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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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Carrier red blood cells (RBCs) can be used for vascular delivery o f encapsulated drugs, biologicals and nanoparticies o f various compositions with multiple advantages including bioavailability, biocompatibility, large carrier volumes and vascular residence time. Iron-based magnetic nanoparticies (MNPs), with size less than 15 nm became superparamagnetic and they can be used for both, diagnostic (imagistic) and therapeutic purposes, including as controlled release drug delivery systems. For these reasons, the objective o f this study was to employ human erythrocytes for the encapsulation of carbon shell iron-based core nanoparticies (obtained by continuous wave infrared laser pyrolysis o f Fe(CO)(5) by a transient opening o f cell membrane pores using different hypo-osmotic dialysis. In order to evaluate the encapsulation o f nanoparticies into red blood cells (RBCs), normal, unloaded and loaded red blood cells (RBCs) were examined by Scanning/Transmission Electron Microscopy and Energy-dispersive X-ray spectroscopy analysis (EDX). Here, it is reported that these composite iron-based nanoparticies that were synthesized and tested could lead to their use in conjunction with the red blood cells (RBCs) as a promising agent in biomedical applications.

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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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Anemia is one of the most common disorders in the world generated by multiple causes. Despite a good understanding of the causes of anemia, there is still uncertainty about how best this should be investigated, prevented and managed. This reflects the limitations of laboratory tests, as well as the poor understanding of the complex physiological mechanisms. A better understanding of the nature of anemia and the changes in erythrocytes may provide new strategies to benefits of patients. In this study, it was identified by flow cytometric and SEM analysis, the morphological changes of forms that deviate from the classical discoid shape, which had an increase in the mean fluorescence intensity of calcein (erythrocyte viability measured by the level of intracellular esterase activity with the Calcein-AM method). The results obtained for RBCs from the patients with different types of anemia did not demonstrate a massive phosphatidylserine externalization measurable with Annexin-V-FITC compared to the values for normal erythrocytes. The present study provides that flow cytometric analysis can be a quick and efficient method for diagnosing in haematological diseases and monitoring and in the medical biotechnology industry in order to develop drugs to treat anemia.

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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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The paper deals with the cellulase-mediated hydrolysis applied to several residual biomass resulting after extraction of biologically active principles from three medicinal plants: Melissa officinalis L., Melilotus officinalis L., Viola tricolor L. The yield of hydrolysis to hexoses was determined based on the amount of free glucose in the reaction mixture identified by spectrophotometric analysis, and total conversion of biomass residues was calculated. It was found that biomass resulted from Viola tricolor L. exhibits best glucose amount (10.35%) after 1 h of enzymatic hydrolysis, while that sourced from Melissa officinalis L. gives the highest total conversion of solid biomass (82.13%).

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The Danube River-Danube Delta-Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already

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The Danube River–Danube Delta–Black Sea (DBS) region has witnessed major political, social and economic changes during the past three decades, which have profoundly affected the riverine, coastal and marine systems, their water management situation and the development of related research programmes. We reviewed the research activities in the DBS system of the past twenty years to determine the main funding bodies and to assess key research areas and how they varied over time and geographic region. As data basis we used a metadatabase filled with 478 projects addressing environmental and water management issues in the Danube River Basin, covering also the Danube Delta and the north-western Black Sea. As overall outcome extensive research efforts in the field of water management could be proven for the past two decades, despite the tumultuous times of political and economic transformations. One of the main findings was that EU funded projects played a key role for the development of transboundary research collaboration and were also the scientifically most productive one's. Historically, nutrient pollution was the main problem addressed, shifting to pollution in a broader sense and hydromorphological alterations in recent years. The newly arising challenges of climate change impacts and sediment management became important research questions in the last years, too. Most research was performed in the thematic field of navigation, followed by restoration and biodiversity issues. To meet all of the already identified and newly emerging challenges in the DBS System, cross-border and integrated (river-delta-sea) research activities are of major importance and have to be further promoted. We thus suggest drawing up a regional DBS Research Agenda linked to key challenges in water management to strengthen research collaboration and advance targeted scientific projects, an approach fostering also the scientific capacity in the region. © 2015 Elsevier B.V.

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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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The paper summarises the results of the 478 projects from the FP7-ENVIRONMENT proiect, DANube macroregion: Capacity building and Excellence in River Systems (basin, delta and sea) DANCERS database considering different attributes recorded for these projects. An analysis is performed on the recorded data and the significant characteristics are presented. The analysis performs a research output assessment in order to quantify the success of the projects. Trends are identified not only by thematic area and region of implementation, but also by coordinating country region and level of financing. A need to homogenising the level of financing as well as the level of funding efforts among the EU Strategy for the Danube Region (EUSDR) countries and not only, transpires at the end of the analysis. A concentrated effort towards inter and intra disciplinary collaboration as well as within and between institutional collaboration and knowledge sharing is also apparent.

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Transfusion medicine relies on the possibility of storing red blood cells (RBCs) for a prolonged period of time. A better understanding of the nature of changes in stored RBCs may provide new strategies to improve the balance of benefits and transfusion's risks. In the light of recent results on the mechanism of programmed cell death of RBCs (erythroptosis), where numerous cellular changes are common hallmarks of the apoptotic phenomenon, we have developed new flow cytometric criteria to evaluate the viability of stored erythrocytes. In order to evaluate the possible benefic effect of low-intensity laser irradiation for increasing the blood preservation period, we irradiated the whole blood from healthy donors in specially designed bags for research purposes by MacoPharma Company containing SAGM medium, and conserved it for 3 weeks. LED (Light emitting diode) (lambda=465nm, P=60mW, P/S=100mW/cm(2)) and laser diode (lambda=660nm, P=30mW, P/S= 50mW/cm(2)) in continuous wave have been used as sources of irradiation. Doses were ranged between 0 and 2J/cm(3). After that period RBCs were analyzed by flow cytometry for morphological changes (FSC/SSC), apoptosis/necrosis analysis (FITC-annexin-V labeling/PI) and viability using an original Calcein-AM method on a FACScan cytometer using CellQuest Pro software for acquisition and analysis. Complementary, the RBCs integrity was analyzed by scanning electron microscopy (SEM). Morphological changes assessment of red blood cells by flow cytometry and scanning electron microscopy showed a good preservation of the discoidal shape for the irradiated cells compared with control.

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In this work we describe a new segmentation technique for the Affymetrix microarray images. We prove that our method can offer better predictions on the gene levels as opposed to the standard Affymetrix segmentation implemented in the Affymetrix GeneChip Operating Software (GCOS). To check the accuracy and show the benefits of the new segmentation method we use a previously implemented methodology to simulate microarray images with realistic features. Using such an artificial image provides us with the actual levels for each spot and each gene investigated in the microarray. Using this information we then proceed to segment the same image twice (with GCOS and our new method). The two segmentations will produce two sets of gene levels that are then compared to the known gene levels (known since the moment of generating the artificial image). Using this methodology we are able to show statistically (using 50 replicates of the same steps of generating the image, segmenting, comparing the results) that in some cases our new method greatly outperforms the GCOS implemented segmentation method, while in the rest of the cases performs in similar fashion. (C) 2015 Elsevier B.V. All rights reserved.

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