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Abstract We studied the inhibitory actions of docosahexaenoic acid (DHA) on the contractions induced by carbachol (CCh), angiotensin II (Ang II), and bradykinin (BK) in guinea pig (GP) gastric fundus smooth muscle (GFSM), particularly focusing on the possible inhibition of store-operated Ca2+ channels (SOCCs). DHA significantly suppressed the contractions induced by CCh, Ang II, and BK; the inhibition of BK-induced contractions was the strongest. Although all contractions were greatly dependent on external Ca2+, more than 80% of BK-induced contractions remained even in the presence of verapamil, a voltage-dependent Ca2+ channel inhibitor. BK-induced contractions in the presence of verapamil were not suppressed by LOE-908 (a receptor-operated Ca2+ channel (ROCC) inhibitor) but were suppressed by SKF-96365 (an SOCC and ROCC inhibitor). BK-induced contractions in the presence of verapamil plus LOE-908 were strongly inhibited by DHA. Furthermore, DHA inhibited GFSM contractions induced by cyclopiazonic acid (CPA) in the presence of verapamil plus LOE-908 and inhibited the intracellular Ca2+ increase due to Ca2+ addition in CPA-treated 293T cells. These findings indicate that Ca2+ influx through SOCCs plays a crucial role in BK-induced contraction in GP GFSM and that this inhibition by DHA is a new mechanism by which this fatty acid inhibits GFSM contractions.

ABSTRACTBayesian optimization, coupled with Gaussian process regression and acquisition functions, has proven to be a powerful tool in the field of experimental design. Nevertheless, it demands a profound proficiency in software programming, machine learning, and statistical concepts. This steep learning curve presents a substantial obstacle when implementing Bayesian optimization for experimental design. In order to overcome this challenge, a user-friendly graphical interface for Gaussian process regression and acquisition functions is proposed. This accessible tool can be readily accessed via web browsers, courtesy of the established CADS platform (available at https://cads.eng.hokudai.ac.jp/). Thus, the interface offers to perform Bayesian optimization without any programming or any extensive prior knowledge about Bayesian optimization and machine learning.

Abstract The empirical aspect of descriptor design in catalyst informatics, particularly when confronted with limited data, necessitates adequate prior knowledge for delving into unknown territories, thus presenting a logical contradiction. This study introduces a technique for automatic feature engineering (AFE) that works on small catalyst datasets, without reliance on specific assumptions or pre-existing knowledge about the target catalysis when designing descriptors and building machine-learning models. This technique generates numerous features through mathematical operations on general physicochemical features of catalytic components and extracts relevant features for the desired catalysis, essentially screening numerous hypotheses on a machine. AFE yields reasonable regression results for three types of heterogeneous catalysis: oxidative coupling of methane (OCM), conversion of ethanol to butadiene, and three-way catalysis, where only the training set is swapped. Moreover, through the application of active learning that combines AFE and high-throughput experimentation for OCM, we successfully visualize the machine’s process of acquiring precise recognition of the catalyst design. Thus, AFE is a versatile technique for data-driven catalysis research and a key step towards fully automated catalyst discoveries.

Abstract In this study, geodetic and seismic phenomena occurring in the subduction zone were observed with two tiltmeters that were installed in seafloor boreholes drilled in the Kumano Basin in the Nankai Trough, southwest Japan. We used one electrolytic-type tiltmeter and one pendulum-type tiltmeter installed 6 and 19 m below the seafloor, respectively. The two tiltmeters have been continuously operated since 2019 and 2021, respectively. The records of the two tiltmeters showed microseisms, seismic signals of normal earthquakes, and variations that correlated well with the M2 tide (tidal response). The noise environment relative to existing seafloor observatories was assessed by comparing the power spectral densities of the tiltmeters and broadband seismometers in the seismic frequency band. The two tiltmeters and the seismometers showed similar spectral peaks in the microseism band, and at lower frequencies below 10–2 Hz, the pendulum tiltmeter had a noise level that was up to 20 dB lower than that of the broadband seismometers. The tidal responses of the tiltmeters were analyzed to reveal corresponding mechanisms because a large amplitude of the tidal response makes it difficult to detect geodetic phenomena. Considerable azimuthal dependence was observed in the NW–SE direction for both tiltmeters. The principal direction was approximately the same as the down-slope direction of the local bathymetry. This tendency was thus interpreted to be caused by the differences in the thickness of the sedimentary layer along the direction of the slope. Furthermore, the validity of the tilt measurements for the two tiltmeters was demonstrated by in-situ loading experiments, where the theoretical response of an elastic half-space medium was computed and compared with the experimental results. The results of the loading experiments can be explained using theoretical values with a set of realistic elastic moduli. Graphical Abstract

Abstract Neonicotinoid pesticides are a class of insecticides that reportedly have harmful effects on bees and dragonflies, causing a reduction in their numbers. Neonicotinoids act as neuroreceptor modulators, and some studies have reported their association with neurodevelopmental disorders. However, the precise effect of neonicotinoids on the central nervous system has not yet been identified. Herein, we conducted in vivo Ca2+ imaging using a two-photon microscope to detect the abnormal activity of neuronal circuits in the brain after neonicotinoid application. The oral administration of acetamiprid (ACE) (20 mg/kg body weight (BW) in mature mice with a quantity less than the no-observed-adverse-effect level (NOAEL) and a tenth or half of the median lethal dose (LD50) of nicotine (0.33 or 1.65 mg/kg BW, respectively), as a typical nicotinic acetylcholine receptor (nAChR) agonist, increased anxiety-like behavior associated with altered activities of the neuronal population in the somatosensory cortex. Furthermore, we detected ACE and its metabolites in the brain, 1 h after ACE administration. The results suggested that in vivo Ca2+ imaging using a two-photon microscope enabled the highly sensitive detection of neurotoxicant-mediated brain disturbance of nerves.

Cementitious materials have potential for infrastructure development in low-temperature marine environments, including in seawater at high latitudes and in deep-sea environments (water depths of >1000 m). Although the marine deterioration of cementitious materials has been widely investigated, the influence of seawater temperature has not been elucidated. In this study, to determine the effects of low-temperature seawater on the durability of cementitious materials, cement paste specimens were immersed in a seawater tank at room temperature and 2 °C for 433 days. The specimen immersed in low-temperature seawater exhibited significant deterioration with a partially collapsed surface, whereas the specimen immersed in room-temperature seawater maintained its original shape. Following low-temperature immersion, Ca dissolution was more pronounced and dissolved portlandite, decalcified calcium (alumino)silicate hydrate (C–(A-)S–H), magnesium (alumino)silicate hydrate (M–(A-)S–H), and thaumasite were observed on the collapsed surface. Such significant deterioration can be attributed to the increased solubility of portlandite under low-temperature conditions, which could promote Ca dissolution and subsequently lead to C–(A-)S–H decalcification and the formation of M–(A-)S–H and thaumasite. These insights are expected to contribute to the successful construction and maintenance of cementitious structures in low-temperature seawater.

Abstract Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the composition, the surface area and the local structure of the Cu zeolite active site, are collected from the Database of Zeolite Structures of the International Zeolite Association (IZA). Also analytical studies based on inductively coupled plasma-optical emission spectrometry (ICP-OES), X-ray fluorescence (XRF), N2 adsorption specific surface area measurement and X-ray absorption fine structure (XAFS) spectral measurement are performed. The relationships between catalytic activity and the structural variables are subsequently revealed by data science techniques, specifically, classification using unsupervised and supervised machine learning and data visualization using pairwise correlation. Based on the unveiled relationships and a detailed analysis of the XAFS spectra, the local structures of the Cu zeolites with high activity are proposed.

The influence of hydraulic pressure (max. 20 MPa) on the internal damage of cement-based materials is experimentally studied. In order to observe in situ the internal damage of cement-based materials under hydraulic pressure, a new testing apparatus equipped with an X-ray micro-computed tomography (X-μCT) scanner is developed. The behaviors of water infiltration and strain development are evaluated for mortar specimens with different water-to-cement ratios. Although the internal damage of the mortar specimens under hydraulic pressure was not detected by the X-μCT scanner and fluorescent imaging, the mechanical properties tested after hydraulic pressure loadings were altered, indicative of the occurrence of microcracks (

A transfomer oil immersion cooling server is designed and constructed for machine learning applications and first principle calculations that are carried out for materials-related research. CPU, motherboard, random access memory, hard disk drive, solid state drive, graphic card, and the power supply unit are submerged into the transformer oil in order to cool the entire system. Benchmark tests reveal that overall performance is improved while performance times for multicore calculations are dramatically improved. Furthermore, calculation times for machine learning with large data sets and density functional theory calculations are shortened during single core calculations. Thus, a transformer oil immersion cooling server is proposed to be an alternative cooling system used for improving the performance of first principle calculations and machine learning.

A method has been developed to measure the similarity between materials, focusing on specific physical properties. The information obtained can be utilized to understand the underlying mechanisms and support the prediction of the physical properties of materials. The method consists of three steps: variable evaluation based on nonlinear regression, regression-based clustering, and similarity measurement with a committee machine constructed from the clustering results. Three data sets of well characterized crystalline materials represented by critical atomic predicting variables are used as test beds. Herein, the focus is on the formation energy, lattice parameter and Curie temperature of the examined materials. Based on the information obtained on the similarities between the materials, a hierarchical clustering technique is applied to learn the cluster structures of the materials that facilitate interpretation of the mechanism, and an improvement in the regression models is introduced to predict the physical properties of the materials. The experiments show that rational and meaningful group structures can be obtained and that the prediction accuracy of the materials' physical properties can be significantly increased, confirming the rationality of the proposed similarity measure.

The palladium catalyzed carbonylation of 1 using the chiral ligand L1 afforded 2 in a highly diastereoselective manner. The stereochemistry of the major diastereomer 2a was determined by X-ray crystallographic analysis. AR luciferase reporter assay studies suggested that 2a was the active constituent of YK11 (2).

Tea is one of the world’s most popular beverages due to health promoting effects. Despite these, there have been concerns about the adverse effects of tea contamination by neonicotinoid insecticides. Only a handful of studies on neonicotinoid insecticides in tea have been carried out and this study was therefore performed to determine the concentrations of seven neonicotinoid insecticides and 20 metabolites in Japanese green tea leaves, and black tea leaves from Sri Lanka; and assess the Maximum Daily Intake (MDI) of neonicotinoid insecticides. From the results, the seven parent compounds were detected in Japanese tea leaves and beverages. Dinotefuran (3004 ng/g) was found at the highest level in green tea leaves. Ten of the 20 metabolites were detected in Japanese tea products. Dinotefuran-urea (92%) and thiacloprid-amide (89%) were most frequently detected in Japanese tea leaves. Clothianidin-urea (100 ng/g) was found at the highest level in green tea leaves. Neonicotinoid insecticides and metabolites were not detected in Sri Lankan black tea leaves. The concentrations and MDI of neonicotinoid insecticides in tea leaves were below the Maximum Residual Levels (MRLs) and Acceptable Daily Intakes (ADIs), respectively. Keywords: Neonicotinoid, Tea, Japan, Sri Lanka, Dinotefuran

Abstract The genome of Drosophila melanogaster contains seven rhodopsin genes. Rh1-6 proteins are known to have respective absorption spectra and function as visual pigments in ocelli and compound eyes. In contrast, Rh7 protein was recently revealed to function as a circadian photoreceptor in the brain. However, its molecular properties have not been characterized yet. Here we successfully prepared a recombinant protein of Drosophila Rh7 in mammalian cultured cells. Drosophila Rh7 bound both 11-cis-retinal and 11-cis-3-hydroxyretinal to form photo-pigments which can absorb UV light. Irradiation with UV light caused formation of a visible-light absorbing metarhodopsin that activated Gq-type of G protein. This state could be photoconverted back to the original state and, thus Rh7 is a Gq-coupled bistable pigment. Interestingly, Rh7 (lambda max = 350 nm) exhibited an unusual broad spectrum with a longer wavelength tail reaching 500 nm, whose shape is like a composite of spectra of two pigments. In contrast, replacement of lysine at position 90 with glutamic acid caused the formation of a normal-shaped absorption spectrum with maximum at 450 nm. Therefore, Rh7 is a unique photo-sensor that can cover a wide wavelength region by a single pigment to contribute to non-visual photoreception.

Introduction: Although initial treatments for pyogenic spondylitis include conservative approaches such as rest and antibiotics, some cases are refractory to conservative therapy. The objective of this study was to clarify the predictors for achievement of C-reactive protein (CRP) normalization in pyogenic spondylitis by conservative therapy. Methods: In the present study, we enrolled 83 patients (51 men and 32 women) with conservatively treated pyogenic spondylitis from 2006 to 2015. Multiple logistic regression analysis was used to examine the association of achievement of CRP normalization with the number of infected vertebrae, bacterial strain, blood data, and the expansion of abscess to the epidural space by using functional magnetic resonance imaging. Results: We found significant differences in the subjects with and without achievement of CRP normalization with respect to age, the number of affected vertebrae, ratio of resistant pathogenic bacteria, ratio of expansion of abscess to the epidural space, and blood data such as Hb, ALB, eGFR, Cr, and ALP levels. After adjustment for age and sex, the number of infected vertebral bodies, resistant bacteria, expansion of abscess to the epidural space, and Hb level showed significant associations with the normalization of CRP. In addition, we used multiple logistic regression analysis with age, sex, number of infected vertebral bodies, resistant bacteria, expansion of abscess to the epidural space, and serum Hb level as explanatory variables. We found that expansion of the abscess to the epidural and paravertebral spaces was significantly associated with the normalization of CRP level. Conclusions: The number of infected vertebral bodies, resistant strains of pathogenic bacteria, expansion of abscess to the epidural and paravertebral spaces, and serum Hb level predicts the prognosis of patients with pyogenic spondylitis. Particularly, expansion of abscess to the epidural and paravertebral spaces was strongly associated with the achievement of CRP normalization.

We investigated transcriptomic markers of late-onset major depressive disorder (LOD; onset age of first depressive episode ≥ 50 years) from the genes expressed in blood cells and identified state-dependent transcriptomic markers in these patients. We assessed the genes expressed in blood cells by microarray and found that the expression levels of 3,066 probes were state-dependently changed in the blood cells of patients with LOD. To select potential candidates from those probes, we assessed the genes expressed in the blood of an animal model of depression, ovariectomized female mice exposed to chronic ultra-mild stress, by microarray and cross-matched the differentially expressed genes between the patients and the model mice. We identified 14 differentially expressed genes that were similarly changed in both patients and the model mice. By assessing statistical significance using real-time quantitative PCR (RT-qPCR), the following 4 genes were selected as candidates: cell death-inducing DFFA-like effector c (CIDEC), ribonuclease 1 (RNASE1), solute carrier family 36 member-1 (SLC36A1), and serine/threonine/tyrosine interacting-like 1 (STYXL1). The discriminating ability of these 4 candidate genes was evaluated in an independent cohort that was validated. Among them, CIDEC showed the greatest discriminant validity (sensitivity 91.3% and specificity 87.5%). Thus, these 4 biomarkers should be helpful for properly diagnosing LOD.

During fabrication process of laminated fibrous composites, asymmetric laminates result in skewed surfaces after curing due to strong anisotropy of each layer, and composites with specific lay-ups and dimensions show bi-stable states in terms of surface shapes. The present study performs a multi-objective optimization for the composite shell with bi-stable shapes. Objective functions are amount of averaged deformation between two stable shapes of shell (snap-thorough deformation) and critical temperature of surroundings which is the maximum temperature to keep the bi-stable characteristics. These properties indicate a trade-off relation each other and are maximized simultaneously by using an effective multi-objective genetic algorithm method, SPEA+. Shell shapes after curing are predicted by the thermal deformation analysis based on the Rayleigh-Ritz method with directly assumed strain functions. Calculated results agree well with those from experiments with respect to shell shapes, and the present multi-objective optimization reveals wide-ranging Pareto optimum solutions. The numerical results show that spirally laminated fiber orientation angles are effective to increase amount of snap-thorough deformation.

An efficient PdII/Pd0-p-benzoquinone/hydroquinone-CuCl2/CuCl catalyst system was developed that uses environmentally friendly molecular oxygen as the terminal oxidant to catalyze the cyclization-carbonylation-cyclization coupling reaction (CCC-coupling reaction) of (o-alkynyl phenyl) (methoxymethyl) sulfides.