Hovenia dulcis Fruit Peduncle Polysaccharides Reduce Intestinal Dysbiosis and Hepatic Fatty Acid Metabolism Disorders in Alcohol-Exposed Mice.

Alcohol abuse can lead to alcoholic liver disease, becoming a major global burden. Hovenia dulcis fruit peduncle polysaccharides (HDPs) have the potential to alleviate alcoholic liver injury and play essential roles in treating alcohol-exposed liver disease; however, the hepatoprotective effects and mechanisms remain elusive. In this study, we investigated the hepatoprotective effects of HDPs and their potential mechanisms in alcohol-exposed mice through liver metabolomics and gut microbiome. The results found that HDPs reduced medium-dose alcohol-caused dyslipidemia (significantly elevated T-CHO, TG, LDL-C), elevated liver glycogen levels, and inhibited intestinal-hepatic inflammation (significantly decreased IL-4, IFN-γ and TNF-α), consequently reversing hepatic pathological changes. When applying gut microbiome analysis, HDPs showed significant decreases in Proteobacteria, significant increases in Firmicutes at the phylum level, increased Lactobacillus abundance, and decreased Enterobacteria abundance, maintaining the composition of gut microbiota. Further hepatic metabolomics analysis revealed that HDPs had a regulatory effect on hepatic fatty acid metabolism, by increasing the major metabolic pathways including arachidonic acid and glycerophospholipid metabolism, and identified two important metabolites-C00157 (phosphatidylcholine, a glycerophospholipid plays a central role in energy production) and C04230 (1-Acyl-sn-glycero-3-phosphocholine, a lysophospholipid involved in the breakdown of phospholipids)-involved in the above metabolism. Overall, HDPs reduced intestinal dysbiosis and hepatic fatty acid metabolism disorders in alcohol-exposed mice, suggesting that HDPs have a beneficial effect on alleviating alcohol-induced hepatic metabolic disorders.

Acetyl Tributyl Citrate Exposure at Seemingly Safe Concentrations Induces Adverse Effects in Different Genders of Type 2 Diabetes Mice, Especially Brain Tissue.

Acetyl tributyl citrate (ATBC) is a widely used phthalate substitute. Although ATBC is considered to be with a safe dosage of up to 1000 mg/kg/day, studies on its effects in some sensitive populations, such as diabetic patients, are relatively rare. Epidemiological studies have shown that there is a link between diabetes and nervous system diseases. However, toxicological studies have not fully confirmed this yet. In this study, glycolipid metabolism, cognitive deficits, brain tissue damage, levels of neurotransmitters, beta-amyloid plaques (Aß), hyperphosphorylated tau protein (p-Tau), oxidative stress and inflammation, as well as glial cell homeostatic levels in the brain tissue of type 2 diabetes (T2DM) mice, were determined after ATBC exposure (0, 2, 20, and 200 mg/kg/day) for 90 days. The results confirmed that ATBC exposure aggravated the disorder of glycolipid metabolism and caused cognitive deficits in T2DM mice; induced histopathological alterations and Aß and p-Tau accumulation, and reduced the levels of 5-hydroxytryptamine and acetylcholine in T2DM mouse brains; oxidative stress and glial cell homeostatic levels in T2DM mouse brains were also changed. Some of the adverse effects were gender-dependent. These findings support the theory that T2DM mice, especially males, are more sensitive to ATBC exposure. Although the safe dose of ATBC is high, prolonged exposure at seemingly safe concentrations has the potential to aggravate diabetes symptoms and cause brain tissue damage in T2DM mice.

MutualNet: Adaptive ConvNet via Mutual Learning From Different Model Configurations.

Most existing deep neural networks are static, which means they can only perform inference at a fixed complexity. But the resource budget can vary substantially across different devices. Even on a single device, the affordable budget can change with different scenarios, and repeatedly training networks for each required budget would be incredibly expensive. Therefore, in this work, we propose a general method called MutualNet to train a single network that can run at a diverse set of resource constraints. Our method trains a cohort of model configurations with various network widths and input resolutions. This mutual learning scheme not only allows the model to run at different width-resolution configurations but also transfers the unique knowledge among these configurations, helping the model to learn stronger representations overall. MutualNet is a general training methodology that can be applied to various network structures (e.g., 2D networks: MobileNets, ResNet, 3D networks: SlowFast, X3D) and various tasks (e.g., image classification, object detection, segmentation, and action recognition), and is demonstrated to achieve consistent improvements on a variety of datasets. Since we only train the model once, it also greatly reduces the training cost compared to independently training several models. Surprisingly, MutualNet can also be used to significantly boost the performance of a single network, if dynamic resource constraints are not a concern. In summary, MutualNet is a unified method for both static and adaptive, 2D and 3D networks. Code and pre-trained models are available at https://github.com/taoyang1122/MutualNet.

High-efficiency and robust binary fringe optimization for superfast 3D shape measurement.

By utilizing 1-bit binary fringe patterns instead of conventional 8-bit sinusoidal patterns, binary defocusing techniques have been successfully applied for high-speed 3D shape measurement. However, simultaneously achieving high accuracy and high speed remains challenging. To overcome this limitation, we propose a high-efficiency and robust binary fringe optimization method for superfast 3D shape measurement, which consists of 1D optimization and 2D modulation. Specifically, for 1D optimization, the three-level OPWM technique is introduced for high-order harmonics elimination, and an optimization framework is presented for generating the 'best' three-level OPWM pattern especially for large fringe periods. For 2D modulation, a single-pattern three-level OPWM strategy is proposed by utilizing all the dimensions for intensity modulation to decrease the required projection patterns. Thus, the proposed method essentially belongs to the 2D modulation technique, yet iterative optimization is carried out along one dimension, which drastically improves the computational efficiency while ensuring high accuracy. With only one set of optimized patterns, both simulations and experiments demonstrate that high-quality phase maps can be consistently generated for a wide range of fringe periods (e.g., from 18 to 1140 pixels) and different amounts of defocusing, and it can achieve superfast and high-accuracy 3D shape measurement.

Mechanisms of Pb(II) coprecipitation with natrojarosite and its behavior during acid dissolution.

Lead (Pb) coprecipitation with jarosite is common in natural and engineered environments, such as acid mine drainage (AMD) sites and hydrometallurgical industry. Despite the high relevance for environmental impact, few studies have examined the exact interaction of Pb with jarosite and the dissolution behavior of each phase. In the present work, we demonstrate that Pb mainly interacts with jarosite in four modes, namely incorporation, occlusion, physically mixing, and chemically mixing. For comparison, the four modes of Pb-bearing natrojarosite were synthesized and characterized separately. Batch dissolution experiments were undertaken on these synthetic Pb-bearing natrojarosites under pH 2 to simulate the AMD environments. The introduction of Pb decreases the final Fe releasing efficiency of jarosite-type compounds from 18.18% to 3.45%-5.01%, showing a remarkable inhibition of their dissolution. For Pb releasing behavior, PbSO4 dissolves in preference to Pb-substituted natrojarosite, i.e., (Na, Pb)-jarosite, which primarily results in the sharp increase of Pb releasing concentration (> 40 mg/L). PbSO4 occlusion by jarosite-type compounds can significantly reduce the release of Pb. The results of this study could provide useful information regarding Fe and Pb cycling in acidic natural and engineered environments.

Chromatographic Determination of the Mycotoxin Patulin in 219 Chinese Tea Samples and Implications for Human Health.

Patulin (PAT) is a mycotoxin, with several acute, chronic, and cellular level toxic effects, produced by various fungi. A limit for PAT in food of has been set by authorities to guarantee food safety. Research on PAT in tea has been very limited although tea is the second largest beverage in the world. In this paper, HPLC-DAD and GC-MS methods for analysis of PAT in different tea products, such as non-fermented (green tea), partially fermented (oolong tea, white tea, yellow tea), completely fermented (black tea), and post-fermented (dark tea and Pu-erh tea) teas were developed. The methods showed good selectivity with regard to tea pigments and 5-hydroxymethylfurfural (5-HMF) and a recovery of 90-102% for PAT at a 10-100 ppb spiking level. Limit of detection (LOD) and limit of quantification (LOQ) in tea were 1.5 ng/g and 5.0 ng/g for HPLC-UV, and 0.25 ng/g and 0.83 ng/g for GC-MS. HPLC was simpler and more robust, while GC-MS showed higher sensitivity and selectivity. GC-MS was used to validate the HPLC-UV method and prove its accuracy. The PAT content of 219 Chinese tea samples was investigated. Most tea samples contained less than 10 ng/g, ten more than 10 ng/g and two more than 50 ng/g. The results imply that tea products in China are safe with regard to their PAT content. Even an extreme daily consumption of 25 g of the tea with the highest PAT content (124 ng/g), translates to an intake of only 3 µg/person/day, which is still an order of magnitude below the maximum allowed daily intake of 30 µg for an adult.

Visual Explanation for Deep Metric Learning.

This work explores the visual explanation for deep metric learning and its applications. As an important problem for learning representation, metric learning has attracted much attention recently, while the interpretation of the metric learning model is not as well-studied as classification. To this end, we propose an intuitive idea to show where contributes the most to the overall similarity of two input images by decomposing the final activation. Instead of only providing the overall activation map of each image, we propose to generate point-to-point activation intensity between two images so that the relationship between different regions is uncovered. We show that the proposed framework can be directly applied to a wide range of metric learning applications and provides valuable information for model understanding. Both theoretical and empirical analyses are provided to demonstrate the superiority of the proposed overall activation map over existing methods. Furthermore, our experiments validate the effectiveness of the proposed point-specific activation map on two applications, i.e. cross-view pattern discovery and interactive retrieval. Code is available at https://github.com/Jeff-Zilence/Explain_Metric_Learning.

Transcriptomic-based toxicological investigations of ethanol to human umbilical vein endothelial cells.

Ethanol has a complex effect on the cardiovascular system in humans, but the systemic effects of ethanol to endothelial cells were rarely investigated. In this study, we exposed human umbilical vein endothelial cells (HUVECs) to 5- or 50-mM ethanol and performed transcriptomics to investigate the systemic effects of ethanol. While these concentrations of ethanol did not significantly affect HUVEC viability, 5-mM ethanol significantly upregulated and downregulated 59 and 73 genes, respectively, whereas 50-mM ethanol significantly upregulated and downregulated 50 and 80 genes, respectively. Totally, 37 genes were shared by the two concentrations of ethanol. The most significantly altered gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway after 5-mM ethanol treatment were nucleic acid binding (GO:0003676) and Herpes simplex virus 1 infection (ko05168), respectively, whereas the most significantly altered GO term and KEGG pathway by 50-mM ethanol treatment were aryl sulfotransferase activity (GO:0004062) and chemical carcinogenesis (ko05204). We further verified that ethanol treatment downregulated the mRNA levels of CD38 molecule (CD38), ORAI calcium release-activated calcium modulator 2 (ORAI2), cysteinyl leukotriene receptor 2 (CYSLTR2), key genes involved in calcium signaling pathway (ko04020), as well as integrin subunit alpha 2 (ITGA2), and cAMP responsive element binding protein 3 like 2 (CREB3L2), key genes involved in PI3K-Akt signaling pathway (ko04151). The results from this study suggested that ethanol could induce systemic effects and alter signaling pathways in HUVECs.

Effects of layering techniques on the micro-tensile bond strength to dentin in resin composite restorations.

OBJECTIVES: The purpose of this work was to investigate the effects of layering techniques in resin composite restorations on the micro-tensile bond strength to the dentin of the occlusal cavity. METHODS: Human premolars were extracted and randomly divided into four groups. The occlusal enamel was then removed to expose a flat superficial dentin surface. Cavities 3.5mm long and 3.5mm wide were prepared to a depth 3mm below the dentin surface. The adhesive Single Bond was applied according to the manufacturer's instructions. The teeth were then restored with Z100 resin composite as follows: Group 1 was restored in horizontal increments (three layers). Groups 2 and 3 were restored in different oblique increments (three layers). Group 4 was restored in oblique increments (four layers). After 24h storage at 37 degrees C in water, all the teeth were sectioned to obtain bar-shaped specimens with a bonded surface area of approximately 0.9 mm x 0.9 mm. Dentin micro-tensile bond strength was measured at a crosshead speed of 0.5mm/min. The results obtained were statistically analyzed using one-way ANOVA and SNK test at a significance level of P=0.05. All fractures were then observed under a scanning electron microscope (SEM). RESULTS: The results showed that there is a significant difference between the strength of the micro-tensile bonds to the dentin of occlusal cavities depending on which of the four layering restorative techniques was used (P<0.01). SEM observation showed that failure patterns were most evidently interfacial cohesive failure. SIGNIFICANCE: Layering techniques in resin composite restorations affected the micro-tensile bond strength between the resin composite and the dentin. But the outcomes related to only Single Bond, as the same using other adhesives might have different outcomes.