Reconsidering the classification of sweet taste liker phenotypes: a methodological review

Human ingestive behavior depends on myriad factors, including both sensory and non-sensory determinants. Of the sensory determinants, sweet taste is a powerful stimulus and liking for sweetness is widely accepted as an innate human trait. However, the universality of sweet-liking has been challenged. Sub-groups exhibiting strong liking (sweet likers) or having aversive responses to sweet taste (sweet dislikers) have been described, but the methods defining these phenotypes are varied and inconsistent across studies. Here, we explore the strengths and weaknesses of different methodological approaches in identifying sweet taste liker phenotypes in a comprehensive review. Prior studies (N = 71) using aqueous sucrose solution-based taste tests and a definition of two or more distinct hedonic responses reported between 1970 and 2017 were summarized. Broadly speaking, four different phenotyping methods have been used: 1. Interpretation (visual or statistical) of the shape of hedonic response curves, 2. Highest preference using ratings, 3. Average liking above mid-point or Positive/Negative average liking method, and 4. Highest preference via paired comparisons. Key methodological weaknesses included the use of subjective or arbitrary criteria as well as adoption of protocols unsuitable for large-scale implementation. Overall, we did not identify a method distinctly superior to the others. Given the role of both hedonics and reward in food intake, a better understanding of individual variations in sweet taste perception could clarify how sweet-liking interplays with obesity or addictive behaviors such as alcohol misuse and abuse. The development of a universally used statistically robust and less time-consuming classification method is needed

Quantifying sweet taste liker phenotypes: time for some consistency in the classification criteria

Taste hedonics is a well-documented driver of food consumption. The role of sweetness in directing ingestive behavior is largely rooted in biology. One can then intuit that individual differences in sweet-liking may constitute an indicator of variations in the susceptibility to diet-related health outcomes. Despite half a century of research on sweet-liking, the best method to identify the distinct responses to sweet taste is still debated. To help resolve this issue, liking and intensity ratings for eight sucrose solutions ranging from 0 to 1 M were collected from 148 young adults (29% men). Hierarchical cluster analysis (HCA) revealed three response patterns: a sweet-liker (SL) phenotype characterized by a rise in liking as concentration increased, an inverted U-shaped phenotype with maximum liking at 0.25 M, and a sweet-disliker (SD) phenotype characterized by a decline in liking as a function of concentration. Based on sensitivity and specificity analyses, present data suggest the clearest discrimination between phenotypes is seen with 1.0 M sucrose, where a liking rating between −15 and +15 on a −50/+50 scale reliably distinguished individuals with an inverted U-shaped response from the SLs and the SDs. If the efficacy of this approach is confirmed in other populations, the discrimination criteria identified here can serve as the basis for a standard method for classifying sweet taste liker phenotypes in adults

What Explains the Incidence of the Use of a Common Sediment Control on Lots with Houses Under Construction?

To analyze compliance with one aspect of the regulation of stormwater discharge, we estimate a random-utility model of the probability that a builder uses a silt fence to control sediments on a lot with a house under construction in an urbanizing county of South Carolina. The probability increases if the builder is responsible to the subdivision’s developer or if a homeowners association exists. The probability also increases as the cost to install a silt fence decreases or the number of houses under construction per built house in a subdivision increases. The results can help county officials target inspection to improve compliance.compliance with regulation, erosion and sediment control, filter fabric, management of stormwater runoff, random-utility model, silt fence, storm water pollution prevention plan, Agribusiness, Community/Rural/Urban Development, Demand and Price Analysis, Environmental Economics and Policy, Industrial Organization, Land Economics/Use, Q01, Q24, Q53, Q58,

Degree of free fatty acid saturation influences chocolate rejection in human assessors

In foods, free fatty acids (FFA) traditionally have been viewed as contributing an odor, yet evidence has accumulated that FFA also contribute a unique taste (“oleogustus”). However, minimal work has been conducted using actual foods to test the contribution of FFA to taste preferences. We chose to investigate flavor, taste, and aroma contributions of added FFA in chocolate, as some commercial manufacturers already use lipolysis of triglycerides to generate unique profiles. We hypothesized small added concentrations of FFA would increase preferences for chocolate while higher added concentrations would decrease preferences. We also hypothesized a saturated fatty acid (stearic C18) would have a lesser effect than a monounsaturated (oleic C18:1), which would have a lesser effect than a polyunsaturated (linoleic C18:2) fatty acid. For each, paired preference tests were conducted for 10 concentrations (0.04% to 2.25%) of added FFA compared to control chocolate without added FFAs. Stearic acid was tested for flavor (tasting, nares open), while the unsaturated fatty acids were tested for both aroma (orthonasal only, no tasting) and taste (tasting with nares blocked to eliminate retronasal odor). We found no preference for any added FFA chocolate; however, rejection was observed independently for both taste and aroma of unsaturated fatty acids, with linoleic acid reaching rejection at lower concentrations than oleic acid. These data indicate degree of unsaturation influences rejection of both FFA aroma and taste in chocolate. Thus, alterations of FFA profiles in foods should be approached cautiously to avoid shifting concentrations of unsaturated fatty acids to hedonically unacceptable levels

Applicability of tandem affinity purification MudPIT to pathway proteomics in yeast

A combined multidimensional chromatography-mass spectrometry approach known as "MudPIT" enables rapid identification of proteins that interact with a tagged bait while bypassing some of the problems associated with analysis of polypeptides excised from SDS-polyacrylamide gels. However, the reproducibility, success rate, and applicability of MudPIT to the rapid characterization of dozens of proteins have not been reported. We show here that MudPIT reproducibly identified bona fide partners for budding yeast Gcn5p. Additionally, we successfully applied MudPIT to rapidly screen through a collection of tagged polypeptides to identify new protein interactions. Twenty-five proteins involved in transcription and progression through mitosis were modified with a new tandem affinity purification (TAP) tag. TAP-MudPIT analysis of 22 yeast strains that expressed these tagged proteins uncovered known or likely interacting partners for 21 of the baits, a figure that compares favorably with traditional approaches. The proteins identified here comprised 102 previously known and 279 potential physical interactions. Even for the intensively studied Swi2p/Snf2p, the catalytic subunit of the Swi/Snf chromatin remodeling complex, our analysis uncovered a new interacting protein, Rtt102p. Reciprocal tagging and TAP-MudPIT analysis of Rtt102p revealed subunits of both the Swi/Snf and RSC complexes, identifying Rtt102p as a common interactor with, and possible integral component of, these chromatin remodeling machines. Our experience indicates it is feasible for an investigator working with a single ion trap instrument in a conventional molecular/cellular biology laboratory to carry out proteomic characterization of a pathway, organelle, or process (i.e. "pathway proteomics") by systematic application of TAP-MudPIT