Harmonic resonance and entrainment of propagating chemical waves by external mechanical stimulation in BZ self-oscillating hydrogels.

Smart polymer materials that are nonliving yet exhibit complex "life-like" or biomimetic behaviors have been the focus of intensive research over the past decades, in the quest to broaden our understanding of how living systems function under nonequilibrium conditions. Identification of how chemical and mechanical coupling can generate resonance and entrainment with other cells or external environment is an important research question. We prepared Belousov-Zhabotinsky (BZ) self-oscillating hydrogels which convert chemical energy to mechanical oscillation. By cyclically applying external mechanical stimulation to the BZ hydrogels, we found that when the oscillation of a gel sample entered into harmonic resonance with the applied oscillation during stimulation, the system kept a "memory" of the resonant oscillation period and maintained it post stimulation, demonstrating an entrainment effect. More surprisingly, by systematically varying the cycle length of the external stimulation, we revealed the discrete nature of the stimulation-induced resonance and entrainment behaviors in chemical oscillations of BZ hydrogels, i.e., the hydrogels slow down their oscillation periods to the harmonics of the cycle length of the external mechanical stimulation. Our theoretical model calculations suggest the important roles of the delayed mechanical response caused by reactant diffusion and solvent migration in affecting the chemomechanical coupling in active hydrogels and consequently synchronizing their chemical oscillations with external mechanical oscillations.

Ensemble dynamics and information flow deduction from whole-brain imaging data.

The recent advancements in large-scale activity imaging of neuronal ensembles offer valuable opportunities to comprehend the process involved in generating brain activity patterns and understanding how information is transmitted between neurons or neuronal ensembles. However, existing methodologies for extracting the underlying properties that generate overall dynamics are still limited. In this study, we applied previously unexplored methodologies to analyze time-lapse 3D imaging (4D imaging) data of head neurons of the nematode Caenorhabditis elegans. By combining time-delay embedding with the independent component analysis, we successfully decomposed whole-brain activities into a small number of component dynamics. Through the integration of results from multiple samples, we extracted common dynamics from neuronal activities that exhibit apparent divergence across different animals. Notably, while several components show common cooperativity across samples, some component pairs exhibited distinct relationships between individual samples. We further developed time series prediction models of synaptic communications. By combining dimension reduction using the general framework, gradient kernel dimension reduction, and probabilistic modeling, the overall relationships of neural activities were incorporated. By this approach, the stochastic but coordinated dynamics were reproduced in the simulated whole-brain neural network. We found that noise in the nervous system is crucial for generating realistic whole-brain dynamics. Furthermore, by evaluating synaptic interaction properties in the models, strong interactions within the core neural circuit, variable sensory transmission and importance of gap junctions were inferred. Virtual optogenetics can be also performed using the model. These analyses provide a solid foundation for understanding information flow in real neural networks.

Anisotropically self-oscillating gels by spatially patterned interpenetrating polymer network.

Here we introduce sub-millimeter self-oscillating gels that undergo the Belousov-Zhabotinsky (BZ) reaction and can anisotropically oscillate like cardiomyocytes. The anisotropically self-oscillating gels in this study were realized by spatially patterning an acrylic acid-based interpenetrating network (AA-IPN). We found that the patterned AA-IPN regions, locally introduced at both ends of the gels through UV photolithography, can constrain the horizontal gel shape deformation during the BZ reaction. In other words, the two AA-IPN regions could act as a physical barrier to prevent isotropic deformation. Furthermore, we controlled the anisotropic deformation behavior during the BZ reaction by varying the concentration of acrylic acid used in the patterning process of the AA-IPN. As a result, a specific directional deformation behavior (66% horizontal/vertical amplitude ratio) was fulfilled, similar to that of cardiomyocytes. Our study can provide a promising insight to fabricating robust gel systems for cardiomyocyte modeling or designing novel autonomous microscale soft actuators.

Temperature-Adaptative Self-Oscillating Gels: Toward Autonomous Biomimetic Soft Actuators with Broad Operating Temperature Region.

Self-oscillating gel systems exhibiting an expanded operating temperature and accompanying functional adaptability are showcased. The developed system contains nonthermoresponsive main-monomers, such as N,N-dimethylacrylamide (DMAAm) or 2-acrylamido-2-methylpropane sulfonic acid (AMPS) or acrylamide (AAm) or 3-(methacryloylamino)propyl trimethylammonium chloride (MAPTAC). The gels volumetrically self-oscillate within the range of the conventional (20.0 °C) and extended (27.0 and 36.5 °C) temperatures. Moreover, the gels successfully adapt to the environmental changes; they beat faster and smaller as the temperature increases. The period and amplitude are also controlled by tuning the amount of main-monomers and N-(3-aminopropyl) acrylamide. Furthermore, the record amplitude in the bulk gel system consisting of polymer strand and cross-linker at 36.5 °C is achieved (≈10.8%). The study shows new self-oscillation systems composed of unprecedented combinations of materials, giving the community a robust material-based insight for developing more life-like autonomous biomimetic soft robots with various operating temperatures and beyond.

Fabrication of submillimeter-sized spherical self-oscillating gels and control of their isotropic volumetric oscillatory behaviors.

In this study, we established a fabrication method and analyzed the volumetric self-oscillatory behaviors of submillimeter-sized spherical self-oscillating gels. We validated that the manufactured submillimeter-sized spherical self-oscillating gels exhibited isotropic volumetric oscillations during the Belousov-Zhabotinsky (BZ) reaction. In addition, we experimentally elucidated that the volumetric self-oscillatory behaviors (i.e., period and amplitude) and the oscillatory profiles depended on the following parameters: (1) the molar composition of N-(3-aminopropyl)methacrylamide hydrochloride (NAPMAm) in the gels and (2) the concentration of Ru(bpy)3-NHS solution containing an active ester group on conjugation. These clarified relationships imply that controlling the amount of Ru(bpy)3 in the gel network could influence the gel volumetric oscillation during the BZ reaction. These results of submillimeter-sized and spherical self-oscillating gels bridge knowledge gaps in the current field because the gels with corresponding sizes and shapes have not been systematically explored yet. Therefore, our study could be a cornerstone for diverse applications of (self-powered) gels in various scales and shapes, including soft actuators exhibiting life-like functions.

A surface-grafted hydrogel demonstrating thermoresponsive adhesive strength change.

Here, we designed a surface-grafted hydrogel (SG gel) that exhibits thermoresponsive changes in surface properties. Quantitative measurements using a self-made device showed that the adhesive strength between the SG gel surface and a Bakelite plate due to hydrophobic interaction changed significantly with temperature.

SMiPoly: Generation of a Synthesizable Polymer Virtual Library Using Rule-Based Polymerization Reactions.

Recent advances in machine learning have led to the rapid adoption of various computational methods for de novo molecular design in polymer research, including high-throughput virtual screening and inverse molecular design. In such workflows, molecular generators play an essential role in creation or sequential modification of candidate polymer structures. Machine learning-assisted molecular design has made great technical progress over the past few years. However, the difficulty of identifying synthetic routes to such designed polymers remains unresolved. To address this technical limitation, we present Small Molecules into Polymers (SMiPoly), a Python library for virtual polymer generation that implements 22 chemical rules for commonly applied polymerization reactions. For given small organic molecules to form a candidate monomer set, the SMiPoly generator conducts possible polymerization reactions to generate an exhaustive list of potentially synthesizable polymers. In this study, using 1083 readily available monomers, we generated 169,347 unique polymers forming seven different molecular types: polyolefin, polyester, polyether, polyamide, polyimide, polyurethane, and polyoxazolidone. By comparing the distribution of the virtually created polymers with approximately 16,000 real polymers synthesized so far, it was found that the coverage and novelty of the SMiPoly-generated polymers can reach 48 and 53%, respectively. Incorporating the SMiPoly library into a molecular design workflow will accelerate the process of de novo polymer synthesis by shortening the step to select synthesizable candidate polymers.

Construction of a nano-phase-separated structure on a hydrogel surface.

A hydrogel surface with a nano-phase-separated structure was successfully fabricated by grafting a fluorine-containing polymer using activators regenerated by electron transfer atom transfer radical polymerisation (ARGET ATRP). The modified hydrogel surface exhibits water repellency and high elasticity with maintaining transparency.

Functional Output Regression for Machine Learning in Materials Science.

In recent years, there has been a rapid growth in the use of machine learning in material science. Conventionally, a trained predictive model describes a scalar output variable, such as thermodynamic, electronic, or mechanical properties, as a function of input descriptors that vectorize the compositional or structural features of any given material, such as molecules, chemical compositions, or crystalline systems. In machine learning of material data, on the other hand, the output variable is often given as a function. For example, when predicting the optical absorption spectrum of a molecule, the output variable is a spectral function defined in the wavelength domain. Alternatively, in predicting the microstructure of a polymer nanocomposite, the output variable is given as an image from an electron microscope, which can be represented as a two- or three-dimensional function in the image coordinate system. In this study, we consider two unified frameworks to handle such multidimensional or functional output regressions, which are applicable to a wide range of predictive analyses in material science. The first approach employs generative adversarial networks, which are known to exhibit outstanding performance in various computer vision tasks such as image generation, style transfer, and video generation. We also present another type of statistical modeling inspired by a statistical methodology referred to as functional data analysis. This is an extension of kernel regression to deal with functional outputs, and its simple mathematical structure makes it effective in modeling even with small amounts of data. We demonstrate the proposed methods through several case studies in materials science.

Autonomous Nanoscale Chemomechanical Oscillation on the Self-Oscillating Polymer Brush Surface by Precise Control of Graft Density.

As a novel functional surface, a self-oscillating polymer brush that undergoes autonomous, periodic swelling/deswelling during the Belousov-Zhabotinsky (BZ) reaction has been developed. Although extensive research has revealed how the fundamental aspects of the BZ reaction can be regulated based on the surface design of the self-oscillating polymer brush, design strategies for the induction of mechanical oscillation remain unexplored. Herein, we investigated the graft density effects on the phase transition behavior, which is an important design parameter for the mechanical oscillation of the modified polymer. The self-oscillating polymer-modified substrates with controlled graft densities were prepared by immobilizing various compositions of an initiator and a noninitiator followed by surface-initiated atom transfer radical polymerization of the self-oscillating polymer chains. In addition to the characterization of each prepared substrate, atomic force microscopy (AFM) and digital holographic microscopy (DHM) were employed to evaluate the density effects on the static and dynamic surface structures. AFM revealed that equilibrium swelling as well as thermoresponsive behavior is profoundly affected by the graft density. Moreover, using DHM, autonomous mechanical oscillation was captured only on the self-oscillating polymer brush with adequate graft density. Notably, the oscillation amplitude (150 nm) and the period (20 s) in this study were superior to those in a previous report on the self-oscillating polymer modified through the grafting-to method by 10- and 3-fold, respectively. This study presents design guidelines for future applications, such as autonomous transport devices.

Neuron ID dataset facilitates neuronal annotation for whole-brain activity imaging of C. elegans.

BACKGROUND: Annotation of cell identity is an essential process in neuroscience that allows comparison of cells, including that of neural activities across different animals. In Caenorhabditis elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal has been limited due to the lack of quantitative information on the location and identity of neurons. RESULTS: Here, we present a dataset that facilitates the annotation of neuronal identities, and demonstrate its application in a comprehensive analysis of whole-brain imaging. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. We found large positional variations that illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters driving distinct fluorescence and generated optimal strains for the annotation of most head neurons in an animal. We also developed an automatic annotation method with human interaction functionality that facilitates annotations needed for whole-brain imaging. CONCLUSION: Our neuron ID dataset and optimal fluorescent strains enable the annotation of most neurons in the head region of adult C. elegans, both in full-automated fashion and a semi-automated version that includes human interaction functionalities. Our method can potentially be applied to model species used in research other than C. elegans, where the number of available cell-type-specific promoters and their variety will be an important consideration.

Investigation of inspiratory intercostal muscle activity in patients with spinal cord injury: a pilot study using electromyography, ultrasonography, and respiratory inductance plethysmography.

[Purpose] The respiratory function in patients with cervical spinal cord injury is influenced by inspiratory intercostal muscle function. However, inspiratory intercostal muscle activity has not been conclusively evaluated. We evaluated the inspiratory intercostal muscle activity in patients with cervical spinal cord injury by using inspiratory intercostal electromyography, respiratory inductance plethysmography, and ultrasonography. [Participants and Methods] Three patients with cervical spinal cord injury were assessed. The change in mean amplitude (rest vs. maximum inspiration) was calculated by using intercostal muscle electromyography. Changes in intercostal muscle thickness (resting expiration and maximum inspiration) were also evaluated on ultrasonography. The waveform was converted to spirometry ventilation with respiratory inductance plethysmography, and the waveform at the xiphoid was considered to determine the rib cage volume. Each index was compared with the inspiratory capacities in each case. [Results] Intercostal muscle electromyography failed to measure the notable myoelectric potential in all the patients. The rib cage volume was higher at higher inspiratory capacities. The changes in muscle thickness were not significantly different between the patients. [Conclusion] The rib cage volume (measured with inductance plethysmography) was greater in the patients with cervical spinal cord injury when inspiratory intercostal muscle activity was high. Respiratory inductance plethysmography can capture inspiratory intercostal muscle function in patients with cervical spinal cord injury.

Statistical inference of the rate of RNA polymerase II elongation by total RNA sequencing.

MOTIVATION: Sequencing total RNA without poly-A selection enables us to obtain a transcriptomic profile of nascent RNAs undergoing transcription with co-transcriptional splicing. In general, the RNA-seq reads exhibit a sawtooth pattern in a gene, which is characterized by a monotonically decreasing gradient across introns in the 5'-3' direction, and by substantially higher levels of RNA-seq reads present in exonic regions. Such patterns result from the process of underlying transcription elongation by RNA polymerase II, which traverses the DNA strand in a 5'-3' direction as it performs a complex series of mRNA synthesis and processing. Therefore, data of sequenced total RNAs could be utilized to infer the rate of transcription elongation by solving the inverse problem. RESULTS: Though solving the inverse problem in total RNA-seq has the great potential, statistical methods have not yet been fully developed. We demonstrate what extent the newly developed method can be useful. The objective is to reconstruct the spatial distribution of transcription elongation rates in a gene from a given noisy, sawtooth-like profile. It is necessary to recover the signal source of the elongation rates separately from several types of nuisance factors, such as unobserved modes of co-transcriptionally occurring mRNA splicing, which exert significant influences on the sawtooth shape. The present method was tested using published total RNA-seq data derived from mouse embryonic stem cells. We investigated the spatial characteristics of the estimated elongation rates, focusing especially on the relation to promoter-proximal pausing of RNA polymerase II, nucleosome occupancy and histone modification patterns. AVAILABILITY AND IMPLEMENTATION: A C implementation of PolSter and sample data are available at https://github.com/yoshida-lab/PolSter. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Reconstruction of the "Archaeal" Mevalonate Pathway from the Methanogenic Archaeon Methanosarcina mazei in Escherichia coli Cells.

The mevalonate pathway is a well-known metabolic route that provides biosynthetic precursors for myriad isoprenoids. An unexpected variety of the pathway has been discovered from recent studies on microorganisms, mainly on archaea. The most recently discovered example, called the "archaeal" mevalonate pathway, is a modified version of the canonical eukaryotic mevalonate pathway and was elucidated in our previous study using the hyperthermophilic archaeon Aeropyrum pernix This pathway comprises four known enzymes that can produce mevalonate 5-phosphate from acetyl coenzyme A, two recently discovered enzymes designated phosphomevalonate dehydratase and anhydromevalonate phosphate decarboxylase, and two more known enzymes, i.e., isopentenyl phosphate kinase and isopentenyl pyrophosphate:dimethylallyl pyrophosphate isomerase. To show its wide distribution in archaea and to confirm if its enzyme configuration is identical among species, the putative genes of a lower portion of the pathway-from mevalonate to isopentenyl pyrophosphate-were isolated from the methanogenic archaeon Methanosarcina mazei, which is taxonomically distant from A. pernix, and were introduced into an engineered Escherichia coli strain that produces lycopene, a red carotenoid pigment. Lycopene production, as a measure of isoprenoid productivity, was enhanced when the cells were grown semianaerobically with the supplementation of mevalonolactone, which demonstrates that the archaeal pathway can function in bacterial cells to convert mevalonate into isopentenyl pyrophosphate. Gene deletion and complementation analysis using the carotenogenic E. coli strain suggests that both phosphomevalonate dehydratase and anhydromevalonate phosphate decarboxylase from M. mazei are required for the enhancement of lycopene production.IMPORTANCE Two enzymes that have recently been identified from the hyperthermophilic archaeon A. pernix as components of the archaeal mevalonate pathway do not require ATP for their reactions. This pathway, therefore, might consume less energy than other mevalonate pathways to produce precursors for isoprenoids. Thus, the pathway might be applicable to metabolic engineering and production of valuable isoprenoids that have application as pharmaceuticals. The archaeal mevalonate pathway was successfully reconstructed in E. coli cells by introducing several genes from the methanogenic or hyperthermophilic archaeon, which demonstrated that the pathway requires the same components even in distantly related archaeal species and can function in bacterial cells.

Bayesian Algorithm for Retrosynthesis.

The identification of synthetic routes that end with the desired product is considered an inherently time-consuming process that is largely dependent on expert knowledge regarding a limited proportion of the entire reaction space. At present, emerging machine learning technologies are reformulating the process of retrosynthetic planning. This study aimed to discover synthetic routes backwardly from a given desired molecule to commercially available compounds. The problem is reduced to a combinatorial optimization task with the solution space subject to the combinatorial complexity of all possible pairs of purchasable reactants. We address this issue within the framework of Bayesian inference and computation. The workflow consists of the training of a deep neural network, which is used to forwardly predict a product of the given reactants with a high level of accuracy, followed by inversion of the forward model into the backward one via Bayes' law of conditional probability. Using the backward model, a diverse set of highly probable reaction sequences ending with a given synthetic target is exhaustively explored using a Monte Carlo search algorithm. With a forward model prediction accuracy of approximately 87%, the Bayesian retrosynthesis algorithm successfully rediscovered 81.8 and 33.3% of known synthetic routes of one-step and two-step reactions, respectively, with top-10 accuracy. Remarkably, the Monte Carlo algorithm, which was specifically designed for the presence of multiple diverse routes, often revealed a ranked list of hundreds of reaction routes to the same synthetic target. We also investigated the potential applicability of such diverse candidates based on expert knowledge of synthetic organic chemistry.

Fabrication of Self-Oscillating Micelles with a Built-In Oxidizing Agent.

Various biological behaviors are fueled by "respiration", which is an example of catabolism. So far, we have reported various self-oscillating soft materials exhibiting bioinspired dynamic movements. These autonomous polymer systems are driven by the Belousov-Zhabotinsky (BZ) reaction, which is analogous to the tricarboxylic acid (TCA) cycle that is an integral part of respiration. However, in the BZ reaction, the external addition of an oxidizing agent is necessary to initiate the oxidation process, which is realized by intracellular moieties such as ubiquinone in living systems. Herein, we realized self-oscillating micelles that are driven without the external addition of an oxidizing agent. This was achieved by embedding the oxidizing source into the structure of the self-oscillating AB diblock copolymers. This strategy introduces a new function equivalent to intracellular oxidizing moieties, and is useful for the design of completely autonomous bioinspired materials.

Reliability of voluntary cough assessments using respiratory flow waveform.

[Purpose] Voluntary cough can be assessed by recording flow waves. The purpose of this study was to examine the reliability of the measurements of respiratory flow waveforms, using equipment that recorded flow waves during cough. [Participants and Methods] Twenty healthy participants were recruited for this study. They underwent spirometry on them and, subsequently, their flow waves during single and consecutive voluntary cough tasks in the sitting position were recorded. The intra-class correlation coefficient was used to assess the intra-rater and inter-rater reliabilities for the voluntary cough data. [Results] The intra-class correlation coefficients were 0.6 to 0.8 for 'intra-rater reliability' and higher than 0.9 for 'inter-rater reliability', for single and consecutive cough tasks. The first assessment of cough peak flow was significantly higher than the second, during consecutive cough tasks. Similarly, the first assessment of cough volume acceleration was significantly higher than the second. [Conclusion] Our results demonstrated high intra-rater and inter-rater reliabilities for single and consecutive cough tasks. Following additional procedures and valuations, including the storage of data and standard range decisions, this method of cough assessment will be applied to patients with reduced cough function.

Stable and Prolonged Autonomous Oscillation in a Self-Oscillating Polymer Brush Prepared on a Porous Glass Substrate.

We developed an autonomous functional surface, named a "self-oscillating polymer brush surface", which exhibits swelling-deswelling of the modified polymer chains synchronized with the Belousov-Zhabotinsky (BZ) reaction. The grafted polymer chain is a random copolymer composed of thermoresponsive N-isopropylacrylamide, N-(3-aminopropyl)methacrylamide, and ruthenium tris(2,2'-bipyridine) [Ru(bpy)3]. To provide stable oscillations over a long period of time, suppression of the dilution of the BZ reactants inside the polymer surface and the increase in the amount of immobilized Ru(bpy)3 are important. Here, we modified the self-oscillating polymer brush on a porous glass substrate and characterized its dynamic behavior. The increased surface area of the porous glass allowed for an efficient introduction of the metal catalyst, which resulted in a stable BZ reaction observable by optical microscopy. Compared with an aqueous BZ solution and the self-oscillating polymer modified on a glass coverslip, the wave velocity and diffusion coefficient were significantly lower for the porous glass system, which suggested that the reaction-diffusion of the reactants was markedly different than those of the other two systems. Moreover, the wave velocity was unchanged on the porous glass system for 1 h, whereas that of the solution dropped by 30 µm s-1. Waveform analyses based on the Field-Körös-Noyes mechanism revealed that densely packed Ru(bpy)3 in the porous glass system affects the duration of the key processes in the BZ reaction. These findings can help with understanding the dynamic behavior of the self-oscillating polymer brush on a porous glass substrate. Stable self-oscillations on the polymer brush-grafted porous glass substrate will aid future applications such as mass transport systems.

Pattern Formation in Heterostructured Gel by the Ferrocyanide-Iodate-Sulfite Reaction.

Pattern formation in the reaction-diffusion systems for the ferrocyanide-iodate-sulfite reaction has been investigated. Previous studies have been conducted in a uniform medium. However, in this study, we reported the pattern formation in heterostructured gels with different network densities. The chemical states of the gel depend on the diffusivity, which in turn depends on the network density of the gel. Consequently, a pH pattern reflecting the heterostructured gel emerged. Furthermore, adjusting the condition produces novel patterns in the heterostructured gel.

Ingestion of difructose anhydride III partially suppresses the deconjugation and 7α-dehydroxylation of bile acids in rats fed with a cholic acid-supplemented diet.

Difructose anhydride III (DFAIII) is a prebiotic involved in the reduction of secondary bile acids (BAs). We investigated whether DFAIII modulates BA metabolism, including enterohepatic circulation, in the rats fed with a diet supplemented with cholic acid (CA), one of the 12α-hydroxylated BAs. After acclimation, the rats were fed with a control diet or a diet supplemented with DFAIII. After 2 weeks, each group was further divided into two groups and was fed diet with or without CA supplementation at 0.5 g/kg diet. BA levels were analyzed in aortic and portal plasma, liver, intestinal content, and feces. As a result, DFAIII ingestion reduced the fecal deoxycholic acid level via the partial suppression of deconjugation and 7α-dehydroxylation of BAs following CA supplementation. These results suggest that DFAIII suppresses production of deoxycholic acid in conditions of high concentrations of 12α-hydroxylated BAs in enterohepatic circulation, such as obesity or excess energy intake. Abbreviation: BA: bile acid; BSH: bile salt hydrolase; CA: cholic acid; DCA: deoxycholic acid; DFAIII: difructose anhydride III; MCA: muricholic acid; MS: mass spectrometry; NCDs: non-communicable diseases; LC: liquid chromatography; SCFA: short-chain fatty acid; TCA: taurocholic acid; TCDCA: taurochenodeoxycholic acid; TDCA: taurodeoxycholic acid; TUDCA: tauroursodeoxychlic acid; TαMCA: tauro-α-muricholic acid; TßMCA: tauro-ß-muricholic acid; TωMCA: tauro-ω-muricholic acid.