Fucoidans from Pearsonothuria graeffei prevent obesity by regulating intestinal lipid metabolism and inflammation related signalling pathways.

Background: Fucoidans extracted from sea cucumber Pearsonothuria graeffei (fuc-Pg) are rich in 4-O-sulfation, and have been shown to be potential functional polysaccharides for preventing metabolic syndromes. Objective: The present study was conducted to investigate the effect of fuc-Pg on the prevention of obesity and its underlying mechanism. Method: Mice were fed a normal diet, high-fat diet (HFD), HFD plus low and high dosage of fuc-Pg, and HFD plus simvastatin for 8 weeks. Results: fuc-Pg intervention could significantly decrease weight gain and fat accumulation in the HFD-fed mice. Moreover, fuc-Pg improved serum lipid profile by decreasing serum concentrations of TG, TC, LDL-C, sCD36, ApoB48, and ApoB100 compared with the HFD group. HFD-induced upregulation of intestinal CD36, FABP-1, P-ERK1, and the ratio of p-ERK/ERK was reversed by the fuc-Pg treatment. Moreover, fuc-Pg improved the normal function of white adipose tissue by increasing the expression of UCP1, PPAR-γ, and PGC-1α in the HFD-fed mice. Furthermore, fuc-Pg alleviated systemic inflammation by reducing serum pro-inflammatory factors and breaking the TLR4/NF-κB pathway in both the colon and liver. Conclusion: Fuc-Pg is a potential functional polysaccharide for preventing obesity and systemic inflammation caused by HFD.

Correlation between weighted spectral distribution and average path length in evolving networks.

The weighted spectral distribution (WSD) is a metric defined on the normalized Laplacian spectrum. In this study, synchronic random graphs are first used to rigorously analyze the metric's scaling feature, which indicates that the metric grows sublinearly as the network size increases, and the metric's scaling feature is demonstrated to be common in networks with Gaussian, exponential, and power-law degree distributions. Furthermore, a deterministic model of diachronic graphs is developed to illustrate the correlation between the slope coefficient of the metric's asymptotic line and the average path length, and the similarities and differences between synchronic and diachronic random graphs are investigated to better understand the correlation. Finally, numerical analysis is presented based on simulated and real-world data of evolving networks, which shows that the ratio of the WSD to the network size is a good indicator of the average path length.