Acanthopanax senticosus improves cognitive impairment in Alzheimer's disease by promoting the phosphorylation of the MAPK signaling pathway.

Background: Acanthopanax senticosus (AS) can improve sleep, enhance memory, and reduce fatigue and is considered as an effective drug for Alzheimer's disease (AD). The therapeutic effect and mechanism need to be further investigated. Methods: To confirm the AS play efficacy in alleviating memory impairment in mice, 5×FAD transgenic mice were subjected to an open-field experiment and a novelty recognition experiment. Network pharmacology technique was used to analyze the information of key compounds and potential key targets of AS for the treatment of AD, molecular docking technique was applied to predict the binding ability of targets and compounds, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also performed on the targets to derive the possible metabolic processes and pathway mechanisms of AS in treating AD. Quantitative real-time PCR (qRT-PCR) and western blot technique were carried out to validate the candidate genes and pathways. Results: In the open-field experiment, compared with the wild-type (WT) group, the number of times the mice in the AD group crossed the central zone was significantly reduced (P< 0.01). Compared with the AD group, the number of times the mice in the AS group crossed the central zone was significantly increased (P< 0.001). In the new object recognition experiment, compared with the WT group, the percentage of times the AD group explored new objects was significantly reduced (P< 0.05). Compared with the AD group, the AS group had an increase in the percentage of time spent exploring new things and the number of times it was explored (P< 0.05). At the same time, the donepezil group had a significantly higher percentage of times exploring new things (P< 0.01). By using network pharmacology technology, 395 common targets of AS and AD were retrieved. The Cytoscape software was used to construct the protein-protein interaction (PPI) network of common targets. Using the algorithm, nine key targets were retrieved: APP, NTRK1, ESR1, CFTR, CSNK2A1, EGFR, ESR2, GSK3B, and PAK1. The results of molecular docking indicate that 11 pairs of compounds and their corresponding targets have a significant binding ability, as the molecular binding energies were less than -7.0. In comparison to the AD group, the mRNA expression of the key target genes was significantly decreased in the AS treatment group (P< 0.001). The KEGG analysis showed that the MAPK signaling pathway was significantly enriched, and Western blot confirmed that the TRAF6 protein decreased significantly (P< 0.0001). Meanwhile, the levels of MAP3K7 and P38 phosphorylation increased, and there was also an increase in the expression of HSP27 proteins. Conclusion: Our study indicates that the multi-component and multi-target properties of AS play an important role in the alleviation of anxiety and memory impairment caused by AD, and the mechanism is involved in the phosphorylation and activation of the MAPK signaling pathway. The results of this study could provide a novel perspective for the clinical treatment of AD.

Regime Map of the Effective Medium Approximation Modelling of Micro-Rough Surfaces in Ellipsometry.

In this work, we discuss the precision of the effective medium approximation (EMA) model in the data analysis of spectroscopic ellipsometry (SE) for solid materials with micro-rough surfaces by drawing the regime map. The SE parameters ψ (amplitude ratio) and Δ (phase difference) of the EMA model were solved by rigorous coupled-wave analysis. The electromagnetic response of the actual surfaces with micro roughness was simulated by the finite-difference time-domain method, which was validated by the experimental results. The regime maps associated with the SE parameters and optical constants n (refractive index) and k (extinction coefficient) of the EMA model were drawn by a comparison of the actual values with the model values. We find that using EMA to model micro-rough surfaces with high absorption can result in a higher precision of the amplitude ratio and extinction coefficient. The precisions of ψ, Δ, n and k increase as the relative roughness σ/λ (σ: the root mean square roughness, λ: the incident wavelength) decreases. The precision of ψ has an influence on the precision of k and the precision of Δ affects the precision of n. Changing σ alone has little effect on the regime maps of the relative errors of SE parameters and optical constants. A superior advantage of drawing the regime map is that it enables the clear determination as to whether EMA is able to model the rough surfaces or not.

Aerobic exercise combined with chlorogenic acid exerts neuroprotective effects and reverses cognitive decline in Alzheimer's disease model mice (APP/PS1) via the SIRT1/ /PGC-1α/PPARγ signaling pathway.

Alzheimer's disease (AD) is a prevalent neurodegenerative disease account for 60-80% of the total number of people with dementia, but its treatment and prevention strategies are still in a long process of exploration. It has been reported that a healthy lifestyle may be an effective non-pharmacological intervention for the prevention and treatment of AD, including increased physical activity and the consumption of polyphenol-rich foods. This study, therefore, investigated the effects of 8 weeks of moderate-intensity aerobic exercise (EX), administration of chlorogenic acid administration (GCA), and a combination of both (EX+GCA) on ß-amyloid (Aß) deposition, inflammatory factors, oxidative stress markers, neuronal damage, and cognitive performance in the brains of AD model mice (APP/PS1) and which signaling pathways may be responsible for these effects. The study used Western blot to detect the expression of signaling pathway-related proteins, enzyme-linked immunosorbent assay to detect the expression of inflammatory factors, hematoxylin-eosin staining to detect hippocampal neuronal morphology, immunohistochemistry to detect changes in Aß deposition in the hippocampus, an oxidative stress marker kit to detect oxidative stress status and the Morris water maze to detect changes in cognitive performance. This study showed that an 8-week intervention (EX/GCA/EX+GCA) activating the SIRT1/PGC-1α signaling pathway improved oxidative stress, neuroinflammation, Aß deposition, and cognitive performance in mice. However, there was no obvious difference between the EX and GCA groups. In contrast, the combined EX+GCA intervention was significantly better than phase EX or GCA. Our study suggests that although relief of Aß deposition, neuroinflammation, oxidative stress, neuronal damage, and cognitive decline could also be achieved with EX or GCA, the combined EX+GCA intervention showed better results. These relief effects on AD-related conditions may be obtained by mediating the activation of the SIRT1/PGC-1α signaling pathway. This study is the first to explore the improvement of AD-related conditions with a combined lifestyle of EX+GCA. This healthy lifestyle could be a candidate option for the treatment of AD.

Swin Transformer-Based Edge Guidance Network for RGB-D Salient Object Detection.

Salient object detection (SOD), which is used to identify the most distinctive object in a given scene, plays an important role in computer vision tasks. Most existing RGB-D SOD methods employ a CNN-based network as the backbone to extract features from RGB and depth images; however, the inherent locality of a CNN-based network limits the performance of CNN-based methods. To tackle this issue, we propose a novel Swin Transformer-based edge guidance network (SwinEGNet) for RGB-D SOD in which the Swin Transformer is employed as a powerful feature extractor to capture the global context. An edge-guided cross-modal interaction module is proposed to effectively enhance and fuse features. In particular, we employed the Swin Transformer as the backbone to extract features from RGB images and depth maps. Then, we introduced the edge extraction module (EEM) to extract edge features and the depth enhancement module (DEM) to enhance depth features. Additionally, a cross-modal interaction module (CIM) was used to integrate cross-modal features from global and local contexts. Finally, we employed a cascaded decoder to refine the prediction map in a coarse-to-fine manner. Extensive experiments demonstrated that our SwinEGNet achieved the best performance on the LFSD, NLPR, DES, and NJU2K datasets and achieved comparable performance on the STEREO dataset compared to 14 state-of-the-art methods. Our model achieved better performance compared to SwinNet, with 88.4% parameters and 77.2% FLOPs. Our code will be publicly available.

15.26Gb/s Si-substrate GaN high-speed visible light photodetector with super-lattice structure.

In this paper, we studied a series of high-speed photodetectors (PD) with different super-lattice interlayer periods and the scale of the effective area to examine their communication performance. The mini-PDs are designed with a single 1 mm × 1 mm effective area. The mini-PDs have three different super-lattice (SL) periods in the interlayer: 8, 15, and 32. The micro-PD sample has multiple 50um by 50um photosensitive areas that form a 4 × 4 receiver array, which shares a common N electrode. Its SL period is 26. The experiment shows that mini-PDs have the advantages such as better tolerance to beam spot deviation, larger field of view (FoV), higher responsibility, and wider peak width in spectral response. But micro-LED samples outperform the others in communication capacity and wavelength selectivity. The 8, 15, and 32 SL mini-PD samples achieve 6.6, 7.3, and 8.8 Gb/s data rates, respectively. The micro-PD gains the maximum data rate of 14.38Gb/s without applying waveform level post-equalization, and 15.26Gb/s after using an NN-based post-equalizer. This experiment shows that with proper DSP, GaN-based PD would be suitable for high-speed VLC systems, especially for the short wavelength spectrum in visible light.

Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection.

RGB-D saliency detection aims to accurately localize salient regions using the complementary information of a depth map. Global contexts carried by the deep layer are key to salient objection detection, but they are diluted when transferred to shallower layers. Besides, depth maps may contain misleading information due to the depth sensors. To tackle these issues, in this paper, we propose a new cross-modal cross-scale network for RGB-D salient object detection, where the global context information provides global guidance to boost performance in complex scenarios. First, we introduce a global guided cross-modal and cross-scale module named G2CMCSM to realize global guided cross-modal cross-scale fusion. Then, we employ feature refinement modules for progressive refinement in a coarse-to-fine manner. In addition, we adopt a hybrid loss function to supervise the training of G2CMCSNet over different scales. With all these modules working together, G2CMCSNet effectively enhances both salient object details and salient object localization. Extensive experiments on challenging benchmark datasets demonstrate that our G2CMCSNet outperforms existing state-of-the-art methods.

Active Alignment of Large-Aperture Space Telescopes for Optimal Ellipticity Performance.

Ellipticity performance of space telescopes is important for exploration of dark matter. However, traditional on-orbit active optical alignment of space telescopes often takes "minimum wavefront error across the field of view" as the correction goal, and the ellipticity performance after correcting the wave aberration is not optimal. This paper proposes an active optical alignment strategy to achieve optimal ellipticity performance. Based on the framework of nodal aberration theory (NAT), the aberration field distribution corresponding to the optimal full field-of-view ellipticity is determined using global optimization. The degrees of freedom (DOFs) of the secondary mirror and the folded flat mirror are taken as the compensation DOFs to achieve the optimal ellipticity performance. Some valuable insights into aberration field characteristics corresponding to optimal ellipticity performance are presented. This work lays a basis for the correction of ellipticity for complicated optical systems.

Fast High-Resolution Phase Diversity Wavefront Sensing with L-BFGS Algorithm.

The presence of manufacture error in large mirrors introduces high-order aberrations, which can severely influence the intensity distribution of point spread function. Therefore, high-resolution phase diversity wavefront sensing is usually needed. However, high-resolution phase diversity wavefront sensing is restricted with the problem of low efficiency and stagnation. This paper proposes a fast high-resolution phase diversity method with limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, which can accurately detect aberrations in the presence of high-order aberrations. An analytical gradient of the objective function for phase-diversity is integrated into the framework of the L-BFGS nonlinear optimization algorithm. L-BFGS algorithm is specifically suitable for high-resolution wavefront sensing where a large phase matrix is optimized. The performance of phase diversity with L-BFGS is compared to other iterative method through simulations and a real experiment. This work contributes to fast high-resolution image-based wavefront sensing with a high robustness.

Detecting radius of curvature (ROC) mismatch among primary mirror (PM) segments.

A segmented primary mirror (PM) is an efficient solution to the problems of a monolithic PM manufacture, testing, transportation, and launch. However, the problem of the radius of curvature (ROC) matching among PM segments will arise, which if not solved will seriously degrade the final imaging quality of the system. Accurately detecting ROC mismatch among PM segments from the wavefront map is of crucial importance for efficiently correcting this kind of manufacturing error, while currently there are few related studies. Based on the inherent relation between the PM segment's ROC error and corresponding sub-aperture defocus aberration, this paper proposes that the ROC mismatch can be accurately estimated from the sub-aperture defocus aberration. Secondary mirror (SM) lateral misalignments will influence the accuracy of estimating ROC mismatch. A strategy is also proposed to reduce the influence of SM lateral misalignments. Detailed simulations are performed to demonstrate the effectiveness of the proposed method for detecting ROC mismatch among PM segments. This paper paves a road for detecting ROC mismatch using image-based wavefront sensing methods.

Jitter-Robust Phase Retrieval Wavefront Sensing Algorithms.

Phase retrieval wavefront sensing methods are now of importance for imaging quality maintenance of space telescopes. However, their accuracy is susceptible to line-of-sight jitter due to the micro-vibration of the platform, which changes the intensity distribution of the image. The effect of the jitter shows some stochastic properties and it is hard to present an analytic solution to this problem. This paper establishes a framework for jitter-robust image-based wavefront sensing algorithm, which utilizes two-dimensional Gaussian convolution to describe the effect of jitter on an image. On this basis, two classes of jitter-robust phase retrieval algorithms are proposed, which can be categorized into iterative-transform algorithms and parametric algorithms, respectively. Further discussions are presented for the cases where the magnitude of jitter is unknown to us. Detailed simulations and a real experiment are performed to demonstrate the effectiveness and practicality of the proposed approaches. This work improves the accuracy and practicality of the phase retrieval wavefront sensing methods in the space condition with non-ignorable micro-vibration.

Night warming at the vegetative stage improves pre-anthesis photosynthesis and plant productivity involved in grain yield of winter wheat.

We conducted pot experiments during the 2018-2020 growing seasons to study the effects of night warming at different growth stages of wheat on the photosynthetic performance; accumulation, transportation, and distribution of dry matter; and grain yield of winter wheat. Night warming at all the different growth stages resulted in an elevation of wheat yield by increasing the 1000-grain weight and the number of grains per ear. Night warming during the period from jointing to booting stage resulted in the greatest increase in wheat yield. It also increased the amount of overall dry matter and transferrable amount of dry matter in plants and increased the distribution of dry matter to grains to increase grain weight. Night warming treatments at three different growth stages enhanced pre-anthesis photosynthetic capacity by increasing flag leaf net photosynthetic rate, chlorophyll content, and photochemical efficiency of winter wheat at the early stage of grain filling, especially in the night warming treatment from jointing to booting stage. Night warming not only increased the stomatal density and stomatal index of wheat leaves but also increased stomatal conductance and transpiration rate in the early stage of grain filling, thus being conducive to the smooth progress of photosynthesis. In conclusion, night warming treatment at different growth stages increased the photosynthesis of flag leaves at the early stage of grain filling, and promoted the accumulation of dry matter in plants after anthesis, which was conducive to the grain yield of winter wheat.

Deep learning wavefront sensing for fine phasing of segmented mirrors.

Segmented primary mirror provides many crucial important advantages for the construction of extra-large space telescopes. The imaging quality of this class of telescope is susceptible to phasing error between primary mirror segments. Deep learning has been widely applied in the field of optical imaging and wavefront sensing, including phasing segmented mirrors. Compared to other image-based phasing techniques, such as phase retrieval and phase diversity, deep learning has the advantage of high efficiency and free of stagnation problem. However, at present deep learning methods are mainly applied to coarse phasing and used to estimate piston error between segments. In this paper, deep Bi-GRU neural work is introduced to fine phasing of segmented mirrors, which not only has a much simpler structure than CNN or LSTM network, but also can effectively solve the gradient vanishing problem in training due to long term dependencies. By incorporating phasing errors (piston and tip-tilt errors), some low-order aberrations as well as other practical considerations, Bi-GRU neural work can effectively be used for fine phasing of segmented mirrors. Simulations and real experiments are used to demonstrate the accuracy and effectiveness of the proposed methods.

Comparison of nonlinear equalizers for high-speed visible light communication utilizing silicon substrate phosphorescent white LED.

Compared with multicolor-chip integrated white LEDs, phosphor-based white LEDs are more attractive for daily illumination due to lower cost and complexity, and thus they are preferable for future commercial use of visible light communication (VLC) systems. However, the application of phosphorescent white LEDs has a lower data rate than multicolor-chip integrated LEDs because of severe nonlinear impairments and limited bandwidth caused by the slow-responding phosphor. In this paper, for the first time we propose to employ phosphorescent white LEDs based on silicon substrate with adaptive bit-loading discrete multitone (DMT) modulation and a memoryless polynomial based nonlinear equalizer to achieve a high-speed VLC system. We also present a comprehensive comparison among nonlinear equalizers based on the Volterra series model, memory polynomial model, memoryless polynomial model and deep neural network (DNN) with experimental results utilizing a silicon substrate phosphorescent white LED, and provide detailed suggestions on how to choose the most suitable nonlinear mitigation scheme considering different practical conditions and the tradeoff between complexity and performance. Beyond 3.00 Gb/s DMT VLC transmission over 1-m indoor free space is successfully demonstrated with bit error rate (BER) under the 7% forward error correction (FEC) limit of 3.8×10-3. As far as we know, this is the highest data rate ever reported for VLC systems based on a single high-power phosphorescent white LED.

Cross-iteration deconvolution strategy for differential optical transfer function (dOTF) wavefront sensing.

Differential optical transfer function (dOTF) is a promising analytic image-based wavefront sensing approach, which is simple in both hardware implementation and mathematical operation. However, there is one deep-rooted problem inherent in this approach, i.e., the essential trade-off between the signal ratio and resolution due to the effect of convolution. In this Letter, a cross-iteration deconvolution strategy is proposed to solve this problem with two different dOTFs, based on the understanding of an underlying prior knowledge when pupil blockage is used to introduce pupil modification. This Letter contributes to the development of a deterministic, efficient, and precise image-based wavefront sensing technique.

Large-coverage underwater visible light communication system based on blue LED employing equal gain combining with integrated PIN array reception.

In this paper, we proposed a large-coverage underwater visible light communication (VLC) system utilizing quadrature amplitude modulation-discrete multitone (QAM-DMT) and integrated 2×2 positive-intrinsic-negative (PIN) array reception to achieve equal-gain combining (EGC) receiving. The transmitter consists of a lens group and blue-emitting silicon substrate light-emitting diode peak emission, the wavelength of which is 458 nm. After 1.2 m underwater transmission, a data rate of over 1 Gbit/s is successfully achieved with a spot of 25 cm in diameter and 11 cm alignment tolerances. A data rate of 1.8 Gbit/s is also achieved when using parallel light reception. Both are the highest data rates to our knowledge so far in a large-coverage underwater VLC system, which shows the benefit and feasibility of using an integrated PIN array with QAM-DMT modulation and EGC.

Effect of same-temperature GaN cap layer on the InGaN/GaN multiquantum well of green light-emitting diode on silicon substrate.

GaN green LED was grown on Si (111) substrate by MOCVD. To enhance the quality of InGaN/GaN MQWs, same-temperature (ST) GaN protection layers with different thickness of 8 Å, 15 Å, and 30 Å were induced after the InGaN quantum wells (QWs) layer. Results show that a relative thicker cap layer is benefit to get InGaN QWs with higher In percent at fixed well temperature and obtain better QW/QB interface. As the cap thickness increases, the indium distribution becomes homogeneous as verified by fluorescence microscope (FLM). The interface of MQWs turns to be abrupt from XRD analysis. The intensity of photoluminescence (PL) spectrum is increased and the FWHM becomes narrow.

Enantioselective open-tubular capillary electrochromatography using cyclodextrin-modified gold nanoparticles as stationary phase.

Enantioselective open-tubular CEC (OTCEC) with thiolated ß-CD modified gold nanoparticles (CD-GNPs) as stationary phase was developed. The enantioselective OT capillary column was fabricated by electrostatic assembly of poly(diallydimethylammonium chloride) (PDDA) followed by self-adsorption of negatively charged CD-GNPs. The enantioselective capillary column has a steady EOF mobility over a wide pH range of 3.0 to 9.2 (RSD 4.8%), and is quite stable over 240 min with very good column to column reproducibility. Efficient enantioseparation of the presented method was demonstrated by analyzing three drug enantiomers. Our results show that the column exhibits good run-to-run repeatability for enantioseparations and can maintain the enantioselectivity for more than 1 month if the column was stored in CD-GNPs solution at 4 °C.

Nitrogen-doped TiO2 modified with NH4F for efficient photocatalytic degradation of formaldehyde under blue light-emitting diodes.

A nitrogen-doped TiO(2) (N-TiO(2)) photocatalyst was prepared by calcination of the hydrolysis precipitate of Ti(SO(4))(2) with aqueous ammonia. The prepared N-TiO(2) was treated with NH(4)F (F-N-TiO(2)) by an impregnation-calcination method. The photocatalyst (F-N-TiO(2)) was characterized by X-ray diffraction (XRD), Fourier Transform Infrared (FT-IR), UV-vis diffusive reflectance spectroscopy (DRS), BET and X-ray photoelectron spectroscopy (XPS). With blue light-emitting diode (LED) as the light source, its photocatalytic activity for the degradation of formaldehyde was investigated. NH(4)F treatment enhances markedly photocatalytic activity of N-TiO(2). The treatment increases the visible absorption of N-TiO(2), decreases its specific surface area and influences the concentration of oxygen vacancies in N-TiO(2). Photocatalytic activity of F-N-TiO(2) depends on the visible absorption, the specific surface area, and the concentration of oxygen vacancies. The preparation conditions, such as the calcination temperature and the initial molar ratio of NH(4)F to N-TiO(2), have a significant influence on the photocatalytic activity. The doping mechanism of NH(4)F was investigated.

Immobilized hemin affinity chromatography as a probe for proteins having potentiality to bind with heme.

After Sepharose 4B polymer beads were activated by using epichlorohydrin, hemin was binded with them to prepare an immobilized hemin affinity chromatography column. The coupling rate of this column was very high, more than 0.25mg hemin could be fixed by 1g of wet Sepharose 4B beads. The column equilibrated with deionized water and eluated with pH 3.0 NaAc-HAc buffer was applied to capture the proteins in human serum, earthworm body and Bacillus subtilis cells. Three polypeptides in human serum were captured, one of which was verified as serum albumin after comparison to the control. At least one polypeptide in earthworm body, two in Bacillus subtilis cells displayed the powerful binding specificity to hemin. Our experiments demonstrated that the immobilized hemin affinity chromatography was available as a probe for some proteins having potentiality to bind with heme.

[Visible spectral character of heme iron in biomacromolecules].

The visible spectra of hemin, hemoglobin, cytochrome C, peroxidase and so on were compared and analyzed based on the experiments. The fifth and sixth coordinate bond of heme iron in biomacromolecule may affect their visible spectra in peak form and position. The sixth coordinate bond of ferrous heme iron that is in low-spin displays two peaks, and in high-spin, ferrous heme without the sixth coordinate bond of iron gives only one peak. That is in favor of our understanding of the character, function and stability of heme-containing biomacromolecule. The spectral character of iron coordinate bonds is due to that these coordinate bonds change the iron position related to porphyrin plane and its spin state.