Efecto del fotoperiodo sobre la calidad comercial de plantas de Althaea rosea obtenidas a partir de germoplasma elite

157-161Althaea rosea has little spread in Buenos Aires despite of its decorative value. Starting from seeds of wild plants and after 3 cycles of selection, we have obtained germplasm with good behavior in pots. With the aim of disseminating A rosea, we faced tests in pots, with the objective of estimating photoperiod effects on commercial quality of the elite germ plasm obtained. The plants that received 16 h of light showed less number of days until the appearance of the first bud than those receiving natural light. This result is interesting because it indicates that the first ones could arrive early for sale. Differences were also found for petal length and area in plants with 16 h photoperiod, its showed larger flowers and wider petals than tended to overlap when they were compared with those observed in the flowers of plants that received natural light. The plans treated with long photoperiod exhibited less variation coefficient for the measured values, allowing the conclusion that light supplementation is an effective tool to focus the sale and increase quality of A. rosea potted plants

Efecto del fotoperiodo sobre la calidad comercial de plantas de Althaea rosea obtenidas a partir de germoplasma elite

157-161Althaea rosea has little spread in Buenos Aires despite of its decorative value. Starting from seeds of wild plants and after 3 cycles of selection, we have obtained germplasm with good behavior in pots. With the aim of disseminating A rosea, we faced tests in pots, with the objective of estimating photoperiod effects on commercial quality of the elite germ plasm obtained. The plants that received 16 h of light showed less number of days until the appearance of the first bud than those receiving natural light. This result is interesting because it indicates that the first ones could arrive early for sale. Differences were also found for petal length and area in plants with 16 h photoperiod, its showed larger flowers and wider petals than tended to overlap when they were compared with those observed in the flowers of plants that received natural light. The plans treated with long photoperiod exhibited less variation coefficient for the measured values, allowing the conclusion that light supplementation is an effective tool to focus the sale and increase quality of A. rosea potted plants

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets

Antibiotic resistance genes in treated wastewater and in the receiving water bodies: a pan-European survey of urban settings

There is increasing public concern regarding the fate of antibiotic resistance genes (ARGs) during wastewater treatment, their persistence during the treatment process and their potential impacts on the receiving water bodies. In this study, we used quantitative PCR (qPCR) to determine the abundance of nine ARGs and a class 1 integron associated integrase gene in 16 wastewater treatment plant (WWTP) effluents from ten different European countries. In order to assess the impact on the receiving water bodies, gene abundances in the latter were also analysed. Six out of the nine ARGs analysed were detected in all effluent and river water samples. Among the quantified genes, intI1 and sul1 were the most abundant. Our results demonstrate that European WWTP contribute to the enrichment of the resistome in the receiving water bodies with the particular impact being dependent on the effluent load and local hydrological conditions. The ARGs concentrations in WWTP effluents were found to be inversely correlated to the number of implemented biological treatment steps, indicating a possible option for WWTP management. Furthermore, this study has identified bla as a possible resistance gene for future studies investigating the impact of WWTPs on their receiving water. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

The distributed p-median problem in computer networks

Many distributed services in computer networks rely on a set of active facilities that are selected among a potentially large number of candidates. The active facilities then contribute and cooperate to deliver a specific service to the users of the distributed system. In this scenario graph partitioning or clustering is often adopted to determine the most efficient locations of the facilities. The identification of the optimal set of facility locations is known as the p-median problem in networks, is NP-hard and is typically solved by using heuristic methods. The goal is to select p locations among all candidate network nodes such that some cost function is minimised. A typical example of such a function is the overall communication cost to deliver the service to the users of the distributed system. Locating facilities in near-optimal locations has been extensively studied for different application domains. Most of these studies have investigated sequential algorithms and centralised approaches. However, centralised approaches are practically infeasible in large-scale and dynamic networks, where the problem is inherently distributed or because of the large communication overhead and memory requirements for gathering complete information about the network topology and the users. In this work distributed approaches to the p-median problem are investigated. Two solutions are proposed for addressing the facility locations problem in a fully distributed environment. Two different iterative heuristic approaches are applied to gradually improve a random initial solution and to converge to a final solution with a local minimum of the overall cost. While the first approach adopts a fine granularity by identifying a single change to improve the solution at each iteration, the second approach applies changes to every component of the solution at each iteration. An experimental comparative analysis based on simulations has shown that the approach with a finer granularity is able to deliver a better optimisation of the overall cost with longer convergence time. Both approaches have excellent scalability and provide an effective tool to optimise the facility locations from within the network. No prior knowledge of the system is required, no data needs to be gathered in a centralised server and the same process is used to identify and to deploy the facility locations solution in the network since the process is fully decentralised

Intervention Services for Autistic Adults: An ASDEU Study of Autistic Adults, Carers, and Professionals' Experiences

The Autism Spectrum Disorders in the European Union (ASDEU) survey investigated local services' use experiences of autistic adults, carers and professionals with interventions for autistic adults. The majority of the 697 participants experienced recommended considerations prior to deciding on intervention and during the intervention plan and implementation. Psychosocial interventions were the most commonly experienced interventions, while pharmacological interventions NOT recommended for core autistic symptoms were reported by fairly large proportions of participants. Family interventions were experienced slightly more commonly by carers than adults or professionals. Less than the 26% of autistic adult responders who had experienced challenging behaviors reported receiving an intervention to change them. These results provide insights for improving gaps in service provision of interventions among autistic adults.Peer reviewe

MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants

Microbial communities are responsible for biological wastewater treatment, but our knowledge of their diversity and function is still poor. Here, we sequence more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and use the sequences to construct the ‘MiDAS 4’ database. MiDAS 4 is an amplicon sequence variant resolved, full-length 16S rRNA gene reference database with a comprehensive taxonomy from domain to species level for all sequences. We use an independent dataset (269 WWTPs) to show that MiDAS 4, compared to commonly used universal reference databases, provides a better coverage for WWTP bacteria and an improved rate of genus and species level classification. Taking advantage of MiDAS 4, we carry out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting regions of the 16S rRNA gene, revealing how environmental conditions and biogeography shape the activated sludge microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 966 genera and 1530 species that represent approximately 80% and 50% of the accumulated read abundance, respectively. Finally, we show that for well-studied functional guilds, such as nitrifiers or polyphosphate-accumulating organisms, the same genera are prevalent worldwide, with only a few abundant species in each genus

Making waves: collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making

The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE "SARS-CoV-2 in sewage" database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice. [Abstract copyright: Copyright © 2021 Elsevier Ltd. All rights reserved.

The NORMAN Association and the European Partnership for Chemicals Risk Assessment (PARC): let’s cooperate! [Commentary]

The Partnership for Chemicals Risk Assessment (PARC) is currently under development as a joint research and innovation programme to strengthen the scientific basis for chemical risk assessment in the EU. The plan is to bring chemical risk assessors and managers together with scientists to accelerate method development and the production of necessary data and knowledge, and to facilitate the transition to next-generation evidence-based risk assessment, a non-toxic environment and the European Green Deal. The NORMAN Network is an independent, well-established and competent network of more than 80 organisations in the field of emerging substances and has enormous potential to contribute to the implementation of the PARC partnership. NORMAN stands ready to provide expert advice to PARC, drawing on its long experience in the development, harmonisation and testing of advanced tools in relation to chemicals of emerging concern and in support of a European Early Warning System to unravel the risks of contaminants of emerging concern (CECs) and close the gap between research and innovation and regulatory processes. In this commentary we highlight the tools developed by NORMAN that we consider most relevant to supporting the PARC initiative: (i) joint data space and cutting-edge research tools for risk assessment of contaminants of emerging concern; (ii) collaborative European framework to improve data quality and comparability; (iii) advanced data analysis tools for a European early warning system and (iv) support to national and European chemical risk assessment thanks to harnessing, combining and sharing evidence and expertise on CECs. By combining the extensive knowledge and experience of the NORMAN network with the financial and policy-related strengths of the PARC initiative, a large step towards the goal of a non-toxic environment can be taken