Cynanotophyllosides E-F, two minor pregnane glycosides from the roots of cultivated Cynanchum otophyllum.

Cynanotophyllosides E-F, two new minor pregnane glycosides were isolated from the antidepressant active fraction of cultivated Cynanchum otophyllum, and their structures were determined as 12-O-vanilloyl-deacetylmetaplexigenin 3-O-ß-D-glucopyranosyl-(1→4)-ß-D-glucopyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-oleandropyranosyl-(1→4)-ß-D-digitoxopyranoside, and 12-O-nicotinoyl-deacetylmetaplexigenin 3-O-ß-D-glucopyranosyl-(1→4)-ß-D-glucopyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-oleandropyranosyl-(1→4)-ß-D-cymaropyranoside respectively, with the combination of spectroscopic and chemical analysis.

Acteoside attenuates acute lung injury following administration of cobra venom factor to mice.

Background: Acteoside, a water-soluble active constituent of diverse valuable medicinal vegetation, has shown strong anti-inflammatory property. However, studies on the anti-inflammatory property of acteoside in complement-induced acute lung injury (ALI) are limited. Therefore, this study aims to evaluate the anti-inflammatory activity of acteoside in cobra venom factor (CVF)-stimulated human microvascular endothelial cells (HMEC) and in ALI mice model. Methods: In this study, we investigated the effects of acteoside (20, 10, and 5 µg/mL) in vitro in CVF induced HMECs and the activity of acteoside (100, 50, and 20 mg/kg/day bodyweight) in vivo in CVF induced ALI mice. Each eight male mice were orally administered acteoside or the positive drug PDTC (100 mg/kg/day) for 7 days before CVF (35 µg/kg) injection. After injection for 1 h, the pharmacological effects of acteoside were investigated by spectrophotometry, pathological examination, enzyme-linked immunosorbent assay, and immunohistochemistry. Results: In vitro, acteoside (20, 10, and 5 µg/mL) reduced the protein expression of adhesion molecules and pro-inflammatory cytokines and transcriptional activity of NF-κB (P < 0.01). In vivo studies showed that acteoside dose-dependently alleviated lung histopathologic lesion, inhibited the production of the protein content of BALF, leukocyte cell number, lung MPO activity, and expression levels of IL-6, TNF-α, and ICAM-1, and suppressed the C5b-9 deposition and NF-κB activation in CVF-induced acute lung inflammation in mice (P < 0.05, 0.01). Conclusion: This study demonstrates that acteoside exerts strong anti-inflammatory activities in the CVF-induced acute lung inflammation model and suggests that acteoside is a potential therapeutic agent for complement-related inflammatory diseases.

CIRBP Regulates Pancreatic Cancer Cell Ferroptosis and Growth by Directly Binding to p53.

Pancreatic cancer is one of the most malignant gastrointestinal tumors, and it is of great significance to explore the molecular mechanism of its progression and find new biological therapeutic targets. CIRBP is a cold-induced protein that plays a key role in many physiological and pathological processes, but its role in pancreatic cancer is still unclear. The expression of CIRBP in pancreatic cancer tissues was slightly lower than that in normal tissues, and the high expression of CIRBP was beneficial to survival. At the same time, immunohistochemical detection showed that the expression level of CIRBP in the cytoplasm of cancer tissues was significantly lower than that of adjacent tissues; survival curve analysis showed that pancreatic cancer patients with high nuclear CIRBP expression had a longer overall survival period. RIP results showed that CIRBP antibody significantly enriched p53 RNA, indicating that it could directly bind to p53. Cold treatment of pancreatic cancer cells significantly induced the expression of CIRBP, DPP4, NOX1, and FTH1 and inhibited the expression of p53 and GPX4. Cold induction enhanced the accumulation of Fe2+ in cells, promoted the generation of ROS, and inhibited the expression of GSH-Px. Therefore, cold induction promotes the process of ferroptosis by inducing the expression of CIRBP and then regulating key factors such as p53 and GPX4. In addition, cold induction significantly inhibited the proliferation of pancreatic cancer cells and induced cell apoptosis, but after the addition of ferroptosis inhibitor, cell proliferation and apoptosis did not change significantly. Therefore, CIRBP acts as a tumor suppressor gene in pancreatic cancer and induces ferroptosis through the p53/GPX4 pathway to inhibit cell growth, which may be an important target for the diagnosis and treatment of pancreatic cancer.

Effects of Nano-copper Oxide on Antioxidant Function of Copper-Deficient Kazakh Sheep.

Kazakh sheep are vital to the production system of the Barkol prairie. The purpose of this study was to determine the effect of nano-copper oxide (Nano-Cu2O) on the antioxidant system of Cu-deficient Kazakh sheep in the Barkol prairie in Xinjiang, China. We analyzed mineral contents in soil, forage, and animal tissues. Blood parameters were also measured at the same time. The results showed that compared with healthy grassland, the Cu content in the soil and forage in Cu-deficient pastures was significantly lower than that in healthy grassland (P < 0.01). The Cu content in the blood, wool, and liver of Cu-deficient Kazakh sheep was significantly lower than that of healthy animals (P < 0.01). After Kazakh sheep were supplemented with Nano-Cu2O or CuSO4, the blood Cu concentration increased significantly (P < 0.01). From the 5th day, the Cu content of the Nano-Cu2O group was significantly higher than that of the CuSO4 group. The levels of hemoglobin (Hb), erythrocyte count (RBC), and packed cell volume (PCV) in the two experimental groups were significantly higher than those in Cu-deficient Kazakh sheep (P < 0.01). Compared with Cu-deficient Kazakh sheep, the serum ceruloplasmin (Cp) level of the two experimental groups increased significantly (P < 0.01), while the serum lactate dehydrogenase (LDH), alkaline phosphatase (AKP), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) decreased significantly (P < 0.01). Compared with Cu-deficient Kazakh sheep, the activities of serum superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and total antioxidant capacity (T-AOC) in Nano-Cu2O and CuSO4 groups increased significantly (P < 0.01), while the level of serum malondialdehyde (MDA) decreased significantly (P < 0.01). Therefore, Nano-Cu2O could not only significantly increase the Cu content in the blood of Cu-deficient Kazakh sheep, but also greatly improve the antioxidant capacity.

Ligustrum robustum (Roxb.) blume extract modulates gut microbiota and prevents metabolic syndrome in high-fat diet-fed mice.

ETHNOPHARMACOLOGICAL RELEVANCE: In Chinese folk medicine, Ligustrum robustum (Roxb.) Blume has been widely used as a healthy tea beverage for improvement in obesity and lipidemic metabolic disorders. AIM OF THE STUDY: We aimed to investigate the effect of L. robustum extract (LRE) on metabolic syndrome in high-fat diet (HFD)-fed mice and to explore the underlying role of gut microbiota during the treatment. MATERIALS AND METHODS: The ground dried leaves of L. robustum (Roxb.) Blume were extracted with ethanol and then purified by a resin column. The composition of L. robustum extract (LRE) was analyzed by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). C57BL/6 J mice fed with HFD were treated with LRE for 16 weeks. RT-qPCR and morphological staining were utilized to reveal the impact of LRE on hepatic glucolipid metabolism and gut integrity. The next-generation sequencing of 16 S rDNA was applied for analyzing the gut microbial community of fecal samples. RESULTS: LRE, mainly composed of ligupurpuroside A and aceteoside, alleviated insulin resistance, improved hepatic metabolism, enhanced intestinal integrity, and suppressed inflammatory responses in HFD-fed mice. Moreover, LRE treatment reshaped the gut microbiota structure by increasing the levels of genera Streptococcus, Lactobacillus, and Mucispirillum and decreasing the populations of Alistipes and Lachnospiraceae NK4A136 group in HFD-fed mice. The alteration of gut microbiota was associated with several metabolic pathways of gut bacteria. Spearman's correlation analysis further confirmed the links between the changed intestinal bacteria and multiple disease indices. CONCLUSIONS: LRE prevented gut microbiota dysbiosis and metabolic disorder in HFD-fed mice, which helps to promote the application in LRE-mediated prevention from metabolic syndrome as a gut microbial regulator.

Melanin-concentrating hormone in rat nucleus accumbens or lateral hypothalamus differentially impacts morphine and food seeking behaviors.

BACKGROUND: Identifying neural substrates that are differentially affected by drugs of abuse and natural rewards is key to finding a target for an efficacious treatment for substance abuse. Melanin-concentrating hormone is a polypeptide with an inhibitory effect on the mesolimbic dopamine system. Here we test the hypothesis that melanin-concentrating hormone in the lateral hypothalamus and nucleus accumbens shell is differentially involved in the regulation of morphine and food-rewarded behaviors. METHODS: Male Sprague-Dawley rats were trained with morphine (5.0 mg/kg, subcutaneously) or food pellets (standard chow, 10-14 g) to induce a conditioned place preference, immediately followed by extinction training. Melanin-concentrating hormone (1.0 µg/side) or saline was infused into the nucleus accumbens shell or lateral hypothalamus before the reinstatement primed by morphine or food, and locomotor activity was simultaneously monitored. As the comparison, melanin-concentrating hormone was also microinjected into the nucleus accumbens shell or lateral hypothalamus before the expression of food or morphine-induced conditioned place preference. RESULTS: Microinfusion of melanin-concentrating hormone into the nucleus accumbens shell (but not into the lateral hypothalamus) prevented the reinstatement of morphine conditioned place preference but had no effect on the reinstatement of food conditioned place preference. In contrast, microinfusion of melanin-concentrating hormone into the lateral hypothalamus (but not in the nucleus accumbens shell) inhibited the reinstatement of food conditioned place preference but had no effect on the reinstatement of morphine conditioned place preference. CONCLUSIONS: These results suggest a clear double dissociation of melanin-concentrating hormone in morphine/food rewarding behaviors and melanin-concentrating hormone in the nucleus accumbens shell. Melanin-concentrating hormone could be a potential target for therapeutic intervention for morphine abuse without affecting natural rewards.

Two new secolignans from the roots of Urtica fissa.

Two new secolignans, 3,4-trans-3-hydroxymethyl-4-[bis(4-hydroxy-3- methoxyphenyl)methyl]butyrolactone (1) and 3,4-trans-3-hydroxymethyl-4- [bis(3,4-dimethoxyphenyl)methyl]butyrolactone (2) have been isolated from the roots of Urtica fissa E.Pritz. Their structures were determined on the basis of spectroscopic methods, especially 1H NMR, 13C NMR, 2D NMR, and HR-ESI-MS. The inhibitory effects on N1 and N2, two subtypes of neuraminidases (NAs), of these two compounds were assayed.

Superpixel Hierarchy.

Superpixel segmentation has been one of the most important tasks in computer vision. In practice, an object can be represented by a number of segments at finer levels with consistent details or included in a surrounding region at coarser levels. Thus, a superpixel segmentation hierarchy is of great importance for applications that require different levels of image details. However, there is no method that can generate all scales of superpixels accurately in real time. In this paper, we propose the superhierarchy algorithm which is able to generate multi-scale superpixels as accurately as the state-of-the-art methods but with one to two orders of magnitude speed-up. The proposed algorithm can be directly integrated with recent efficient edge detectors to significantly outperform the state-of-the-art methods in terms of segmentation accuracy. Quantitative and qualitative evaluations on a number of applications demonstrate that the proposed algorithm is accurate and efficient in generating a hierarchy of superpixels.

Biocatalysis mechanisms and characterization of a novel denitrification process with porphyrin compounds based on the electron transfer chain.

In this research, the nitrate reduction rate increased 2-3 fold in the presence of five different porphyrin compounds (0.25 mM), among which hemin expressed the best accelerating effectiveness. Therefore, hemin was used to explore the catalytic characteristics and mechanisms during denitrification. The relationship between hemin concentrations (Chemin) and nitrate reduction rates (k) could be best described by the equation k = 8.7463 + 0.44528ln (Chemin-0.00993) (R2 = 0.9908). Furthermore, the activation energy decreased 87% compared to the hemin-free system. Two active centers of hemin, the Fe3+ atom and the porphyrin ligand, might be involved in catalyzing the denitrification process. Additionally, the accelerating site of hemin in the denitrification electron transfer chain was elucidated by different metabolic inhibitors. This study provides a better understanding of porphyrin compounds in bio-multistage redox reactions and is a promising strategy for its practice application.

Spatiotemporal GMM for Background Subtraction with Superpixel Hierarchy.

We propose a background subtraction algorithm using hierarchical superpixel segmentation, spanning trees and optical flow. First, we generate superpixel segmentation trees using a number of Gaussian Mixture Models (GMMs) by treating each GMM as one vertex to construct spanning trees. Next, we use the -smoother to enhance the spatial consistency on the spanning trees and estimate optical flow to extend the -smoother to the temporal domain. Experimental results on synthetic and real-world benchmark datasets show that the proposed algorithm performs favorably for background subtraction in videos against the state-of-the-art methods in spite of frequent and sudden changes of pixel values.

Divergent Synthesis of Solanidine and 22-epi-Solanidine.

A divergent synthesis of solanidine and 22-epi-solanidine, two 25S natural steroidal alkaloids, from 25R-configured diosgenin acetate, is described. Initially, solanidine was synthesized through a series of transformations including a cascade ring-switching process of furostan-26-acid, an epimerization of C25 controlled by the conformation of six-membered lactone ring, an intramolecular Schmidt reaction, and an imine reduction/intramolecular aminolysis process. To address the epimerization issue during Schmidt reaction, an improved synthesis was developed, which also led to a synthesis of 22-epi-solanidine. In this synthesis, selective transformation of azido lactone to azido diol and amino diol was realized through a reduction relay tactic. The azido diol was transformed to solanidine via an intramolecular Schmidt reaction/N-alkylation/reduction process and to 22-epi-solanidine via an intramolecular double N-alkylation process.

RGBD Salient Object Detection via Deep Fusion.

Numerous efforts have been made to design various low-level saliency cues for RGBD saliency detection, such as color and depth contrast features as well as background and color compactness priors. However, how these low-level saliency cues interact with each other and how they can be effectively incorporated to generate a master saliency map remain challenging problems. In this paper, we design a new convolutional neural network (CNN) to automatically learn the interaction mechanism for RGBD salient object detection. In contrast to existing works, in which raw image pixels are fed directly to the CNN, the proposed method takes advantage of the knowledge obtained in traditional saliency detection by adopting various flexible and interpretable saliency feature vectors as inputs. This guides the CNN to learn a combination of existing features to predict saliency more effectively, which presents a less complex problem than operating on the pixels directly. We then integrate a superpixel-based Laplacian propagation framework with the trained CNN to extract a spatially consistent saliency map by exploiting the intrinsic structure of the input image. Extensive quantitative and qualitative experimental evaluations on three data sets demonstrate that the proposed method consistently outperforms the state-of-the-art methods.

Pregnane glycosides from the antidepressant active fraction of cultivated Cynanchum otophyllum.

Based on the bioactive screening results, four new pregnane glycosides, namely cynanotophyllosides A-D (1-4) were isolated from the anti-depressant active fraction of cultivated Cynanchum otophyllum, along with thirteen known compounds (5-17). The new compounds were characterized as qingyangshengenin 3-O-ß-D-glucopyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-oleandropyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-cymaropyranoside (1), qingyangshengenin-3-O-ß-D-glucopyranosyl-(1→4)-ß-D-glucopyranosyl-(1→4)-ß-D-oleandropyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-α-L-cymaropyranosyl-(1→4)-ß-D-cymaropyranoside (2), caudatin-3-O-ß-D-glucopyranosyl-(1→4)-ß-D-thevetopyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-digitoxopyranoside (3) caudatin-3-O-ß-D-glucopyranosyl -(1→4)-ß-D-thevetopyranosyl-(1→4)-ß-D-cymaropyranosyl-(1→4)-ß-D-cymaropyranoside (4), by detailed spectroscopic analysis and acidic hydrolysis.

Multimodal Multipart Learning for Action Recognition in Depth Videos.

The articulated and complex nature of human actions makes the task of action recognition difficult. One approach to handle this complexity is dividing it to the kinetics of body parts and analyzing the actions based on these partial descriptors. We propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts. To represent dynamics and appearance of parts, we employ a heterogeneous set of depth and skeleton based features. The proper structure of multimodal multipart features are formulated into the learning framework via the proposed hierarchical mixed norm, to regularize the structured features of each part and to apply sparsity between them, in favor of a group feature selection. Our experimental results expose the effectiveness of the proposed learning method in which it outperforms other methods in all three tested datasets while saturating one of them by achieving perfect accuracy.

Efficient and Robust Specular Highlight Removal.

A robust and effective specular highlight removal method is proposed in this paper. It is based on a key observation--the maximum fraction of the diffuse colour component in diffuse local patches in colour images changes smoothly. The specular pixels can thus be treated as noise in this case. This property allows the specular highlights to be removed in an image denoising fashion: an edge-preserving low-pass filter (e.g., the bilateral filter) can be used to smooth the maximum fraction of the colour components of the original image to remove the noise contributed by the specular pixels. Recent developments in fast bilateral filtering techniques enable the proposed method to run over 200× faster than state-of-the-art techniques on a standard CPU and differentiates it from previous work.

Stereo Matching Using Tree Filtering.

Matching cost aggregation is one of the oldest and still popular methods for stereo correspondence. While effective and efficient, cost aggregation methods typically aggregate the matching cost by summing/averaging over a user-specified, local support region. This is obviously only locally-optimal, and the computational complexity of the full-kernel implementation usually depends on the region size. In this paper, the cost aggregation problem is re-examined and a non-local solution is proposed. The matching cost values are aggregated adaptively based on pixel similarity on a tree structure derived from the stereo image pair to preserve depth edges. The nodes of this tree are all the image pixels, and the edges are all the edges between the nearest neighboring pixels. The similarity between any two pixels is decided by their shortest distance on the tree. The proposed method is non-local as every node receives supports from all other nodes on the tree. The proposed method can be naturally extended to the time domain for enforcing temporal coherence. Unlike previous methods, the non-local property guarantees that the depth edges will be preserved when the temporal coherency between all the video frames are considered. A non-local weighted median filter is also proposed based on the non-local cost aggregation algorithm. It has been demonstrated to outperform all local weighted median filters on disparity/depth upsampling and refinement.

Recursive approximation of the bilateral filter.

This paper presents a complete proof that the bilateral filter can be implemented recursively, as long as: 1) the spatial filter can be implemented recursively and 2) the range filter can be decomposed into a recursive product. As a result, an O(ND) solution can be obtained for bilateral filtering, where N is the image size and D is the dimensionality.

Fast edge-preserving PatchMatch for large displacement optical flow.

The speed of optical flow algorithm is crucial for many video editing tasks such as slow motion synthesis, selection propagation, tone adjustment propagation, and so on. Variational coarse-to-fine optical flow algorithms can generally produce high-quality results but cannot fulfil the speed requirement of many practical applications. Besides, large motions in real-world videos also pose a difficult problem to coarse-to-fine variational approaches. We, in this paper, present a fast optical flow algorithm that can handle large displacement motions. Our algorithm is inspired by recent successes of local methods in visual correspondence searching as well as approximate nearest neighbor field algorithms. The main novelty is a fast randomized edge-preserving approximate nearest neighbor field algorithm, which propagates self-similarity patterns in addition to offsets. Experimental results on public optical flow benchmarks show that our method is significantly faster than state-of-the-art methods without compromising on quality, especially when scenes contain large motions. Finally, we show some demo applications by applying our technique into real-world video editing tasks.

Tree Filtering: Efficient Structure-Preserving Smoothing With a Minimum Spanning Tree.

We present a new efficient edge-preserving filter-"tree filter"-to achieve strong image smoothing. The proposed filter can smooth out high-contrast details while preserving major edges, which is not achievable for bilateral-filter-like techniques. Tree filter is a weighted-average filter, whose kernel is derived by viewing pixel affinity in a probabilistic framework simultaneously considering pixel spatial distance, color/intensity difference, as well as connectedness. Pixel connectedness is acquired by treating pixels as nodes in a minimum spanning tree (MST) extracted from the image. The fact that an MST makes all image pixels connected through the tree endues the filter with the power to smooth out high-contrast, fine-scale details while preserving major image structures, since pixels in small isolated region will be closely connected to surrounding majority pixels through the tree, while pixels inside large homogeneous region will be automatically dragged away from pixels outside the region. The tree filter can be separated into two other filters, both of which turn out to have fast algorithms. We also propose an efficient linear time MST extraction algorithm to further improve the whole filtering speed. The algorithms give tree filter a great advantage in low computational complexity (linear to number of image pixels) and fast speed: it can process a 1-megapixel 8-bit image at ~ 0.25 s on an Intel 3.4 GHz Core i7 CPU (including the construction of MST). The proposed tree filter is demonstrated on a variety of applications.

Hardware-Efficient Bilateral Filtering for Stereo Matching.

This paper presents a new bilateral filtering method specially designed for practical stereo vision systems. Parallel algorithms are preferred in these systems due to the real-time performance requirement. Edge-preserving filters like the bilateral filter have been demonstrated to be very effective for high-quality local stereo matching. A hardware-efficient bilateral filter is thus proposed in this paper. When moved to an NVIDIA GeForce GTX 580 GPU, it can process a one megapixel color image at around 417 frames per second. This filter can be directly used for cost aggregation required in any local stereo matching algorithm. Quantitative evaluation shows that it outperforms all the other local stereo methods both in terms of accuracy and speed on Middlebury benchmark. It ranks 12th out of over 120 methods on Middlebury data sets, and the average runtime (including the matching cost computation, occlusion handling, and post processing) is only 15 milliseconds (67 frames per second).