Extraction of Protein from Four Different Seaweeds Using Three Different Physical Pre-Treatment Strategies

peer-reviewedSeaweeds are a rich source of protein and can contain up to 47% on the dry weight basis. It is challenging to extract proteins from the raw biomass of seaweed due to resilient cell-wall complexes. Four species of macroalgae were used in this study-two brown, Fucus vesiculosus and Alaria esculenta, and two red, Palmaria palmata and Chondrus crispus. Three treatments were applied individually to the macroalgal species: (I) high-pressure processing (HPP); (II) laboratory autoclave processing and (III) a classical sonication and salting out method. The protein, ash and lipid contents of the resulting extracts were estimated. Yields of protein recovered ranged from 3.2% for Fucus vesiculosus pre-treated with high pressure processing to 28.9% protein recovered for Chondrus crispus treated with the classical method. The yields of protein recovered using the classical, HPP and autoclave pre-treatments applied to Fucus vesiculosus were 35.1, 23.7% and 24.3%, respectively; yields from Alaria esculenta were 18.2%, 15.0% and 17.1% respectively; yields from Palmaria palmata were 12.5%, 14.9% and 21.5% respectively, and finally, yields from Chondrus crispus were 35.2%, 16.1% and 21.9%, respectively. These results demonstrate that while macroalgal proteins may be extracted using either physical or enzymatic methods, the specific extraction procedure should be tailored to individual species

Breaking into the blackbox: Trend following, stop losses and the frequency of trading - The case of the S&P500

In this article, we compare a variety of technical trading rules in the context of investing in the S&P500 index. These rules are increasingly popular, both among retail investors and CTAs and similar investment funds. We find that a range of fairly simple rules, including the popular 200-day moving average (MA) trading rule, dominate the long-only, passive investment in the index. In particular, using the latter rule we find that popular stop-loss rules do not add value and that monthly end-of-month investment decision rules are superior to those which trade more frequently: this adds to the growing view that trading can damage your wealth. Finally, we compare the MA rule with a variety of simple fundamental metrics and find the latter far inferior to the technical rules over the last 60 years of investing

Two-photon Lithography for 3D Magnetic Nanostructure Fabrication

Ferromagnetic materials have been utilised as recording media within data storage devices for many decades. Confinement of the material to a two dimensional plane is a significant bottleneck in achieving ultra-high recording densities and this has led to the proposition of three dimensional (3D) racetrack memories that utilise domain wall propagation along nanowires. However, the fabrication of 3D magnetic nanostructures of complex geometry is highly challenging and not easily achievable with standard lithography techniques. Here, by using a combination of two-photon lithography and electrochemical deposition, we show a new approach to construct 3D magnetic nanostructures of complex geometry. The magnetic properties are found to be intimately related to the 3D geometry of the structure and magnetic imaging experiments provide evidence of domain wall pinning at a 3D nanostructured junction

Do dividends signal future earnings in the Nordic stock markets?

We study the informational content of dividends on three Nordic civil law markets, where other simultaneous but blurring motives for dividends may be weaker. Using aggregate data on real earnings per share and payout ratios, long time series from 1969 to 2010, and methodologies which address problems of endogeneity, non-stationarity and autocorrelation (including a Vector Error Correction Model approach), we find evidence on dividend signaling in Nordic markets. However, we also find heterogeneity in the relationship between dividends and earnings on markets similar in many respects, suggesting that even small variations in the institutional surroundings may be important for the results

Identification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the BovineSNP50 BeadChip

Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n = 1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n = 878) and loci under selection (n = 190) were identified with the FST-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1−30.1 million years before present)

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability