural space. However, neural population dynamics are poorly related to the conventional analytical framework of single-neuron activity, the rate-coding regime that analyzes firing rate modulations using task parameters. To link the rate-coding and dynamic models, we developed a variant of state-space analysis in the regression subspace, which describes the temporal structures of neural modulations using continuous and categorical task parameters. In macaque monkeys, using two neural population datasets containing either of two standard task parameters, continuous and categorical, we revealed that neural modulation structures are reliably captured by these task parameters in the regression subspace as trajectory geometry in a lower dimension. Furthermore, we combined the classical optimal-stimulus response analysis (usually used in rate-coding analysis) with the dynamic model and found that the most prominent modulation dynamics in the lower dimension were derived from these optimal responses. Using those analyses, we successfully extracted geometries for both task parameters that formed a straight geometry, suggesting that their functional relevance is characterized as a unidimensional feature in their neural modulation dynamics. Collectively, our approach bridges neural modulation in the rate-coding model and the dynamic system, and provides researchers with a significant advantage in exploring the temporal structure of neural modulations for pre-existing datasets.

Dynamic prospect theory: Two core decision theories coexist in the gambling behavior of monkeys and humans.

Research in the multidisciplinary field of neuroeconomics has mainly been driven by two influential theories regarding human economic choice: prospect theory, which describes decision-making under risk, and reinforcement learning theory, which describes learning for decision-making. We hypothesized that these two distinct theories guide decision-making in a comprehensive manner. Here, we propose and test a decision-making theory under uncertainty that combines these highly influential theories. Collecting many gambling decisions from laboratory monkeys allowed for reliable testing of our model and revealed a systematic violation of prospect theory's assumption that probability weighting is static. Using the same experimental paradigm in humans, substantial similarities between these species were uncovered by various econometric analyses of our dynamic prospect theory model, which incorporates decision-by-decision learning dynamics of prediction errors into static prospect theory. Our model provides a unified theoretical framework for exploring a neurobiological model of economic choice in human and nonhuman primates.

A neuronal prospect theory model in the brain reward circuitry.

Prospect theory, arguably the most prominent theory of choice, is an obvious candidate for neural valuation models. How the activity of individual neurons, a possible computational unit, obeys prospect theory remains unknown. Here, we show, with theoretical accuracy equivalent to that of human neuroimaging studies, that single-neuron activity in four core reward-related cortical and subcortical regions represents the subjective valuation of risky gambles in monkeys. The activity of individual neurons in monkeys passively viewing a lottery reflects the desirability of probabilistic rewards parameterized as a multiplicative combination of utility and probability weighting functions, as in the prospect theory framework. The diverse patterns of valuation signals were not localized but distributed throughout most parts of the reward circuitry. A network model aggregating these signals reconstructed the risk preferences and subjective probability weighting revealed by the animals' choices. Thus, distributed neural coding explains the computation of subjective valuations under risk.

Development of multiplex S-gene-targeted RT-PCR for rapid identification of SARS-CoV-2 variants by extended S-gene target failure.

BACKGROUND: Tracking SARS-CoV-2 variants of concern (VOC) by genomic sequencing is time-consuming. The rapid screening of VOCs is necessary for clinical laboratories. In this study, we developed a rapid screening method based on multiplex RT-PCR by extended S-gene target failure (eSGTF), a false negative result caused by S-gene mutations. METHODS: Three S-gene target (SGT) regions (SGT1, codons 65-72; SGT2, codons 152-159; and SGT3, codons 370-377) and an N-gene region (for internal control) were detected in single-tube. Four types of VOC (Alpha, Delta, Omicron BA.1, and Omicron BA.2) are classified by positive/negative patterns of 3 S-gene regions (eSGTF pattern). RESULTS: The eSGTF patterns of VOCs were as follows (SGT1, SGT2, SGT3; P, positive; N, negative): Alpha, NPP; Delta, PNP; Omicron BA.1, NPN pattern; and Omicron BA.2, PPN. As compared with the S-gene sequencing, eSGTF patterns were identical to the specific VOCs (concordance rate = 96.7%, N = 206/213). Seven samples with discordant results had a minor mutation in the probe binding region. The epidemics of VOCs estimated by eSGTF patterns were similar to those in Japan. CONCLUSIONS: Multiplex RT-PCR and eSGTF patterns enable high-throughput screening of VOCs. It will be useful for the rapid determination of VOCs in clinical laboratories.

Development of TfOH-Catalyzed Spirocyclization by Intramolecular Friedel-Crafts-type 1,4-Addition: Application to the Total Synthesis of the Unusual Proaporphine Alkaloid (±)-Misrametine.

An effective method was developed for TfOH-catalyzed construction of spiroindanes and spirotetralines containing an all-carbon quaternary stereocenter. Intramolecular Friedel-Crafts-type 1,4-addition of the substrates which were di- or trimethoxybenzene and 2-cyclohexenone linked by an alkyl chain proceeded smoothly in the presence of 30 mol % of TfOH. A variety of spiroindanes and spirotetralines were obtained with moderate to excellent yield by this method. The reaction was successfully applied in the first total synthesis of the unusual proaporphine alkaloid (±)-misrametine, which included the gram-scale spirocyclization and selective O-demethylation used KCN in DMSO condition as key steps.

Tracking SARS-CoV-2 variants by entire S-gene analysis using long-range RT-PCR and Sanger sequencing.

INTRODUCTION: Genomic surveillance of the SARS-CoV-2 virus is important to assess transmissibility, disease severity, and vaccine effectiveness. The SARS-CoV-2 genome consists of approximately 30 kb single-stranded RNA that is too large to analyze the whole genome by Sanger sequencing. Thus, in this study, we performed Sanger sequencing following long-range RT-PCR of the entire SARS-CoV-2 S-gene and analyzed the mutational dynamics. METHODS: The 4 kb region, including the S-gene, was amplified by two-step long-range RT-PCR. Then, the entire S-gene sequence was determined by Sanger sequencing. The amino acid mutations were identified as compared with the reference SARS-CoV-2 genome. RESULTS: The S:D614G mutation was found in all samples. The R.1 variants were detected after January 2021. Alpha variants started to emerge in April 2021. Delta variants replaced Alpha in July 2021. Then, Omicron variants were detected after December 2021. These mutational dynamics in samples collected in the Chiba University Hospital were similar to those in Japan. CONCLUSION: The emergence of variants of concern (VOC) has been reported by the entire S-gene analysis. As the VOCs have unique mutational patterns of the S-gene region, analysis of the entire S-gene will be useful for molecular surveillance of the SARS-CoV-2 in clinical laboratories.

Neural Population Dynamics Underlying Expected Value Computation.

Computation of expected values (i.e., probability × magnitude) seems to be a dynamic integrative process performed by the brain for efficient economic behavior. However, neural dynamics underlying this computation is largely unknown. Using lottery tasks in monkeys (Macaca mulatta, male; Macaca fuscata, female), we examined (1) whether four core reward-related brain regions detect and integrate probability and magnitude cued by numerical symbols and (2) whether these brain regions have distinct dynamics in the integrative process. Extraction of the mechanistic structure of neural population signals demonstrated that expected value signals simultaneously arose in the central orbitofrontal cortex (cOFC; medial part of area 13) and ventral striatum (VS). Moreover, these signals were incredibly stable compared with weak and/or fluctuating signals in the dorsal striatum and medial OFC. Temporal dynamics of these stable expected value signals were unambiguously distinct: sharp and gradual signal evolutions in the cOFC and VS, respectively. These intimate dynamics suggest that the cOFC and VS compute the expected values with unique time constants, as distinct, partially overlapping processes.SIGNIFICANCE STATEMENT Our results differ from those of earlier studies suggesting that many reward-related regions in the brain signal probability and/or magnitude and provide a mechanistic structure for expected value computation employed in multiple neural populations. A central part of the orbitofrontal cortex (cOFC) and ventral striatum (VS) can simultaneously detect and integrate probability and magnitude into an expected value. Our empirical study on these neural population dynamics raises a possibility that the cOFC and VS cooperate on this computation with unique time constants as distinct, partially overlapping processes.

Structural and affinity analyses of g-quadruplex DNA aptamers for camptothecin derivatives.

We recently selected DNA aptamers that bind to camptothecin (CPT) and CPT derivatives from a 70-mer oligodeoxyribonucleotide (ODN) library using the Systematic Evolution of Ligands by EXponential enrichment (SELEX) method. The target-binding activity of the obtained 70-mer CPT-binding DNA aptamer, termed CA-70, which contains a 16-mer guanine (G)-core motif (G3TG3TG3T2G3) that forms a three-tiered G-quadruplex, was determined using fluorescence titration. In this study, truncated fragments of CA-70 that all have the G-core motif, CA-40, -20, -19, -18A, -18B, -17, and -16, were carefully analyzed. We found that CA-40 retained the target-binding activity, whereas CA-20, -19, and -18B exhibited little or no binding activities. Further, not only CA-18A but also the shorter length fragments CA-17 and -16 clearly retained the binding activity, indicating that tail strands of the G-quadruplex structure can significantly affect the target binding of G-quadruplex DNA aptamers. Further analyses using circular dichroism (CD) spectroscopy and fluorescence polarization (FP) assay were conducted to investigate the structure and affinity of G-quadruplex DNA aptamers.

Efficacy of base-modification on target binding of small molecule DNA aptamers.

Nucleic acid aptamers are receptors of single-stranded oligonucleotides that specifically bind to their targets. Significant interest is currently focused on development of small molecule aptamers owing to their applications in biosensing, diagnostics, and therapeutics involving low molecular weight biomarkers and drugs. Despite great potential for their diverse applications, relatively few aptamers that bind to small molecules have been reported, and methodologies to enhance and broaden their functions by expanding chemical repertories have barely been examined. Here we describe construction of a modified DNA library that includes (E)-5-(2-(N-(2-(N(6)-adeninyl)ethyl))carbamylvinyl)-uracil bases and discovery of high-affinity camptothecin-binding DNA aptamers using a systematic evolution of ligands by the exponential enrichment method. Our results are the first to demonstrate the superior efficacy of base modification on affinity enhancement and the usefulness of unnatural nucleic acid libraries for development of small molecule aptamers.

Expression of podoplanin and classical cadherins in salivary gland epithelial cells of klotho-deficient mice.

We have recently shown that salivary gland myoepithelial cells express podoplanin. Podoplanin indirectly binds the actin filament network which links classical cadherins. The study here is aimed to investigate the expression of podoplanin and cadherins on salivary gland myoepithelial cells and the changes in the aging cells using klotho-deficient (kl/kl) mice. The submandibular glands of kl/kl mouse lack granular ducts which express klotho in wild type mice, suggesting that klotho may be a gene responsible for granular duct development. Although aging resulted in growth suppression of myoepithelial cells because of the sparse distribution of the cells in kl/kl mouse salivary glands, the expression of podoplanin and E-cadherin was shown in aging myoepithelial cells. It is thought that podoplanin participates in the actin-E-cadherin networks which are maintained in aging myoepithelial cells. It was also shown that granular ducts were filled with P-cadherin, and that the P-cadherin amount was larger in the wild type mouse submandibular glands than in the sublingual and parotid glands of wild type mouse, and in the submandibular glands of kl/kl mouse. These findings suggest that the granular duct is an organ secreting soluble P-cadherin into the saliva.

Immunohistochemical examination for the distribution of podoplanin-expressing cells in developing mouse molar tooth germs.

We recently reported the expression of podoplanin in the apical bud of adult mouse incisal tooth. This study was aimed to investigate the distribution of podoplanin-expressing cells in mouse tooth germs at several developing stages. At the bud stage podoplanin was expressed in oral mucous epithelia and in a tooth bud. At the cap stage podoplanin was expressed on inner and outer enamel epithelia but not in mesenchymal cells expressing the neural crest stem cell marker nestin. At the early bell stage nestin and podoplanin were expressed in cervical loop and odontoblasts. At the root formation stage both nestin and podoplanin were weakly expressed in odontoblasts generating radicular dentin. Podoplanin expression was also found in the Hertwig epithelial sheath. These results suggest that epithelial cells of developing tooth germ acquire the ability to express nestin, and that tooth germ epithelial cells maintain the ability to express podoplanin in oral mucous epithelia. The expression of podoplanin in odontoblasts was induced as tooth germ development advanced, but was suppressed with the completion of the primary dentin, suggesting that podoplanin may be involved in the cell growth of odontoblasts. Nestin may function as an intermediate filament that binds podoplanin in odontoblasts.