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Hamiltonian matrices in electronic and nuclear contexts are highly computation intensive to calculate, mainly due to the cost for the potential matrix. Typically, these matrices contain many off-diagonal elements that are orders of magnitude smaller than diagonal elements. We illustrate that here for vibrational H-matrices of H2O, C2H3 (vinyl), and C2H5NO2 (glycine) using full-dimensional ab initio-based potential surfaces. We then show that many of these small elements can be replaced by zero with small errors of the resulting full set of eigenvalues, depending on the threshold value for this replacement. As a result of this empirical evidence, we investigate three machine learning approaches to predict the zero elements. This is shown to be successful for these H-matrices after training on a small set of calculated elements. For H-matrices of vinyl and glycine, of order 15 552 and 8828, respectively, training on a percent or so of elements is sufficient to obtain all eigenvalues with a mean absolute error of roughly 2 cm−1. [ABSTRACT FROM AUTHOR]

During the early Cenozoic, the collision and convergence between India and Eurasia resulted in the uplift of the Tibetan Plateau and continuous northward compression, forming the Circum‐Tibetan Plateau Basin and Orogen System (CTPBOS). The Tarim Basin, located between the Tibetan Plateau and the Tianshan Mountains, plays a crucial role for studying the convergence‐driving strain propagation mechanism intra‐Asian continent during the growth processes of the Tibetan Plateau. Owing to the lack of accurate geophysical information on the deep structure of the Tarim crust，the mechanism of Cenozoic deformation in the Tarim Basin has been under debate. In this paper, the teleseismic data acquired by the broadband seismic profile across the Tarim Basin from south to north and the S‐wave receiver function method were used to obtain the depth of the Moho and the discontinuities in the lithosphere beneath the Tarim Basin. The SRF result shows that the Moho geometry has an abrupt relief under the Bachu Uplift, and Moho offset under the fault zone between the Kalashayi Fault and the Tumuxiuke Fault. The regional dip of the Moho under the Bachu area can be explained by the root of the Bachu basement‐involved uplift cutting across the whole crust and locally penetrating into the mantle lithosphere. The Bachu Uplift, located in the central Tarim terrane, has a relatively weak lithosphere. In the process of forming the Tarim large igneous province during the early Permian, the crust beneath the Bachu area was weakened and thinned by the thermo‐mechanical erosion from upwelling mantle plume. As the collision and convergence of India and Eurasia since the early Cenozoic, the convergence‐driving strain was propagated into the Tarim Basin. The pre‐existing weak Bachu Uplift was reactivated. The Tarim Basin absorbs Cenozoic compressional deformation through the crustal shortening and Moho offset of the Bachu Uplift. [ABSTRACT FROM AUTHOR]

We wish to describe a potential energy surface by using a basis of permutationally invariant polynomials whose coefficients will be determined by numerical regression so as to smoothly fit a dataset of electronic energies as well as, perhaps, gradients. The polynomials will be powers of transformed internuclear distances, usually either Morse variables, exp(−ri,j/λ), where λ is a constant range hyperparameter, or reciprocals of the distances, 1/ri,j. The question we address is how to create the most efficient basis, including (a) which polynomials to keep or discard, (b) how many polynomials will be needed, (c) how to make sure the polynomials correctly reproduce the zero interaction at a large distance, (d) how to ensure special symmetries, and (e) how to calculate gradients efficiently. This article discusses how these questions can be answered by using a set of programs to choose and manipulate the polynomials as well as to write efficient Fortran programs for the calculation of energies and gradients. A user-friendly interface for access to monomial symmetrization approach results is also described. The software for these programs is now publicly available. [ABSTRACT FROM AUTHOR]

We report a new permutationally invariant polynomial (PIP) fit to CCSD(T)/aug-cc-pVTZ energies for $ \hbox {CH}_5^{+} $ CH 5 + that provides fast analytical forces, unlike the original PIP fit of 2006. The new fit, which is slightly more precise than the previous one, is used in classical molecular dynamics, diffusion Monte Carlo and path integral molecular dynamics calculations of CH and HH radial distribution functions (RDFs) at temperatures of 10 and $ 50\,\hbox {K} $ 50 K . Corresponding RDFs are also reported for $ \hbox {CD}_{3}\hbox {H}_{2}^{+} $ CD 3 H 2 + . The well-known quantum localisation of the H atoms to the diatomic site from previous and present DMC calculations is maintained at $ 10\,\hbox {K} $ 10 K but shows additional delocalisation to the ' $ \hbox {CH}_{3}^{+} $ CH 3 + ' site at $ 50\,\hbox {K} $ 50 K . [ABSTRACT FROM AUTHOR]

Social hierarchies can be inferred through observational learning of social relationships between individuals. Yet, little is known about the causal role of specific brain regions in learning hierarchies. Here, using transcranial direct current stimulation, we show a causal role of the medial prefrontal cortex (mPFC) in learning social versus non-social hierarchies. In a Training phase, participants acquired knowledge about social and non-social hierarchies by trial and error. During a Test phase, they were presented with two items from hierarchies that were never encountered together, requiring them to make transitive inferences. Anodal stimulation over mPFC impaired social compared with non-social hierarchy learning, and this modulation was influenced by the relative social rank of the members (higher or lower status). Anodal stimulation also impaired transitive inference making, but only during early blocks before learning was established. Together, these findings demonstrate a causal role of the mPFC in learning social ranks by observation. A brain stimulation study (tDCS) on healthy humans shows that the medial prefrontal cortex plays a causal role in learning social hierarchical relationships by observation. [ABSTRACT FROM AUTHOR]

There has been great progress in developing methods for machine-learned potential energy surfaces. There have also been important assessments of these methods by comparing so-called learning curves on datasets of electronic energies and forces, notably the MD17 database. The dataset for each molecule in this database generally consists of tens of thousands of energies and forces obtained from DFT direct dynamics at 500 K. We contrast the datasets from this database for three "small" molecules, ethanol, malonaldehyde, and glycine, with datasets we have generated with specific targets for the potential energy surfaces (PESs) in mind: a rigorous calculation of the zero-point energy and wavefunction, the tunneling splitting in malonaldehyde, and, in the case of glycine, a description of all eight low-lying conformers. We found that the MD17 datasets are too limited for these targets. We also examine recent datasets for several PESs that describe small-molecule but complex chemical reactions. Finally, we introduce a new database, "QM-22," which contains datasets of molecules ranging from 4 to 15 atoms that extend to high energies and a large span of configurations. [ABSTRACT FROM AUTHOR]

Permutationally invariant polynomial (PIP) regression has been used to obtain machine-learned potential energy surfaces, including analytical gradients, for many molecules and chemical reactions. Recently, the approach has been extended to moderate size molecules with up to 15 atoms. The algorithm, including "purification of the basis," is computationally efficient for energies; however, we found that the recent extension to obtain analytical gradients, despite being a remarkable advance over previous methods, could be further improved. Here, we report developments to further compact a purified basis and, more significantly, to use the reverse differentiation approach to greatly speed up gradient evaluation. We demonstrate this for our recent four-body water interaction potential. Comparisons of training and testing precision on the MD17 database of energies and gradients (forces) for ethanol against numerous machine-learning methods, which were recently assessed by Dral and co-workers, are given. The PIP fits are as precise as those using these methods, but the PIP computation time for energy and force evaluation is shown to be 10–1000 times faster. Finally, a new PIP potential energy surface (PES) is reported for ethanol based on a more extensive dataset of energies and gradients than in the MD17 database. Diffusion Monte Carlo calculations that fail on MD17-based PESs are successful using the new PES. [ABSTRACT FROM AUTHOR]

"Δ-machine learning" refers to a machine learning approach to bring a property such as a potential energy surface (PES) based on low-level (LL) density functional theory (DFT) energies and gradients close to a coupled cluster (CC) level of accuracy. Here, we present such an approach that uses the permutationally invariant polynomial (PIP) method to fit high-dimensional PESs. The approach is represented by a simple equation, in obvious notation VLL→CC = VLL + ΔVCC–LL, and demonstrated for CH4, H3O+, and trans and cis-N-methyl acetamide (NMA), CH3CONHCH3. For these molecules, the LL PES, VLL, is a PIP fit to DFT/B3LYP/6-31+G(d) energies and gradients and ΔVCC–LL is a precise PIP fit obtained using a low-order PIP basis set and based on a relatively small number of CCSD(T) energies. For CH4, these are new calculations adopting an aug-cc-pVDZ basis, for H3O+, previous CCSD(T)-F12/aug-cc-pVQZ energies are used, while for NMA, new CCSD(T)-F12/aug-cc-pVDZ calculations are performed. With as few as 200 CCSD(T) energies, the new PESs are in excellent agreement with benchmark CCSD(T) results for the small molecules, and for 12-atom NMA, training is done with 4696 CCSD(T) energies. [ABSTRACT FROM AUTHOR]

Costly punishment of social norm transgressors by third-parties has been considered as a decisive stage in the evolution of human cooperation. An important facet of social relationship knowledge concerns the strength of the social ties between individuals, as measured by social distance. Yet, it is unclear how the enforcement of social norms is influenced by the social distance between a third-party and a norm violator at the behavioral and the brain system levels. Here, we investigated how social distance between punishers and norm-violators influences third-party punishment. Participants as third-party punished norm violators more severely as social distance between them increased. Using model-based fMRI, we disentangled key computations contributing to third-party punishment: inequity aversion, social distance between participant and norm violator and integration of the cost to punish with these signals. Inequity aversion increased activity in the anterior cingulate cortex and bilateral insula, and processing social distance engaged a bilateral fronto-parietal cortex brain network. These two brain signals and the cost to punish were integrated in a subjective value signal of sanctions that modulated activity in the ventromedial prefrontal cortex. Together, our results reveal the neurocomputational underpinnings of third-party punishment and how social distance modulates enforcement of social norms in humans. [ABSTRACT FROM AUTHOR]

We report full and fragmented potential energy surfaces (PESs) for N-methyl acetamide that contain the cis and trans isomers and the saddle points separating them. The full PES uses Permutationally Invariant Polynomials (PIPs) in reduced symmetry which describe the three-fold symmetry of each methyl rotor. A more efficient PES is an extension of the fragmented PIP approach we reported recently. In this approach, the set of Morse variables is partitioned and the fragmented PIP basis is the union of the PIP basis for each set of variables. This approach is general and can be used with neural network fits. The fits are done using roughly 250 000 electronic energies and gradients obtained from direct dynamics, using the B3LYP/cc-pVDZ level of theory. The full PIP basis in 66 Morse variables, with a maximum polynomial order of 3, contains 8040 linear coefficients. The fragmented PIP basis, also with a maximum polynomial order of 3, contains 6121 coefficients. The root-mean-square errors of both PESs are roughly 100 cm−1 for energies and 15 cm−1/bohr per atom for gradients, for energies up to roughly 45 000 cm−1, relative to the trans minimum. Energies and normal mode frequencies of the cis and trans isomers for the full and fragmented PESs agree well with direct calculations. The energies of the two saddle points separating these minima are precisely given by both PESs. Diffusion Monte Carlo calculations of the zero-point energies of the two isomers are also reported. [ABSTRACT FROM AUTHOR]

We describe and apply a method to extend permutationally invariant polynomial (PIP) potential energy surface (PES) fitting to molecules with more than 10 atoms. The method creates a compact basis of PIPs as the union of PIPs obtained from fragments of the molecule. An application is reported for trans-N-methyl acetamide, where B3LYP/cc-pVDZ electronic energies and gradients are used to develop a full-dimensional potential for this prototype peptide molecule. The performance of several fragmented bases is verified against a benchmark PES using all (66) Morse variables. The method appears feasible for much larger molecules. [ABSTRACT FROM AUTHOR]

• Studies on functional molecule surface segregation in electrospinning are reviewed. • Design and regulation methods of surface segregation are illustrated. • Characterization methods revealing the surface segregation extent are summarized. • Prevalent applications of surface segregation electrospun fibers are discussed. Electrospinning has garnered significant attention for fabricating functional composite fibers. Recently, surface segregation exhibits great potential in shaping functional surface of fibers due to the ability to impart surface compositions different from those in the bulk phase. Moreover, the segregation behavior could be effectively regulated by altering the components' properties and the process designs, generating various functional composite electrospun fibers with controllable morphologies and superior performance. Despite the ongoing development and various applications of surface segregation electrospun fibers, surface segregation engineering in electrospinning has not been reviewed by far. To address this gap, this review presents the state-of-the-art developments of the functional molecules surface segregation engineering in electrospinning. Firstly, surface segregation phenomenon and the combination with electrospinning is presented. Secondary, process design and regulation methods of surface segregation during the whole electrospinning process are illustrated. Thirdly, characterization methods revealing the occurrence and extent of the surface segregation are comprehensively summarized. Finally, application of surface segregation electrospun fibers in prevalent fields such as gas sensing, separation and purification, superhydrophobization, anti-bacteria and biocompatibility improvement is discussed. We also highlight the challenges and further perspectives of the surface segregation engineering in electrospinning. This review aims to provide a comprehensive understanding and serve as a guide for future research and innovation in the design and application of functional molecules' surface segregation in electrospun fibers. [ABSTRACT FROM AUTHOR]

We present high-level, coupled-mode calculations of the infrared spectrum of the cyclic formic acid dimer. The calculations make use of full-dimensional, ab initio potential energy and dipole moment surfaces. The potential is a linear least-squares fit to 13 475 CCSD(T)-F12a/haTZ (haTZ means aug-cc-pVTZ basis set for O and C, and cc-pVTZ for H) energies, and the dipole moment surface is a fit to the dipole components, calculated at the MP2/haTZ level of theory. The variables of both fits are all (45) internuclear distances (actually Morse variables). The potential, which is fully permutationally invariant, is the one published recently and the dipole moment surface is newly reported here. Details of the fits, especially the dipole moment, and the database of configurations are given. The infrared spectrum of the dimer is calculated by solving the nuclear Schrödinger equation using a vibrational self-consistent field and virtual-state configuration interaction method, with subsets of the 24 normal modes, up to 15 modes. The calculations indicate strong mode-coupling in the C—H and O—H stretching region of the spectrum. Comparisons are made with experiments and the complexity of the experimental spectrum in the C—H and O—H stretching region is successfully reproduced. [ABSTRACT FROM AUTHOR]

For preparing high-performance electrospun fibers with functional molecules that cannot cross-entangle themselves, such as conductive polymers, promoting the aggregation of functional molecules on the surface by surface segregation is a promising approach. In the present study, electrospun polymethyl methacrylate/polyaniline (PMMA/PANI) fibers were prepared under various conditions, including solution composition, applied voltage, tip-to-collector distance, temperature, humidity, and gas-phase solvent concentration, to examine the effects of the parameters on fiber morphology and surface segregation. The changes in fiber morphology and variations in the intensity of PANI and PMMA's characteristic bands were investigated with scanning electron microscopy (SEM) and Raman spectroscopy. The results demonstrated that by changing the saturation difference and the viscosity, the amount of PMMA and PANI added significantly influenced whether surface segregation could occur. The effect of other investigated parameters on surface segregation was concluded to alter the molecular migratable time by affecting the jet flight time and the solvent volatilization rate. Among them, increasing the solvent concentration could significantly promote surface segregation without sacrificing morphological advantages. When the solvent concentration increased from 1.4 to 158 mg/m3, the Raman peak intensity ratio of PANI and PMMA increased from 2.91 to 5.05, while the fiber diameter remained essentially constant. [ABSTRACT FROM AUTHOR]

Objective: High concentrate diets are widely used to satisfy high-yielding dairy cows; however, long-term feeding of high concentrate diets can cause subacute ruminal acidosis (SARA). The endocrine disturbance is one of the important reasons for metabolic disorders caused by SARA. However, there is no current report about thyroid hormones involved in liver metabolic disorders induced by a high concentrate diet. Methods: In this study, 12 mid-lactating dairy cows were randomly assigned to HC (high concentrate) group (60% concentrate of dry matter, n = 6) and LC (low concentrate) group (40% concentrate of dry matter, n = 6). All cows were slaughtered on the 21st day, and the samples of blood and liver were collected to analyze the blood biochemistry, histological changes, thyroid hormones, and the expression of genes and proteins. Results: Compared with LC group, HC group showed decreased serum triglyceride, free fatty acid, total cholesterol, low-density lipoprotein cholesterol, increased hepatic glycogen, and glucose. For glucose metabolism, the gene and protein expression of glucose-6- phosphatase and phosphoenolpyruvate carboxykinase 1 in the liver were significantly up-regulated in HC group. For lipid metabolism, the expression of sterol regulatory element-binding protein 1, long-chain acyl-CoA synthetase 1, and fatty acid synthase in the liver was decreased in HC group, whereas carnitine palmitoyltransferase 1α and peroxisome proliferator activated receptor α were increased. Serum triiodothyronine, thyroxin, free triiodothyronine (FT3), and hepatic FT3 increased in HC group, accompanied by increased expression of thyroid hormone receptor (THR) in the liver. Conclusion: Taken together, thyroid hormones may increase hepatic gluconeogenesis, β-oxidation and reduce fatty acid synthesis through the THR pathway to participate in the metabolic disorders caused by a high concentrate diet. [ABSTRACT FROM AUTHOR]

Bamboo-cultured cells (BCCs) were produced under three phytohormone conditions. BCC lignin was then isolated and characterized by heteronuclear single-quantum coherence-nuclear magnetic resonance (HSQC-NMR) analysis. HSQC-NMR analysis revealed that all three BCC lignin samples were composed of guaiacyl (G), syringyl (S), oxidized syringyl (S′), and p-hydroxyphenyl (H) units. p-Coumaric acid (pCA) and ferulic acid (FA) were identified as well. Main lignin substructures, including β-O-4, β-5, and β-β, were also detected. However, β-O-4/α-O-4, spirodienone, dibenzodioxocin, or tricin structures were absent in the BCC lignin. The BCC lignin contained higher proportions of H, FA, and β-5 structures, but less proportions of S, S′, and β-O-4 structures than the mature bamboo lignin. The removal of auxin 2,4-dichlorophenoxyacetic acid (2,4-D) from the subculture medium promoted G unit formations. Nevertheless, it suppressed H and pCA unit formations. Cytokinin 6-benzyladenine (BA) promoted H and β-β structure formations as well but suppressed β-O-4 formations than in the mature bamboo and BCC lignin produced under phytohormone free conditions. [ABSTRACT FROM AUTHOR]

• The neurocomputational bases of moral decisions can be studied with model-based fMRI. • Moral choices are modeled as decisions weighing self-interests against moral costs. • Decision value computations preside moral choices. • Distinct prediction error signals can be distinguished to account for moral learning. The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making. [ABSTRACT FROM AUTHOR]

Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculations based on the measures above. Simulation studies show that the estimators perform well for common values of the C-statistic and outcome prevalence when the linear predictor is marginally Normal. Their performance deteriorates only slightly when the normality assumptions are violated. We also propose estimators which do not require normality assumptions but require specification of the marginal distribution of the linear predictor and require the use of numerical integration. These estimators were also seen to perform very well under marginal normality. Our sample size equations require a specified standard error (SE) and the anticipated C-statistic and outcome prevalence. The sample size requirement varies according to the prognostic strength of the model, outcome prevalence, choice of the performance measure and study objective. For example, to achieve an SE < 0.025 for the C-statistic, 60–170 events are required if the true C-statistic and outcome prevalence are between 0.64–0.85 and 0.05–0.3, respectively. For the calibration slope and calibration in the large, achieving SE < 0.15 would require 40–280 and 50–100 events, respectively. Our estimators may also be used for survival outcomes when the proportion of censored observations is high. [ABSTRACT FROM AUTHOR]

Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculations based on the measures above. Simulation studies show that the estimators perform well for common values of the C-statistic and outcome prevalence when the linear predictor is marginally Normal. Their performance deteriorates only slightly when the normality assumptions are violated. We also propose estimators which do not require normality assumptions but require specification of the marginal distribution of the linear predictor and require the use of numerical integration. These estimators were also seen to perform very well under marginal normality. Our sample size equations require a specified standard error (SE) and the anticipated C-statistic and outcome prevalence. The sample size requirement varies according to the prognostic strength of the model, outcome prevalence, choice of the performance measure and study objective. For example, to achieve an SE < 0.025 for the C-statistic, 60-170 events are required if the true C-statistic and outcome prevalence are between 0.64-0.85 and 0.05-0.3, respectively. For the calibration slope and calibration in the large, achieving SE < 0.15 would require 40-280 and 50-100 events, respectively. Our estimators may also be used for survival outcomes when the proportion of censored observations is high. [ABSTRACT FROM AUTHOR]

Holes are commonly associated with high-dimensional, non-parametric representations of potential energy surfaces (PESs). These are regions of the PES with large negative values. Typically these occur at highly distorted geometries of (in reality) high energy. Finding holes in a systematic and efficient way is thus an important aspect in the development of PESs. Here we propose using diffusion Monte Carlo (DMC) with artificially reduced masses to automatically and robustly sample large regions of a fit, including those at very high energies. We demonstrate this for a recent PES of methane that was obtained using energies and gradients. The DMC software with the methane potential is available for download. [ABSTRACT FROM AUTHOR]

Dynamic buckling of a submerged cylindrical shell subjected to underwater explosion (UNDEX) is numerically investigated by coupled acoustic-structural analysis with ABAQUS/Explicit. The total wave algorithm is adopted due to cavitation induced by fluid-structure interaction, and the critical buckling load is predicted by the Budiansky-Roth criterion. Three failure modes closely related to the immersion depth and charge mass are observed, and numerical results indicate shock wave and bubble pulsation generated by UNDEX lead to completely different buckling modes of the cylindrical shell. For the small immersion depth and charge mass, shock wave results in local buckling near both ends of the shell due to stress concentration and stress wave propagation. With the increase of the charge mass or the immersion depth, the local buckling observed in the shock wave stage evolves to global buckling in the middle region of the shell during the subsequent bubble pulsation stage. However, the further increase of the immersion depth results in a significant increase in the bubble pulsation load. Then, although the shock wave below the critical buckling load can not cause local buckling of the shell, the subsequent bubble pulsation directly results in global buckling in the middle region of the shell. • Dynamic buckling of a cylindrical shell subjected to the coupled hydrostatic pressure and underwater explosion loads are investigated. • Three failure modes closely related to the immersion depth and charge mass are observed, and the failure mechanisms are investigated. • Axial and circumferential buckling modes of the cylindrical shell subjected to shock wave and bubble pulsation are compared. [ABSTRACT FROM AUTHOR]

Nanopores can serve as a molecule channel for transport of fluid, where water diffusion differs remarkably from that of simple particles. Hydrogen bonds play an essential role in the diffusion anomaly. Detailed investigations are carried out on the systems of rigid (6, 6), (7, 7), (8, 8), (9, 9), and (10, 10) armchair carbon nanotubes, solvated with Lennard-Jones water fluids. The role of hydrogen bonds is examined by diffusivity statistics and animation snapshots. It is found that in small (6,6) CNT, hydrogen bonds tend to aggregate water into a wire and lead to rapid collective drift. Confinement can stabilize the hydrogen bond of water molecules and enhance its lifetime. In relatively smaller CNTs, the diffusion mechanism could be altered by the temperature. Moreover, in larger nanotubes hydrogen bonding network allows the water to form regional concentrated clusters. This allows water fluid in extremely low density exhibit rather slow self-diffusion motion. This fundamental study attempts to provide insights in understanding nanoscale delivery system in aqueous solution. [ABSTRACT FROM AUTHOR]

Intermolecular interactions in bulk water are dominated by pairwise and non‐pairwise cooperative interactions. While accurate descriptions of the pairwise interactions are available and can be tested by precise low‐frequency spectra of the water dimer up to 550 cm−1, the same does not hold for the three‐body interactions. Here, we report the first comprehensive spectrum of the water trimer in the frequency region from 70 to 620 cm−1 using helium‐nanodroplet isolation and free‐electron lasers. By comparison to accompanying high‐level quantum calculations, the experimentally observed intermolecular bands can be assigned. The transition frequencies of the degenerate translation, the degenerate in‐plane and the non‐degenerate out‐of‐plane libration, as well as additional bands of the out‐of‐plane librational mode are reported for the first time. These provide a benchmark for state‐of‐the‐art water potentials and dipole‐moment surfaces, especially with respect to three‐body interactions. [ABSTRACT FROM AUTHOR]

Intermolecular interactions in bulk water are dominated by pairwise and non‐pairwise cooperative interactions. While accurate descriptions of the pairwise interactions are available and can be tested by precise low‐frequency spectra of the water dimer up to 550 cm−1, the same does not hold for the three‐body interactions. Here, we report the first comprehensive spectrum of the water trimer in the frequency region from 70 to 620 cm−1 using helium‐nanodroplet isolation and free‐electron lasers. By comparison to accompanying high‐level quantum calculations, the experimentally observed intermolecular bands can be assigned. The transition frequencies of the degenerate translation, the degenerate in‐plane and the non‐degenerate out‐of‐plane libration, as well as additional bands of the out‐of‐plane librational mode are reported for the first time. These provide a benchmark for state‐of‐the‐art water potentials and dipole‐moment surfaces, especially with respect to three‐body interactions. [ABSTRACT FROM AUTHOR]

Immoral behavior often consists of weighing transgression of a moral norm against maximizing personal profits. One important question is to understand why immoral behaviors vary based on who receives specific benefits and what are the neurocomputational mechanisms underlying such moral flexibility. Here, we used model-based functional magnetic resonance imaging to investigate how immoral behaviors change when benefiting oneself or someone else. Participants were presented with offers requiring a tradeoff between a moral cost (i.e. profiting a morally bad cause) and a benefit for either oneself or a charity. Participants were more willing to obtain ill-gotten profits for themselves than for a charity, driven by a devaluation of the moral cost when deciding for their own interests. The subjective value of an immoral offer, computed as a linear summation of the weighed monetary gain and moral cost, recruited the ventromedial prefrontal cortex (PFC) regardless of beneficiaries. Moreover, paralleling the behavioral findings, this region enhanced its functional coupling with mentalizing-related regions while deciding whether to gain morally tainted profits for oneself vs charity. Finally, individual differences in moral preference differentially modulated choice-specific signals in the dorsolateral PFC according to who benefited from the decisions. These findings provide insights for understanding the neurobiological basis of moral flexibility. [ABSTRACT FROM AUTHOR]

Inhibitor of apoptosis proteins (IAPs) maintain the balance between cell proliferation and cell death by inhibiting caspase activities and mediating immune responses. In the present study, a homolog of IAP (designated as EsIAP1) was identified from Chinese mitten crab Eriocheir sinensis. EsIAP1 consisted of 451 amino acids containing two baculoviral IAP repeat (BIR) domains with the conserved Cx2 Cx6 Wx3 Dx5 Hx6 C motifs. EsIAP1 mRNA was expressed in various tissues and its expression level in hemocytes increased significantly (p < 0.01) at 12–48 h after lipopolysaccharide stimulation. In the hemocytes, EsIAP1 protein was mainly distributed in the cytoplasm. The hydrolytic activity of recombinant EsCaspase-3/7-1 against the substrate Ac-DEVD-pNA decreased after incubation with rEsIAP1. Moreover, rEsIAP1 could directly combine with rEsCaspase-3/7-1 in vitro. After EsIAP1 was interfered by dsRNA, the mRNA expression and the hydrolytic activity of EsCaspase-3/7-1 increased significantly, which was 2.26-fold (p < 0.05) and 1.71-fold (p < 0.05) compared to that in the dsGFP group, respectively. These results collectively demonstrated that EsIAP1 might play an important role in apoptosis pathway by regulating the activity of EsCaspase-3/7-1 in E. sinensis. [ABSTRACT FROM AUTHOR]

Background: Risk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise model performance when the model is applied to new patients. For binary outcomes, the calibration slope (CS) and the mean absolute prediction error (MAPE) are two key measures on which sample size calculations for the development of risk models have been based. CS quantifies the degree of model overfitting while MAPE assesses the accuracy of individual predictions. Methods: Recently, two formulae were proposed to calculate the sample size required, given anticipated features of the development data such as the outcome prevalence and c-statistic, to ensure that the expectation of the CS and MAPE (over repeated samples) in models fitted using MLE will meet prespecified target values. In this article, we use a simulation study to evaluate the performance of these formulae. Results: We found that both formulae work reasonably well when the anticipated model strength is not too high (c-statistic < 0.8), regardless of the outcome prevalence. However, for higher model strengths the CS formula underestimates the sample size substantially. For example, for c-statistic = 0.85 and 0.9, the sample size needed to be increased by at least 50% and 100%, respectively, to meet the target expected CS. On the other hand, the MAPE formula tends to overestimate the sample size for high model strengths. These conclusions were more pronounced for higher prevalence than for lower prevalence. Similar results were drawn when the outcome was time to event with censoring. Given these findings, we propose a simulation-based approach, implemented in the new R package 'samplesizedev', to correctly estimate the sample size even for high model strengths. The software can also calculate the variability in CS and MAPE, thus allowing for assessment of model stability. Conclusions: The calibration and MAPE formulae suggest sample sizes that are generally appropriate for use when the model strength is not too high. However, they tend to be biased for higher model strengths, which are not uncommon in clinical risk prediction studies. On those occasions, our proposed adjustments to the sample size calculations will be relevant. [ABSTRACT FROM AUTHOR]

This work focuses on the dynamic properties and energetics of the protein/peptide drug during its transport through carbon nanotubes (CNTs). A systematic study was performed on the interaction between the peptide and the CNTs. In the molecular dynamics (MD) simulations, the protein/peptide molecule Zadaxin® is observed to be encapsulated inside the nanotube after its spontaneous insertion and oscillates around the center of the tube, where the van der Waals interaction energy is observed to be a minimum. Furthermore, it is found by performing steered MD simulations that the pulling force applied to the peptide reaches a maximum value, which demonstrates the ability of the CNTs to trap protein/peptide drugs. Such effects, attributed to van der Waals interactions, can be influenced by varying the lengths and diameters of the CNTs. Longer nanotubes provide a broader area to trap the peptide, while smaller nanotubes are able to encapsulate the peptide with a deeper interaction energy well. This investigation provides insights into nanoscale pharmaceutical drug delivery devices. [ABSTRACT FROM AUTHOR]

• Hepatic impairment increases the risk of drug overexposure in septic patients. • Up to now there has been a lack of effective indicators to predict linezolid overexposure risk. • ICG-PDR is an independent predictor of linezolid overexposure. • First pilot application of the ICG test demonstrating its potential to predict linezolid overexposure in septic patients. Hepatic impairment increases the risk of drug overexposure in septic patients. However, there is a lack of effective indicators to predict overexposure risk. The indocyanine green (ICG) clearance test is a helpful method for dynamically assessing hepatic function and perfusion. This study aimed to investigate whether the ICG test could serve as a potential predictor of linezolid trough concentration (C min) and to compare its efficacy with that of conventional liver function markers. A total of 35 consecutive septic patients treated with linezolid were grouped into either linezolid C min of ≤7 µg/mL or >7 µg/mL. Correlations between linezolid C min and ICG-PDR (plasma disappearance rate), ICG-R15 (retention ratio after 15 min) and other traditional indicators were analysed by Spearman's rank test. A multivariable regression model was employed to discern factors contributing independently to overexposure. Statistical differences were observed between groups for APACHE II score (P = 0.031), SOFA score (P = 0.018), creatinine clearance (CL Cr) (P = 0.003), thrombocytes (P = 0.039), lactate (P = 0.003), ICG-PDR (P < 0.001) and ICG-R15 (P < 0.001). Moreover, linezolid C min was correlated with ICG-PDR (ρ = –0.628, P < 0.001), ICG-R15 (ρ = 0.676, P < 0.001) and CL Cr (ρ = –0.503, P = 0.002). ICG-PDR was identified as an independent predictor of linezolid overexposure, with an optimal cut-off value of 17.70%/min (93.3% sensitivity, 85.0% specificity; P < 0.001). This pilot clinical trial represents the first investigation of potential of the ICG test to predict linezolid overexposure in septic patients. [ABSTRACT FROM AUTHOR]

Localized inflammation is accompanied by the diabetic-induced fracture. The present study aims to investigate the therapeutic effects of glyburide, an NLRP3 inflammasome inhibitor, in a diabetic-induced fracture model. An animal model of diabetic-induced fracture was established and the mice were administrated with metformin or glyburide for 3 weeks. Quantitative polymerase chain reaction (qPCR) and Western blotting were used to evaluate the relative expressions of IFN-γ, TNF-α, and IL-6. Micro-computed tomography (μCT) scanning was applied to evaluate bone callus formation. Histopathology examinations of fractured femur sections were performed using Tartrate-resistant acid phosphatase (TRAP) staining and Alcian blue and orange G staining. Bone strength was evaluated using Torsional testing. Our results showed that treatment of glyburide significantly decreased the expressions of IFN-γ, TNF-α, and IL-6 in the fracture calluses in diabetic-induced fracture model, while bone callus volume and bone volume fraction were increased. Additionally, our results also demonstrated that treatment of glyburide rescued the increase of osteoclasts in the bone-cartilage interface. Apart from decreasing a percentage of cartilage area and increasing the percentage of bone and fibrotic tissue area, treatment of glyburide increased the maximum torque and yield torque of fractures. These results implied that glyburide might be used as a potential drug candidate for diabetic-induced fracture. [ABSTRACT FROM AUTHOR]

Using the helium nanodroplet isolation setup at the ultrabright free‐electron laser source FELIX in Nijmegen (BoHeNDI@FELIX), the intermolecular modes of water dimer in the frequency region from 70 to 550 cm−1 were recorded. Observed bands were assigned to donor torsion, acceptor wag, acceptor twist, intermolecular stretch, donor torsion overtone, and in‐plane and out‐of‐plane librational modes. This experimental data set provides a sensitive test for state‐of‐the‐art water potentials and dipole moment surfaces. Theoretical calculations of the IR spectrum are presented using high‐level quantum and approximate quasiclassical molecular dynamics approaches. These calculations use the full‐dimensional ab initio WHHB potential and dipole moment surfaces. Based on the experimental data, a considerable increase of the acceptor switch and a bifurcation tunneling splitting in the librational mode is deduced, which is a consequence of the effective decrease in the tunneling barrier. [ABSTRACT FROM AUTHOR]

Using the helium nanodroplet isolation setup at the ultrabright free‐electron laser source FELIX in Nijmegen (BoHeNDI@FELIX), the intermolecular modes of water dimer in the frequency region from 70 to 550 cm−1 were recorded. Observed bands were assigned to donor torsion, acceptor wag, acceptor twist, intermolecular stretch, donor torsion overtone, and in‐plane and out‐of‐plane librational modes. This experimental data set provides a sensitive test for state‐of‐the‐art water potentials and dipole moment surfaces. Theoretical calculations of the IR spectrum are presented using high‐level quantum and approximate quasiclassical molecular dynamics approaches. These calculations use the full‐dimensional ab initio WHHB potential and dipole moment surfaces. Based on the experimental data, a considerable increase of the acceptor switch and a bifurcation tunneling splitting in the librational mode is deduced, which is a consequence of the effective decrease in the tunneling barrier. [ABSTRACT FROM AUTHOR]

Tumor cells avoid immunosurveillance during the tumorigenesis, metastasis and recurrence periods thanks to the overexpressed immunosuppressive molecules on their surface. For instance, the programmed cell death 1 ligand (PD-L1) binds with the T-cells' programmed cell death receptor 1 (PD-1) impairing the anti-tumor activity of the host T cells. In this study, a new reactive oxygen species (ROS) responsive nanoparticle (NP), modified with the HAIYPRH (T7) peptide, was developed for the co-delivery of siRNA-PD-L1 and doxorubicin (Dox). These NPs can block the inhibitory signal responding to T cells and enhance cytotoxicity of Dox against tumor cells. The T7 modification binds to the overexpressed transferrin receptor on tumor cells facilitating its cellular uptake. Dox rapid release is then triggered by the high tumor cells cytoplasmic concentration of ROS, leading to cell apoptosis. Our results demonstrated these NPs exhibited a T7-mediated cellular uptake and an intracellular ROS-triggered payloads release in vitro. They also suggested an improved in vivo 4T1 tumor targeting efficiency and chemoimmunotherapy. Most notably, the co-delivery system exhibited a significantly enhanced antitumor effect over Dox-only loaded NPs following prompting the proliferation of T cells by siRNA-PD-L1. In conclusion, these ROS-responsive NPs provided a promising strategy to combine siRNA-PD-L1 immunotherapy and Dox chemotherapy. [ABSTRACT FROM AUTHOR]

Humans not only value extrinsic monetary rewards but also their own morality and their image in the eyes of others. Yet violating moral norms is frequent, especially when people know that they are not under scrutiny. When moral values and monetary payoffs are at odds, how does the brain weigh the benefits and costs of moral and monetary payoffs? Here, using a neurocomputational model of decision value (DV) and functional (f)MRI, we investigated whether different brain systems are engaged when deciding whether to earn money by contributing to a "bad cause" and when deciding whether to sacrifice money to contribute to a "good cause," both when such choices were made privately or in public. Although similar principles of DV computations were used to solve these dilemmas, they engaged 2 distinct valuation systems. When weighing monetary benefits and moral costs, people were willing to trade their moral values in exchange for money, an effect accompanied by DV computation engaging the anterior insula and the lateral prefrontal cortex (PFC). In contrast, weighing monetary costs against compliance with one's moral values engaged the ventral putamen. Moreover, regardless of the type of dilemma, a brain network including the anterior cingulate cortex (ACC), anterior insula, and the right temporoparietal junction (TJP) was more engaged in public than in private settings. Together, these findings identify how the brain processes three sources of motivation: extrinsic rewards, moral values, and concerns for image. [ABSTRACT FROM AUTHOR]

Diffusion Monte Carlo (DMC) simulations have been used to obtain quantum zero‐point energies of methanol and all its isotopologs and isotopomers, using a new, accurate semi‐global potential energy surface. This potential energy surface is a precise, permutationally invariant fit to 6676 ab initio energies, obtained at the CCSD(T)‐F12b/aug‐cc‐pVDZ level of theory. Quantum zero‐point energies of deuterated methanol isotopomers are very close to each other and so a simple statistical argument can be used to estimate the populations of each isotopomer at very low‐temperatures. The DMC simulations also indicate that there is virtually zero probability for H/D exchange in the zero‐point state. © 2019 Wiley Periodicals, Inc. Diffusion Monte Carlo trajectories for indicated isotopologs and isotopomers of methanol. [ABSTRACT FROM AUTHOR]

Background: HER3 (ErbB3), a member of the human epidermal growth factor receptor family, is frequently overexpressed in various cancers. Multiple HER3-targeting antibodies and antibody–drug conjugates (ADCs) were developed for the solid tumor treatment, however none of HER3-targeting agent has been approved for tumor therapy yet. We developed DB-1310, a HER3 ADC composed of a novel humanized anti-HER3 monoclonal antibody covalently linked to a proprietary DNA topoisomerase I inhibitor payload (P1021), and evaluate the efficacy and safety of DB-1310 in preclinical models. Methods: The binding of DB-1310 to Her3 and other HER families were measured by ELISA and SPR. The competition of binding epitope for DB-1310 and patritumab was tested by FACS. The sensitivity of breast, lung, prostate and colon cancer cell lines to DB-1310 was evaluated by in vitro cell killing assay. In vivo growth inhibition study evaluated the sensitivity of DB-1310 to Her3 + breast, lung, colon and prostate cancer xenograft models. The safety profile was also measured in cynomolgus monkey. Results: DB-1310 binds HER3 via a novel epitope with high affinity and internalization capacity. In vitro, DB-1310 exhibited cytotoxicity in numerous HER3 + breast, lung, prostate and colon cancer cell lines. In vivo studies in HER3 + HCC1569 breast cancer, NCI-H441 lung cancer and Colo205 colon cancer xenograft models showed DB-1310 to have dose-dependent tumoricidal activity. Tumor suppression was also observed in HER3 + non-small cell lung cancer (NSCLC) and prostate cancer patient-derived xenograft (PDX) models. Moreover, DB-1310 showed stronger tumor growth-inhibitory activity than patritumab deruxtecan (HER3-DXd), which is another HER3 ADC in clinical development at the same dose. The tumor-suppressive activity of DB-1310 synergized with that of EGFR tyrosine kinase inhibitor, osimertinib, and exerted efficacy also in osimertinib-resistant PDX model. The preclinical assessment of safety in cynomolgus monkeys further revealed DB-1310 to have a good safety profile with a highest non severely toxic dose (HNSTD) of 45 mg/kg. Conclusions: These finding demonstrated that DB-1310 exerted potent antitumor activities against HER3 + tumors in in vitro and in vivo models, and showed acceptable safety profiles in nonclinical species. Therefore, DB-1310 may be effective for the clinical treatment of HER3 + solid tumors. [ABSTRACT FROM AUTHOR]

The enzyme catalysis conversion of lignocellulosic biomass into valuable chemicals and fuels showed a bright outlook for replacing fossil resources. However, the high cost and easy deactivation of free enzymes restrict the conversion process. Immobilization of enzymes in metal–organic frameworks (MOFs) is one of the most promising strategies due to MOF materials' tunable building units, multiple pore structures, and excellent biocompatibility. Also, MOFs are ideal support materials and could enhance the stability and reusability of enzymes. In this paper, recent progress on the conversion of cellulose, hemicellulose, and lignin by MOF-immobilized enzymes is extensively reviewed. This paper focuses on the immobilized enzyme performances and enzymatic mechanism. Finally, the challenges of the conversion of lignocellulosic biomass by MOF-immobilized enzyme are discussed. [ABSTRACT FROM AUTHOR]

Two practical and simple synthetic methodologies towards various heterobenzyl halides were developed. A series of 2-halomethylquinolines were readily prepared by the one-pot reaction of 2-methylquinolines with CuX (X = I, Br, Cl) and TBHP in CH 3 CN. A large variety of heterobenzyl iodides, including 2-iodomethylquinolines, 2-iodomethylquinoxalines, 2-iodiomethylbenzooxazole, and 2-iodiomethylbenzothiazole, were efficiently synthesized by one-pot reaction of 2-methylheterocycles with iodine in the presence of CuSO 4 ·5H 2 O in CH 3 CN. [ABSTRACT FROM AUTHOR]

Over the past decade, about 50 potential energy surfaces (PESs) for polyatomics with 4-11 atoms and for clusters have been calculated using the permutationally invariant polynomial method. This is a general, mainly linear least-squares method for precise mathematical fitting of tens of thousands of electronic energies for reactive and nonreactive systems. A brief tutorial of the methodology is given, including several recent improvements. Recent applications to the formic acid dimer (the current record holder in size for a reactive system), the H2-H2O complex, and four protonated water clusters [H+(H2O) n=2,3,4,6] are given. The last application also illustrates extension to large clusters using the many-body representation. [ABSTRACT FROM AUTHOR]

Suppressor of cytokine signaling (SOCS) is a family of cytokine-inducible negative regulators of cytokine signaling and it plays a crucial role in various physiological processes. In the present study, the full-length cDNA of a SOCS (designated as Es SOCS6) was cloned from Chinese mitten crab Eriocheir sinensis . The open reading frame of Es SOCS6 cDNA was of 1266 bp, which encoded a polypeptide of 421 amino acid residues. There were two typically conserved SOCS family domains in Es SOCS6, including a central Src homology 2 (SH2) domain and a C-terminal SOCS box. The deduced amino acid sequence of Es SOCS6 shared 72–76% similarity with those of other SOCS6 family members. Es SOCS6 mRNA was constitutively expressed in all the examined tissues with higher expression levels in the immune-related tissues, such as hepatopancreas, hemocytes and gill. The mRNA expression levels of the Es SOCS6 in hemocytes were significantly up-regulated after the stimulations with lipopolysaccharide (LPS), Aeromonas hydrophila and polyinosinic-polycytidylic acid (poly (I:C)). The mRNA expressions of threonine/serine protein kinase ( Es Akt) and Es Relish were dramatically declined after Es SOCS6 was interfered by dsRNA. Collectively, these results demonstrated that Es SOCS6 might regulate the activation of the NF-κB signaling pathway and play an important role in the innate immune responses of E. sinensis . [ABSTRACT FROM AUTHOR]

To study the influence of the defects on the flexural behavior of laminated T‐beams, full‐scale beam tests of three reinforced concrete laminated T‐beams with incomplete bonding and one non‐defective reinforced concrete laminated T‐beam were conducted under monotonic loading. The results showed that the failure modes and crack patterns of the defective beams were similar to those of beams without defects. However, horizontal cracks appeared in these defects. Although the peak loads of the four specimens were relatively close, the difference in the maximum deflection was distinct. The deflection span ratio of each specimen exceeded 1/17, and the displacement ductility ratio exceeded 15. The results indicate that internal defects have only a slight influence on the flexural capacity of laminated beams but significantly influence their ductility. [ABSTRACT FROM AUTHOR]

Severe fever with thrombocytopenia syndrome (SFTS) is a new infectious disease caused by bunyavirus, and the critically cases conform to the definition of sepsis. In order to compare the differences between SFTS sepsis and non-SFTS sepsis, a retrospective analysis was performed. Thirty-seven SFTS sepsis and 96 non-SFTS sepsis patients were enrolled. The clinical characteristics, laboratory results were compared between the two groups and independent prognostic risk of mortality were investigated respectively. Compared with non-SFTS sepsis, SFTS cases had lower white blood cell, neutrophil and platelet counts, prolonged activated partial thromboplastin time and decreased fibrinogen, slightly elevated inflammatory indicators. Interleukin-6 (IL-6), and acute physiology and chronic health evaluation Ⅱ (APACHE II) score were independent prognostic risk factors in non-SFTS sepsis. The mortality risk of STFS sepsis was related to the viral clearance. There was no difference in viral load between SFTS survivors and non-survivors on admission. However, the differences were significant on 5th, 7th, 10th, and 14th day, and all SFTS non-survivors died within 14 days. Viral clearance rate on 7th day was an independent risk factor for mortality in SFTS sepsis. The mortality risk of STFS sepsis was related to the viral clearance rate. • SFTS cases had lower leukocyte, neutrophil, platelet, coagulation disorder, elevated inflammatory indicators. • Interleukin-6, and APACHE II score were independent prognostic risk factors in non-SFTS sepsis. • Viral clearance rate (7th) was an independent risk factor for mortality in SFTS sepsis. [ABSTRACT FROM AUTHOR]

A high sensitive and selective electrochemical sensor for detection of daidzein based on molecular imprinted polymer (MIP) modified electrode was established. The sensitive layer was prepared by electropolymerization of o -phenylenediamine (o-PD) on the surface of Poly (sodium 4-styrenesulfonate)-reduced graphene oxide (PSS-rGO) modified glassy carbon electrode (PSS-rGO/GCE) in the presence of daidzein as a template molecule. The negatively charged poly(sodium 4-styrenesulfonate) units and benzene rings of PSS-rGO can attract positive charged o-PD and provide π-π stacking effect of o-PD and daidzein, which makes the compact imprinted film and more imprinted points. The MIP/PSS-rGO composite could specifically recognize daidzein in aqueous solutions which result in the decrease of peak current of K 3 [Fe(CN) 6 ]/K 4 [Fe(CN) 6 ] at the MIP/PSS-rGO/GCE. Under the optimized conditions, the decrease of the peak current was linear with the concentration of daidzein in the range of 1.0-20.0 nM. The detection limit was calculated as 0.5 nM (S/N = 3). Relative to the other structurally similar substances, the current response of the MIP/PSS-rGO/GCE toward daidzein was about 6.0, 3.1, 6.9 and 5.2 times higher than those of puerarin, quercetin, genistein and chrysin which suggesting the high selectivity of MIP/PSS-rGO/GCE. The modified electrode was successfully applied to determine daidzein in human serum and pueraria extraction with satisfied recovery suggesting the potential applications in the daidzein determination of clinical samples and nature products. [ABSTRACT FROM AUTHOR]

In the course of evolution, social dominance has been a strong force shaping the organization of social systems in many species. Individuals with a better ability to represent social dominance relationships and to adapt their behavior accordingly usually achieve better access to resources, hence providing benefits in terms of reproduction, health, and wellbeing. Understanding how and to what extent our brains are affected by social dominance requires interdisciplinary efforts. Here, we integrate findings from social neuroscience, evolutionary biology, and developmental psychology to highlight how social hierarchies are learned and represented in primates. We also review neuropharmacological findings showing how dopamine, serotonin, and testosterone influence social hierarchies and we emphasize their key clinical implications on vulnerabilities to neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

A practical and efficient method for the synthesis of 2-aroxy(alkoxy)quinolines has been developed by direct crossdehydrogenative coupling reaction between quinoline N-oxides and readily available phenols and alcohols in the presence of H-phosphonate and CCl4 under mild conditions. [ABSTRACT FROM AUTHOR]

The edges of 2D materials show novel electronic, magnetic, and optical properties, especially when reduced to nanoribbon widths. Therefore, methods to create atomically flat edges in 2D materials are essential for future exploitation. Atomically flat edges in 2D materials are found after brittle fracture or when electrically biasing, but a simple scalable approach for creating atomically flat periodic edges in monolayer 2D transition metal dichalcogenides has yet to be realized. Here, we show how heating monolayer MoS2 to 800 °C in vacuum produces atomically flat Mo terminated zigzag edges in nanoribbons. We study this at the atomic level using an ultrastable in situ heating holder in an aberration-corrected transmission electron microscope and discriminating Mo from S at the edge, revealing unique Mo terminations for all zigzag orientations that remain stable and atomically flat when cooling back to room temperature. Highly faceted MoS2 nanoribbon constrictions are produced with Mo rich edge structures that have theoretically predicted spin separated transport channels, which are promising for spin logic applications. [ABSTRACT FROM AUTHOR]

The dynamic bubble behaviors on submerged micro-orifices are investigated experimentally. The orifice diameters are within the range of 0.11–0.24 mm, and the range of gas flow rate is between 0.167 and 25 ml/min. The experimental data were recorded using a high-speed camera, and images were analyzed with the help of MATLAB. The bubble formation processes on the submerged micro-orifices show some new and different dynamic behaviors, such as multi-bubble coalescence, and the alternate appearance of paring and single bubbles. At low Bond numbers (variation in the orifice radii), with an increase in Weber number (variation in the gas flow rate), a bubble first emerges during a single period stage followed by a multi-bubble coalescence stage. The bubble coalescence processes can be divided into five cases according to the number of coalescing bubbles. With an increase in the gas flow rate, it was found that the complete bubble detachment time and the detachment volume increase. Meanwhile, based on an analysis of the bubble aspect ratio and rising velocity, departing bubbles were shown to suffer stronger oscillations. At a higher Bond number, a bubble first appears in a single form, followed by a period of double bubble behaviors, and back to a period of single form. Finally, a bubbling regime map was constructed to describe the dynamic behaviors of bubbles under the conditions of different Weber and Bond numbers. [ABSTRACT FROM AUTHOR]

Epithelial-mesenchymal transition (EMT) is a phenomenon in cancer progression during which cancer cells undergo remarkable alteration acquiring highly invasive property. The aim of this study was to evaluate specific N-glycan alterations during EMT induced by epidermal growth factor (EGF) in GE11 epithelial cells. Herein, we demonstrated that EGF activated epidermal growth factor receptor (EGFR)/Akt/extracellular signal-regulated kinase (ERK) phosphorylation and promoted GE11 cell proliferation. Meanwhile, EGF stimulated the epithelial cells to undergo morphological alteration, destroying cell-cell inter-contact and exhibiting mesenchymal cells higher metastatic potential. A wound-healing assay showed the migratory ability increased 1.5-fold after EGF treatment. Moreover, the relative intensity of N-cadherin versus E-cadherin increased 2.6-fold, and the E-cadherin distribution in cell-cell junctions became jagged and faint after EGF incubation for 72 h. Interestingly, the amounts of bisecting GlcNAc structure were dramatically declined, by contrast, the formation of β1,6 GlcNAc branches on cell surface was upregulated during EMT induced by EGF. To understand the roles of N-glycans in EGF-induced EMT, the cells were stably transfected with N-acetylglucosaminyltransferase III (GnT-III), which catalyzes the bisecting GlcNAc structure formation. As the markers for EMT, EGF-induced E-cadherin decrease and fibronectin increase were delayed in GnT-III-overexpressing cells. Taken together, these results demonstrated that specific N-glycan alterations were coupled in EMT induced by EGF, which might be contributed to diagnosis and therapy of tumor metastasis. [ABSTRACT FROM AUTHOR]

A full-dimensional, permutationally invariant potential energy surface (PES) for the glycine amino acid is reported. A precise fit to energies and gradients calculated at the density functional theory (DFT)/B3LYP level of electronic-structure theory with Dunning's aug-cc-pVDZ basis set is performed involving 20 000 low-energy points and associated Cartesian gradients plus about 50 000 additional higher-energy points. The fact that newly calculated DFT/B3LYP energies for the main stationary points are close to the coupled-cluster single-double-triple [CCSD(T)] values, recently reported in the literature, provides reassurance about the accuracy of the constructed PES. Eight conformers and numerous saddle points are identified and characterized by describing geometries, relative stability, and harmonic frequencies. Stochastic and dynamical approaches are employed to study the vibrational ground state. Specifically, diffusion Monte Carlo simulations and approximate quantum dynamics, performed by means of the adiabatic switching semiclassical initial value representation technique, provide zero-point energies in excellent agreement with each other. The PES we report is sufficiently complete to permit spectroscopic and dynamical studies on glycine, which may be of interest to the biochemical and astrochemistry communities. [ABSTRACT FROM AUTHOR]

Ethnopharmacological relevance American ginseng is capable of ameliorating cardiac dysfunction and activating Nrf2, a master regulator of antioxidant defense, in the heart. This study was designed to isolate compounds from American ginseng and to determine those responsible for the Nrf2-mediated resolution of inflamed macrophage-induced cardiomyocyte hypertrophy. Materials and methods A standardized crude extract of American ginseng was supplied by the National Research Council of Canada, Institute for National Measurement Standards. A bioassay-based fractionization of American ginseng was performed to identify the putative substances which could activate Nrf2-mediated suppression of pro-inflammatory cytokine expression in macrophages and macrophage-mediated pro-hypertrophic growth in cardiomyocytes. Results A hexane fraction of an anti-inflammatory crude extract of American ginseng was found to be most effective in suppressing the inflammatory responses in macrophages. Preparative, reverse-phase HPLC and a comparative analysis by analytical scale LC–UV/MS revealed the hexane fraction contains predominantly C 17 polyacetylenes and linolenic acid. Panaxynol, one of the major polyacetylenes, was found to be a potent Nrf2 activator. Panaxynol posttranscriptionally activated Nrf2 by inhibiting Kelch-like ECH-associated protein (Keap) 1-mediated degradation without affecting the binding of Keap1 and Nrf2. Moreover, panaxynol suppressed a selected set of cytokine expression via the activation of Nrf2 while minimally regulating nuclear factor-kappa B (NF-κB)-mediated cytokine expression in macrophages. It also dramatically inhibited the inflamed macrophage-mediated cardiomyocyte death and hypertrophy by activating Nrf2 in macrophages. Conclusions These results demonstrate that American ginseng-derived panaxynol is a specific Nrf2 activator and panaxynol-activated Nrf2 signaling is at least partly responsible for American ginseng-induced health benefit in the heart. [ABSTRACT FROM AUTHOR]