237 research outputs found

    Phase Coupled Firing of Prefrontal Parvalbumin Interneuron With High Frequency Oscillations

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    The prefrontal cortex (PFC) plays a central role in executive functions and inhibitory control over many cognitive behaviors. Dynamic changes in local field potentials (LFPs), such as gamma oscillation, have been hypothesized to be important for attentive behaviors and modulated by local interneurons such as parvalbumin (PV) cells. However, the precise relationships between the firing patterns of PV interneurons and temporal dynamics of PFC activities remains elusive. In this study, by combining in vivo electrophysiological recordings with optogenetics, we investigated the activities of prefrontal PV interneurons and categorized them into three subtypes based on their distinct firing rates under different behavioral states. Interestingly, all the three subtypes of interneurons showed strong phase-locked firing to cortical high frequency oscillations (HFOs), but not to theta or gamma oscillations, despite of behavior states. Moreover, we showed that sustained optogenetic stimulation (over a period of 10 s) of PV interneurons can consequently modulate the activities of local pyramidal neurons. Interestingly, such optogenetic manipulations only showed moderate effects on LFPs in the PFC. We conclude that prefrontal PV interneurons are consist of several subclasses of cells with distinct state-dependent modulation of firing rates, selectively coupled to HFOs

    SAR-to-Optical Image Translation via Thermodynamics-inspired Network

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    Synthetic aperture radar (SAR) is prevalent in the remote sensing field but is difficult to interpret in human visual perception. Recently, SAR-to-optical (S2O) image conversion methods have provided a prospective solution for interpretation. However, since there is a huge domain difference between optical and SAR images, they suffer from low image quality and geometric distortion in the produced optical images. Motivated by the analogy between pixels during the S2O image translation and molecules in a heat field, Thermodynamics-inspired Network for SAR-to-Optical Image Translation (S2O-TDN) is proposed in this paper. Specifically, we design a Third-order Finite Difference (TFD) residual structure in light of the TFD equation of thermodynamics, which allows us to efficiently extract inter-domain invariant features and facilitate the learning of the nonlinear translation mapping. In addition, we exploit the first law of thermodynamics (FLT) to devise an FLT-guided branch that promotes the state transition of the feature values from the unstable diffusion state to the stable one, aiming to regularize the feature diffusion and preserve image structures during S2O image translation. S2O-TDN follows an explicit design principle derived from thermodynamic theory and enjoys the advantage of explainability. Experiments on the public SEN1-2 dataset show the advantages of the proposed S2O-TDN over the current methods with more delicate textures and higher quantitative results

    Blue phase liquid crystals stabilized by linear photo-polymerization

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    Stabilizing a photopolymer-embedded blue phase liquid crystal precursor with linearly polarized UV light is investigated experimentally. When the UV polarization axis is perpendicular to the stripe electrodes of an in-plane-switching cell, anisotropic polymer networks are formed through the linear photo-polymerization process and the electrostriction effect is suppressed. As a result, the measured hysteresis is dramatically reduced from 6.95% to 0.36% and the response time shortened by similar to 2x compared to unpolarized UV exposure. To induce larger anisotropy in polymer networks for mitigating the electrostriction effect, high-intensity linearly polarized UV exposure is preferred

    Electro-optic response of polymer-stabilized blue phase liquid crystals

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    The dynamic response of a polymer-stabilized blue phase liquid crystal (BPLC) is comprised of two distinct processes: Kerr effect-induced local reorientation and electrostriction-induced lattice distortion. A double exponential rise/decay model is proposed to analyze the underlying physical mechanisms. If the electric field is below a critical field (E-c), Kerr effect dominates and the response time is fast. However, when E \u3e E-c electrostriction effect manifests, leading to an increased response time and a noticeable hysteresis. A higher polymer concentration helps suppress electrostriction, but the tradeoff is increased operation voltage. These results provide useful guidelines for future BPLC material and device optimizations

    Evolution of anthropogenic air pollutant emissions in Guangdong Province, China, from 2006 to 2015

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    Guangdong Province (GD), one of the most prosperous and populous regions in China, still experiences haze events and growing ozone pollution in spite of the substantial air-quality improvement in recent years. Integrated control of fine particulate matter (PM2.5) and ozone in GD calls for a systematic review of historical emissions. In this study, emission trends, spatial variations, source-contribution variations, and reduction potentials of sulfur dioxide (SO2), nitrogen oxides (NO), PM2.5, inhalable particles (PM10), carbon monoxide (CO), ammonia (NH3), and volatile organic compounds (VOCs) in GD from 2006 to 2015 were first examined using a dynamic methodology, taking into account economic development, technology penetration, and emission controls. The relative change rates of anthropogenic emissions in GD during 2006-2015 are -48% for SO2, -0.5% for NO, -16% for PM2.5, -22% for PM10, 13% for CO, 3% for NH3, and 13% for VOCs. The declines of SO2, NO, PM2.5, and PM10 emissions in the whole province mainly resulted from the stringent emission control in the Pearl River delta (PRD) region, where most previous control measures were focused, especially on power plants (SO2 and NO), industrial combustion (SO2, PM2.5, PM10), on-road mobile sources (NO), and dust sources (PM2.5 and PM10). Emissions from other areas (non-PRD, NPRD), nevertheless, remain relatively stable due to the lax control measures and rapidly growing energy consumption. In addition, emission leaks of SO2 and NO from industries are observed from PRD to NPRD in 2010 and 2011. As a result, emissions in NPRD are increasingly important in GD, particularly those from industrial combustion. The contribution of NPRD to the total SO2 emissions in GD, for example, increased from 27% in 2006 to 48% in 2015. On-road mobile sources and solvent use are the two key sources that should receive more effective control measures in GD. Current control-driven emission reductions from on-road mobile sources are neutralized by the substantial growth of the vehicle population, while VOC emissions in GD steadily increase due to the growth of solvent use and the absence of effective control measures. Besides, future work could focus on power plants and industrial combustion in GD and industrial process sources in NPRD, which still have large emission reduction potentials. The historical emission inventory developed in this study not only helps to understand the emission evolution in GD, but also provides robust data to quantify the impact of emission and meteorology variations on air quality and unveil the primary cause of significant air-quality change in GD in the recent decade

    Emerging role of METTL3 in inflammatory diseases: mechanisms and therapeutic applications

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    Despite improvements in modern medical therapies, inflammatory diseases, such as atherosclerosis, diabetes, non-alcoholic fatty liver, chronic kidney diseases, and autoimmune diseases have high incidence rates, still threaten human health, and represent a huge financial burden. N6-methyladenosine (m6A) modification of RNA contributes to the pathogenesis of various diseases. As the most widely discussed m6A methyltransferase, the pathogenic role of METTL3 in inflammatory diseases has become a research hotspot, but there has been no comprehensive review of the topic. Here, we summarize the expression changes, modified target genes, and pathogenesis related to METTL3 in cardiovascular, metabolic, degenerative, immune, and infectious diseases, as well as tumors. In addition to epithelial cells, endothelial cells, and fibroblasts, METTL3 also regulates the function of inflammation-related immune cells, including macrophages, neutrophils, dendritic cells, Th17 cells, and NK cells. Regarding therapeutic applications, METTL3 serves as a target for the treatment of inflammatory diseases with natural plant drug components, such as emodin, cinnamaldehyde, total flavonoids of Abelmoschus manihot, and resveratrol. This review focuses on recent advances in the initiation, development, and therapeutic application of METTL3 in inflammatory diseases. Knowledge of the specific regulatory mechanisms involving METTL3 can help to deepen understanding of inflammatory diseases and lay the foundation for the development of precisely targeted drugs to address inflammatory processes

    On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies

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    Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772–0.942, 0.774–0.970, 0754–0.960, and 0.800–0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index
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