High-accuracy machine learning techniques for functional connectome fingerprinting and cognitive state decoding.

The human brain is a complex network comprised of functionally and anatomically interconnected brain regions. A growing number of studies have suggested that empirical estimates of brain networks may be useful for discovery of biomarkers of disease and cognitive state. A prerequisite for realizing this aim, however, is that brain networks also serve as reliable markers of an individual. Here, using Human Connectome Project data, we build upon recent studies examining brain-based fingerprints of individual subjects and cognitive states based on cognitively demanding tasks that assess, for example, working memory, theory of mind, and motor function. Our approach achieves accuracy of up to 99% for both identification of the subject of an fMRI scan, and for classification of the cognitive state of a previously unseen subject in a scan. More broadly, we explore the accuracy and reliability of five different machine learning techniques on subject fingerprinting and cognitive state decoding objectives, using functional connectivity data from fMRI scans of a high number of subjects (865) across a number of cognitive states (8). These results represent an advance on existing techniques for functional connectivity-based brain fingerprinting and state decoding. Additionally, 16 different functional connectome (FC) matrix construction pipelines are compared in order to characterize the effects of different aspects of the production of FCs on the accuracy of subject and task classification, and to identify possible confounds.

Effect of salinity on valves morphology in freshwater diatoms.

Increased salt concentration is one of the most widespread problems affecting freshwater worldwide. Aquatic communities, and in particular periphytic diatoms, react to this alteration in water quality by modifying their structural parameters and physiology at the individual level, which is commonly manifested by the appearance of teratological forms. The present work presents the results of an experimental laboratory study in which a biofilm grown on artificial substrates was subjected to a gradient of water conductivities for 4 weeks. The results show an increase in the number of deformed valves over time proportionally to the increase in conductivity for each experimental treatment. These effects are also verified by analyzing the concentration of chlorophyll-a in the experimental biofilms, which demonstrate a metabolic response to the induced osmotic stress. No changes were recorded; however, in species richness or diversity of taxa present in the treatments. Our results, therefore, confirm at the experimental level numerous previous field observations about the harmful effect of salinity on periphytic diatoms, and also their ability to reintegrate with the new stress conditions.

Microalgae and Cyanobacteria Strains as Producers of Lipids with Antibacterial and Antibiofilm Activity.

Lipids are one of the primary metabolites of microalgae and cyanobacteria, which enrich their utility in the pharmaceutical, feed, cosmetic, and chemistry sectors. This work describes the isolation, structural elucidation, and the antibiotic and antibiofilm activities of diverse lipids produced by different microalgae and cyanobacteria strains from two European collections (ACOI and LEGE-CC). Three microalgae strains and one cyanobacteria strain were selected for their antibacterial and/or antibiofilm activity after the screening of about 600 strains carried out under the NoMorFilm European project. The total organic extracts were firstly fractionated using solid phase extraction methods, and the minimum inhibitory concentration and minimal biofilm inhibitory concentration against an array of human pathogens were determined. The isolation was carried out by bioassay-guided HPLC-DAD purification, and the structure of the isolated molecules responsible for the observed activities was determined by HPLC-HRESIMS and NMR methods. Sulfoquinovosyldiacylglycerol, monogalactosylmonoacylglycerol, sulfoquinovosylmonoacylglycerol, α-linolenic acid, hexadeca-4,7,10,13-tetraenoic acid (HDTA), palmitoleic acid, and lysophosphatidylcholine were found among the different active sub-fractions selected. In conclusion, cyanobacteria and microalgae produce a great variety of lipids with antibiotic and antibiofilm activity against the most important pathogens causing severe infections in humans. The use of these lipids in clinical treatments alone or in combination with antibiotics may provide an alternative to the current treatments.

Chlorosphaerolactylates A-D: Natural Lactylates of Chlorinated Fatty Acids Isolated from the Cyanobacterium Sphaerospermopsis sp. LEGE 00249.

Four natural lactylates of chlorinated fatty acids, chlorosphaerolactylates A-D (1-4), were isolated from the methanolic extract of the cyanobacterium Sphaerospermopsis sp. LEGE 00249 through a combination of bioassay-guided and MS-guided approaches. Compounds 1-4 are esters of (mono-, di-, or tri)chlorinated lauric acid and lactic acid, whose structures were assigned on the basis of spectrometric and spectroscopic methods inclusive of 1D and 2D NMR experiments. High-resolution mass-spectrometry data sets also demonstrated the existence of other minor components that were identified as chlorosphaero(bis)lactylate analogues. The chlorosphaerolactylates were tested for potential antibacterial, antifungal, and antibiofilm properties using bacterial and fungal clinical isolates. Compounds 1-4 showed a weak inhibitory effect on the growth of Staphylococcus aureus S54F9 and Candida parapsilosis SMI416, as well as on the biofilm formation of coagulase-negative Staphylococcus hominis FI31.

Exploring the effects of acid mine drainage on diatom teratology using geometric morphometry.

Metal pollution of aquatic habitats is a major and persistent environmental problem. Acid mine drainage (AMD) affects lotic systems in numerous and interactive ways. In the present work, a mining area (Roșia Montana) was chosen as study site, and we focused on two aims: (i) to find the set of environmental predictors leading to the appearance of the abnormal diatom individuals in the study area and (ii) to assess the relationship between the degree of valve outline deformation and AMD-derived pollution. In this context, morphological differences between populations of Achnanthidium minutissimum and A. macrocephalum, including normal and abnormal individuals, were evidenced by means of valve shape analysis. Geometric morphometry managed to capture and discriminate normal and abnormal individuals. Multivariate analyses (NMDS, PLS) separated the four populations of the two species mentioned and revealed the main physico-chemical parameters that influenced valve deformation in this context, namely conductivity, Zn, and Cu. ANOSIM test evidenced the presence of statistically significant differences between normal and abnormal individuals within both chosen Achnanthidium taxa. In order to determine the relative contribution of each of the measured physico-chemical parameters in the observed valve outline deformations, a PLS was conducted, confirming the results of the NMDS. The presence of deformed individuals in the study area can be attributed to the fact that the diatom communities were strongly affected by AMD released from old mining works and waste rock deposits.

Influence of biogas flow rate on biomass composition during the optimization of biogas upgrading in microalgal-bacterial processes.

The influence of biogas flow rate (0, 0.3, 0.6, and 1.2 m(3) m(-2) h(-1)) on the elemental and macromolecular composition of the algal-bacterial biomass produced from biogas upgrading in a 180 L photobioreactor interconnected to a 2.5 L external bubbled absorption column was investigated using diluted anaerobically digested vinasse as cultivation medium. The influence of the external liquid recirculation/biogas ratio (0.5 < L/G < 67) on the removal of CO2 and H2S, and on the concentrations of O2 and N2 in the upgraded biogas, was also evaluated. A L/G ratio of 10 was considered optimum to support CO2 and H2S removals of 80% and 100%, respectively, at all biogas flow rates tested. Biomass productivity increased at increasing biogas flow rate, with a maximum of 12 ± 1 g m(-2) d(-1) at 1.2 m(3) m(-2) h(-1), while the C, N, and P biomass content remained constant at 49 ± 2%, 9 ± 0%, and 1 ± 0%, respectively, over the 175 days of experimentation. The high carbohydrate contents (60-76%), inversely correlated to biogas flow rates, would allow the production of ≈100 L of ethanol per 1000 m(3) of biogas upgraded under a biorefinery process approach.

What do diatom indices indicate? Modeling the specific pollution sensitivity index.

Diatoms are commonly used in environmental assessments to detect pollution and eutrophication. The specific pollution sensitivity index (SPI) is one of the most frequently used indices, which assigns scores to diatom taxa based on their sensitivity to pollution. The study analyzed diatom communities in the Duero River basin in Spain to examine the relationship between SPI scores and various limnological variables. A GLM model showed that phosphates, nitrites, and water temperature were the main factors explaining SPI variability. The study also reviews previous results using SPI for water quality monitoring in different world regions, highlighting the role of nutrients in general as major drivers of SPI values worldwide. Overall, the findings reinforce the reliability of SPI as a metric for biological monitoring in various watercourses.

Assessing nitrous oxide emissions from algal-bacterial photobioreactors devoted to biogas upgrading and digestate treatment.

Nitrous oxide (N2O) emissions in High Rate Algal Ponds (HRAP) can negatively affect the sustainability of algal-bacterial processes. N2O emissions from a pilot HRAP devoted to biogas upgrading and digestate treatment were herein monitored for 73 days. The influence of the pH (7.5, 8.5, and 9.5), nitrogen sources (100 mg L-1 of N-NO2-, N-NO3-, and N-NH4+) and illumination on N2O emissions from the algal-bacterial biomass of the HRAP was also assessed in batch tests. Significantly higher N2O gas concentrations of 311.8 ± 101.1 ppmv were recorded in the dark compared to the illuminated period (236.9 ± 82.6 ppmv) in the HRAP. The batch tests revealed that the highest N2O emission rates (49.4 mmol g-1 TSS·h-1) occurred at pH 8.5 in the presence of 100 mg N-NO2-/L under dark conditions. This study revealed significant N2O emissions in HRAPs during darkness.

The Duero Diatom Index (DDI) for river water quality assessment in NW Spain: design and validation.

Diatom indices developed in certain geographic regions are frequently used elsewhere, despite the strong evidence that such metrics are less useful when applied in regions other than that where species-environment relationships were originally assessed, showing that species have particular autoecological requirements in different geographic areas. The goal of this study was to develop a new metric, the Duero Diatom Index (DDI), aimed at monitoring water quality in Duero basin watercourses (NW Spain). In summer 2008 and 2009, a total of 355 epilithic diatom samples were collected following standard protocols. The 2008 samples were used to develop the DDI, whereas the samples collected during 2009 were used in the index testing. Weighted averages method was used to derive the autoecological profiles of diatoms with respect to pH, conductivity, biological oxygen demand, ammonia, nitrates, and phosphates. The optimum and tolerance values for the measured environmental variables were determined for 137 taxa with abundances and frequencies of occurrence above 1%, and subsequent trophic indicator and sensitivity values were defined for the DDI. The correlation between the observed and the diatom-inferred nutrient concentrations was highest for phosphates (ρ (S) = 0.72). Significant statistical relationship were observed between DDI values and the chemistry-based General Quality Index values (p = 0.006) and the specific pollution index (SPI) diatom metric (p = 0.04). DDI has demonstrated a better correlation with water chemistry than SPI diatom metric.

European river typologies fail to capture diatom, fish, and macrophyte community composition.

Typology systems are frequently used in applied and fundamental ecology and are relevant for environmental monitoring and conservation. They aggregate ecosystems into discrete types based on biotic and abiotic variables, assuming that ecosystems of the same type are more alike than ecosystems of different types with regard to a specific property of interest. We evaluated whether this assumption is met by the Broad River Types (BRT), a recently proposed European river typology system, that classifies river segments based on abiotic variables, when it is used to group biological communities. We compiled data on the community composition of diatoms, fishes, and aquatic macrophytes throughout Europe and evaluated whether the composition is more similar in site groups with the same river type than in site groups of different river types using analysis of similarities, classification strength, typical species analysis, and the area under zeta diversity decline curves. We compared the performance of the BRT with those of four region-based typology systems, namely, Illies Freshwater Ecoregions, the Biogeographic Regions, the Freshwater Ecoregions of the World, and the Environmental Zones, as well as spatial autocorrelation (SA) classifications. All typology systems received low scores from most evaluation methods, relative to predefined thresholds and the SA classifications. The BRT often scored lowest of all typology systems. Within each typology system, community composition overlapped considerably between site groups defined by the types of the systems. The overlap tended to be the lowest for fishes and between Illies Freshwater Ecoregions. In conclusion, we found that existing broad-scale river typology systems fail to delineate site groups with distinct and compositionally homogeneous communities of diatoms, fishes, and macrophytes. A way to improve the fit between typology systems and biological communities might be to combine segment-based and region-based typology systems to simultaneously account for local environmental variation and historical distribution patterns, thus potentially improving the utility of broad-scale typology systems for freshwater biota.

Rimoportula Distribution, Heterovalvy and Heteropolarity in Hyalosira (Bacillariophyta: Rhabdonematales), with Revision of H. hesperia and Two New Species.

The genus Hyalosira Kützing was recently split and emended based on morphology and molecular phylogeny but many uniseriate taxa could not be resolved. All populations examined in that study had one rimoportula on each valve (i.e., 1 + 1 in the cell). Recent collections from Turkey, Australia, and Micronesia had uniseriate taxa with different numbers of rimoportulae and other new features distinguishing them from all other uniseriate taxa. Two species had two rimoportulae per valve (i.e., 2 + 2) and deep septa, of which one is shown to be Hyalosira hesperia Álvarez-Blanco & S.Blanco, for which we provide a revised description, and the other, from Melbourne and Yap, is proposed as H. pacifica, sp. nov. They are separated by stria density and copula areola density. A third species, from the Great Barrier Reef, H. flexa, sp. nov., is the first Hyalosira found with heterovalvy-including a rimoportula on only one valve (i.e., 1 + 0)-and heteropolarity, including three variously reduced pore fields and the fourth, with the rimoportula, always involved in attachment, essentially a basal pole. A corrected diagnosis of the genus is provided and implications for exploring the functions of rimoportulae are discussed.

Diffeomorphic transforms for data augmentation of highly variable shape and texture objects.

BACKGROUND AND OBJECTIVE: Training a deep convolutional neural network (CNN) for automatic image classification requires a large database with images of labeled samples. However, in some applications such as biology and medicine only a few experts can correctly categorize each sample. Experts are able to identify small changes in shape and texture which go unnoticed by untrained people, as well as distinguish between objects in the same class that present drastically different shapes and textures. This means that currently available databases are too small and not suitable to train deep learning models from scratch. To deal with this problem, data augmentation techniques are commonly used to increase the dataset size. However, typical data augmentation methods introduce artifacts or apply distortions to the original image, which instead of creating new realistic samples, obtain basic spatial variations of the original ones. METHODS: We propose a novel data augmentation procedure which generates new realistic samples, by combining two samples that belong to the same class. Although the idea behind the method described in this paper is to mimic the variations that diatoms experience in different stages of their life cycle, it has also been demonstrated in glomeruli and pollen identification problems. This new data augmentation procedure is based on morphing and image registration methods that perform diffeomorphic transformations. RESULTS: The proposed technique achieves an increase in accuracy over existing techniques of 0.47%, 1.47%, and 0.23% for diatom, glomeruli and pollen problems respectively. CONCLUSIONS: For the Diatom dataset, the method is able to simulate the shape changes in different diatom life cycle stages, and thus, images generated resemble newly acquired samples with intermediate shapes. In fact, the other methods compared obtained worse results than those which were not using data augmentation. For the Glomeruli dataset, the method is able to add new samples with different shapes and degrees of sclerosis (through different textures). This is the case where our proposed DA method is more beneficial, when objects highly differ in both shape and texture. Finally, for the Pollen dataset, since there are only small variations between samples in a few classes and this dataset has other features such as noise which are likely to benefit other existing DA techniques, the method still shows an improvement of the results.

Multi-exposure microscopic image fusion-based detail enhancement algorithm.

Traditional microscope imaging techniques are unable to retrieve the complete dynamic range of a diatom species with complex silica-based cell walls and multi-scale patterns. In order to extract details from the diatom, multi-exposure images are captured at variable exposure settings using microscopy techniques. A recent innovation shows that image fusion overcomes the limitations of standard digital cameras to capture details from high dynamic range scene or specimen photographed using microscopy imaging techniques. In this paper, we present a cell-region sensitive exposure fusion (CS-EF) approach to produce well-exposed fused images that can be presented directly on conventional display devices. The ambition is to preserve details in poorly and brightly illuminated regions of 3-D transparent diatom shells. The aforesaid objective is achieved by taking into account local information measures, which select well-exposed regions across input exposures. In addition, a modified histogram equalization is introduced to improve uniformity of input multi-exposure image prior to fusion. Quantitative and qualitative assessment of proposed fusion results reveal better performance than several state-of-the-art algorithms that substantiate the method's validity.

Current Concentrations of Zn, Cu, and As in Piggery Wastewater Compromise Nutrient Removals in Microalgae-Bacteria Photobioreactors Due to Altered Microbial Communities.

The treatment of pig manure is a major environmental issue, and photobioreactors containing consortia of microalgae and bacteria have proven to be a promising and sustainable treatment alternative. This work studies the effect of Cu, Zn and As, three toxic elements frequently present in piggery wastewater, on the performance and microbiome of photobioreactors. After dopage with Zn (100 mg/L), Cu (100 mg/L), and As (500 µg/L), the high biomass uptake of Zn (69-81%) and Cu (81-83%) decreased the carbon removal in the photobioreactors, inhibited the growth of Chlorella sp., and affected heterotrophic bacterial populations. The biomass As uptake result was low (19%) and actually promoted microalgae growth. The presence of Cu and As decreased nitrogen removal, reducing the abundance of denitrifying bacterial populations. The results showed that metal(loid)s significantly affected 24 bacterial genera and that they did not recover after exposure. Therefore, this study makes an important contribution on the impact of the presence of metal(loid)s in piggery wastewater that compromises the overall performance of PBRs, and so, the environmental and health impact of treated effluents.

Mechanisms for parasites removal in a waste stabilisation pond.

A waste stabilisation pond (WSP) system formed by two anaerobic ponds, a facultative pond and a maturation pond was studied from December 2003 to September 2004 in north-western Spain in order to evaluate its efficiency in the removal of faecal indicator bacteria (total coliforms, Escherichia coli, faecal streptococci), coliphages, helminth eggs and protozoan (oo)cysts (Cryptosporidium and Giardia). Furthermore, sediment samples were collected from the bottom of the ponds to assess the settling rates and thus determine the main pathogen removal mechanisms in the WSPs system. The overall removal ranged from 1.4 log units for coliphages in the cold period to 5.0 log units for E. coli in the hot period. Cryptosporidium oocysts were reduced by an average of 96%, Giardia cysts by 98% and helminth eggs by 100%. The anaerobic ponds showed significantly higher surface removal rates (4.6, 5.2 and 3.7 log (oo)cysts/eggs removed m(-2) day(-1), respectively) than facultative and maturation ponds. Sunlight and water physicochemical conditions were the main factors influencing C. parvum oocysts removal both in the anaerobic and maturation ponds, whereas other factors like predation or natural mortality were more important in the facultative pond. Sedimentation, the most commonly proposed mechanism for cyst removal had, therefore, a negligible influence in the studied ponds.

Effect of operational conditions on the degradation of organic matter and development of microalgae-bacteria consortia when treating swine slurry.

There is great controversy regarding the best substrate (fresh or anaerobically digested swine slurry) for the development of microalgae-bacteria consortia. This study aims to elucidate the best substrate by assessing biomass productivity, microorganism predominance, and their ability for organic matter removal. In addition to the different substrates, different operational conditions and influent strengths were evaluated. Increasing organic matter content when favourable temperature and illumination conditions were present improved biomass production. However, these conditions were not favourable for microalgal growth, but they were favourable for bacteria. Regardless of the operational conditions, reactors fed with fresh slurry not only resulted in the highest biomass productivity, but also the greatest removal of total and soluble chemical oxygen demand (COD). On the other hand, reactors fed with digested slurry showed biomass productivity and COD removal values lower than those obtained for reactors fed with fresh slurry, most probably due to the recalcitrant nature of the former. Nevertheless, digested slurry was the substrate more appropriate for microalgae growth under harsh operational conditions (16 °C and 9-h illumination) at low influent strength and optimum operational conditions (30 °C and 24-h illumination) at higher influent strength.

Nonsubsampled contourlet transform based tone-mapping operator to optimize the dynamic range of diatom shells.

The diatoms have intricate silica-based cell walls with multi-scale patterns. High dynamic range (HDR) imaging is widely used to examine the three-dimensional structure of diatoms for recovering the wide range of contrast and brightness. In order to construct a HDR image of a diatom, multiple images of the specimen are taken at different exposure settings with bright or dark field microscopy. In the proposed method, multi-scale decomposition based on nonsubsampled contourlet transform is adopted to separate the structured and detailed information of the HDR image. And then, by processing all layers independently, the tone-mapped image is reconstructed to retain details present in the dark and light regions. Quantitative and qualitative analysis is performed in order to assess the performance of the proposed and seven existing tone-mapping operators. In analysis, the study indicates that the proposed method enhances the diatom frustules to extract more details.

Innovative operational strategies in photosynthetic biogas upgrading in an outdoors pilot scale algal-bacterial photobioreactor.

Three innovative operational strategies were successfully evaluated to improve the quality of biomethane in an outdoors pilot scale photobioreactor interconnected to an external absorption unit: i) the use of a greenhouse during winter conditions, ii) a direct CO2 stripping in the photobioreactor via air stripping during winter conditions and iii) the use of digestate as make-up water during summer conditions. CO2 concentrations in the biomethane ranged from 0.4% to 6.1% using the greenhouse, from 0.3% to 2.6% when air was injected in the photobioreactor and from 0.4% to 0.9% using digestate as make up water. H2S was completely removed under all strategies tested. On the other hand, CH4 concentrations in biomethane ranged from 89.5% to 98.2%, from 93.0% to 98.2% and from 96.3% to 97.9%, when implementing strategies i), ii) and iii), respectively. The greenhouse was capable of maintaining microalgae productivities of 7.5 g m-2 d-1 during continental weather conditions, while mechanical CO2 stripping increased the pH in order to support an effective CO2 and H2S removal. Finally, the high evaporation rates during summer conditions allowed maintaining high inorganic carbon concentrations in the cultivation broth using centrate, which provided a cost-effective biogas upgrading.

Integration of algae-based sewage treatment with anaerobic digestion of the bacterial-algal biomass and biogas upgrading.

The domestic sewage treatment performance of an integrated anoxic-aerobic photobioreactor with biomass settling and recycling, coupled with anaerobic digestion of the produced bacterial-algal biomass and biogas upgrading in the photobioreactor was investigated. Hydraulic retention time in the photobioreactor initially was 4 days (stage I and II) and then reduced to 2.5 days (stage III). The integrated system supported high total organic carbon removals of 98.9 ± 1.1% regardless of the operational stage. A high total nitrogen removal of 90.8 ± 8.0% was recorded in the integrated system during the three operational stages, while total phosphorus removals accounted for 68.4 ± 20.1%, 68.3 ± 20.8% and 53.4 ± 25.0% in stages I, II and III, respectively. Biogas upgrading in the absorption column exhibited maximum removals of CO2 and H2S of 74.7 ± 3.0% and 99.0 ± 2.8%, respectively. Biomass settling and recycling resulted in overall improvement of biomass settleability.

DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms.

Diatoms are important organisms in freshwater ecosystems due to their position as primary producers and therefore, analyzing their assemblages provides relevant information on ecosystem functioning. Diatoms have historically been identified based on morphological traits, which is time-consuming and requires well-trained specialists. Nevertheless, DNA barcoding offers an alternative approach to overcome some limitations of the morphological method. Here, we assess if both approaches are comparable methods to study patterns and mechanisms (including environmental filtering and dispersal limitation) of epiphytic diatom metacommunities using a comprehensive dataset from 22 Mediterranean ponds at different taxonomic resolutions. We used a fragment of rbcL barcode gene combined with High-Throughput Sequencing to infer diatom community composition. The overall degree of correspondence between both approaches was assessed by Procrustean rotation analysis and Procrustean randomization tests, whereas the role of local environmental variables and geographical distances was studied using a comprehensive combination of BIOENV, Mantel tests and distance-based redundancy analysis. Our results showed a relatively poor correspondence in the compositional variation of diatom metacommunity between both approaches. We speculate that the incompleteness of the reference database and the bioinformatics processing are the biases most likely affecting the molecular approach, whereas the limited counting effort and the presence of cryptic species are presumably the major biases related with the morphological method. On the other hand, variation in diatom community composition detected with both approaches was strongly related to the environmental template, which may be related with the narrow community-environment relationships in diatoms. Nevertheless, we found no significant relationship between compositional variation and geographical distances. Overall, our work shows the complementary nature of both approaches and highlights the importance of DNA metabarcoding to address empirical research questions of community ecology in freshwaters, especially once the reference databases include most genotypes of occurring taxa and bioinformatics biases are overcome.