To what extent is researchers' data-sharing motivated by formal mechanisms of recognition and credit?

Scientometrics - Data sharing by researchers is a centerpiece of Open Science principles and scientific progress. For a sample of 6019 researchers, we analyze the extent/frequency of their data...     

Identification of the pharmaceuticals for human use contaminating the Italian aquatic environment

A predictive approach seems useful to identify pharmaceuticals in the environment and give an idea of overall levels of contamination, so as to restrict monitoring to those molecules most likely to be contaminants. We propose an approach based on two parts. The first is to rank the molecules according to the predicted environmental loads; the second is to refine the list by analysing the pharmaceuticals in sewage treatment plants (STPs) and comparing the concentrations with levels previously measured in surface water. This approach identified a restricted group of priority pollutants (ofloxacin, furosemide, atenolol, hydrochlorothiazide, carbamazepine, ibuprofen, spiramycin, bezafibrate, erythromycin, lincomycin and clarithromycin) in the aquatic environment in Italy, for further studies and monitoring.     

Picogram per liter level determination of estrogens in natural waters and waterworks by a fully automated on-line solid-phase extraction-liquid chromatography-electrospray tandem mass spectrometry method

The present work describes a novel, fully automated method, based on on-line solid-phase extraction-liquid chromatography-electrospray tandem mass spectrometry (SPE-LC-ESI-MS-MS), which allows the unequivocal identification and quantification of the most environmentally relevant estrogens (estradiol, estrone, estriol, estradiol-17-glucuronide, estradiol-17-acetate, estrone-3-sulfate, ethynyl estradiol, diethylstilbestrol) in natural and treated waters at levels well below those of concern (limits of quantification between 0.02 and 1.02 ng/L). The method is highly precise, with relative standard deviations varying between 1.43 and 3.89%, and accurate (recovery percentages >74 %). This method was used to track the presence and fate of the target compounds in a waterworks and to evaluate the removal efficiency of the treatment processes applied. Only estrone and estrone-3-sulfate were detected in the river water used as source (at 0.68 and 0.33 ng/L, respectively). After progressive removal through the various treatment steps, none of them were detected in the finished drinking water. In addition to selectivity, sensitivity, repeatability, and automation (up to 15 samples plus 6 calibration solutions and 1 blank can be analyzed unattended), this technique offers fairly high throughput (analysis time per sample is 60 min), low time and solvent consumption, and ease of use.     

Monitoring a labeled degree-corrected stochastic block model

The stochastic block model (SBM) is a random graph model that focuses on partitioning the nodes into blocks or communities. A degree-corrected stochastic block model (DCSBM) considers degree heterogeneity within nodes. Investigation of the type of edge label can be useful for studying networks. We have proposed a labeled degree-corrected stochastic block model (LDCSBM), added the probability of the occurrence of each edge label, and monitored the behavior of this network. The LDCSBM is a dynamic network that varies over time; thus, we applied the monitoring process to both the US Senate voting network and simulated networks by defining structural changes. We used the Shewhart control chart for detecting changes and studied the effect of Phase I parameter estimation on Phase II performance. The efficiency of the model for surveillance has been evaluated using the average run length for estimated parameters.     

Alcalase-generated proteolysates of stone fish (Actinopyga lecanora) flesh as a new source of antioxidant peptides

In the present study, the alcalase-generated proteolysates obtained after 8 h of proteolysis of stone fish flesh showed the most potent antioxidant activity in terms of DPPH^? radical scavenging activity (77.43%, IC₅₀ of 0.5 mg/mL), ABTS^? radical scavenging activity (92.73%, IC₅₀ of 0.33 mg/mL) and FRAP value (39.2 mmol/100 mL FeSO₄). These proteolysates profiled and characterized as antioxidative peptides. The proteolysates were initially subjected to ultrafiltration using MWCO Spin-X UF. Potent fractions were further characterized based on hydrophobicity using reversed-phase high-performance liquid chromatography (RP-HPLC) and isoelectric point using an OFFGEL isoelectric focusing fractionator. Results indicated that most of the antioxidative peptides found in fractions with a molecular weight (MW) of less than 2 kDa, hydrophilic (hydrophilicity >80%) and basic (pI = 9.7). The final purified fraction with the highest antioxidant activity was selected for peptide identification and sequencing using Q-TOF mass spectrometry. A total of four peptides were identified, from which Peptide 1 (GVSGLHID) showed the highest antioxidant activity and this has potential as a novel bioingredient of nutraceuticals and functional foods to promote human health.     

Attributing human foodborne illness to food sources and water in Latin America and the Caribbean using data from outbreak investigations

Foodborne pathogens are responsible for an increasing burden of disease worldwide. Knowledge on the contribution of different food sources and water for disease is essential to prioritize food safety interventions and implement appropriate control measures. Source attribution using outbreak data utilizes readily available data from outbreak surveillance to estimate the contribution of different sources to human disease. We developed a probabilistic model based on outbreak data that attributes human foodborne disease by various bacterial pathogens to sources in Latin America and the Caribbean (LA&C). Foods implicated in outbreaks were classified by their ingredients as simple foods (i.e. belonging to one single food category), or complex foods (i.e. belonging to multiple food categories). For each agent, the data from simple-food outbreaks were summarized, and the proportion of outbreaks caused by each category was used to define the probability that an outbreak was caused by a source. For the calculation of the number of outbreaks attributed to each source, simple-food outbreaks were attributed to the single food category in question, and complex-food outbreaks were partitioned to each category proportionally to the estimated probability. We analysed all bacterial pathogens together, focused on important bacterial pathogens separately, and, when data were sufficient, performed analyses by country, decade and location. Between 1993 and 2010, 6313 bacterial outbreaks were reported by 20 countries. In general, the most important sources of bacterial disease were meat, dairy products, water and vegetables in the 1990s, and eggs, vegetables, and grains and beans in the 2000s. We observed fluctuations of the most important sources of disease for each pathogen between decades and countries, which may be a consequence of changes in the control of zoonotic disease over the years, of changes in food consumption habits, or of changes in public health focus and availability of data of different pathogens. This study identified data gaps in the region and highlighted the importance of effective surveillance systems to identify sources of disease. Still, the application of this method for source attribution in the LA&C region was successful, and we concluded that this approach can be used to attribute disease to food sources and water in other regions, including developing regions with limited data on the public health impact of foodborne diseases.     

The Expanding Role of Traceability in Seafood: Tools and Key Initiatives

In the last decade, a range of drivers within the seafood sector have incentivized the application of traceability to issues beyond food safety and inventory management. Some of the issues motivating the expanded use of traceability within the global seafood sector include: increased media attention on the legal and social risks within some seafood supply chains, governmental traceability requirements, private‐sector sustainability commitments, and others. This article begins with an overview of these topics in the seafood industry, and why many nongovernment organizations (NGOs), companies, and government actors have turned to traceability as a tool to address them. We discuss how traceability connects to key requirements of environmental sustainability and social responsibility. Later, we review the range of traceability services, tools, software solutions, and the due diligence measures that are currently being leveraged within the seafood sector. The paper concludes with a discussion of several NGO‐ and industry‐led traceability initiatives that are examples of seafood traceability improvements.