The Potential Effects of Isoleucine Restricted Diet on Cognitive Impairment in High-Fat-Induced Obese Mice via Gut Microbiota-Brain Axis.

SCOPE: Obesity induced by high-fat diet (HFD) can cause lipid metabolism disorders and cognitive impairment. Isoleucine restriction can effectively alleviate lipid metabolism disorders caused by HFD but the underlying mechanisms on cognition are unknown. METHODS AND RESULTS: Thirty 3-month-old C57BL/6J mice are divided equally into the following groups: the control group, HFD group, and HFD Low Ile group (67% reduction in isoleucine in high fat feeds). Feeding for 11 weeks with behavioral testing, which shows that isoleucine restriction attenuates HFD-induced cognitive dysfunction. As observed by staining, isoleucine restriction inhibits HFD-induced neuronal damage and microglia activation. Furthermore, isoleucine restriction significantly increases the relative abundance of gut microbiota, decreases the proportion of Proteobacteria, and reduces the levels of lipopolysaccharide (LPS) in serum and brain. Isoleucine restriction reduces protein expression of TLR4/MyD88/NF-κB signaling pathway and inhibits upregulation of proinflammatory cytokine genes and protein expression in mice brain. In addition, isoleucine restriction significantly improves insulin resistance in the brain as well as synaptic plasticity impairment. CONCLUSION: Isoleucine restriction may be a potential intervention to reduce HFD-induced cognitive impairment by altering gut microbiota, reducing neuroinflammation, insulin resistance, and improving synaptic plasticity in mice brain.

Combined effects of zearalenone and deoxynivalenol on oxidative stress, hepatotoxicity, apoptosis, and inflammation in zebrafish embryos.

Co-existence of mycotoxins may pose a greater risk. It remains less known about the toxic effect of co-exposure of zearalenone (ZEA) and deoxynivalenol (DON) on aquatic life. In the present study, the toxic effects of the combine treatment of ZEA and DON on zebrafish (Danio rerio) embryos were investigated. The results showed that the combined treatment of ZEA (200, 400, 800 µg/L) and DON (4000 µg/L) did not cause apparent deaths, but induced a developmental toxicity as indicated by decreased movement times and heartbeat. At 96 h post-fertilization (hpf), co-exposure of ZEA and DON (Z400 + D4000 and Z800 + D4000 group) led to significant oxidative stress as evidenced by the increased ROS level and MDA content, as well as the changes of antioxidant enzymes (SOD, CAT and GPX) and their genes. Besides, the combined treatment of ZEA and DON triggered hepatotoxicity as shown by the changes of Fabp10a, Gclc, Gsr, Nqo1 genes, apoptosis through upregulating apoptosis-related genes (p53, Caspase-9, Caspase-3) and downregulating Bcl-2 gene, as well as inflammation by promoting the expression of IL-1ß, IL-6, TNF-α, TLR4, MyD88, NF-κBp65 genes. These results indicated the co-exposure of ZEA and DON caused oxidative stress, leading to stronger potential toxic effects to zebrafish embryos than their respective single treatment. Therefore, more attention should be paid to risk management of the co-contamination of mycotoxins.

Pickering emulsions stabilized by zein-proanthocyanidins-pectin ternary composites (ZPAAPs): Construction and delivery studies.

Proanthocyanidins (Pas) are widely used in the preparation of functional foods due to their diverse biological activities. Taking advantage of the effect of Pas on the stability of Pickering emulsions, this study constructed the zein-proanthocyanidins-pectin ternary composites (ZPAAPs) as stabilizer to establish Pickering emulsions with potential delivery capacity. The appearance of the emulsion was pink which could be found in visual observation. The emulsion was stable during long-term storage in the range of 0.1 âˆ¼ 0.7 oil phase. CLSM showed that the oil droplets were coated with covering layer formed by ZPAAPs, which effectively prevented droplets congregating. The rheological results indicated that ZPAAPEs had elastic gel-like structure. In addition, ZPAAPEs still contained 54.4 % curcumin after storage for 15 d. And the bioavailability of curcumin was increased to 39.7 % ± 0.3. These studies may contribute to the controllable fabrication of Pickering emulsions for nutrient delivery in the food and pharmaceutical fields.

Attenuation of Palmitic Acid-Induced Intestinal Epithelial Barrier Dysfunction by 6-Shogaol in Caco-2 Cells: The Role of MiR-216a-5p/TLR4/NF-κB Axis.

Palmitic acid (PA) can lead to intestinal epithelial barrier dysfunction. In this study, the protective effects and working mechanisms of 6-shogaol against PA-induced intestinal barrier dysfunction were investigated in human intestinal epithelial Caco-2 cells. Transepithelial electrical resistance (TEER), paracellular flux, qRT-PCR, immunofluorescence, and Western blot experiments showed that the 24-h treatment with 400 µM PA damaged intestinal barrier integrity, as evidenced by a reduction of 48% in the TEER value, a 4.1-fold increase in the flux of fluorescein isothiocyanate-dextran 4000 (FD-4), and decreases in the mRNA and protein expression of tight junction (TJ)-associated proteins (claudin-1, occludin, and ZO-1), compared with the control. The PA treatment significantly (p < 0.05) increased the levels of pro-inflammatory cytokines (interleukin (IL)-6, IL-1ß, and tumor necrosis factor-alpha (TNF-α)) in Caco-2 cells due to the upregulation of toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), phosphorylated nuclear factor kappa-B (NF-κB) proteins, and downregulation of miR-216a-5p (which directly targeted TLR4). Co-treatment with PA and 6-shogaol (2.5 µM) significantly (p < 0.05) attenuated PA-induced changes through regulation of TJs via the miR-216a-5p/TLR4/NF-κB signaling pathway. This study provides insights into the functions and working mechanisms of 6-shogaol as a promising food-derived agent against PA-induced intestinal epithelial barrier dysfunction.

Apple phenolic extracts ameliorate lead-induced cognitive impairment and depression- and anxiety-like behavior in mice by abating oxidative stress, inflammation and apoptosis via the miR-22-3p/SIRT1 axis.

Lead can lead to neurotoxicity and cognitive impairment. In this study, for the first time, the protective effects and working mechanisms of apple phenolic extracts (APEs) against lead acetate (Pb(Ac)2)-induced cognitive impairment and depression- and anxiety-like behavior were examined in vivo. Forty male mice were administered daily (via gastric gavage; 8 weeks) with 0.9% normal saline (control), Pb(Ac)2 (20 ppm), APE (200 ppm) or Pb(Ac)2 (20 ppm) + APE (200 ppm). The APE contained five major phenolic compounds: chlorogenic acid, proanthocyanidin B2, epicatechin, phloridzin and phloretin. Behavioral tests, histopathological examinations and biochemical analyses revealed that Pb(Ac)2-treated mice exhibited cognitive and behavioral deficits (i.e. a reduced percentage of spontaneous alternation, prolonged duration of immobility and decreased open field test scores compared with the control. Pb(Ac)2 exposure significantly increased cellular oxidative damage and the levels of pro-inflammatory cytokines (interleukin (IL)-1ß, IL-6 and tumor necrosis factor-α (TNF-α), ionized calcium binding adaptor molecule 1 (Iba1) and pro-apoptotic proteins (caspase 3, caspase 9 and Bax), while downregulating the expression of Bcl-2 in the brain. APE administration alleviated these Pb(Ac)2-induced changes through regulating oxidative stress, neuroinflammation and apoptosis via the miR-22-3p/Sirtuin 1 (SIRT1) signaling pathway. Taken together, the APE has the potential to treat lead-induced neurotoxicity and neurodegenerative disorders via antioxidant, anti-inflammatory and anti-apoptotic actions.

Bridging Text Visualization and Mining: A Task-Driven Survey.

Visual text analytics has recently emerged as one of the most prominent topics in both academic research and the commercial world. To provide an overview of the relevant techniques and analysis tasks, as well as the relationships between them, we comprehensively analyzed 263 visualization papers and 4,346 mining papers published between 1992-2017 in two fields: visualization and text mining. From the analysis, we derived around 300 concepts (visualization techniques, mining techniques, and analysis tasks) and built a taxonomy for each type of concept. The co-occurrence relationships between the concepts were also extracted. Our research can be used as a stepping-stone for other researchers to 1) understand a common set of concepts used in this research topic; 2) facilitate the exploration of the relationships between visualization techniques, mining techniques, and analysis tasks; 3) understand the current practice in developing visual text analytics tools; 4) seek potential research opportunities by narrowing the gulf between visualization and mining techniques based on the analysis tasks; and 5) analyze other interdisciplinary research areas in a similar way. We have also contributed a web-based visualization tool for analyzing and understanding research trends and opportunities in visual text analytics.

An Interactive Method to Improve Crowdsourced Annotations.

In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-crowds models have introduced expert validation. However, little research has been done on facilitating the validation procedure. In this paper, we propose an interactive method to assist experts in verifying uncertain instance labels and unreliable workers. Given the instance labels and worker reliability inferred from a learning-from-crowds model, candidate instances and workers are selected for expert validation. The influence of verified results is propagated to relevant instances and workers through the learning-from-crowds model. To facilitate the validation of annotations, we have developed a confusion visualization to indicate the confusing classes for further exploration, a constrained projection method to show the uncertain labels in context, and a scatter-plot-based visualization to illustrate worker reliability. The three visualizations are tightly integrated with the learning-from-crowds model to provide an iterative and progressive environment for data validation. Two case studies were conducted that demonstrate our approach offers an efficient method for validating and improving crowdsourced annotations.