Effects of Ivermectin and Perfluorobutanesulfonic Acid (PFBS) on Lipid Metabolism

Accumulating evidence has shown a link between environmental contaminants and altered lipid metabolism. There is currently, however, limited knowledge regarding the causal molecular mechanisms. Therefore, we investigated the molecular mechanisms of two environmental contaminants, ivermectin and perfluorobutanesulfonic acid (PFBS), on lipid metabolism in adipocytes and hepatocytes using cell culture models. We first studied the effects of ivermectin, an anti-parasitic agent, on the adipogenesis of 3T3-L1 preadipocytes. Our current results suggest that ivermectin inhibits adipogenesis in 3T3-L1 preadipocytes and the expression of adipogenic genes where these effects were found to be partially via PPARγ-dependent, but not FXR-dependent, pathway. Additionally, ivermectin also activates the expression of glycine receptor subunits, potentially related to the inhibitory effect on adipogenesis. PFBS is the replacement of perfluorooctanesulfonic acid, which has been reported to disrupt lipid metabolisms. There is no report, however, of the effect of PFBS on lipid metabolisms. We found that PFBS treatment extensively promoted the differentiation of 3T3-L1 preadipocytes, resulting in significantly increased TG levels. The effects of PFBS were found to target the early stage of differentiation, in particular via MEK/ERK-dependent pathway. The effects of PFBS on hepatic lipid metabolisms were also investigated by using HepG2 hepatocytes. The current results suggested that PFBS increased the hepatic TG accumulation when supplemented with fatty acid mixture. The effects were also found mediated by PPARγ-mediated pathways

Sub-Nyquist optical pulse sampling for photonic blind source separation

We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short pulse sampling maintains the accuracy of the sampled signals, so the statistical properties of the under-sampled signals are the same as the statistical properties of the original signals. The linear power range measurement shows that the sampling system with ultra-narrow optical pulse achieves a 30dB power dynamic range

Sub-Nyquist optical pulse sampling for photonic blind source separation

We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short pulse sampling maintains the accuracy of the sampled signals, so the statistical properties of the under-sampled signals are the same as the statistical properties of the original signals. The linear power range measurement shows that the sampling system with ultra-narrow optical pulse achieves a 30dB power dynamic range

R\'{e}nyi Divergence Deep Mutual Learning

This paper revisits Deep Mutual Learning (DML), a simple yet effective computing paradigm. We propose using R\'{e}nyi divergence instead of the KL divergence, which is more flexible and tunable, to improve vanilla DML. This modification is able to consistently improve performance over vanilla DML with limited additional complexity. The convergence properties of the proposed paradigm are analyzed theoretically, and Stochastic Gradient Descent with a constant learning rate is shown to converge with $\mathcal{O}(1)$-bias in the worst case scenario for nonconvex optimization tasks. That is, learning will reach nearby local optima but continue searching within a bounded scope, which may help mitigate overfitting. Finally, our extensive empirical results demonstrate the advantage of combining DML and R\'{e}nyi divergence, which further improves generalized models

trans-Trismethoxy Resveratrol Decreased Fat Accumulation Dependent on Fat-6 and Fat-7 in Caenorhabditis Elegans

trans-Trismethoxy resveratrol (TMR) is a methyl analog of resveratrol. It is found to exhibit enhanced biological effects compared to resveratrol, such as inhibition of cancer cell growth and pro-apoptotic activities. However, the role of TMR in lipid metabolism is not fully understood. In this study, we used Caenorhabditis elegans, an in vivo nematode model which has been widely applied in disease research, including research on obesity, to investigate the effect of TMR on lipid metabolism. Treatment with TMR (100 and 200 μM) for 4 days significantly reduced triglyceride accumulation (14% and 20% reduction over the control, respectively) of C. elegans, without affecting nematode growth, food intake and reproduction. Treatment with TMR significantly downregulated stearoyl-CoA desaturase genes, fat-6 and fat-7, accompanied by a decrease in the desaturation index of fatty acids, the ratio of oleic acid to stearic acid. These results suggest that TMR inhibits fat accumulation by downregulating stearoyl-CoA desaturase in C. elegans

Effect of ultrasonic degradation on the physicochemical property and bioactivity of polysaccharide produced by Chaetomium globosum CGMCC 6882

Similar to the enzymatic process, there might also be an active fragment in polysaccharides, how to obtain is important for investigating the bioactivity and pharmacological mechanism of polysaccharides. Presently, a Gynostemma pentaphyllum endophytic fungus Chaetomium globosum CGMCC 6882 polysaccharide [Genistein Combined Polysaccharide (GCP)] was degraded by ultrasonic treatment, two polysaccharide fragments of GCP-F1 and GCP-F2 were obtained. Physicochemical results showed that GCP-F1 and GCP-F2 had the same monosaccharide composition of arabinose, galactose, glucose, xylose, mannose, and glucuronic acid as compared to GCP with slightly different molar ratios. However, weight-average molecular weights of GCP-F1 and GCP-F2 decreased from 8.093 × 104 Da (GCP) to 3.158 × 104 Da and 1.027 × 104 Da, respectively. In vitro scavenging assays illustrated that GCP-F1 and GCP-F2 had higher antioxidant activity against 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, superoxide anions, and hydroxyl radical than GCP, the order was GCP < GCP-F1 < GCP-F2. Meanwhile, antibacterial tests showed that ultrasonic degradation increased the antibacterial activity of GCP-F1 as compared to GCP, but GCP-F2 almost lost its antibacterial activity with further ultrasound treatment. Changes in the antioxidant and antibacterial activities of GCP-F1 and GCP-F2 might be related to the variation of their molecular weights

Anomalous thermo-osmotic conversion performance of ionic covalent-organic-framework membranes in response to charge variations

Authors of the article systematically investigated how the membrane charge populations affect permselectivity by decoupling their effects from the impact of the pore structure using a multivariate strategy for constructing covalent-organic-framework membranes. The complex interplay between pore-pore interactions in response to charge variations for ion transport across the upscaled nanoporous membranes helps explain the obtained results. This study has far-reaching implications for the rational design of ionic membranes to augment energy extraction rather than intuitively focusing on achieving high densities