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The boron-vacancy spin defect ( V B − ) in hexagonal boron nitride (hBN) has a great potential as a quantum sensor in a two-dimensional material that can directly probe various external perturbations in atomic-scale proximity to the quantum sensing layer. Here, we apply first-principles calculations to determine the coupling of the V B − electronic spin to strain and electric fields. Our work unravels the interplay between local piezoelectric and elastic effects contributing to the final response to the electric fields. The theoretical predictions are then used to analyse optically detected magnetic resonance (ODMR) spectra recorded on hBN crystals containing different densities of V B − centres. We prove that the orthorhombic zero-field splitting parameter results from local electric fields produced by surrounding charge defects. This work paves the way towards applications of V B − centres for quantitative electric field imaging and quantum sensing under pressure. [ABSTRACT FROM AUTHOR]

Objective: Myocardial ischemia/reperfusion (MI/R) injury is a complicated pathophysiological process associated with cardiomyocyte pyroptosis. Methyltransferase-like protein 3 (METTL3) catalyzes the formation of N6-methyl-adenosine (m6A) and participates in various biological processes. This study probed into the mechanism of METTL3 in cardiomyocyte pyroptosis in MI/R injury. Methods: A rat model of MI/R was established. Rat cardiomyocytes were subjected to oxygen–glucose deprivation/reoxygenation (OGD/R) treatment for the establishment of a cell model in vitro. METTL3 expression in myocardial tissues of MI/R rats and OGD/R-treated cardiomyocytes was determined using RT-qPCR and Western blot. The pathological changes of rat myocardial tissues were observed using hematoxylin and eosin staining. The positive expression of NLRP3 in myocardial tissues or cardiomyocytes was observed through immunohistochemistry or immunofluorescence. The activity of caspase-1 was measured using the colorimetric method. The expressions of GSDMD and cleaved caspase-1, as well as the levels of IL-1β and IL-18 in rat myocardial tissues or cardiomyocytes were determined. m6A modification level was quantified. The binding relationship between pri-miR-143-3p and DGCR8 and the enrichment of m6A on pri-miR-143-3p were detected. The binding relationship between miR-143-3p and protein kinase C epsilon (PRKCE) was verified. Results: METTL3 expression was elevated in MI/R rats and OGD/R cardiomyocytes. METTL3 silencing alleviated myocardial injury, reduced the number of NLRP3-positive cardiomyocytes, suppressed caspase-1 activity, decreased the protein levels of GSDMD-N and cleaved caspase-1, and decreased IL-1β and IL-18 levels. METTL3 increased the total m6A level in MI/R rats and injured cardiomyocytes, promoted DGCR8 binding to pri-miR-143-3p, and enhanced miR-143-3p expression. miR-143-3p suppressed PRKCE transcription, and miR-143-3p overexpression reversed the inhibitory effect of METTL3 silencing on cardiomyocyte pyroptosis. Conclusion: METTL3 promoted DGCR8 binding to pri-miR-143-3p through m6A modification, thus enhancing miR-143-3p expression to inhibit PRKCE transcription and further aggravating cardiomyocyte pyroptosis and MI/R injury. [ABSTRACT FROM AUTHOR]

Phonon polariton (PhP) nanoresonators can dramatically enhance the coupling of molecular vibrations and infrared light, enabling ultrasensitive spectroscopies and strong coupling with minute amounts of matter. So far, this coupling and the resulting localized hybrid polariton modes have been studied only by far-field spectroscopy, preventing access to modal near-field patterns and dark modes, which could further our fundamental understanding of nanoscale vibrational strong coupling (VSC). Here we use infrared near-field spectroscopy to study the coupling between the localized modes of PhP nanoresonators made of h-BN and molecular vibrations. For a most direct probing of the resonator-molecule coupling, we avoid the direct near-field interaction between tip and molecules by probing the molecule-free part of partially molecule-covered nanoresonators, which we refer to as remote near-field probing. We obtain spatially and spectrally resolved maps of the hybrid polariton modes, as well as the corresponding coupling strengths, demonstrating VSC on a single PhP nanoresonator level. Our work paves the way for near-field spectroscopy of VSC phenomena not accessible by conventional techniques. Vibrational strong coupling (VSC) promises ultrasensitive IR spectroscopy and modification of material properties. Here, nanoscale mapping of VSC between organic molecules and individual IR nanoresonators is achieved by remote near-field spectroscopy. [ABSTRACT FROM AUTHOR]

Polaritons enable subwavelength confinement and highly anisotropic flows of light over a wide spectral range, holding the promise for applications in modern nanophotonic and optoelectronic devices. However, to fully realize their practical application potential, facile methods enabling nanoscale active control of polaritons are needed. Here, we introduce a hybrid polaritonic-oxide heterostructure platform consisting of van der Waals crystals, such as hexagonal boron nitride (hBN) or alpha-phase molybdenum trioxide (α-MoO3), transferred on nanoscale oxygen vacancy patterns on the surface of prototypical correlated perovskite oxide, samarium nickel oxide, SmNiO3 (SNO). Using a combination of scanning probe microscopy and infrared nanoimaging techniques, we demonstrate nanoscale reconfigurability of complex hyperbolic phonon polaritons patterned at the nanoscale with high resolution. Hydrogenation and temperature modulation allow spatially localized conductivity modulation of SNO nanoscale patterns, enabling robust real-time modulation and nanoscale reconfiguration of hyperbolic polaritons. Our work paves the way towards nanoscale programmable metasurface engineering for reconfigurable nanophotonic applications. Phonon polaritons in anisotropic van der Waals materials enable subwavelength confinement and controllable flow of light at the nanoscale. Here, the authors exploit correlated perovskite oxide (SmNiO3) substrates with tunable conductivity to obtain real-time modulation and nanoscale reconfiguration of hyperbolic polaritons in hBN and α-MoO3 crystals. [ABSTRACT FROM AUTHOR]

Feature extraction is one of most important steps in the control of multifunctional prosthesis based on surface electromyography (sEMG) pattern recognition. In this paper, a new sEMG feature extraction method based on muscle active region is proposed. This paper designs an experiment to classify four hand motions using different features. This experiment is used to prove that new features have better classification performance. The experimental results show that the new feature, active muscle regions (AMR), has better classification performance than other traditional features, mean absolute value (MAV), waveform length (WL), zero crossing (ZC) and slope sign changes (SSC). The average classification errors of AMR, MAV, WL, ZC and SSC are 13%, 19%, 26%, 24% and 22%, respectively. The new EMG features are based on the mapping relationship between hand movements and forearm active muscle regions. This mapping relationship has been confirmed in medicine. We obtain the active muscle regions data from the original EMG signal by the new feature extraction algorithm. The results obtained from this algorithm can well represent hand motions. On the other hand, the new feature vector size is much smaller than other features. The new feature can narrow the computational cost. This proves that the AMR can improve sEMG pattern recognition accuracy rate. [ABSTRACT FROM AUTHOR]

Conventional univariate drought frequency analysis should be replaced by the multivariate framework due to the correlated characteristics, such as duration, peak intensity, and severity. Compared to the bivariate case, trivariate analysis would be more considerable. Furthermore, the absence of historical records has a great impact on the reliability of statistical estimates. Multivariate regional frequency analysis approach would be a better choice for providing reliable information for risks assessment and management purpose. Standardized precipitation evapotranspiration index was used in this study to define and detect drought because of the global warming effect. A method based on the cubic spline interpolation was applied to derive drought samples. Applying the multivariate discordancy and homogeneity test, the Pearl River basin was divided into five homogeneous subregions. Regional distributions including marginal distribution and copula function were chosen based on the goodness-of-fit test. Finally, return periods were computed from a regional perspective to assess the different drought risks. The results indicate that high drought risks might exist in the Pearl River basin and the spatial distinction must be taken seriously. Due to the contradiction of water supply and requirement among different districts or provinces, policies needed to be made seriously and urgently to solve the unbalance between water resource and socioeconomic development. [ABSTRACT FROM AUTHOR]

Resveratrol (RSV), a natural polyphenolic antioxidant, has been considered an anticarcinogenic agent as it triggers tumor cell apoptosis through activation of the mitochondrial pathway. In our study, the effects of RSV on mitochondria, especially on the mitochondrial permeability transition (MPT) process, were investigated by multiple methods. We found that RSV induced a collapse of membrane potential and matrix swelling related to MPT. We further demonstrated that Ca was necessary for this RSV-induced MPT opening. In addition, RSV induced the inner membrane permeabilization to H and K, the depression of respiration and changes in membrane fluidity. The results suggested that RSV-induced MPT was accompanied by mitochondrial dysfunction. But the prohibition on lipid peroxidation and different effects of low- and high-dose RSV on membrane fluidity and respiration showed that the interaction of RSV and the mitochondria could not be the result of a single simple mechanism. [ABSTRACT FROM AUTHOR]

Genomic imprinting, an epigenetic phenomenon of parent-of-origin-specific gene expression, has been widely observed in plants, animals, and humans. To detect imprinting genes influencing quantitative traits, the least squares and maximum likelihood approaches for fitting a single quantitative trait locus (QTL) and Bayesian methods for simultaneously modeling multiple QTL have been adopted, respectively, in various studies. However, most of these studies have only estimated imprinting main effects and thus ignored imprinting epistatic effects. In the presence of extremely complex genomic imprinting architectures, we introduce a Bayesian model selection method to analyze the multiple interacting imprinted QTL (iQTL) model. This approach will greatly enhance the computational efficiency through setting the upper bound of the number of QTLs and performing selective sampling for QTL parameters. The imprinting types of detected main-effect QTLs can be estimated from the Bayes factor statistic formulated by the posterior probabilities for the genetic effects being compared. The performance of the proposed method is demonstrated by several simulation experiments. Moreover, this method is applied to dissect the imprinting genetic architecture for body weight in mouse and fruit weight in tomato. Matlab code for implementing this approach will be available from the authors upon request. [ABSTRACT FROM AUTHOR]

Genomic imprinting, a genetic phenomenon of non-equivalent allele expression that depends on parental origins, has been ubiquitously observed in nature. It does not only control the traits of growth and development but also may be responsible for survival traits. Based on the accelerated failure time model, we construct a general parametric model for mapping the imprinted QTL (iQTL). Within the framework of interval mapping, maximum likelihood estimation of iQTL parameters is implemented via EM algorithm. The imprinting patterns of the detected iQTL are statistically tested according to a series of null hypotheses. BIC model selection criterion is employed to choose an optimal baseline hazard function with maximum likelihood and parsimonious parameters. Simulations are used to validate the proposed mapping procedure. A published dataset from a mouse model system was used to illustrate the proposed framework. Results show that among the five commonly used survival distributions, Log-logistic distribution is the optimal baseline hazard function for mapping QTL of hyperoxic acute lung injury (HALI) survival; under the log-logistic distribution, four QTLs were identified, in which only one QTL was inherited in Mendelian fashion, whereas others were imprinted in different imprinting patterns. [ABSTRACT FROM AUTHOR]

Without consideration of other linked QTLs responsible for dynamic trait, original functional mapping based on a single QTL model is not optimal for analyzing multiple dynamic trait loci. Despite that composite functional mapping incorporates the effects of genetic background outside the tested QTL in mapping model, the arbitrary choice of background markers also impact on the power of QTL detection. In this study, we proposed Bayesian functional mapping strategy that can simultaneously identify multiple QTL controlling developmental patterns of dynamic traits over the genome. Our proposed method fits the change of each QTL effect with the time by Legendre polynomial and takes the residual covariance structure into account using the first autoregressive equation. Also, Bayesian shrinkage estimation was employed to estimate the model parameters. Especially, we specify the gamma distribution as the prior for the first-order auto-regressive coefficient, which will guarantee the convergence of Bayesian sampling. Simulations showed that the proposed method could accurately estimate the QTL parameters and had a greater statistical power of QTL detection than the composite functional mapping. A real data analysis of leaf age growth in rice is used for the demonstration of our method. It shows that our Bayesian functional mapping can detect more QTLs as compared to composite functional mapping. [ABSTRACT FROM AUTHOR]

lthough genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data. [ABSTRACT FROM AUTHOR]

Polaritons formed by the coupling of light and material excitations enable light-matter interactions at the nanoscale beyond what is currently possible with conventional optics. However, novel techniques are required to control the propagation of polaritons at the nanoscale and to implement the first practical devices. Here we report the experimental realization of polariton refractive and meta-optics in the mid-infrared by exploiting the properties of low-loss phonon polaritons in isotopically pure hexagonal boron nitride interacting with the surrounding dielectric environment comprising the low-loss phase change material Ge3Sb2Te6. We demonstrate rewritable waveguides, refractive optical elements such as lenses, prisms, and metalenses, which allow for polariton wavefront engineering and sub-wavelength focusing. This method will enable the realization of programmable miniaturized integrated optoelectronic devices and on-demand biosensors based on high quality phonon resonators. Here, the authors experimentally demonstrate a platform for tunable polariton refractive and meta-optics based on hexagonal boron nitride and phase change Ge3Sb2Te6. This combination has the advantage of the long-lived phonon-polariton with switchable refractive index of the phase change material. [ABSTRACT FROM AUTHOR]

Hexagonal boron nitride (h-BN) has been predicted to exhibit an in-plane thermal conductivity as high as ~ 550 W m−1 K−1 at room temperature, making it a promising thermal management material. However, current experimental results (220–420 W m−1 K−1) have been well below the prediction. Here, we report on the modulation of h-BN thermal conductivity by controlling the B isotope concentration. For monoisotopic 10B h-BN, an in-plane thermal conductivity as high as 585 W m−1 K−1 is measured at room temperature, ~ 80% higher than that of h-BN with a disordered isotope concentration (52%:48% mixture of 10B and 11B). The temperature-dependent thermal conductivities of monoisotopic h-BN agree well with first principles calculations including only intrinsic phonon-phonon scattering. Our results illustrate the potential to achieve high thermal conductivity in h-BN and control its thermal conductivity, opening avenues for the wide application of h-BN as a next-generation thin-film material for thermal management, metamaterials and metadevices. Hexagonal boron nitride has been theoretically predicted to have high values for its thermal conductivity which would make it useful for thermal management of devices but these values have not been experimentally achieved. The authors manipulate the isotope concentration of B to increase the thermal conductivity and reach these predicted values. [ABSTRACT FROM AUTHOR]