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The activity of alpha-tocopherol, Trolox, propyl gallate, gallic acid, methyl carnosoate, and carnosic acid was studied in two oil-in-water (o/w) emulsions, in two water-in-oil (w/o) emulsions, and in bulk oil with and without added emulsifiers. All antioxidants had either moderate or higher activity in bulk oil than in the emulsions. In most emulsions, the most polar antioxidants, propyl gallate and gallic acid, exhibited either prooxidant activity or no antioxidant activity. Methyl carnosoate was the most active antioxidant in w/o emulsions but was less active than Trolox in o/w emulsions. alpha-Tocopherol was less active in bulk oil than in emulsions, but its activity in bulk oil was markedly enhanced by the addition of o/w emulsifiers. Partitioning of antioxidants, hydrogen bonding, interphase transport, surface accessibility, and interaction of emulsifier with antioxidants are considered to be important parameters that determine antioxidant activity in lipid-containing systems.

The primary structure of hevamine, an enzyme with lysozyme/chitinase activity from Hevea hrasiliensis latex, has been determined predominantly with conventional non-automatic methods. The positions of three disulfide bridges have been determined. The sequence has about 60% identity with that of a chitinase from cucumber and 95% with the N-terminal sequence of the lysozyme/chitinase of Purthenocissus quinquefolia. The half-cystine residues in hevein and cucumber chitinase are located at identical positions. Hevamine is a basic protein from the lutoids (vacuoles) of rubber latex and may have a role in plugging the latex vessels and cessation of latex flow. The differences in cellular location, charge properties and sequence between hevainine and cucumber chitinase are similar to those between class I and class 11 chitinases from tobacco and other plant species. [5, 61 with affinity for chitin [7] or N-acetylglucosamine [S].Other chitinases (class 11) are acidic proteins. They belong to the pathogenesis-related proteins and are excreted by cells under several stress conditions. The sequences of acid chitinases are similar to those of the basic ones, but they lack the N-terminal hevein domain [8, Fresh latex obtained by tapping the rubber tree Hevea brasiliensis can be separated by centrifugation into three main fractions [lS]. These are a white upper layer of rubber particles, an aqueous layer containing the cytoplasma from the cells of the latex vessels and a 'bottom fraction' which consists of lutoids, vacuoles with a low internal pH that may be the equivalent of animal lysosomes [16]. Archer [I71 isolated two major basic proteins with very similar amino acid compositions from rubber latex lutoids and called them hevamine A and B, respectively. Tata et al. [18], using a similar isolation procedure, isolated the same proteins and demonstrated that both are bifunctional lysozymes/chitinases. The N-terminal sequences of hevamine, the lysozyme/chitinase of Parthenorissus and cucumber chitinase [lo, 141 are homologous or very similar.The crystallization of hevamine has been described recently [19]. In this paper we describe the complete primary structure of hevamine obtained as a bifunctional lysozyme/ chitinase from the latex of H . brasiliensis. MATERIALS A N D METHODSHevamine was isolated from freeze-dried bottom Faction of rubber latex (Hevea brasiliensis) as described by Archer [17] with several modifications [19]. Tryptic pep tidesBatches (40 mg) of hevamine were reduced and Scarboxymethylated [20J, citraconylated [21 J and digested with trypsin [22]. Digests were fractionated by gel filtration on

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Smartphones have made sharing images of branded experiences nearly effortless. This research classifies social media brand imagery and studies user response. Aside from packshots (standalone product images), two types of brand-related selfie images appear online: consumer selfies (featuring brands and consumers' faces) and an emerging phenomenon we term brand selfies (invisible consumers holding a branded product). We use convolutional neural networks to identify these archetypes and train language models to infer social media response to more than a quarter million brand-image posts (185 brands on Twitter and Instagram). We find consumer-selfie images receive more sender engagement (i.e., likes and comments), whereas brand selfies result in more brand engagement, expressed by purchase intentions. These results cast doubt on whether conventional social media metrics are appropriate indicators of brand engagement. Results for display ads are consistent with this observation, with higher click-through rates for brand selfies than for consumer selfies. A controlled lab experiment suggests self-reference is driving the differential response to selfie images. Collectively, these results demonstrate how (interpretable) machine learning helps to extract marketing-relevant information from unstructured multimedia content and that selfie images are a matter of perspective in terms of actual brand engagement.