Using Machine Learning to Uncover Latent Research Topics in Fishery Models

© 2018 The Author(s). Published with license by Taylor & Francis © 2018, Shaheen Syed and Charlotte Teresa Weber. Modeling has become the most commonly used method in fisheries science, with numerous types of models and approaches available today. The large variety of models and the overwhelming amount of scientific literature published yearly can make it difficult to effectively access and use the output of fisheries modeling publications. In particular, the underlying topic of an article cannot always be detected using keyword searches. As a consequence, identifying the developments and trends within fisheries modeling research can be challenging and time-consuming. This paper utilizes a machine learning algorithm to uncover hidden topics and subtopics from peer-reviewed fisheries modeling publications and identifies temporal trends using 22,236 full-text articles extracted from 13 top-tier fisheries journals from 1990 to 2016. Two modeling topics were discovered: estimation models (a topic that contains the idea of catch, effort, and abundance estimation) and stock assessment models (a topic on the assessment of the current state of a fishery and future projections of fish stock responses and management effects). The underlying modeling subtopics show a change in the research focus of modeling publications over the last 26 years

SPIRE - combining SGI-110 with cisplatin and gemcitabine chemotherapy for solid malignancies including bladder cancer: study protocol for a phase Ib/randomised IIa open label clinical trial

Background Urothelial bladder cancer (UBC) accounts for 10,000 new diagnoses and 5000 deaths annually in the UK (Cancer Research UK, http://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/bladder-cancer, Cancer Research UK, Accessed 26 Mar 2018). Cisplatin-based chemotherapy is standard of care therapy for UBC for both palliative first-line treatment of advanced/metastatic disease and radical neoadjuvant treatment of localised muscle invasive bladder cancer. However, cisplatin resistance remains a critical cause of treatment failure and a barrier to therapeutic advance in UBC. Based on supportive pre-clinical data, we hypothesised that DNA methyltransferase inhibition would circumvent cisplatin resistance in UBC and potentially other cancers. Methods The addition of SGI-110 (guadecitabine, a DNA methyltransferase inhibitor) to conventional doublet therapy of gemcitabine and cisplatin (GC) is being tested within the phase Ib/IIa SPIRE clinical trial. SPIRE incorporates an initial, modified rolling six-dose escalation phase Ib design of up to 36 patients with advanced solid tumours followed by a 20-patient open-label randomised controlled dose expansion phase IIa component as neoadjuvant treatment for UBC. Patients are being recruited from UK secondary care sites. The dose escalation phase will determine a recommended phase II dose (RP2D, primary endpoint) of SGI-110, by subcutaneous injection, on days 1–5 for combination with GC at conventional doses (cisplatin 70 mg/m2, IV infusion, day 8; gemcitabine 1000 mg/m2, IV infusion, days 8 and 15) in every 21-day cycle. In the dose expansion phase, patients will be randomised 1:1 to GC with or without SGI-110 at the proposed RP2D. Secondary endpoints will include toxicity profiles, SGI-110 pharmacokinetics and pharmacodynamic biomarkers, and pathological complete response rates in the dose expansion phase. Analyses will not be powered for formal statistical comparisons and descriptive statistics will be used to describe rates of toxicity, efficacy and translational endpoints by treatment arm. Discussion SPIRE will provide evidence for whether SGI-110 in combination with GC chemotherapy is safe and biologically effective prior to future phase II/III trials as a neoadjuvant therapy for UBC and potentially in other cancers treated with GC

Linking learning with governance in networks and clusters: key issues for analysis and policy

In this paper we analyse the relationship between governance and learning in clusters and networks. In particular, we see these two key elements as interdependent, suggesting that, under particular circumstances, such interdependence may drive clusters and networks towards a dynamic development trajectory. A pure ‘governance perspective’ makes the development of any locality dependent on the system of powers which exists within the locality or across the global value chain. In parallel, a pure ‘competence-based approach’ focuses mainly on the capabilities of actors to learn and undertake activities. In contrast, we open the prospects for an interdependent relation that may change the actual competences of actors as well as the governance settings and dynamics in networks and clusters. When supported by public policies, the learning process may have the potential to modify the governance environment. Simultaneously, the learning process is intrinsically influenced by economic power, which may seriously affect the development prospects of clusters and networks. This is why an intertwined consideration of both aspects is necessary to promote specific approaches to learning and to design appropriate policies. In this paper we offer two preliminary case studies to clarify some of these dynamics: the first taken from the computers cluster in Costa Rica and the second from an Italian bio-pharmaceutical firm and its production network. The first case study refers to the software cluster that was created from scratch in Costa Rica thanks to an enlightened government policy in coordination with new local enterprises and an important foreign direct investor; while the second reflects on the ability of an individual company to create a network of relationships with large transnational companies in order to acquire new competences without falling into a subordinate position with respect to its larger partners

Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.

SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures

Challenges for Implementing an Ecosystem Approach to Fisheries Management

The ecosystem approach is being promoted as the foundation of solutions to the unsustainability of fisheries. However, because the ecosystem approach is broadly inclusive, the science for its implementation is often considered to be overly complex and difficult. When the science needed for an ecosystem approach to fisheries is perceived this way, science products cannot keep pace with fisheries critics, thus encouraging partisan political interference in fisheries management and proliferation of “faith-based solutions. In this paper we argue that one way to effectively counter politicization of fisheries decision-making is to ensure that new ecosystem-based approaches in fisheries are viewed only as an emergent property of innovation in science and policy. We organize our essay using three major themes to focus the discussion: empirical, jurisdictional, and societal challenges. We undertake at least partial answers to the following questions: (1) has conventional fisheries management really failed?; (2) can short-comings in conventional fisheries management be augmented with new tools, such as allocation of rights?; (3) is the Ecosystem Approach to Fisheries (EAF) equivalent to Ecosystem-Based Management?; and (4) is restoration of degraded ecosystems a necessary component of an EAF

Effective control of sars-cov-2 transmission between healthcare workers during a period of diminished community prevalence of covid-19

Previously, we showed that 3% (31/1032)of asymptomatic healthcare workers (HCWs) from a large teaching hospital in Cambridge, UK, tested positive for SARS-CoV-2 in April 2020. About 15% (26/169) HCWs with symptoms of coronavirus disease 2019 (COVID-19) also tested positive for SARS-CoV-2 (Rivett et al., 2020). Here, we show that the proportion of both asymptomatic and symptomatic HCWs testing positive for SARS-CoV-2 rapidly declined to nearzero between 25th April and 24th May 2020, corresponding to a decline in patient admissions with COVID-19 during the ongoing UK ‘lockdown’. These data demonstrate how infection prevention and control measures including staff testing may help prevent hospitals from becoming independent ‘hubs’ of SARS-CoV-2 transmission, and illustrate how, with appropriate precautions, organizations in other sectors may be able to resume on-site work safely

Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission

Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3-week period (April 2020), 1,032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19) >7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B·1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff

Combined Point-of-Care Nucleic Acid and Antibody Testing for SARS-CoV-2 following Emergence of D614G Spike Variant

Rapid COVID-19 diagnosis in the hospital is essential, although this is complicated by 30%–50% of nose/throat swabs being negative by SARS-CoV-2 nucleic acid amplification testing (NAAT). Furthermore, the D614G spike mutant dominates the pandemic and it is unclear how serological tests designed to detect anti-spike antibodies perform against this variant. We assess the diagnostic accuracy of combined rapid antibody point of care (POC) and nucleic acid assays for suspected COVID-19 disease due to either wild-type or the D614G spike mutant SARS-CoV-2. The overall detection rate for COVID-19 is 79.2% (95% CI 57.8–92.9) by rapid NAAT alone. The combined point of care antibody test and rapid NAAT is not affected by D614G and results in very high sensitivity for COVID-19 diagnosis with very high specificity

From Sea to Sea: Canada's Three Oceans of Biodiversity

Evaluating and understanding biodiversity in marine ecosystems are both necessary and challenging for conservation. This paper compiles and summarizes current knowledge of the diversity of marine taxa in Canada's three oceans while recognizing that this compilation is incomplete and will change in the future. That Canada has the longest coastline in the world and incorporates distinctly different biogeographic provinces and ecoregions (e.g., temperate through ice-covered areas) constrains this analysis. The taxonomic groups presented here include microbes, phytoplankton, macroalgae, zooplankton, benthic infauna, fishes, and marine mammals. The minimum number of species or taxa compiled here is 15,988 for the three Canadian oceans. However, this number clearly underestimates in several ways the total number of taxa present. First, there are significant gaps in the published literature. Second, the diversity of many habitats has not been compiled for all taxonomic groups (e.g., intertidal rocky shores, deep sea), and data compilations are based on short-term, directed research programs or longer-term monitoring activities with limited spatial resolution. Third, the biodiversity of large organisms is well known, but this is not true of smaller organisms. Finally, the greatest constraint on this summary is the willingness and capacity of those who collected the data to make it available to those interested in biodiversity meta-analyses. Confirmation of identities and intercomparison of studies are also constrained by the disturbing rate of decline in the number of taxonomists and systematists specializing on marine taxa in Canada. This decline is mostly the result of retirements of current specialists and to a lack of training and employment opportunities for new ones. Considering the difficulties encountered in compiling an overview of biogeographic data and the diversity of species or taxa in Canada's three oceans, this synthesis is intended to serve as a biodiversity baseline for a new program on marine biodiversity, the Canadian Healthy Ocean Network. A major effort needs to be undertaken to establish a complete baseline of Canadian marine biodiversity of all taxonomic groups, especially if we are to understand and conserve this part of Canada's natural heritage