Aged garlic has more potent antiglycation and antioxidant properties compared to fresh garlic extract in vitro

Protein glycation involves formation of early (Amadori) and late advanced glycation endproducts (AGEs) together with free radicals via autoxidation of glucose and Amadori products. Glycation and increased free radical activity underlie the pathogenesis of diabetic complications. This study investigated whether aged garlic has more potent antiglycation and antioxidant properties compared to fresh garlic extract in vitro in a cell-free system. Proteins were glycated by incubation with sugars (glucose, methylglyoxal or ribose) ±5–15 mg/mL of aged and fresh garlic extracts. Advanced glycation endproducts were measured using SDS-PAGE gels and by ELISA whereas Amadori products were assessed by the fructosamine method. Colorimetric methods were used to assess antioxidant activity, free radical scavenging capacity, protein-bound carbonyl groups, thiol groups and metal chelation activities in addition to phenolic, total flavonoid and flavonol content of aged and fresh garlic extracts. Aged garlic inhibited AGEs by 56.4% compared to 33.5% for an equivalent concentration of fresh garlic extract. Similarly, aged garlic had a higher total phenolic content (129 ± 1.8 mg/g) compared to fresh garlic extract (56 ± 1.2 mg/g). Aged garlic has more potent antiglycation and antioxidant properties compared to fresh garlic extract and is more suitable for use in future in vivo studies

The Recognition of N-Glycans by the Lectin ArtinM Mediates Cell Death of a Human Myeloid Leukemia Cell Line

ArtinM, a d-mannose-binding lectin from Artocarpus heterophyllus (jackfruit), interacts with N-glycosylated receptors on the surface of several cells of hematopoietic origin, triggering cell migration, degranulation, and cytokine release. Because malignant transformation is often associated with altered expression of cell surface glycans, we evaluated the interaction of ArtinM with human myelocytic leukemia cells and investigated cellular responses to lectin binding. The intensity of ArtinM binding varied across 3 leukemia cell lines: NB4>K562>U937. The binding, which was directly related to cell growth suppression, was inhibited in the presence of Manα1-3(Manα1-6)Manβ1, and was reverted in underglycosylated NB4 cells. ArtinM interaction with NB4 cells induced cell death (IC50 = 10 µg/mL), as indicated by cell surface exposure of phosphatidylserine and disruption of mitochondrial membrane potential unassociated with caspase activation or DNA fragmentation. Moreover, ArtinM treatment of NB4 cells strongly induced reactive oxygen species generation and autophagy, as indicated by the detection of acidic vesicular organelles in the treated cells. NB4 cell death was attributed to ArtinM recognition of the trimannosyl core of N-glycans containing a ß1,6-GlcNAc branch linked to α1,6-mannose. This modification correlated with higher levels of N-acetylglucosaminyltransferase V transcripts in NB4 cells than in K562 or U937 cells. Our results provide new insights into the potential of N-glycans containing a β1,6-GlcNAc branch linked to α1,6-mannose as a novel target for anti-leukemia treatment

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms