1001. CRISPR/Cas-mediated plant genome editing : outstanding challenges a decade after implementationTeodoro Cardi, Jana Murovec, Allah Bakhsh, Vladislava Galović, Tjaša Lukan, Kubilay Yıldırım, Milica Zlatković, Katrijn Van Laere, 2023, review article Abstract: The discovery of the CRISPR/Cas genome-editing system has revolutionized our understanding of the plant genome. CRISPR/Cas has been used for over a decade to modify plant genomes for the study of specific genes and biosynthetic pathways as well as to speed up breeding in many plant species, including both model and non-model crops. Although the CRISPR/Cas system is very efficient for genome editing, many bottlenecks and challenges slow down further improvement and applications. In this review we discuss the challenges that can occur during tissue culture, transformation, regeneration, and mutant detection. We also review the opportunities provided by new CRISPR platforms and specific applications related to gene regulation, abiotic and biotic stress response improvement, and de novo domestication of plants.
Keywords: CRISPR applications, CRISPR platforms, gene regulations, mutant detection, plant regeneration
Published in DiRROS: 05.08.2024; Views: 306; Downloads: 283
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1002. The importance of population contextual data for large-scale biomonitoring using an apex predator : the Tawny Owl (Strix aluco)Urška Ratajc, Rui Lourenço, Silvia Espín, Pablo Sánchez Virosta, Simon Birrer, Dani Studler, Chris Wernham, Al Vrezec, 2023, review article Abstract: Top predators are often used as sentinel species in contaminant monitoring due to their exposure and vulnerability to persistent, bioaccumulative and, in some cases, biomagnificable contaminants. Some of their ecological traits can vary in space and time, and are known to influence the contamination levels and therefore information on ecological traits should be used as contextual data for correct interpretation of large-scale contaminant spatial patterns. These traits can explain spatiotemporal variation in contaminant exposure (traits such as diet and dispersal distances) or contaminant impacts (traits such as population trend and clutch size). The aim of our research was to review the spatial variation in selected contextual parameters in the Tawny Owl (Strix aluco), a species identified by the COST Action European Raptor Biomonitoring Facility as one of the most suitable candidates for pan-European biomonitoring. A considerable variation in availability of published and unpublished contextual data across Europe was found, with diet being the most extensively studied trait. We demonstrate that the Tawny Owl is a suitable biomonitor at local scale but also that taking spatial variation of other contextual data (e.g. diet) into account is necessary. We found spatial gaps in knowledge about the species ecology and biology in Southern Europe, along with gaps in certain population parameters (e.g. population trends) in several countries. Based on our findings, we proposed a minimal recommended scheme for monitoring of population contextual data as one of the first steps towards a pan-European monitoring scheme using the Tawny Owl.
Keywords: raptors, sentinel species, contamination exposure, contamination impact, diet, minimal recommended monitoring scheme
Published in DiRROS: 05.08.2024; Views: 323; Downloads: 245
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1003. DELWAVE 1.0 : deep learning surrogate model of surface wave climate in the Adriatic BasinPeter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, Matjaž Ličer, 2024, original scientific article Abstract: We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the behaviour of a numerical surface ocean wave model (Simulating WAves Nearshore, SWAN) at a sparse set of locations, thus enabling numerically cheap large-ensemble prediction over synoptic to climate timescales. DELWAVE was trained on COSMO-CLM (Climate Limited-area Model) and SWAN input data during the period of 1971–1998, tested during 1998–2000, and cross-evaluated over the far-future climate time window of 2071–2100. It is constructed from a convolutional atmospheric encoder block, followed by a temporal collapse block and, finally, a regression block. DELWAVE reproduces SWAN model significant wave heights with a mean absolute error (MAE) of between 5 and 10 cm, mean wave directions with a MAE of 10–25°, and a mean wave period with a MAE of 0.2 s. DELWAVE is able to accurately emulate multi-modal mean wave direction distributions related to dominant wind regimes in the basin. We use wave power analysis from linearised wave theory to explain prediction errors in the long-period limit during southeasterly conditions. We present a storm analysis of DELWAVE, employing threshold-based metrics of precision and recall to show that DELWAVE reaches a very high score (both metrics over 95 %) of storm detection. SWAN and DELWAVE time series are compared to each other in the end-of-century scenario (2071–2100) and compared to the control conditions in the 1971–2000 period. Good agreement between DELWAVE and SWAN is found when considering climatological statistics, with a small (≤ 5 %), though systematic, underestimate of 99th-percentile values. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Keywords: surrogate modelling, deep learning, DEep Learning WAVe Emulating model, DELWAVE, Simulating WAves Nearshore, SWAN
Published in DiRROS: 05.08.2024; Views: 308; Downloads: 212
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1004. From the sea to aquafeed : a perspective overviewOrhan Tufan Eroldogan, Brett Glencross, Lucie Novoveská, Susana P. Gaudêncio, Buki Rinkevich, Giovanna Cristina Varese, Maria F. Carvalho, Deniz Tasdemir, Ivo Safarik, Soren Laurentius Nielsen, Céline Rebours, Lada Lukić-Bilela, Johan Robbens, Evita Strode, Berat Z. Haznedaroglu, Marlen I. Vasquez, Ivana Čabarkapa, Slađana Rakita, Katja Klun, Ana Rotter, 2023, review article Abstract: Aquaculture has been one of the fastest-growing food production systems sectors for over three decades. With its growth, the demand for alternative, cheaper and high-quality feed ingredients is also increasing. Innovation investments on providing new functional feed alternatives have yielded several viable alternative raw materials. Considering all the current feed ingredients, their circular adaption in the aquafeed manufacturing industry is clearly of the utmost importance to achieve sustainable aquaculture in the near future. The use of terrestrial plant materials and animal by-products predominantly used in aquafeed ingredients puts a heavily reliance on terrestrial agroecosystems, which also has its own sustainability concerns. Therefore, the aquafeed industry needs to progress with functional and sustainable alternative raw materials for feed that must be more resilient and consistent, considering a circular perspective. In this review, we assess the current trends in using various marine organisms, ranging from microorganisms (including fungi, thraustochytrids, microalgae and bacteria) to macroalgae and macroinvertebrates as viable biological feed resources. This review focuses on the trend of circular use of resources and the development of new value chains. In this, we present a perspective of promoting novel circular economy value chains that promote the re-use of biological resources as valuable feed ingredients. Thus, we highlight some potentially important marine-derived resources that deserve further investigations for improving or addressing circular aquaculture.
Published in DiRROS: 05.08.2024; Views: 336; Downloads: 280
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1005. Computerized cognitive training in the older workforce : effects on cognition, life satisfaction, and productivityZdenka Milič Žepič, Voyko Kavcic, Bruno Giordani, Uroš Marušič, 2024, original scientific article Abstract: Background: The accelerated aging of the world’s population will lead to an increase in the number of older people in the workforce. Computerized Cognitive Training (CCT) is effective in improving cognitive outcomes, but its benefits for older workers remain controversial. We investigate the real-world efficacy of CCT in the workplace, focusing on employees aged 50+ years from a public sector agency. Methods: Case managers (n = 82) were randomized to either an intervention group (24 40 min CCT sessions two times per week) or a waiting list passive control group. Cognitive ability, well-being, job satisfaction, and productivity outcome measures were collected and assessed before and after CCT or the comparable control wait time. Results: Participants undergoing CCT improved on a task of executive functioning (p = 0.04). There was a trend toward a change in work productivity after CCT (p = 0.09), with the control group showing a significant decrease (p = 0.02), while the intervention group remained stable. Conclusions: CCT during office hours has a positive effect on cognition and well-being without affecting productivity among white-collar office workers. CCT could be considered as an intervention to support the older workforce in managing the cognitive and behavioral challenges of changing workplace demands.
Keywords: older employees, 50+, computerized cognitive training (CCT), productivity, well-being
Published in DiRROS: 05.08.2024; Views: 352; Downloads: 355
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1006. Adjusting the operational potential window as a tool for prolonging the durability of carbon-supported Pt-alloy nanoparticles as oxygen reduction reaction electrocatalystsTina Đukić, Leonard Moriau, Iva Klofutar, Martin Šala, Luka Pavko, Francisco Javier Gonzalez Lopez, Francisco Ruiz-Zepeda, Andraž Pavlišič, Miha Hotko, Matija Gatalo, Nejc Hodnik, 2024, original scientific article Published in DiRROS: 05.08.2024; Views: 419; Downloads: 248
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1007. Sequestration of membrane cholesterol by cholesterol-binding proteins inhibits SARS-CoV-2 entry into Vero E6 cellsMagdalena Kulma, Aleksandra Šakanović, Apolonija Bedina Zavec, Simon Caserman, Neža Omersa, Gašper Šolinc, Sara Orehek, Iva Hafner Bratkovič, Urška Kuhar, Brigita Slavec, Uroš Krapež, Matjaž Ocepek, Toshihide Kobayashi, Katarzyna Kwiatkowska, Roman Jerala, Marjetka Podobnik, Gregor Anderluh, 2024, original scientific article Published in DiRROS: 05.08.2024; Views: 375; Downloads: 239
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1008. First contribution to the knowledge of coralline algae distribution in the Slovenian circalittoral zone (northern Adriatic)Annalisa Falace, Sara Kaleb, Martina Orlando-Bonaca, Borut Mavrič, Lovrenc Lipej, 2011, original scientific article Abstract: Authors present new data on the coralline algal flora from Slovenia. They come from recent inspection of the Slovenian part of the Gulf of Trieste where peculiar communities, such as the biocoenosis of the coastal detritic bottom, the agglomeration of bioconcretions known in the area under the name of "trezze" or "tengue", and the bank of Mediterranean stony coral Cladocora caespitosa, occur. In such communities 11 coralligenous red algae were found. Five of them, Hydrolithon boreale, Lithothamnion minervae, L. philippii, L. sonderi and Neogoniolithon brassica-florida are newly recorded for Slovenia.
Keywords: coralline algae, Cladocora caespitosa, circalittoral, northern Adriatic, Slovenia
Published in DiRROS: 05.08.2024; Views: 336; Downloads: 228
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1009. CD133/prominin1 is prognostic for GBM patient's survival, but inversely correlated with cysteine cathepsine' expression in gliobastoma derived spheroidsSeyed Yousef Ardebili, Irena Zajc, Boris Gole, Benito Campos, Christel Herold-Mende, Sara Drmota Prebil, Tamara Lah Turnšek, 2011, original scientific article Abstract: Introduction. CD133 is a marker for a population of glioblastoma (GBM) and normal neural stem cells (NNSC). We aimed to reveal whether the migratory potential and differentiation of these stem cells is associated with CD133 expression and with cathepsin proteases (Cats).
Materials and methods. The invasiveness of normal NNSC, GBM/CD133+ cell lines and GBM spheroids was evaluated in 3D collagen, as well as of U87-MG and normal astrocytes (NHA) grown in monolayers in 2D Matrigel. Expression of Cats B, L and S was measured at mRNA and activity levels and their relation to invasiveness, to CD133 mRNA in 26 gliomas, and to the survival of these patients.
Results. The average yield of CD133+ cells from GBM samples was 9.6%. Survival of patients with higher CD133 mRNA expression was significantly shorter (p< 0.005). Invasion, associated with proteolytic degradation of matrix, was higher in normal stem cells and GBM spheroids and cells than in isolated GBM CD133+ cells. In glioma samples, there was no correlation between CD133 mRNA expression and Cat mRNAs, but there was an inverse correlation with Cat activities.
Conclusions. The study confirms CD133 as a prognostic marker for the survival of GBM patients. We demonstrated that NNSC have higher invasion potential and invade the collagen matrix in a mode different from that of GBM, initiating stem cell spheres. This result could have implications for the design of new therapeutics, including protease inhibitors that specifically target invasive tumour stem cells. Increased activity of cathepsins in CD133- cells suggests their role in the invasive behaviour of GBM.
Published in DiRROS: 05.08.2024; Views: 316; Downloads: 161
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1010. SegMine workflows for semantic microarray data analysis in Orange4WSVid Podpečan, Nada Lavrač, Igor Mozetič, Petra Kralj Novak, Igor Trajkovski, Laura Langohr, Kimmo Kulovesi, Hannu Toivonen, Marko Petek, Helena Motaln, Kristina Gruden, 2011, original scientific article Abstract: Background
In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets.
Results
We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes.
Conclusions
Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.
Published in DiRROS: 05.08.2024; Views: 369; Downloads: 228
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