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Erratum to: The sponge microbiome project
Moitinho-Silva, Lucas ; Nielsen, Shaun ; Amir, Amnon ; Gonzalez, Antonio ; Ackermann, Gail L. ; Cerrano, Carlo ; Astudillo-Garcia, Carmen ; Easson, Cole ; Sipkema, Detmer ; Liu, Fang ; Steinert, Georg ; Kotoulas, Giorgos ; McCormack, Grace P. ; Feng, Guofang ; Bell, James J. ; Vicente, Jan ; Björk, Johannes R. ; Montoya, Jose M. ; Olson, Julie B. ; Reveillaud, Julie ; Steindler, Laura ; Pineda, Mari Carmen ; Marra, Maria V. ; Ilan, Micha ; Taylor, Michael W. ; Polymenakou, Paraskevi ; Erwin, Patrick M. ; Schupp, Peter J. ; Simister, Rachel L. ; Knight, Rob ; Thacker, Robert W. ; Costa, Rodrigo ; Hill, Russell T. ; Lopez-Legentil, Susanna ; Dailianis, Thanos ; Ravasi, Timothy ; Hentschel, Ute ; Li, Zhiyong ; Webster, Nicole S. ; Thomas, Torsten - \ 2018
GigaScience 7 (2018)12. - ISSN 2047-217X
microRNA 193a-5p Regulates Levels of Nucleolar- and Spindle-associated Protein 1 to Suppress Hepatocarcinogenesis
Roy, Sanchari ; Hooiveld, Guido J. ; Seehawer, Marco ; Caruso, Stefano ; Heinzmann, Florian ; Schneider, Anne T. ; Frank, Anna K. ; Cardenas, David Vargas ; Sonntag, Roland ; Luedde, Mark ; Trautwein, Christian ; Stein, Ilan ; Pikarsky, Eli ; Loosen, Sven ; Tacke, Frank ; Ringelhan, Marc ; Avsaroglu, Seda Kilinc ; Goga, Andrei ; Buendia, Marie-Annick ; Vucur, Mihael ; Heikenwalder, Mathias ; Zucman-Rossi, Jessica ; Zender, Lars ; Roderburg, Christoph ; Luedde, Tom - \ 2018
Gastroenterology 155 (2018)6. - ISSN 0016-5085 - p. 1951 - 1966.
Background & Aims: We performed an integrated analysis to identify microRNAs (miRNAs) and mRNAs with altered expression in liver tumors from 3 mouse models of hepatocellular carcinoma (HCC) and human tumor tissues. Methods: We analyzed miRNA and mRNA expression profiles of liver tissues from mice with diethylnitrosamine-induced hepatocarcinogenesis, conditional expression of lymphotoxin alpha and lymphotoxin beta , or inducible expression of a Myc transgene (Tet-O-Myc mice), as well as male C57BL/6 mice (controls). miRNA mimics were expressed and miRNAs and mRNAs were knocked down in human (Huh7, Hep3B, JHH2) hepatoma cell lines; cells were analyzed for viability, proliferation, apoptosis, migration, and invasion. Cells were grown as xenograft tumors in nude mice and analyzed. We combined in-silico target gene prediction with mRNA profiles from all 3 mouse models. We quantified miRNA levels in 146 fresh-frozen tissues from patients (125 HCCs, 17 matched non-tumor tissues, and 4 liver samples from patients without cancer) and published human data sets and tested correlations with patient survival times using Kaplan-Meier curves and the log-rank test. Levels of NUSAP1 mRNA were quantified in 237 HCCs and 5 non-tumor liver samples using the Taqman assay. Results: Levels of the microRNA 193a-5p (MIR193A-5p) were reduced in liver tumors from all 3 mouse tumor models and in human HCC samples, compared with non-tumor liver tissues. Expression of a MIR193A-5p mimic in hepatoma cells reduced proliferation, survival, migration, and invasion and their growth as xenograft tumors in nude mice. We found nucleolar and spindle associated protein 1 (NUSAP1) to be a target of MIR193A-5p; HCC cells and tissues with low levels of MIR193A-5p had increased expression of NUSAP1. Increased levels of NUSAP1 in HCC samples correlated with shorter survival times of patients. Knockdown of NUSAP1 in Huh7 cells reduced proliferation, survival, migration, and growth as xenograft tumors in nude mice. Hydrodynamic tail-vein injections of a small hairpin RNA against NUSAP1 reduced growth of AKT1-MYC–induced tumors in mice. Conclusions: MIR193A-5p appears to prevent liver tumorigenesis by reducing levels of NUSAP1. Levels of MIR193A-5p are reduced in mouse and human HCC cells and tissues, leading to increased levels of NUSAP1, associated with shorter survival times of patients. Integrated analyses of miRNAs and mRNAs in tumors from mouse models can lead to identification of therapeutic targets in humans.
Implementation of an automatic 3D vision monitor for dairy cow locomotion in a commercial farm
Hertem, Tom Van; Schlageter Tello, Andrés ; Viazzi, Stefano ; Steensels, Machteld ; Bahr, Claudia ; Romanini, Carlos Eduardo Bites ; Lokhorst, Kees ; Maltz, Ephraim ; Halachmi, Ilan ; Berckmans, Daniel - \ 2018
Biosystems Engineering 173 (2018). - ISSN 1537-5110 - p. 166 - 175.
Automated monitoring - Back curvature - Computer vision - Cow traffic - Implementation
The objective of this study was to evaluate the system performance of a 3D vision system for automatic locomotion monitoring implemented in a commercial dairy farm. Data were gathered during 633 milking sessions on a Belgian commercial dairy farm. After milking, the cows walked in a single-lane alley where the video recording system with a 3D depth camera was installed. The entire monitoring process including video recording, video pre-processing by filtering, cow identification and video analysis was automated. Image processing extracted six feature variables from the recorded videos. Per milking session, 224 ± 10 cows (100%) were identified on average by a radio-frequency identification (RFID) antenna, and 197 ± 16 videos were recorded (88.1 ± 6.6%) by the camera. The cow identification number was merged automatically to a recorded video in 178 ± 14 videos (79.4 ± 5.5%). After video pre-processing and analysis, 110 ± 24 recorded cow-videos (49.3 ± 10.8%) per session resulted in an automatic locomotion score. Daily and cow-individual variations on the merging and analysis rate were due to cow traffic. The minimal cow traffic interval required between consecutive cows was 15 s for optimal merging. System performance was affected by lactation stage, parity of the cows and recording duration. The feature variables curvature angle of back around hip joints (Area Under the Receiver Operating Characteristics Curve (AUC) = 0.719) and back posture measurement (AUC = 0.702) could be considered as fair lameness classifiers. Cow traffic affected the success rate of the video processing. Therefore, automatic monitoring systems need to be adapted to the farm layout.
Parasites of Harmonia axyridis: current research and perspectives
Haelewaters, D. ; Zhao, S.Y. ; Clusella-Trullas, S. ; Cottrell, T.E. ; Kesel, A. De; Fiedler, L. ; Herz, A. ; Hesketh, H. ; Hui, C. ; Kleespies, R.G. ; Losey, J.E. ; Minnaar, I.A. ; Murray, K.M. ; Nedved, O. ; Pfliegler, Walter P. ; Raak-van den Berg, C.L. ; Riddick, E.W. ; Shapiro-Ilan, D.I. ; Smyth, R.R. ; Steenberg, T. ; Wielink, P.S. van; Viglasova, S. ; Zhao, Z. ; Ceryngier, P. ; Roy, H.E. - \ 2017
BioControl 62 (2017)3. - ISSN 1386-6141 - p. 355 - 371.
Harmonia axyridis (Coleoptera: Coccinellidae) has been introduced widely for biological control of agricultural pests. Harmonia axyridis has established in four continents outside of its native range in Asia and it is considered an invasive alien species (IAS). Despite a large body of work on invasion ecology, establishment mechanisms of IAS and their interactions with natural enemies remain open questions. Parasites, defined as multicellular organisms that do not directly kill the host, could potentially play an important role in regulating host populations. This study presents a review of the parasites of H. axyridis, discussing their distributions and effects on host populations across the host’s native and invasive range. These parasites are: Hesperomyces virescens Thaxt. fungi, Coccipolipus hippodamiae (McDaniel and Morrill) mites, and Parasitylenchus bifurcatus Poinar and Steenberg nematodes.
The sponge microbiome project
Moitinho-Silva, Lucas ; Nielsen, Shaun ; Amir, Amnon ; Gonzalez, Antonio ; Ackermann, Gail L. ; Cerrano, Carlo ; Astudillo-Garcia, Carmen ; Easson, Cole ; Sipkema, Detmer ; Liu, Fang ; Steinert, Georg ; Kotoulas, Giorgos ; McCormack, Grace P. ; Feng, Guofang ; Bell, James J. ; Vicente, Jan ; Björk, Johannes R. ; Montoya, Jose M. ; Olson, Julie B. ; Reveillaud, Julie ; Steindler, Laura ; Pineda, Mari Carmen ; Marra, Maria V. ; Ilan, Micha ; Taylor, Michael W. ; Polymenakou, Paraskevi ; Erwin, Patrick M. ; Schupp, Peter J. ; Simister, Rachel L. ; Knight, Rob ; Thacker, Robert W. ; Costa, Rodrigo ; Hill, Russell T. ; Lopez-Legentil, Susanna ; Dailianis, Thanos ; Ravasi, Timothy ; Hentschel, Ute ; Li, Zhiyong ; Webster, Nicole S. ; Thomas, Torsten - \ 2017
GigaScience 6 (2017)10. - ISSN 2047-217X
16S rRNA gene - Archaea - Bacteria - Marine sponges - Microbial diversity - Microbiome - Symbiosis
Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere.
Local expert experiences and perceptions of environmentally induced migration from Bangladesh to India
Stojanov, Robert ; Boas, Ingrid ; Kelman, Ilan ; Duží, Barbora - \ 2017
Asia Pacific Viewpoint 58 (2017)3. - ISSN 1360-7456 - p. 347 - 361.
Bangladesh - Climate change - India - Migration - Perception
This study investigates local expert perceptions of the role of environmental factors, especially in terms of contemporary climate change, in population movements from Bangladesh to India. The aim is to delve into locally held understandings of the phenomenon and to gain a better understanding of these migration processes, which are actively intertwined with local experiences. Both Indian and Bangladeshi experts were interviewed using semi-structured, in-depth interviews in order to explore insights from locally held perceptions and understandings of contextual factors. In total, 10 Bangladeshi and 15 Indian experts were interviewed, covering different disciplines, sectors, regions and job types, together providing a more complete and grounded picture of views of environmentally induced migration in Bangladesh and India. The results show that climate change is perceived by local experts as one of the key factors influencing migration in Bangladesh, both internally and externally. The interviewees, however, placed environmentally induced migration in a broader context of labour and economic migration. In particular, migration for environmental reasons in Bangladesh was evident long before the emergence of climate change as an issue. According to the interviewed experts, this does not preclude increased environmentally induced migration within and from Bangladesh in the future, but its analyses ought to be placed in historical and economical contexts.
Use of sensor systems on Dutch dairy farms
Steeneveld, W. ; Hogeveen, H. - \ 2015
In: Precision Livestock Farming Applications / Halachmi, Ilan, Wageningen Academic Publishers - ISBN 9789086862689 - p. 77 - 86.
A survey was developed to investigate the reasons for investing or not in sensor systems on dairy farms, and to investigate how sensor systems are used in daily cow management. This survey was sent to 1,672 Dutch dairy farmers. The final dataset consisted of 512 dairy farms (response rate of 30.6%); 202 farms indicated that they have one or more sensor systems and 310 farms indicated that they do not have any sensor systems. In total, for 95 dairy farms with oestrus detection sensor systems, information about the average calving interval for the years 2003 to 2013 was available. In addition, for 30 dairy farms with oestrus detection sensor systems for young stock, information about the average first calving age was available for the years 2003 to 2013. The most common sensors on farms with an automatic milking system are sensor systems to measure the colour and electrical conductivity of milk. In total, 41% of farms with an automatic milking system had activity meters/pedometers for dairy cows, and 70% of farms with a conventional milking system and sensor systems also had activity meters/pedometers for dairy cows. The main reasons for investing in activity meters/pedometers for dairy cows were to improve detection, improve the profitability of the farm and to gain insight into the fertility level of the farm. The most important reasons for not investing in sensor systems were economic. Having an oestrus detection sensor system was not linked with the average calving interval of the farm. Furthermore, having an oestrus detection sensor system for young stock was not linked with the average first calving age. These results suggest that the farmers use the same rules on when to start inseminating as without oestrus detection sensor systems, and as a result there is no change in first calving age and calving interval.
Economic Modelling to evaluate the benefits of precision livestock
Kamphuis, C. ; Steeneveld, W. ; Hogeveen, H. - \ 2015
In: Precision Livestock Farming Applications / Halachmi, Ilan, Wageningen : Wageningen Academic Publishers - ISBN 9789086862689 - p. 87 - 94.
‘Precision Livestock Farming’ (PLF) technology is an emerging research field which develops management tools aimed at continuous automatic monitoring of animal production, including real-time monitoring of growth, health and welfare. The purpose of PLF is to support farmers in making daily management decisions by providing extra ‘senses’, and to make farmers less dependent on human labour. Many PLF concepts have been developed in recent years, but the uptake of most of these technologies on commercial farms has been slow. Reasons for this slow uptake include the fact that these PLF technologies generate substantial amounts of data but this data is not converted into useful information for decision management. Another reason is that the investment in PLF technologies can be significant, whereas the economic benefits of the investment are unknown. Insight into the on-farm economics of PLF is therefore important. The objective of the study was to develop a value creation tool that models the economic impact of PLF technologies on dairy, fattening pig and broiler farms. The tool uses technical parameters, and the economic impact of PLF implementation can be estimated at farm level by estimating the impact of PLF technologies on these technical parameters. Twenty key global suppliers of PLF technologies were approached in order to gain insight into their views on which of these technical parameters are affected by their PLF technology and to what extent. The knowledge acquired will be used to validate the tool and to gain insight into the costs and benefits of PLF technologies. This current paper specifically reports on the value creation tool developed for dairy farms. Automated heat detection (Nedap N.V., Groenlo, the Netherlands) is used to demonstrate how this tool works and to calculate the potential added value of this PLF technology. The value creation tool will assist, ultimately, in the development of PLF technologies that add value to onfarm decision-making processes.
The potential of using sensor data to predict the moment of calving for dairy cows
Rutten, C.J. ; Steeneveld, W. ; Kamphuis, C. ; Huijps, K. ; Hogeveen, H. - \ 2015
In: Precision Livestock Farming Applications / Halachmi, Ilan, Wageningen : Wageningen Academic Publishers - ISBN 9789086862689 - p. 161 - 167.
On dairy farms, management of calving is important for the health of dairy cows and the survival rate of calves born. Although an expected calving date is known, farmers need to check their cows regularly to estimate the moment when a cow will start calving. A sensor system which predicts the moment of calving could help farmers to check cows effectively for the occurrence of dystocia. In this study, a total of 450 cows on two farms were equipped with Agis SensOor sensors (Agis Automatisering B.V., Harmelen, the Netherlands), which measure rumination activity, activity and temperature hourly. Data were collected over a one-year period. During that period, the exact moment of 417 calvings was recorded using camera images of the calving pen taken every 5 minutes. In total 110 calvings could be linked with sensor data. The moment when calving started was defined as the hour in which the camera images showed the cow having contractions or labour initially started. Two logit models were developed: a reduced model with the expected calving date as the independent variable and a full model which additionally included independent variables based on sensor data. The areas under the Receiver Operating Characteristic curves were 0.682 and 0.878 for the reduced and full model with, at a false positive rate of 10%, sensitivities of 22 and 69%, respectively. Results indicated that the inclusion of sensor data improved prediction of the start of calving and thus that the sensor data used have some potential for predicting the moment of calving.
Evaluating progesterone profiles to improve automated oestrus detection
Kamphuis, C. ; Huijps, K. ; Hogeveen, H. - \ 2015
In: Precision Livestock Farming Applications / Halachmi, Ilan, Wageningen Academic Publishers - ISBN 9789086862689 - p. 279 - 285.
Adoption of automated heat detection technologies is increasingly popular in the dairy industry. Generally speaking, farmers invest in only one technology on the assumption that this system will find most, if not all, cows in heat. It is, however, known that these technologies do not find all cows in heat. It has been suggested that automated heat detection may improve when sensor data are combined, where this involves combining different sensor measurements, e.g. linking activity with rumination data. So far, the option of combining different technologies has not been studied for the obvious reason that no commercial farms are using technologies from several suppliers. The Smart Dairy Farming (SDF) project, a Dutch initiative, brings together technology providers, knowledge institutions and dairy farms to improve the longevity of dairy cows by developing innovative tools to improve animal health, reproduction and feeding strategies. The SDF project offers a unique opportunity to research whether combining different sensing technologies improves automated heat detection. To do this, progesterone profiles were created by daily measurement of progesterone in milk from 31 cows, over a 24-day period, at two farms participating in the SDF project. One automated heat detection technology is used on both farms, and each farm has a second, different, technology running simultaneously. Heat alerts generated and farmers’ observations were compared with progesterone profiles. The data were used to provide insight into the following issues: do heat detection technologies provide alerts for cows in heat; when do they alert for heat events; how do farmers use the information from the heat detection technologies; and whether the exact timing of true heat may be improved by combining heat alerts. Finally, possible explanations will be studied for those heat events that remain undetected by both oestrus detection systems and farmers’ observations.
Insects as food for insectivores
Finke, M.D. ; Oonincx, D.G.A.B. - \ 2014
In: Mass Production of Beneficial Organisms : Invertebrates and Entomopathogens / Shapiro-Ilan Morales-Ramos, J., Rojas, G., Shapiro-Ilan, D.I., Academic Press - ISBN 9780123914538 - p. 583 - 616.
A variety of insects are commonly fed to captive insectivores. We review the nutrient content of a variety of commercially raised insects and compare those values to the data available for wild insects. These data are discussed in light of the nutrient requirements for domestic animals to identify nutrients of concern for captive insectivores. Additionally, various environmental and dietary factors that can significantly affect insect nutrient composition are reviewed. We then evaluate the various techniques that are currently used to enhance the nutrient content of commercially bred insects, including gut loading and dusting. Lastly, possible negative considerations that might be important factors when feeding captive insectivores, including pathogens, pathogenic microorganisms, toxins, and antinutritional factors, are discussed.
|Production of Entomopathogenic Viruses
Reid, S. ; Chan, L. ; Oers, M.M. van - \ 2014
In: Mass Production of Beneficial Organisms / Morales-Ramos, J.A., Rojas, M.G., Shapiro-Ilan, David, Amsterdam : Elsevier - ISBN 9780123914538 - p. 437 - 482.
|Structure and interactions between adsorbed layers of block copolymers.
Scheutjens, J.M.H.M. ; Fleer, G.J. - \ 1988
In: Abstract Int. Symp. Surface interactions, Neve Ilan, Israel - p. 18 - 18.