Virus-Induced Gene Silencing of the Eggplant Chalcone Synthase Gene during Fruit Ripening Modifies Epidermal Cells and Gravitropism

Eggplant (Solanum melongena L.) fruits accumulate flavonoids in their cuticle and epidermal cells during ripening. Although many mutants available in model plant species, such as Arabidopsis thaliana and Medicago truncatula, are enabling the intricacies of flavonoid-related physiology to be deduced, the mechanisms whereby flavonoids influence eggplant fruit physiology are unknown. Virus-induced gene silencing (VIGS) is a reliable tool for the study of flavonoid function in fruit, and in this study, we successfully applied this technique to downregulate S. melongena chalcone synthase gene (<i>SmCHS</i>) expression during eggplant fruit ripening. In addition to the expected change in fruit color attributable to a lack of anthocyanins, several other modifications, including differences in epidermal cell size and shape, were observed in the different sectors. We also found that silencing of <i>CHS</i> gene expression was associated with a negative gravitropic response in eggplant fruits. These observations indicate that epidermal cell expansion during ripening is dependent upon <i>CHS</i> expression and that there may be a relationship between <i>CHS</i> expression and gravitropism during eggplant fruit ripening

Two-Stage Categorization in Brand Extension Evaluation: Electrophysiological Time Course Evidence

<div><p>A brand name can be considered a mental category. Similarity-based categorization theory has been used to explain how consumers judge a new product as a member of a known brand, a process called brand extension evaluation. This study was an event-related potential study conducted in two experiments. The study found a two-stage categorization process reflected by the P2 and N400 components in brand extension evaluation. In experiment 1, a prime–probe paradigm was presented in a pair consisting of a brand name and a product name in three conditions, i.e., in-category extension, similar-category extension, and out-of-category extension. Although the task was unrelated to brand extension evaluation, P2 distinguished out-of-category extensions from similar-category and in-category ones, and N400 distinguished similar-category extensions from in-category ones. In experiment 2, a prime–probe paradigm with a related task was used, in which product names included subcategory and major-category product names. The N400 elicited by subcategory products was more significantly negative than that elicited by major-category products, with no salient difference in P2. We speculated that P2 could reflect the early low-level and similarity-based processing in the first stage, whereas N400 could reflect the late analytic and category-based processing in the second stage.</p></div

Grand-average ERPs elicited by Subcategory versus Major-category product names with prime effect of brand name at Fz, Cz, and Pz electrodes.

<p>Time window of 140 ms to200 ms for P2 quantification and time window of 200 ms to400 ms for N400 quantification marked in light gray, respectively.</p

Topographic distribution of three product categories (beverage, snack, and household appliance).

<p>Topographic distribution of three product categories (beverage, snack, and household appliance).</p

The Mean AR and RT (M±SD) in the experiment 2.

<p>The Mean AR and RT (M±SD) in the experiment 2.</p

Experiment 1 procedure.

<p>Experiment 1 procedure.</p

Grand-average ERPs elicited by three product categories with prime effect of beverage brand name at 15 electrodes in frontal, central, and parietal areas.

<p>Time window of 150 ms to250 ms for P2 quantification at F3, Fz, F4, FC3, FCz, FC4, C3, Cz, and C4, and time window of 300 ms to450 ms for N400 quantification at F3, Fz, F4, FC3, FCz, FC4, C3, Cz, C4, CP3, CPz, CP4, P3, Pz and P4 marked in light gray, respectively.</p

Electrode groups.

<p>Electrode groups.</p

Determinants of e-commerce participation and determinants of the use intensity (measured by quantity) of OF.

Determinants of e-commerce participation and determinants of the use intensity (measured by quantity) of OF.</p

Cross-statistical analysis of e-commerce participation and the use intensity of organic fertilizers.

Cross-statistical analysis of e-commerce participation and the use intensity of organic fertilizers.</p