Evolutionary impact assessment of the North Sea plaice fishery

There is growing evidence that fishing causes evolution in life-history traits that affect the productivity of fish stocks. Here we explore the impact of fisheries-induced evolu-tion (FIE) on the productivity of North Sea plaice using an eco-genetic individual-based model by comparing management scenarios with and without an evolutionary re-sponse. Under status-quo management, plaice evolve towards smaller size at age, ear-lier maturation, and higher reproductive investment. Current reference points of maximum sustainable yield (MSY) and corresponding fishing-mortality rate ( ) that ignore FIE will decrease and cannot be considered sustainable. The nature and extent of the change through FIE depend on fishing effort and selectivity. The adverse evolutionary effects can be reduced – and even reversed – by implementing a dome-shaped exploitation pattern protecting the large fish. The evolutionarily sustainable maximum yield can be obtained by combining such a dome-shaped exploitation pattern with a reduction in fishing mortality and an increase in mesh size; it is similar to the maximum sustainable yield that would apply if life-history traits were static. Fisheries managers will need to trade off the short-term loss in yield associated with evolutionarily informed management with the long-term loss in yield FIE causes under evolutionarily uninformed management

How MicroRNA and Transcription Factor Co-regulatory Networks Affect Osteosarcoma Cell Proliferation

Osteosarcomas (OS) are complex bone tumors with various genomic alterations. These alterations affect the expression and function of several genes due to drastic changes in the underlying gene regulatory network. However, we know little about critical gene regulators and their functional consequences on the pathogenesis of OS. Therefore, we aimed to determine microRNA and transcription factor (TF) co-regulatory networks in OS cell proliferation. Cell proliferation is an essential part in the pathogenesis of OS and deeper understanding of its regulation might help to identify potential therapeutic targets. Based on expression data of OS cell lines divided according to their proliferative activity, we obtained 12 proliferation-related microRNAs and corresponding target genes. Therewith, microRNA and TF co-regulatory networks were generated and analyzed regarding their structure and functional influence. We identified key co-regulators comprising the microRNAs miR-9-5p, miR-138, and miR-214 and the TFs SP1 and MYC in the derived networks. These regulators are implicated in NFKB- and RB1-signaling and focal adhesion processes based on their common or interacting target genes (e.g., CDK6, CTNNB1, E2F4, HES1, ITGA6, NFKB1, NOTCH1, and SIN3A). Thus, we proposed a model of OS cell proliferation which is primarily co-regulated through the interactions of the mentioned microRNA and TF combinations. This study illustrates the benefit of systems biological approaches in the analysis of complex diseases. We integrated experimental data with publicly available information to unravel the coordinated (post)-transcriptional control of microRNAs and TFs to identify potential therapeutic targets in OS. The resulting microRNA and TF co-regulatory networks are publicly available for further exploration to generate or evaluate own hypotheses of the pathogenesis of OS (http://www.complex-systems.uni-muenster.​de/co_networks.html)

Mitigating seafloor disturbance of bottom trawl fisheries for North Sea sole Solea solea by replacing mechanical with electrical stimulation

Funding: ADR, NTH, PM, HP, JJP, TvK: European Maritime and Fisheries Fund (EMFF) through the Netherlands Ministry of Agriculture Nature and Food Quality (LNV) (Grand/Award Number: 1300021172); NO ADR, JD, ORE, NTH, AI, FO, HP, JJP, TvK: FP 7 project BENTHIS (grant no. 312088); NO.Peer reviewedPublisher PD

Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation

Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific information about genes or microRNAs is quick and easily accessible. Hence, this platform can support the ongoing OS research and biomarker discovery

Scientific, Technical and Economic Committee for Fisheries (STECF) - Report of the STECF Study Group on the Evaluation of Fishery Multi-annual Plans (SGMOS 09-02)

SG-MOS 09-02 was held in IPIMAR, Lisbon, (Portugal), on 23-27 November 2009. The aim of the workshop was to provide Evaluations of three multiannual fisheries management plans:- R(EC) No 388/2006 ¿ multi-annual plan for sole in the Bay of Biscay; R(EC) No 209/2007 ¿ multi-annual plan for sole in the Western Channel R(EC) No676/2007 ¿ multi-annual plan for sole and plaice in the North Sea. STECF reviewed the report during its Plenary meeting on 26-30 April 2010.JRC.DG.G.4-Maritime affair

Maxillofacial Fractures in Electric and Conventional Bicycle-Related Accidents

PURPOSE: With the increased use of both e-bike and conventional bicycle, the number of bicycle-related accidents has increased accordingly. To determine whether there are differences in maxillofacial injuries between these 2 types of bicycle accidents, e-bike and conventional bicycle accidents were compared.MATERIAL AND METHODS: A retrospective cohort study was conducted for all the consecutive patients with maxillofacial injury due to e-bike and conventional bicycle accidents attending the emergency department of 4 hospitals in the Netherlands between May 2018 and October 2019. Primary outcomes are maxillofacial fractures present or absent and the severity of maxillofacial injury using the Maximum Abbreviated Injury Scale and Facial Injury Severity Scale (FISS) after e-bike and conventional bicycle accidents. A binary logistic regression analysis was used to assess differences in risk between an e-bike and conventional bicycle accident, where age, alcohol use, and comorbidities were added as covariates, for maxillofacial fractures, dental injury, and severe maxillofacial fractures.RESULTS: In total, 311 patients were included (73 e-bikers and 238 conventional cyclists). Sex distribution was equal in both groups (45% male vs 55% female). The e-bike group was older (66 vs 53 median age in years, P &lt; .001) and had more comorbidities (0 vs 1, P &lt; .001), while alcohol use was higher in the conventional bicycle group (32% vs 16%, P = .008). e-Bikers sustained midfacial fractures more frequently (47% vs 34%, P = .04), whereas conventional cyclists more often had mandibular fractures (1% vs 11%, P = .01). Although median Maximum Abbreviated Injury Scale and FISS scores did not differ between e-bike and conventional bicycle accidents, severe maxillofacial fractures (FISS score ≥ 2) were observed more often in the conventional cyclists (45% vs 25%, P = .04). No significant differences in risk of midfacial, mandibular, and severe maxillofacial fractures were found between e-bikers and conventional cyclists irrespective of their age, alcohol use, and comorbidities.CONCLUSION: Both the distribution and the severe maxillofacial fractures differed between the e-bike and conventional bicycle accident patients. Patient-specific characteristics, such as age, alcohol use, and comorbidities, may have a greater influence on sustaining maxillofacial fractures than the type of bicycle ridden.</p

Assessing the utility of fisheries-dependent data to support mixed fisheries management: a spatiotemporal simulation framework

Fishers exploit populations that are heterogeneously distributed in space and time without full knowledge of species distributions and with fishing gear that is not fully selective. The ability to change catch composition is limited by species mix at a particular location and time and the capture characteristics of the fishing gear. Models capturing the dynamics of the fisheries (‘fleet dynamics’ models) are often simplistic due to a lack of knowledge of the processes driving these catches, which occur both at large and small scales. We develop a simulation framework to investigate the importance of scaling on the interactions between fish populations and fisheries dynamics. The framework provides i) a realistic but tractable biological model of fish populations in space and time, including daily population processes (mortality, growth and recruitment) and population movement implemented as a combination of diffusive density-dependent processes and migrations; and, ii) a realistic fishing simulation model to capture how fishers may exploit heterogeneously distributed fish populations with different values and uncertain knowledge about the underlying spatial processes. We generate a model system where we investigate the consequences of scaling and data aggregation and validate this simulated data against data collected on fisheries operating in the Celtic Sea. The simulation allows a more in-depth understanding of factors important when using fisheries-dependent data to develop spatial management measures, from the micro- to the large-scale and individual to population processes, not otherwise possible due to the limitations in ‘real-world’ spatiotemporal data on fish distributions