Moving waters to mitigate hydropeaking: a case study from the Italian Alps

We assessed the effect of a hydropeaking diversion mitigation measure that allows for additional hydropower production, which markedly reduced hydropeaking on a 10-km stream reach in the north-eastern Italian Alps. Hydropeaking, caused by a storage hydropower plant, affected the study reach from the 1920s to 2015, when a cascade of three small run-of-the-river plants was installed to divert the hydropeaks from the plant outlet directly into the intake of the RoRs plants, and hydropeaking was released downstream the confluence with a major free-flowing tributary. The flow regime in the mitigated reach shifted from a hydropeaking-dominated to a baseflow-dominated regime in winter, with flow variability represented only by snowmelt and rainfall in late spring and summer. The application of two recently proposed sets of hydropeaking indicators, the hydraulic analysis of the hydropeaking wave, together with the assessment of biotic changes, allowed quantifying the changes in ecohydraulic processes associated with hydropeaking mitigation. The flow regime in the mitigated reach changed to a residual flow type, with much less frequent residual hydropeaks; although an average two-fold increase in downramping rates were recorded downstream the junction with the tributary, these changes did not represent an ecological concern. The functional composition of the macrobenthic communities shifted slightly in response to flow mitigation, but the taxonomic composition did not recover to conditions typical of more natural flow regimes. This was likely due to the reduced dilution of pollutants and resulting slight worsening in water quality. Conversely, the hyporheic communities showed an increase in diversity and abundance of interstitial taxa, especially in the sites most affected by hydropeaking. This effect was likely due to changes in the interstitial space availability, brought by a reduction of fine sediments clogging. Besides illustrating a feasible hydropeaking mitigation option for Alpine streams, our work suggests the importance of monitoring both benthic and hyporheic communities, together with the flow and sediment supply regimes, and physico-chemical water quality parameters

Assessing the eco-hydraulic effects of a hydropeaking mitigation measure with increased energy production in the Noce River (Italian Alps)

We investigated the ecohydraulic effects of a recently implemented hydropeaking mitigation measure in the Upper Noce Stream (NE Italy, Italian Alps), which also allows for additional hydropower production. The Upper Noce, a 3rd order gravel-bed stream, was affected since the mid-1920s by storage hydropower production and associated hydropeaking. The mitigation measure consisted in the diversion of most of the released hydropeaks into a sequence of three newly-installed, cascading run-of-the-river power plants, fed by a penstock running almost parallel to the former hydropeaking reach. The hydropeaking-diversion mitigation measure markedly reduced hydropeaking on a 10-km stream reach, and hydropeaking is now released immediately upstream the confluence with a major free-flowing tributary, which increases the hydropeaking baseflow. The flow regime in the mitigated reach shifted from hydropeaking-dominated to baseflow-dominated regime in winter, with flow variability represented only by snowmelt and rainfall in late spring and summer. We applied two sets of indicators (the Hydropeaking Indicators HP1, HP2 and the COSH method) and conducted a simplified hydraulic analysis of the hydropeaking wave propagation. We assessed the ecological effects of the mitigation measure using three complementary data sources: the analysis of (a) the benthic and (b) hyporheic invertebrate communities, based on datasets collected before and after the implementation of the diversion measure, and (c) ancillary data monitored by the diversion plant manager for required environmental monitoring, which included the suspended sediment regime and the Extended Biotic Index, measured yearly from the year before to the four subsequent years after the implementation of the mitigation measure. Three main changes in eco-hydraulic processes associated with hydropeaking mitigation were detected. i) The flow regime in the mitigated reach changed to a residual flow type, with much less frequent residual hydropeaks, with an average two-fold increase in downramping rates that were recorded downstream the junction with a major tributary. ii) The functional composition of the macrobenthic communities shifted slightly in response to flow mitigation, but the taxonomic composition did not recover to conditions typical of more natural flow regimes. This was likely due to the reduced dilution of pollutants and resulting slight worsening in water quality. iii) The hyporheic communities conversely showed an increase in diversity and abundance of interstitial taxa, especially in the sites most affected by hydropeaking, and this effect was likely due to changes in the interstitial space availability, brought by an alteration of the previous time-space pattern of fine sediment transport, which eventually resulted in reduction of fine sediments clogging of the gravel bed interstices. Besides illustrating a feasible hydropeaking mitigation option for Alpine streams, this work suggests the importance of monitoring both benthic and hyporheic communities, together with the flow and sediment supply regimes, and physico-chemical water quality parameters, for carefully detecting changes in eco-hydraulic processes associated with hydropeaking mitigation that may not be fully expected in the design phase

Classification of dendritic cell phenotypes from gene expression data

<p>Abstract</p> <p>Background</p> <p>The selection of relevant genes for sample classification is a common task in many gene expression studies. Although a number of tools have been developed to identify optimal gene expression signatures, they often generate gene lists that are too long to be exploited clinically. Consequently, researchers in the field try to identify the smallest set of genes that provide good sample classification. We investigated the genome-wide expression of the inflammatory phenotype in dendritic cells. Dendritic cells are a complex group of cells that play a critical role in vertebrate immunity. Therefore, the prediction of the inflammatory phenotype in these cells may help with the selection of immune-modulating compounds.</p> <p>Results</p> <p>A data mining protocol was applied to microarray data for murine cell lines treated with various inflammatory stimuli. The learning and validation data sets consisted of 155 and 49 samples, respectively. The data mining protocol reduced the number of probe sets from 5,802 to 10, then from 10 to 6 and finally from 6 to 3. The performances of a set of supervised classification models were compared. The best accuracy, when using the six following genes --Il12b, Cd40, Socs3, Irgm1, Plin2 and Lgals3bp-- was obtained by Tree Augmented Naïve Bayes and Nearest Neighbour (91.8%). Using the smallest set of three genes --Il12b, Cd40 and Socs3-- the performance remained satisfactory and the best accuracy was with Support Vector Machine (95.9%). These data mining models, using data for the genes Il12b, Cd40 and Socs3, were validated with a human data set consisting of 27 samples. Support Vector Machines (71.4%) and Nearest Neighbour (92.6%) gave the worst performances, but the remaining models correctly classified all the 27 samples.</p> <p>Conclusions</p> <p>The genes selected by the data mining protocol proposed were shown to be informative for discriminating between inflammatory and steady-state phenotypes in dendritic cells. The robustness of the data mining protocol was confirmed by the accuracy for a human data set, when using only the following three genes: Il12b, Cd40 and Socs3. In summary, we analysed the longitudinal pattern of expression in dendritic cells stimulated with activating agents with the aim of identifying signatures that would predict or explain the dentritic cell response to an inflammatory agent.</p

amda 2 13 a major update for automated cross platform microarray data analysis

Microarray platforms require analytical pipelines with modules for data pre-processing including data normalization, statistical analysis for identification of differentially expressed genes, cluster analysis, and functional annotation. We previously developed the Automated Microarray Data Analysis (AMDA, version 2.3.5) pipeline to process Affymetrix 3′ IVT GeneChips. The availability of newer technologies that demand open-source tools for microarray data analysis has impelled us to develop an updated multi-platform version, AMDA 2.13. It includes additional quality control metrics, annotation-driven (annotation grade of Affymetrix NetAffx) and signal-driven (Inter-Quartile Range) gene filtering, and approaches to experimental design. To enhance understanding of biological data, differentially expressed genes have been mapped into KEGG pathways. Finally, a more stable and user-friendly interface was designed to integrate the requirements for different platforms. AMDA 2.13 allows the analysis of Affymetrix..

CD103+ Dendritic Cells Control Th17 Cell Function in the Lung

Th17 cells express diverse functional programs while retaining their Th17 identity, in some cases exhibiting a stem-cell-like phenotype. Whereas the importance of Th17 cell regulation in autoimmune and infectious diseases is firmly established, the signaling pathways controlling their plasticity are undefined. Using a mouse model of invasive pulmonary aspergillosis, we found that lung CD103+ dendritic cells (DCs) would produce IL-2, dependent on NFAT signaling, leading to an optimally protective Th17 response. The absence of IL-2 in DCs caused unrestrained production of IL-23 and fatal hyperinflammation, which was characterized by strong Th17 polarization and the emergence of a Th17 stem-cell-like population. Although several cell types may be affected by deficient IL-2 production in DCs, our findings identify the balance between IL-2 and IL-23 productions by lung DCs as an important regulator of the local inflammatory response to infection

NLRP10 Enhances CD4+ T-Cell-Mediated IFNγ Response via Regulation of Dendritic Cell-Derived IL-12 Release

NLRP10 is a nucleotide-binding oligomerization domain-like receptor that functions as an intracellular pattern recognition receptor for microbial products. Here, we generated a Nlrp10−/− mouse to delineate the role of NLRP10 in the host immune response and found that Nlrp10−/− dendritic cells (DCs) elicited sub-optimal IFNγ production by antigenspecific CD4+ T cells compared to wild-type (WT) DCs. In response to T-cell encounter, CD40 ligation or Toll-like receptor 9 stimulation, Nlrp10−/− DCs produced low levels of IL-12, due to a substantial decrease in NF-κB activation. Defective IL-12 production was also evident in vivo and affected IFNγ production by CD4+ T cells. Upon Mycobacterium tuberculosis (Mtb) infection, Nlrp10−/− mice displayed diminished T helper 1-cell responses and increased bacterial growth compared to WT mice. These data indicate that NLRP10-mediated IL-12 production by DCs is critical for IFNγ induction in T cells and contributes to promote the host defense against Mtb

Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus

Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.Peer reviewe

Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.Peer reviewe