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The aquatic subterranean ecosystems represent research frontiers for ecology and conservation biology. The aquatic subterranean fauna and associated microorganisms are organised in food webs that are essential in the nutrients cycling and energy fluxes within habitats generally characterised by low resources. However, the knowledge of how these trophic networks are structured and conditioned by the interaction with surface ecosystems is scarce. Traditionally, subterranean aquatic food webs were regarded as simple and truncated because of low species diversity and abundance compared to surface. The current review provides an updated description of aquatic subterranean food webs, based on the latest findings from various types of habitats: cave streams, the hyporheic zone and phreatic aquifers, with the general conclusion that such trophic networks are much more complex and dynamic as historically believed. The energylimitation hypothesis and the bottom-up forces are increasingly recognised as the main structuring agents of the aquatic subterranean trophic networks. It is predicted that the bottom-up forces are generated by two interconnected factors: nutrients availability in water and quantity, quality and the types (i.e. surface derived photosynthetic and detrital, in some cases mixed with in situ chemosynthetically based organic matter) of basal energy input. Further recommendations for the integration of groundwater research into the current overarching concepts of surface ecology are made, given this field of science remains currently rather descriptive and less hypothesis-driven.

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The current paper estimated the physico-chemical properties of water in the Danube Delta (Romania), based on Sentinel 2 remote sensing data. Eleven sites from the Danube Delta were sampled in spring and autumn for three years (2018-2020) and 21 water physico-chemical parameters were measured in laboratory. Several families of machine learning algorithms, translated into hundreds of models with different parameterizations for each machine learning algorithm, based on remote sensing data input from Sentinel 2 spectral bands, were employed to find the best models that predicted the values measured in laboratory. This was a novel approach, reflected in the types of selected models that minimised the values of performance metrics for the tested parameters. For alkalinity, calcium, chloride, carbon dioxide, hardness, potassium, sodium, ammonium, dissolved oxygen, sulphates, and suspended matter the results were promising, with an overall percentage bias of the estimates of +/- 10% from the observed values. For copper, magnesium, nitrites, nitrates, turbidity and zinc the estimates were fairly accurate, with percentage biases in the interval +/- 10% - 20%, whereas for detergents, led, and phosphates the percentage bias was higher than 20%. Overall, the results of the current study showed fairly good estimates between remote sensing based estimates and laboratory measured values for most water physico-chemical parameters.

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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

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Impact on aquatic ecosystems from intensive agriculture can be mitigated through a variety of structural and management conservation practices. This article provides an overview of the main Best Management Practices (BMP) for reducing direct or indirect detrimental impact from agriculture on inland waters’ quality and ecological status. The BMP's have been shown to be more efficient compared to conventional ones and comprise a set of recommendations that should be considered carefully by environmental scientists, stakeholders, farmers and land-owners alike. © 2022 Elsevier Inc. All rights reserved

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Current advances in computational modelling and simulation have led to the inclusion of computer scientists as partners in the process of engineering of new nanomaterials and nanodevices. This trend is now, more than ever, visible in the field of deoxyribonucleic acid (DNA)-based nanotechnology, as DNA's intrinsic principle of self-assembly has been proven to be highly algorithmic and programmable. As a raw material, DNA is a rather unremarkable fabric. However, as a way to achieve patterns, dynamic behavior, or nano-shape reconstruction, DNA has been proven to be one of the most functional nanomaterials. It would thus be of great potential to pair up DNA's highly functional assembly characteristics with the mechanic properties of other well-known bio-nanomaterials, such as graphene, cellulos, or fibroin. In the current study, we perform projections regarding the structural properties of a fibril mesh (or filter) for which assembly would be guided by the controlled aggregation of DNA scaffold subunits. The formation of such a 2D fibril mesh structure is ensured by the mechanistic assembly properties borrowed from the DNA assembly apparatus. For generating inexpensive pre-experimental assessments regarding the efficiency of various assembly strategies, we introduced in this study a computational model for the simulation of fibril mesh assembly dynamical systems. Our approach was based on providing solutions towards two main circumstances. First, we created a functional computational model that is restrictive enough to be able to numerically simulate the controlled aggregation of up to 1000s of elementary fibril elements yet rich enough to provide actionable insides on the structural characteristics for the generated assembly. Second, we used the provided numerical model in order to generate projections regarding effective ways of manipulating one of the the key structural properties of such generated filters, namely the average size of the openings (gaps) within these meshes, also known as the filter's aperture. This work is a continuation of Amarioarei et al., 2018, where a preliminary version of this research was discussed.

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Subterranean streams represent unique heterotrophic ecosystems, usually supported by organic matter imported from the surface. Traditionally, the biological communities from subterranean streams were characterized as simple associations, with low diversity and species abundance, comprising mostly aquatic invertebrates connected by few trophic links compared with those of the surface. However, these features have not yet been described in the wider context of fluxes of energy and nutrients through food webs along a gradual switch from autotrophy (dominated by photosynthesis) towards heterotrophy (dominated by detritus) following the surface-subterranean continuum. Combining the most recent predictions of Ecological Stoichiometry and the Metabolic Theory of Ecology, this article provides a theoretical framework aiming to explain the patterns observed along the surface-subterranean continuum in streams. It is predicted that the main factors constraining the structure and functioning of communities and food webs are the decline in the quantity and diversity of basal resources along this gradient, along with nutrients availability in water that affects food quality. With increasing availability of dissolved nutrients in water, sinking-cave streams are hypothesized to fluctuate between being N and/ or P co-limited to C-limited. Combined, the quantity, quality, and diversity of basal resources regulate subterranean aquatic communities through bottom-up mechanisms, reflected in a decreased flux of macronutrients through food webs. The consequences of these bottom-up effects are decreased abundance, biomass, secondary production, consumption rate, and mean body size of communities, together with potential increases in the elemental imbalance for macronutrients, omnivory, trophic position, and niche width and overlap among aquatic consumers along the surface-subterranean continuum. The bottom-up effects induce changes in the topology of stream food webs, which become shorter, with lower trophic diversity at the base of the network, but increased connectance along this environmental gradient.

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Subterranean streams represent unique heterotrophic ecosystems, usually supported by organic matter imported from the surface. Traditionally, the biological communities from subterranean streams were characterized as simple associations, with low diversity and species abundance, comprising mostly aquatic invertebrates connected by few trophic links compared with those of the surface. However, these features have not yet been described in the wider context of fluxes of energy and nutrients through food webs along a gradual switch from autotrophy (dominated by photosynthesis) towards heterotrophy (dominated by detritus) following the surface–subterranean continuum. Combining the most recent predictions of Ecological Stoichiometry and the Metabolic Theory of Ecology, this article provides a theoretical framework aiming to explain the patterns observed along the surface–subterranean continuum in streams. It is predicted that the main factors constraining the structure and functioning of communities and food webs are the decline in the quantity and diversity of basal resources along this gradient, along with nutrients availability in water that affects food quality. With increasing availability of dissolved nutrients in water, sinking-cave streams are hypothesized to fluctuate between being N and/ or P co-limited to C-limited. Combined, the quantity, quality, and diversity of basal resources regulate subterranean aquatic communities through bottom–up mechanisms, reflected in a decreased flux of macronutrients through food webs. The consequences of these bottom–up effects are decreased abundance, biomass, secondary production, consumption rate, and mean body size of communities, together with potential increases in the elemental imbalance for macronutrients, omnivory, trophic position, and niche width and overlap among aquatic consumers along the surface–subterranean continuum. The bottom–up effects induce changes in the topology of stream food webs, which become shorter, with lower trophic diversity at the base of the network, but increased connectance along this environmental gradient. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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Since its introduction in the early 2000s, DNA origami had a big impact on the development of nanotechnology by gathering numerous applications. During this time, many tools were designed and used to generate arbitrary shapes capable of self-assembly which make this technique more approachable. In this paper, we have created the map of Romania at nanoscale dimensions by using a new open-source software - PERDIX. For this purpose, we used a scaffold strand with a length of 6959 nucleotides and 162 staple strands with a variable length ranging between 20 and 63 nucleotides. All the computational tools that were used in this experiment are open-source and user-friendly.

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The Tile Assembly Model, and its many variants, is one of the most fundamental algorithmic assembly formalism within DNA nanotechnology. Most of the research in this field is focused on the complexity of assembling different shapes and patterns. In many cases, the assembly process is intrinsically deterministic and the final product is unique, while the assembly process might evolve through several possible assembly strategies. In this study we consider the controlled assembly of one dimensional tile structures according to predefined assembly graphs. We provide algorithmic approaches for developing such controlled assembly protocols, using the signal-passing Tile Assembly Model, as well as probabilistic approaches for investigating the assembly of such tile-based one-dimensional structures. As a byproduct, we build a generalized TAS (tile assembly system) which generate specific non-local non-associative algebraic computations and we assamble n x n squares using only one tile, which is a better efficiency compared to the staged assembly model. (C) 2019 The Authors. Published by Elsevier B.V.

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This paper presents the latest trends and approaches used for constructing nanoscale structures of 2D objects through DNA folding based on the DNA origami technology developed by Rothemund. The Rothemund method has been used in the construction of various shapes, such as the development of the nanoscale structure for the United States map. Following the steps of Rothemund's technique, we simulate the construction of the Romanian map nanoscale 2D structure, embedding the number 100 into it.

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Investigation of the lake systems can provide a variety of information that can lead to the development of general concepts about how lakes function and respond to environmental changes. The purpose of this study is to assess the current classification of therapeutic lakes based on supervised learning methods applied to several biochemical characteristics of such lakes. In order to classify the therapeutic lakes in a separate class, a dataset consisting of 45 observations from 9 different basins and from three different altitude categories was analysed using clustering and classification methods.

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The TAM (Model Tile Assembly Model) is a mathematical paradigm for modeling DNA self-assembling according to various given shapes, using DNA-tiles (rectangular shape) with sticky ends on each of the four edges that bound together on various shapes desired by the researcher. Although there are various models in the literature, the focus in this manuscript is on a rule based model, specifically the authors present an overview of the one-dimensional hierarchical self-assembly model of DNA tiles. The authors also present the evolution of number of tiles in partial assemblies, the average assembly size and of the number of partial assemblies of sizes 2 through 10 over the total running time. All simulations were run using the NFSim simulator on a preset period of time.

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Screening of 1,000-years old ice layers from the perennial ice block of Scarisoara Ice Cave (NW Romania) revealed the presence of fungal communities. Using culture-dependent methods and molecular techniques based on DGGE fingerprinting of 18S rRNA gene fragments and sequencing, we identified 50 cultured and 14 uncultured fungi in presently-forming, 400 and 900 years old ice layers, corresponding to 28 distinct operational taxonomic units (OTUs). The dominant ice-contained fungal OTUs were related to Ascomycota, Basidiomycota and Cryptomycota phyla. Representatives of Mucoromycota and Chytridiomycota were also isolated from recent and 400 years old ice samples. The cryophilic Mrakia stokesii was the most abundant fungal species found in the cave ice samples of all prospected ages, alongside other cryophilic fungi also identified in various glacial environments. Ice deposits formed during the Little Ice Age (dated between AD 1,250 and 1,850) appeared to have a higher fungal diversity than the ice layer formed during the Medieval Warm Period (prior to AD 1,250). A more complex fungal community adapted to low temperatures was obtained from all analyzed ice layers when cultivated at 4 degrees C as compared to 15 degrees C, suggesting the dominance of cold-adapted fungi in this glacial habitat. The fungal distribution in the analyzed cave ice layers revealed the presence of unique OTUs in different aged-formed ice deposits, as a first hint for putative further identification of fungal biomarkers for climate variations in this icy habitat. This is the first report on fungi from a rock-hosted cave ice block.

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Ice entrenched microcosm represents a vast reservoir of novel species and a proxy for past climate reconstitution. Among glacial ecosystems, ice caves represent one of the scarcely investigated frozen habitats. To characterize the microbial diversity of perennial ice from karst ecosystems, Roche 454 sequencing of 16S rRNA gene amplicons from the underground ice block of Scarisoara Ice Cave (Romania) was applied. The temporal distribution of bacterial and archaeal community structures from newly formed, 400, and 900 years old ice layers was surveyed and analyzed in relation with the age and geochemical composition of the ice substrate. The microbial content of cave ice layers varied from 3.3 10(4) up to 7.5 10(5) cells mL(-1), with 59-78% viability. Pyrosequencing generated 273,102 reads for the five triplicate ice samples, which corresponded to 3,464 operational taxonomic units (OTUs). The distribution of the bacterial phyla in the perennial cave ice varied with age, organic content, and light exposure. Proteobacteria dominated the 1 and 900 years old organic rich ice deposits, while Actinobacteria was mostly found in 900 years old ice strata, and Firmicutes was best represented in 400 years old ice. Cyanobacteria and Chlorobi representatives were identified mainly from the ice block surface samples exposed to sunlight. Archaea was observed only in older ice strata, with a high incidence of Crenarchaeota and Thaumarchaeaota in the 400 years old ice, while Euryarchaeota dominated the 900 years old ice layers, with Methanomicrobia representing the predominant taxa. A large percentage (55.7%) of 16S rRNA gene amplicons corresponded to unidentified OTUs at genus or higher taxa levels, suggesting a greater undiscovered bacterial diversity in this glacial underground habitat. The prokaryotes distribution across the cave ice block revealed the presence of 99 phylotypes specific for different ice layers, in addition to the shared microbial community. Ice geochemistry represented an important factor that explained the microbial taxa distribution in the cave ice block, while the total organic carbon content had a direct impact on the cell density of the ice microcosm. Both bacterial and archaeal community structures appeared to be affected by climate variations during the ice formation, highlighting the cave ice microbiome as a source of putative paleoclimatic biomarkers. This report constitutes the first high-throughput sequencing study of the cave ice microbiome and its distribution across the perennial underground glacier of an alpine ice cave.

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Screening of 1,000-years old ice layers from the perennial ice block of Scǎrişoara Ice Cave (NW Romania) revealed the presence of fungal communities. Using culture-dependent methods and molecular techniques based on DGGE fingerprinting of 18S rRNA gene fragments and sequencing, we identified 50 cultured and 14 uncultured fungi in presently-forming, 400 and 900 years old ice layers, corresponding to 28 distinct operational taxonomic units (OTUs). The dominant ice-contained fungal OTUs were related to Ascomycota, Basidiomycota and Cryptomycota phyla. Representatives of Mucoromycota and Chytridiomycota were also isolated from recent and 400 years old ice samples. The cryophilic Mrakia stokesii was the most abundant fungal species found in the cave ice samples of all prospected ages, alongside other cryophilic fungi also identified in various glacial environments. Ice deposits formed during the Little Ice Age (dated between AD 1,250 and 1,850) appeared to have a higher fungal diversity than the ice layer formed during the Medieval Warm Period (prior to AD 1,250). A more complex fungal community adapted to low temperatures was obtained from all analyzed ice layers when cultivated at 4 °C as compared to 15 °C, suggesting the dominance of cold-adapted fungi in this glacial habitat. The fungal distribution in the analyzed cave ice layers revealed the presence of unique OTUs in different aged-formed ice deposits, as a first hint for putative further identification of fungal biomarkers for climate variations in this icy habitat. This is the first report on fungi from a rock-hosted cave ice block. © 2018 The Author(s).

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In the last few decades, due to the global industrialization and population expansion the level of pollutants has largely increased, being one of the main environmental problems faced worldwide. Consequently, phytoremediation research had been gathering more and more interest. A study of data selected from Scopus is presented by the authors, identifying trends in publication number, collaboration and impact. The trends are identified at the global level followed by a discussion of how Romania performs with respect to the identified trends. When evaluating the research produced by the Romanian institutions, two characteristics are considered: phytoremediation potential of the plants in the Danube Delta and the coastal region and the phytoremediation research temporal evolution and international impact. The paper presents a quantitative analysis without adding variable weights to citations and publications based on the publications ranks offering an overview of the national research status in this research area.

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The regional bioeconomic potential takes into consideration many sectors of the economy that use renewable biological resources. The plants are one of the main resources for the most sectors - food, health, environment, materials and energy. The assessment of bioeconomic potential involves the modeling of the biological and economical aspects. Establishing the indicators involved in the study of this aspect requires a “what we have and what we need” analysis. We started with the development of a database of plants to facilitate an easy access to information for all interested scientist from related research fields. © 2016 Vasile Goldis University Press.

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