New View on Dietary Fiber Selection for Predictable Shifts in Gut Microbiota

ABSTRACT Dietary fibers can be utilized to shape the human gut microbiota. However, the outcomes from most dietary fibers currently used as prebiotics are a result of competition between microbes with overlapping abilities to utilize these fibers. Thus, divergent fiber responses are observed across individuals harboring distinct microbial communities. Here, we propose that dietary fibers can be classified hierarchically according to their specificity toward gut microbes. Highly specific fibers harbor chemical and physical characteristics that allow them to be utilized by only a narrow group of bacteria within the gut, reducing competition for that substrate. The use of such fibers as prebiotics targeted to specific microbes would result in predictable shifts independent of the background microbial composition.

Application of Modified Similarity-Based Method for Cotton Fiber Selection

In today's business environment, sustainability is one of the most significant issues that organizations needs to deal with. Fiber choice is often the initial stride that designers and product developers will consider in minimizing the ecological impact of a garment while achieving sustainability. Cotton fiber, whether alone or blended with some other fiber, is being extensively used in textile industries. However, the selection of optimal cotton fiber depends on its several properties like length, strength, fineness, length uniformity, short fiber content, etc., thus making this selection process s multi-criteria decision-making problem. Thus, for the first time, this chapter examines the applicability and feasibility of a modified similarity-based approach for selection of cotton fiber which in turn assists in achieving sustainable design characteristics. Two illustrative examples from past researches and one existing cotton fiber selection problem of a small textile organization are solved applying the adopted method to validate its veracity and robustness.