A Comparative Analysis of Methods (LC-MS/MS, LC-MS and Rapid Test Kits) for the Determination of Diarrhetic Shellfish Toxins in Oysters, Mussels and Pipis

Rapid methods for the detection of biotoxins in shellfish can assist the seafood industry and safeguard public health. Diarrhetic Shellfish Toxins (DSTs) are produced by species of the dinoflagellate genus Dinophysis, yet the comparative efficacy of their detection methods has not been systematically determined. Here, we examined DSTs in spiked and naturally contaminated shellfish–Sydney Rock Oysters (Saccostrea glomerata), Pacific Oysters (Magallana gigas/Crassostrea gigas), Blue Mussels (Mytilus galloprovincialis) and Pipis (Plebidonax deltoides/Donax deltoides), using LC-MS/MS and LC-MS in 4 laboratories, and 5 rapid test kits (quantitative Enzyme-Linked Immunosorbent Assay (ELISA) and Protein Phosphatase Inhibition Assay (PP2A), and qualitative Lateral Flow Assay (LFA)). We found all toxins in all species could be recovered by all laboratories using LC-MS/MS (Liquid Chromatography—tandem Mass Spectrometry) and LC-MS (Liquid Chromatography—Mass Spectrometry); however, DST recovery at low and mid-level concentrations (0.86 mg/kg) was higher (60–262%). While no clear differences were observed between shellfish, all kits delivered an unacceptably high level (25–100%) of falsely compliant results for spiked samples. The LFA and the PP2A kits performed satisfactorily for naturally contaminated pipis (0%, 5% falsely compliant, respectively). There were correlations between spiked DSTs and quantitative methods was highest for LC-MS (r2 = 0.86) and the PP2A kit (r2 = 0.72). Overall, our results do not support the use of any DST rapid test kit as a stand-alone quality assurance measure at this tim

Adam Deep Learning with SOM for Human Sentiment Classification

Nowadays, with the improvement in communication through social network services, a massive amount of data is being generated from user's perceptions, emotions, posts, comments, reactions, etc., and extracting significant information from those massive data, like sentiment, has become one of the complex and convoluted tasks. On other hand, traditional Natural Language Processing (NLP) approaches are less feasible to be applied and therefore, this research work proposes an approach by integrating unsupervised machine learning (Self-Organizing Map), dimensionality reduction (Principal Component Analysis) and computational classification (Adam Deep Learning) to overcome the problem. Moreover, for further clarification, a comparative study between various well known approaches and the proposed approach was conducted. The proposed approach was also used in different sizes of social network data sets to verify its superior efficient and feasibility, mainly in the case of Big Data. Overall, the experiments and their analysis suggest that the proposed approach is very promissing

Expression profiles of differentially regulated genes during the early stages of apple flower infection with Erwinia amylovora

To identify genes involved in the response to the fire blight pathogen Erwinia amylovora in apple (Malus×domestica), expression profiles were investigated using an apple oligo (70-mer) array representing 40, 000 genes. Blossoms of a fire blight-susceptible apple cultivar Gala were collected from trees growing in the orchard, placed on a tray in the laboratory, and spray-inoculated with a suspension of E. amylovora at a concentration of 108 cfu ml−1. Uninoculated detached flowers served as controls at each time point. Expression profiles were captured at three different time points post-inoculation at 2, 8, and 24 h, together with those at 0 h (uninoculated). A total of about 3500 genes were found to be significantly modulated in response to at least one of the three time points. Among those, a total of 770, 855, and 1002 genes were up-regulated, by 2-fold, at 2, 8, and 24 h following inoculation, respectively; while, 748, 1024, and 1455 genes were down-regulated, by 2-fold, at 2, 8, and 24 h following inoculation, respectively. Over the three time points post-inoculation, 365 genes were commonly up-regulated and 374 genes were commonly down-regulated. Both sets of genes were classified based on their functional categories. The majority of up-regulated genes were involved in metabolism, signal transduction, signalling, transport, and stress response. A number of transcripts encoding proteins/enzymes known to be up-regulated under particular biotic and abiotic stress were also up-regulated following E. amylovora treatment. Those up- or down-regulated genes encode transcription factors, signaling components, defense-related, transporter, and metabolism, all of which have been associated with disease responses in Arabidopsis and rice, suggesting similar response pathways are involved in apple blossoms

Identification of mutations through dominant screening for obesity using C57BL/6 substrains

The discovery of leptin substantiated the usefulness of a forward genetic approach in elucidating the molecular network regulating energy metabolism. However, no successful dominant screening for obesity has been reported, which may be due to the influence of quantitative trait loci between the screening and counter strains and the low fertility of obese mice. Here, we performed a dominant screening for obesity using C57BL/6 substrains, C57BL/6J and C57BL/6N, with the routine use of in vitro fertilization. The screening of more than 5000 mutagenized mice established two obese pedigrees in which single nucleotide substitutions in Mc4r and Sim1 genes were identified through whole-exome sequencing. The mutation in the Mc4r gene produces a premature stop codon, and the mutant SIM1 protein lacks transcriptional activity, showing that the haploinsufficiency of SIM1 and MC4R results in obesity. We further examined the hypothalamic neuropeptide expressions in the mutant pedigrees and mice with diet-induced obesity, which showed that each obesity mouse model has distinct neuropeptide expression profiles. This forward genetic screening scheme is useful and applicable to any research field in which mouse models work

First Detection of Paralytic Shellfish Toxins from Alexandrium pacificum above the Regulatory Limit in Blue Mussels (Mytilus galloprovincialis) in New South Wales, Australia.

In 2016, 2017 and 2018, elevated levels of the species Alexandrium pacificum were detected within a blue mussel (Mytilus galloprovincialis) aquaculture area at Twofold Bay on the south coast of New South Wales, Australia. In 2016, the bloom persisted for at least eight weeks and maximum cell concentrations of 89,000 cells L-1 of A. pacificum were reported. The identity of A. pacificum was confirmed using molecular genetic tools (qPCR and amplicon sequencing) and complemented by light and scanning electron microscopy of cultured strains. Maximum reported concentrations of paralytic shellfish toxins (PSTs) in mussel tissue was 7.2 mg/kg PST STX equivalent. Elevated cell concentrations of A. pacificum were reported along the adjacent coastal shelf areas, and positive PST results were reported from nearby oyster producing estuaries during 2016. This is the first record of PSTs above the regulatory limit (0.8 mg/kg) in commercial aquaculture in New South Wales since the establishment of routine biotoxin monitoring in 2005. The intensity and duration of the 2016 A. pacificum bloom were unusual given the relatively low abundances of A. pacificum in estuarine and coastal waters of the region found in the prior 10 years