Zoekresultaten

Release of major peanut allergens from their matrix under various pH and simulated saliva conditions—Ara h2 and ara h6 are readily bio-accessible

from the article: "Abstract: The oral mucosa is the first immune tissue that encounters allergens upon ingestion of food. We hypothesized that the bio-accessibility of allergens at this stage may be a key determinant for sensitization. Light roasted peanut flour was suspended at various pH in buffers mimicking saliva. Protein concentrations and allergens profiles were determined in the supernatants. Peanut protein solubility was poor in the pH range between 3 and 6, while at a low pH (1.5) and at moderately high pHs (>8), it increased. In the pH range of saliva, between 6.5 and 8.5, the allergens Ara h2 and Ara h6 were readily released, whereas Ara h1 and Ara h3 were poorly released. Increasing the pH from 6.5 to 8.5 slightly increased the release of Ara h1 and Ara h3, but the recovery remained low (approximately 20%) compared to that of Ara h2 and Ara h6 (approximately 100% and 65%, respectively). This remarkable difference in the extraction kinetics suggests that Ara h2 and Ara h6 are the first allergens an individual is exposed to upon ingestion of peanut-containing food. We conclude that the peanut allergens Ara h2 and Ara h6 are quickly bio-accessible in the mouth, potentially explaining their extraordinary allergenicity."

A LEAP INTO FAITH

In this dissertation Maarten ter Huurne investigates why users in the sharing economy trust each other.

Sense of Community and Trust in the Sharing Economy

Property sharing is one of the most prominent examples of the rapidly expanding sharing economy. Travelers around the world often opt to stay at a stranger's apartment instead of any other tourism accommodation. Trust is essential in this choice, because staying with, or taking in, strangers can entail great risks. To create trust between users, sharing platforms often promote a sense of community. However, the relation between sense of community and trust in the sharing economy is still largely unknown. To investigate this relation, both hosts and guests of two sharing platforms, namely Airbnb and SabbaticalHomes, were surveyed. The findings indicate that sense of community indeed enhances trust between users. Moreover, the evidence suggests that hosts have a stronger sense of community than guests. Also, a significantly higher sense of community was found on the platform where identification between users is higher. This study shows that affect for the community contributes to the understanding of trust in the sharing economy.

Reputation Effects in Socially Driven Sharing Economy Transactions

Reputation has often been proposed as the central mechanism that creates trust in the sharing economy. However, some sharing platforms that focus primarily on social rather than economically driven exchanges have managed to facilitate exchanges between users without the use of a reputation system. This could indicate that socially driven exchanges are in less need of reputation systems and that having sufficient trust is less problematic. We examine the effect of seller reputation on sales and price as proxies for trust, using a large dataset from a Dutch meal-sharing platform. This platform aims to stimulate social interactions between people via meal sharing. Multilevel regression analyses were used to test the association of reputation with trust. Our main empirical results are that reputation affects both sales and price positively, consistent with the existing reputation literature. We also found evidence of the presence of an information effect, i.e., the influence of reputation on sharing decreases when additional profile information is provided (e.g., a profile photo, a product description). Our results thus confirm the effectiveness of reputation in more socially driven exchanges also. Consequently, platform owners are advised to use reputation on their platform to increase sharing between its users.

How Linguistic Features of Seller Profiles in the Sharing Economy Predict Trustworthiness

The sharing economy holds promise for the way we consume, work, and interact. However, consuming in the sharing economy is not without risk, as institutional trust measures (e.g. contracts, regulations, guarantees) are often absent. Trust between sellers and buyers is therefore crucial to complete transactions successfully. From a buyer ́s perspective, a seller ́s profile is an important source of information for judging trustworthiness, because it contains multiple trust cues such as a reputation score, a profile picture, and a textual self-description. The effect of a seller’s self-description on perceived trustworthiness is still poorly understood. We examine how the linguistic features of a seller’s self-description predict perceived trustworthiness. To determine the perceived trustworthiness of 259 profiles, 189 real buyers on a Dutch sharing platform rated their trustworthiness. The results show that profiles were perceived as more trustworthy if they contained more words (which could be an indicator of uncertainty reduction), more words related to cooking (indicator of expertise), and more words related to positive emotions (indicator of enthusiasm). Also, a profile’s perceived trustworthiness score correlated positively with the seller’s actual sales performance. These findings indicate that a seller’s self-description is a relevant signal to buyers, eventhough it is cheap talk (i.e. easy to produce). The results can guide sellers on how to self-present themselves on sharing platforms and inform platform owners on how to design their platform so that it enhances trust between platform users.

Kick Off of the Interreg Europe project UNLOCK - Unlocking green H2 economy for SMEs in European regions