Extracts From New Zealand Undaria Pinnatifida Containing Fucoxanthin As Potential Functional Biomaterials Against Cancer in Vitro

This study tested extracts from New Zealand seaweed Undaria pinnatifida containing fucoxanthin, in parallel with pure fucoxanthin, in nine human cancer cell lines, for anticancer activity. Growth inhibition effects of extracts from Undaria pinnatifida were found in all types of cancer cell lines in dose- and time- dependent manners. Cytotoxicity of fucoxanthin in three human non-cancer cell lines was also tested. Compared with pure fucoxanthin, our extracts containing low level of fucoxanthin were found to be more effective in inhibiting the growth of lung carcinoma, colon adenocarcinoma and neuroblastoma. Our results suggest that fucoxanthin is a functional biomaterial that may be used as a chemopreventive phytochemical or in combination chemotherapy. Furthermore, we show for the first time that some unknown compounds with potential selective anti-cancer effects may exist in extracts of New Zealand Undaria pinnatifida, and New Zealand Undaria pinnatifida could be used as a source for either functional biomaterial extraction or production of functional food

Optimization of fermentation medium for nisin production from Lactococcus lactis subsp. lactis using response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA)

Nisin is a bacteriocin approved in more than 50 countries as a safe natural food preservative. Response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA) was employed to optimize the fermentation medium for nisin production. Plackett-Burman design (PBD) was used for identifying the significant components in the fermentation medium. After that, the path of steepest ascent method (PSA) was employed to approach their optimal concentrations. Sequentially, Box-Behnken design experiments were implemented for further optimization. RSM combined with ANNGA were used for analysis of data. Specially, a RSM model was used for determining the individual effect and mutual interaction effect of tested variables on nisin titer (NT), an ANN model was used for NT prediction, and GA was employed to search for the optimum solutions based on the ANN model. As the optimal medium obtained by ANN-GA was located at the verge of the test region, a further Box- Behnken design based on the RSM statistical analysis results was implemented. ANN-GA was implemented using the further Box-Behnken design data to locate the optimum solution which was as follow (g/l): Glucose (GLU) 15.92, peptone (PEP) 30.57, yeast extraction powder (YEP) 39.07, NaCl 5.25, KH2PO4 10.00, and MgSO4·7H2O 0.20, with expected NT of 22216 IU/ml. The validation experiments with the optimum solution were implemented in triplicate and the average NT was 21423 IU/ml, which was 2.13 times higher than that without ANN-GA methods and 8.34 times higher than that without optimization.Key words: Response surface methodology, artificial neural network, genetic algorithm, nisin titer

Anti-proliferation Potential and Content of Fucoidan Extracted From Sporophyll of New Zealand Undaria Pinnatifida

Undaria pinnatifida is a species of brown seaweed known to contain rich amounts of fucoidan, a sulfated polysaccharide known to possess various biological activities. We isolated crude fucoidan (F0) from the sporophylls of U. pinnatifida grown in the Marlborough Sounds, New Zealand. Sulfate content, uronic acid content, and molecular weight of F0 were 15.02, 1.24, and >150 kDa, respectively. F0 was fractionated to yield three further fractions: F1, F2, and F3. Cytotoxicity of two major fractions was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The algal fucoidans specifically suppressed the proliferation of three cancer cell lines with less cytotoxicity against the normal cells. Selective cytotoxicity could relate to the distinctive structures of each fucoidan fraction. Results from this study provide evidence that fucoidan, especially from U. pinnatifida grown in New Zealand, possesses great potential to be used as a functional food to reduce cancer risk or supplement cancer treatment

Real-time ultrasonic assessment of progressive proteoglycan depletion in articular cartilage

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Assessment of Cellular Estrogenic Activity Based on Estrogen Receptor-Mediated Reduction of Soluble-Form Catechol-O-Methyltransferase (COMT) Expression in an ELISA-Based System

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The Natural Compound Fucoidan From New Zealand Undaria Pinnatifida Synergizes With the ERBB Inhibitor Lapatinib Enhancing Melanoma Growth Inhibition

Melanoma remains one of the most aggressive and therapy-resistant cancers. Finding new treatments to improve patient outcomes is an ongoing effort. We previously demonstrated that melanoma relies on the activation of ERBB signaling, specifically of the ERBB3/ERBB2 cascade. Here we show that melanoma tumor growth is inhibited by 60% over controls when treated with lapatinib, a clinically approved inhibitor of ERBB2/EGFR. Importantly, tumor growth is further inhibited to 85% when the natural compound fucoidan from New Zealand U. pinnatifida is integrated into the treatment regimen. Fucoidan not only enhances tumor growth inhibition, it counteracts the morbidity associated with prolonged lapatinib treatment. Fucoidan doubles the cell killing capacity of lapatinib. These effects are associated with a further decrease in AKT and NFκB signaling, two key pathways involved in melanoma cell survival. Importantly, the enhancing cell killing effects of fucoidan can be recapitulated by inhibiting ERBB3 by either a specific shRNA or a novel, selective ERBB3 neutralizing antibody, reiterating the key roles played by this receptor in melanoma. We therefore propose the use of lapatinib or specific ERBB inhibitors, in combination with fucoidan as a new treatment of melanoma that potentiates the effects of the inhibitors while protecting from their potential side effects

Spatially-resolved electronic and vibronic properties of single diamondoid molecules

Diamondoids are a unique form of carbon nanostructure best described as hydrogen-terminated diamond molecules. Their diamond-cage structures and tetrahedral sp3 hybrid bonding create new possibilities for tuning electronic band gaps, optical properties, thermal transport, and mechanical strength at the nanoscale. The recently-discovered higher diamondoids (each containing more than three diamond cells) have thus generated much excitement in regards to their potential versatility as nanoscale devices. Despite this excitement, however, very little is known about the properties of isolated diamondoids on metal surfaces, a very relevant system for molecular electronics. Here we report the first molecular scale study of individual tetramantane diamondoids on Au(111) using scanning tunneling microscopy and spectroscopy. We find that both the diamondoid electronic structure and electron-vibrational coupling exhibit unique spatial distributions characterized by pronounced line nodes across the molecular surfaces. Ab-initio pseudopotential density functional calculations reveal that the observed dominant electronic and vibronic properties of diamondoids are determined by surface hydrogen terminations, a feature having important implications for designing diamondoid-based molecular devices.Comment: 16 pages, 4 figures. to appear in Nature Material

The effect of ex-vivo rotenone intoxication on dopamine re-uptake of LRRK2-R1441G mutant mouse

Poster presentationpublished_or_final_versio

Long-Term Visual Object Tracking Benchmark

We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking. The dataset consists of 50 HD videos from real world scenarios, encompassing a duration of over 400 minutes (676K frames), making it more than 20 folds larger in average duration per sequence and more than 8 folds larger in terms of total covered duration, as compared to existing generic datasets for visual tracking. The proposed dataset paves a way to suitably assess long term tracking performance and train better deep learning architectures (avoiding/reducing augmentation, which may not reflect real world behaviour). We benchmark the dataset on 17 state of the art trackers and rank them according to tracking accuracy and run time speeds. We further present thorough qualitative and quantitative evaluation highlighting the importance of long term aspect of tracking. Our most interesting observations are (a) existing short sequence benchmarks fail to bring out the inherent differences in tracking algorithms which widen up while tracking on long sequences and (b) the accuracy of trackers abruptly drops on challenging long sequences, suggesting the potential need of research efforts in the direction of long-term tracking.Comment: ACCV 2018 (Oral

LRRK2 R1441G mice are more liable to dopamine depletion and locomotor inactivity

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