Abstract It is widely known that ingestion of soluble dietary fiber (SDF) can help lower blood sugar level, whose dominant mechanism, however, remains unclear. This work presents spatiotemporally distributed intestinal absorption models that can be seamlessly coupled with an established glucose-insulin regulation model to predict glycemic lowering by SDF ingestion. Fluid absorption and absorption area evolution in the intestine have been rigorously taken into account. The current model predictions can match in vivo data much better than any existing model. By resorting to this model, key glycemic lowering mechanisms (e.g., delayed gastric emptying, glucose binding and viscosity change) have been systematically explored to identify dominant ones conferred by different SDFs. It is revealed that, taking guar gum as an example, increased intestinal viscosity due to the ingestion of SDF is the dominant mechanism. The model and findings will be valuable for the design of functional foods for human health.

中文翻译：

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可溶性膳食纤维摄入降低血糖的机制探索：预测建模和模拟

摘要 众所周知，摄入可溶性膳食纤维（SDF）有助于降低血糖水平，但其主要机制尚不清楚。这项工作提出了时空分布的肠道吸收模型，可以与已建立的葡萄糖 - 胰岛素调节模型无缝结合，以预测 SDF 摄入引起的血糖降低。肠道中的液体吸收和吸收面积演变已被严格考虑。当前的模型预测可以比任何现有模型更好地匹配体内数据。通过使用该模型，已经系统地探索了关键的降血糖机制（例如，延迟胃排空、葡萄糖结合和粘度变化）以识别由不同 SDF 赋予的主要机制。据透露，以瓜尔豆胶为例，由于摄入 SDF 引起的肠道粘度增加是主要机制。该模型和研究结果对于设计有益于人类健康的功能性食品具有重要价值。