Gastrointestinal Fermentable Polysaccharide Is Beneficial in Alleviating Loperamide-Induced Constipation in Mice.

To investigate the role of gastrointestinal (GI) polysaccharide fermentation in alleviating constipation, two polysaccharide fractions were isolated from a soluble fiber extract with determined anti-constipation activity: a 2.04 kDa neutral fraction (SSP-1) contained 99.29% glucose, and a 41.66 kDa acidic fraction (SSP-2) contained 63.85% uronic acid. After mice were given loperamide for 14 d to induce constipation, the GI transit rate increased significantly in the SSP-1 group (p < 0.05) but not in the SSP-2 group. The stool weight in the SSP-2 group was significantly higher than that in SSP-1 (383.60 mg vs. 226.23 mg) (p < 0.05). Both SSP-1 and SSP-2 groups had significantly increased serum gastrin and motilin levels (p < 0.05) and changes in their fecal short-chain fatty acid (SCFA) profiles, while SSP-1 showed better fermentation properties than SSP-2 in terms of statistically higher fecal contents of acetic acid and total SCFAs (p < 0.05). Bioinformatic analysis indicated that SSP-1 upregulated bacteria such as Oscillibacter to improve SCFA metabolism and stimulate GI hormone secretion, while SSP-2 had less influence on the gut microbiota. These results suggest that the neutral polysaccharide with superior GI fermentation properties exerted beneficial effects on constipation, while the less fermentable pectic fraction might act as a stool-bulking agent.

Effects of Steaming on Sweet Potato Soluble Dietary Fiber: Content, Structure, and Lactobacillus Proliferation In Vitro.

The influence of steaming treatment on the soluble dietary fiber (SDF) of sweet potato was investigated. The SDF content increased from 2.21 to 4.04 g/100 g (in dry basis) during 20 min of steaming. The microcosmic morphology of the fractured cell wall indicated the release of SDF components during steaming. The SDF from fresh (SDF-F) and 20 min steamed (SDF-S) sweet potato was characterized. The neutral carbohydrates and uronic acid levels in SDF-S were significantly higher than SDF-F (59.31% versus 46.83%, and 25.36% versus 9.60%, respectively) (p < 0.05). The molecular weight of SDF-S was smaller than SDF-F (5.32 kDa versus 28.79 kDa). The probiotic property was evaluated by four Lactobacillus spp. fermentation in vitro with these SDF as carbon source, using inulin as the references. SDF-F showed the best proliferation effects on the four Lactobacillus spp. in terms of the OD600 and pH in cultures, and the highest production of propanoic acid and butyric acid after 24 h fermentation. SDF-S presented higher Lactobacillus proliferation effects, but slight lower propanoic acid and butyric acid production than inulin. It was concluded that 20 min of steaming released SDF with inferior probiotic properties, which might derive from the degraded pectin, cell wall components, and resistant dextrin.

An Individual-Difference-Aware Model for Cross-Person Gaze Estimation.

We propose a novel method on refining cross-person gaze prediction task with eye/face images only by explicitly modelling the person-specific differences. Specifically, we first assume that we can obtain some initial gaze prediction results with existing method, which we refer to as InitNet, and then introduce three modules, the Validity Module (VM), Self-Calibration (SC) and Person-specific Transform (PT) module. By predicting the reliability of current eye/face images, VM is able to identify invalid samples, e.g. eye blinking images, and reduce their effects in modelling process. SC and PT module then learn to compensate for the differences on valid samples only. The former models the translation offsets by bridging the gap between initial predictions and dataset-wise distribution. And the later learns more general person-specific transformation by incorporating the information from existing initial predictions of the same person. We validate our ideas on three publicly available datasets, EVE, XGaze, and MPIIGaze dataset. We demonstrate that our proposed method outperforms the SOTA methods significantly on all of them, e.g. respectively 21.7%, 36.0%, and 32.9% relative performance improvements. We are the winner of the GAZE 2021 EVE Challenge and our code can be found here https://github.com/bjj9/EVE_SCPT.