We developed a cost-effective metabarcoding strategy to analyze phytoplankton community structure using the Illumina MiSeq system. The amplicons (404–411 bp) obtained by end-pairing of two reads were sufficiently long to distinguish algal species and provided barcode data equivalent to those generated with the Roche 454 system, but at less than 1/20th of the cost. The original universal primer sequences targeting the 23S rDNA region and the PCR strategy were both modified, and this resulted in higher numbers of eukaryotic algal sequences by excluding non-photosynthetic proteobacterial sequences supporting effectiveness of this strategy. The novel strategy was used to analyze the phytoplankton community structure of six water samples from the East/Japan Sea: surface and 50 m depths at coastal and open-sea sites, with collections in May and July 2014. In total, 345 operational taxonomic units (OTUs) were identified, which covered most of the prokaryotic and eukaryotic algal phyla, including Dinophyta, Rhodophyta, Ochrophyta, Chlorophyta, Streptophyta, Cryptophyta, Haptophyta, and Cyanophyta. This highlights the importance of plastid 23S primers, which perform better than the currently used 16S primers for phytoplankton community surveys. The findings also revealed that more efforts should be made to update 23S rDNA sequences as well as those of 16S in the databases. Analysis of algal proportions in the six samples showed that community structure differed depending on location, depth and season. Across the six samples evaluated, the numbers of OTUs in each phylum were similar but their relative proportions varied. This novel strategy would allow laboratories to analyze large numbers of samples at reasonable expense, whereas this has not been possible to date due to cost and time. In addition, we expect that this strategy will generate a large amount of novel data that could potentially change established methods and tools that are currently used in the realms of oceanography and marine ecology. Traditional phytoplankton surveys have relied mainly on microscopic observations, which require significant time and trained experts to obtain accurate data. This has created a bottleneck and is a major consideration in research planning. For these reasons, there is a need for a faster and more reliable standard method of performing detailed analysis of phytoplankton community structures. Alternatively, phytoplankton communities can be roughly analyzed based on different pigments using flow-cytometry , 2007, whttp://www.ncbi.nlm.nih.gov/) and more than 6,490 phytoplanktonic 16S sequences are currently deposited in the PhytoREF database (http://phytoref.org). Although there is still debate, universal primers targeting 16S rDNA are now most widely used  and a large subunit of the ribulose-1,5-diphophate carxoylase/oxygenase (rbcL) or plastid 16S rDNA region , 2003. Iely used , 2011. Hely used , 2015. Aely used , 2007.The rapid pace of technological advancement in DNA sequencing and bioinformatics analysis has meant that researchers can now analyze phytoplankton community structure simply by massive sequencing of DNA barcodes that are amplified from environmental samples, a process known as “metabarcoding.” In fact, several trials have already been conducted to analyze algal community structure using next generation sequencing (NGS) technology and generating large amounts of data for large survey areas at low cost, as compared with the Sanger method which uses dideoxynucleotide analogs , 2012. TIn this study, we developed a novel strategy of targeting the 23S rDNA region for phytoplankton community analysis using the MiSeq system . Performing large reads (404–411 bp) by paired-end sequencing (2X 300 bp) enabled us to analyze phytoplankton community structure at reduced cost (less than 1/20th of the cost with the Roche 454 system) and with high resolution. Our modified “universal primers” targeting the 23S rDNA region achieved a high level of coverage, amplifying most taxa of prokaryotic and eukaryotic phytoplankton while excluding the non-photosynthetic proteobacterial sequences. The reliability of this NGS strategy was confirmed by analyzing phytoplankton samples from different locations, depths, and seasons in the East/Japan Sea.MIS: surface water from station I in May 2014 Station I surface water; MIIS: surface water from station II in May 2014; MIID: 50 m water from station 2 in May 2014; JIS: surface water from station I in July 2014; JIIS: surface water from station II in July 2014.Sampling was carried out in May and July 2014 under permitting (Department of Fisheries Resource Management-1728 & 2506) for the project “Long-term change of structure and function in marine ecosystems of Korea,” funded by the Ministry of Oceans and Fisheries, Korea. Field water samples from the surface (0 m) and at 50 m depth were collected using 10 L Niskin bottles at two sampling stations in the southwestern East/Japan Sea, Korea. Among various sample site options, station I (StI) was chosen as representative coastal water, whereas station II (StII) was in open sea. Samples were labeled with collection date, location, and depth, as follows: a concentration was measured using a Turner 10AU fluorometer  as described by Water temperature and salinity were measured using an SBE-43 unit . One liter of water was collected from each sampling site and filtered using a 0.45-µm GH Polypro membrane filter . Chlorophyll-®Gel Purification Kit  and eluted with 20 µL elution buffer. The second PCR reaction mixture was the same as the first except that 2 µL of purified PCR product from the first PCR amplification was used. As with the first round, 2 µL of each primer was used for the second PCR (20 pmol). The products were separated by 1.5% agarose gel electrophoresis and stained with loading star . Amplicons of the expected sizes (approximately 410 bp) were purified using the AccuPrep®Gel Purification Kit . A library was constructed from the NGS data using the TruSeq®Sample Preparation kit V2 . The quality and quantity of the library were measured using a 2100 Bioanalyzer  and sequencing was performed using Illumina MiSeq (2 X 300 bp pair-ends) .The “universal” primers for the mini-barcode were redesigned to target the plastid 23S rDNA region , 2007. Ahttp://www.ncbi.nlm.nih.gov/) showing high similarity (>90%) to the amplicons obtained were included in the database. ``Uncultured'' sequences that had been deposited in GenBank by barcoding or metabarcoding projects were excluded. If the end-paired amplicons matched 100% with sequences in the PHYTOGEN database after alignment using BLASTn, the amplicons were named. If they did not match, the amplicons were named as Class name + PKNUE + numbers and entered into the PHYTOGEN database. To avoid errors, operational taxonomic units (OTUs) were not assigned for amplicons that were present in <0.1% of the community. Once the PHYTOGEN database was constructed, the total amplicons were analyzed by a BLASTn search and those with <99% identity in the PHYTOGEN database were described as ``others.''Adapter/index and QV < 20 sequences from the raw data obtained were trimmed, and read length of <120 nucleotides were filtered using CLC Genomics Workbench v. 8.0 . End-paired amplicons were constructed using Mothur software v. 1.35.0 , 2009 wiAs noted, the first step of the study was to modify the original “universal” primers targeting the plastid 23S rDNA region such that they excluded the non-photosynthetic proteobacteria . AmplicoTo determine whether the modified 23S primers and PCR conditions could be directly applied to the phytoplankton survey, the described six samples were chosen and analyzed according to the different locations, seasons, and depths of the East/Japan Sea. After processing the raw reads, the number of end-paired amplicons obtained from each sample ranged from 290,082 to 639,836, and averaged 438,896 . After sTo determine the cut-off value for phylum similarity, the OTUs obtained were screened from 90% to 99% . The datMore OTUs were present in the samples collected from the open sea than in those collected from the coastal seas, and this was mainly to the prokaryotic population, including cyanobacteria and proteobacteria . The cosThe modified universal primers were more effective at identifying prokaryotic and eukaryotic phytoplankton taxa, and effectively excluded proteobacterial sequences. Compared with 16S primers, the modified primers will be more useful for analyzing phytoplankton community structure, as they allow for identification of more photosynthetic phytoplankton. When data produced by both 16S and 23S primers are compared, it will be possible to assess for correlations between autotrophic phytoplankton species and heterotrophic bacteria in the ocean. In the present study, we also found that all the sequences belonging to the Chlorophyta contained a GGACAA sequence rather than GGACAG at the 5′ end of the original universal forward primer region . This fiOf the 345 OTUs identified in this study, only 95 (27.5%) matched the sequences previously listed in the GenBank database, and this is an important limitation of the 23S primers. This is mainly because most phytoplankton researchers have paid more attention to the molecular taxonomy of the 16S rDNA region than the 23S rDNA region. Although many more 16S rDNA sequences have been deposited in the database, it is difficult to design the “universal primers” that will amplify all the prokaryotic and eukaryotic algal taxa that correspond to the 16S rDNA region. In fact, most studies that have used the universal primers have been conducted to determine the biodiversity of a specific taxon or group , 2015. IAfter processing the raw reads, the numbers of end-paired amplicons obtained from each respective sample ranged from 290,082 to 639,836, and averaged 438,896 . CompareThis economic metabarcoding strategy enables large amounts of data to be analyzed at one time and will allow researchers to obtain novel knowledge. We recognize that certain features of the sampling methods should be changed; specifically, the filtered water volume should be 10 L per sample, as opposed to the 0.5 L volume used in our phytoplankton survey. A previous study showed that OTU richness was greater with increased filtered water volume , 2015; t10.7717/peerj.2115/supp-1Supplemental Information 1Click here for additional data file.


Saccharina, Undaria and Sargassum – brown seaweeds, and Gracilaria, Kappaphycus and Eucheuma – red seaweeds). While there is some variability in biochar properties as a function of the origin of seaweed, there are several defining and consistent characteristics of seaweed biochar, in particular a relatively low C content and surface area but high yield, essential trace elements  and exchangeable cations (particularly K). The pH of seaweed biochar ranges from neutral (7) to alkaline (11), allowing for broad-spectrum applications in diverse soil types. We find that seaweed biochar is a unique material for soil amelioration that is consistently different to biochar derived from ligno-cellulosic feedstock. Blending of seaweed and ligno-cellulosic biochar could provide a soil ameliorant that combines a high fixed C content with a mineral-rich substrate to enhance crop productivity.Seaweed cultivation is a high growth industry that is primarily targeted at human food and hydrocolloid markets. However, seaweed biomass also offers a feedstock for the production of nutrient-rich biochar for soil amelioration. We provide the first data of biochar yield and characteristics from intensively cultivated seaweeds ( In contrast, it has recently been demonstrated that biochar can be produced from seaweed to yield a product with several defining characteristics for applications in diverse fields278−1, ~78% global annual seaweed productionGracilaria edulis, Eucheuma spinosum and Kappaphycus alvarezii , and Saccharina japonica, Undaria pinnatifida and Sargassum sp.  (hereafter referred to by genus). Collectively these species account for 75% of global seaweed cultivation and are immediately available to support large-scale environmental biotechnologies based on biochar.Here we provide the first data on the yield and characteristics of biochar produced from species of seaweed that are cultivated at scale and which are commercially available. This study has two main aims. First, we produce biochar from commercially available seaweed feedstock that represents the predominant biomass sources currently available for large-scale biochar production  and three were brown seaweeds .Seaweed biochar was produced from six species of seaweed and each of these species was collected from two geographically distinct locations that are representative of the dominant sources of each biomass feedstock . Three iThe six species of seaweed yielded between 45-62% biochar after slow pyrolysis for 60 14min at 450°C and biochar yield did not differ significantly between biochar produced from red and brown species of seaweed . The biochar samples were relatively consistent with respect to their C, H and O contents regardless of species, location or division  and the organic C content comprised more than 85% of the total C content for all samples .−1, and K from 5.1–119 14g kg−1 (−1 (Eucheuma had a higher surface area (30 14m2 g−1) than biochar produced from the other species (<10 14m2 g−1)  . The sea4m2 g−1) .Saccharina from the two locations had very different concentrations of K (8.9 and 51.9 14g kg−1), while Sargassum from different locations had very different yield (49 and 62%) and S content (0.9 and 2.8%) , as well as the yield and pH as input variables . Biocharnd 2.8%) .Undaria and Kappaphycus which differed by an order of magnitude depending upon location  and with a basic pH. There was, unsurprisingly, some variability in the characteristics of seaweed biochar produced from species collected from different locations. Further research should clearly consider environmental factors that might affect the spatial and temporal variability in seaweed biochar properties if large-scale production from cultivated seaweed is to occur. Nevertheless, the overriding conclusion of our work is that seaweed biochar is fundamentally different to biochar produced from ligno-cellulosic feedstock. Seaweed yields more biochar than ligno-cellulosic biomass during pyrolysis, and the resulting biochar has a relatively low C content, but high concentrations of N, P and exchangeable K and Na relative to ligno-cellulosic feedstock. The seaweed biochars also have a much lower BET surface area than ligno-cellulosic biochar−112Gracilaria, Saccharina and Undaria biochars have a C/N ratio < 20, indicating they could directly contribute bioavailable N and P to soils, in addition to enhancing the retention of supplemental nutrients provided in the form of fertilizer. This prediction is supported by the known beneficial effects of other seaweed biochars on crop productionThe combination of the low C content but high mineral content of seaweed biochar results in a low HHV of seaweed biochar in comparison to ligno-cellulosic biochars, which can exceed 30 14MJ kgThe main limitation of seaweed biochars that requires consideration is the high concentration of exchangeable Na which could increase soil salinity. Previous research suggests that the Na component of seaweed biochar is leachable, but levels are within biosolids limits, and overall positive short-term effects on crop productivity have been described following the application of seaweed biochar to low fertility soilsOrg content of 30%, the scope for C sequestration from seaweed biochar derived from commercially cultivated seaweeds is 0.33 14Mt C yr−1. These figures do not take into account energy costs in the production process as the energy balance of biochar production varies greatly with the scale of the production system2 emissions each year, but is also a non-renewable resource that is being increasingly degradedIncreased seaweed cultivation has been proposed as a sink of “Blue Carbon” in climate change mitigation strategies17In conclusion, we found that biochar can be produced from a range of commercially cultivated seaweeds to yield unique ameliorants that could be applied to improve soil fertility. Biochar produced from red species of seaweed has higher concentrations of K and S, and lower C, H and pH than biochar produced from brown species of seaweed. However, while some properties of seaweed biochar unsurprisingly vary between seaweed divisions and origin of seaweed feedstock, seaweed biochar is consistently different to biochar produced from ligno-cellulosic feedstock with respect to its key characteristics, having low C content but high concentrations of exchangeable nutrients . Therefore, opportunistic harvesting of seaweed blooms such as those that regularly occur in China24Gracilaria edulis, Eucheuma spinosum and Kappaphycus alvarezii , and Sargassum sp., Undaria pinnatifida and Saccharina japonica  (hereafter referred to by genus). Each species was sampled from two geographically distinct regions  was achieved, the samples were left in the furnace at a constant temperature for 60 14min After 60 14min the stainless steel vessel was removed from the furnace and the vessel and biochar was cooled to room temperature while N2 purging continued. The mass of biomass and resulting biochar was recorded to the nearest 0.1 14g before and after pyrolysis respectively to ascertain the yield of biochar, which was expressed as the % of original biomass retained as biochar.Each of the seaweed samples were converted to biochar independently using optimized production conditions that have been previously described23 and 1.0 14ml analytical grade H2O2. The solution was left for 2 14h at room temperature then heated in a microwave to 180°C for 10 14min, then finally diluted with Milli-Q water. The concentrations of P and K were measured with a Varian Liberty series II ICP-OES. Multi-element standard solutions containing the elements of interest were used for calibration and the results were reported after subtracting the procedural blanks. The standards were obtained from Choice Analytical . The Higher Heating Value (HHV) was estimated on the basis of the elemental composition2 mixtures according to Australian standard methods for soil analysis2 adsorption  and Cation Exchange Capacity (CEC) by silver thiourea (AgTU) extracts . Each of these analyses was conducted on a single sample of each species due to the large sample requirements for each measurement.Each biochar sample was characterized for a range of physico-chemical properties. The carbon (C), hydrogen (H), oxygen (O), nitrogen (N) and sulphur (S) contents of each sample were quantified in triplicate using an elemental analyser , while phosphorus (P and K) were measured by Inductively Coupled Plasma Optical Emissions Spectrometer (ICP-OES) after acid digest. First, 100 14mg of the biochar was placed in a Teflon digestion vessel with 3.0 14ml double distilled HNOth root transformed to standardise the measurements and a similarity matrix was constructed from the transformed data using Primer 6, version 6.1.14 (Primer-E Ltd.).Two-tailed t-tests were also performed to test differences between red and brown seaweeds with respect to yield, elemental profile , pH, and CEC. The t-tests used mean values for each species to allow a specific contrast between red and brown seaweed groups.A multivariate resemblance matrix was produced to visualise multivariate properties of seaweed biochar from different locations, species and divisions. This resemblance matrix was visualised using a Canonical Analysis of Principal Coordinates (CAP) ordination with a vector overlay of Spearman rank correlations (limited to variables with a length of at least 0.5). The analysis included yield, C, H, O, N, S, P, K and pH as variables for each sample. The HHV and C/N data were excluded from the analysis as these are auto-correlated with the elemental profiles, while BET and CEC were excluded as they were only measured on individual samples for each species as described in the methods section. The data were 4D.R. conducted the analyses and wrote the manuscript; R.D.N. and N.A.P. obtained funding and assisted with experimental design; S.D. and M.I.B. obtained algal samples and prepared biochar. All authors reviewed the manuscript.Supplementary Information


Previous studies have suggested that female sex hormones have a protective action, because they contribute to reduce the inflammatory degree in females after trauma.This study aimed to investigate sex differences in the course of the inflammatory process in rats subjected to brain death (BD).n = 5; female rats, n = 10; and ovariectomized rats, n = 5) and subjected to BD by rapid inflation of a catheter Fogarty® 4F. The liver, kidneys, lungs and the heart were collected after 6 hours and samples (4 µm) were stained with H&E for histological analyses. Leukocyte infiltration, edema and hemorrhage were measured and data were compared using GraphPad Prism v.6.10, and p values lower than 0.05 were considered significant.Wistar rats were randomized into three groups  and presented also a sudden decrease in estradiol levels 6 hours after BD (p = 0.01). The intensity of hemorrhage was greater in ovariectomized rats compared with the other groups (p = 0.001) in the lungs. All groups presented slight to moderate leukocyte infiltration and absence to slight hemorrhage in the liver. Leukocyte infiltration had a wide distribution in female rat kidneys, and in male and ovariectomized rat kidneys infiltration varied from absent to slight.Female rats exhibited increased leukocyte infiltration into the lungs and the heart when compared with male rats (The increased inflammation in the lungs and heart of female rats might be a result of the lack of female sex hormones. Therefore, the idea of introducing a therapeutic use of female sex hormones on female BD donors could be considered.


AbstractEuterpe , a genus from Central and South America, has species with high economic importance in Brazil, because of their palm heart and fruits, known as açaí berries. Breeding programs have been conducted to increase yield and establish cultivation systems to replace the extraction of wild material. These programs need basic information about the genome of these species to better explore the available genetic variability. The aim of this study was to compare Euterpeedulis , Euterpeoleracea  and Euterpeprecatoria , with regard to karyotype, type of interphase nucleus and nuclear DNA amount. Metaphase chromosomes and interphase nuclei from root tip meristematic cells were obtained by the squashing technique and solid stained for microscope analysis. The DNA amount was estimated by flow cytometry. There were previous reports on the chromosome number of Euterpeedulis and Euterpeoleracea, but chromosome morphology of these two species and the whole karyotype of Euterpeprecatoria are reported for the first time. The species have 2n=36, a number considered as a pleisomorphic feature in Arecoideae since the modern species, according to floral morphology, have the lowest chromosome number (2n=28 and 2n=30). The three Euterpe species also have the same type of interphase nuclei, classified as semi-reticulate. The species differed on karyotypic formulas, on localization of secondary constriction and genome size. The data suggest that the main forces driving Euterpe karyotype evolution were structural rearrangements, such as inversions and translocations that alter chromosome morphology, and either deletion or amplification that led to changes in chromosome size. Euterpe  (Arecaceae-Arecoideae), is composed of seven species distributed from Central to South America , Euterpeoleracea  and Euterpeprecatoria  are considered the most important species of the genus due to their wide distribution and economic importance of their fruits and palm hearts, obtained mainly by extractive activity in Brazil (Euterpeoleracea), has encouraged the development of genetic improvement programs to produce cultivars with higher yield and better quality of fruits and palm heart. In addition to the economic value, cultivation instead of extraction of wild material should favor the conservation of those species, which is urgent in the case of Euterpeedulis since it is a threatened species. America . In Brazn Brazil . The higEuterpeoleracea and Euterpeedulis (2n=36) was reported in Euterpe. Arecaceae and found highly differentiated interphase nuclei, ranging from reticulate and semi-reticulated to an intermediate stage between semi-reticulate and areticulate.Cytogenetic data are critical for germplasm manipulation for such programs, especially when the use of interspecific hybrids is considered as a strategy to increase the variability and to incorporate alleles of interest (Bovi 1987). However, only the chromosome number of Euterpeprecatoria, was the single species analyzed, showing 5.31 pg (1C).Determination of genome size in plants has been recognized as a significant parameter for genomic characterization and may assist in evolutionary studies , geneticEuterpeedulis, Euterpeoleracea and Euterpeprecatoria and discuss the karyotypic evolution within the genus.Therefore, the aims of this study were to compare karyotype, interphase nucleus pattern and genome size of Euterpeoleracea and Euterpeprecatoria. The company Infrater Engenharia LTDA, headquartered in Ipatinga-MG, donated seeds from five specimens of Euterpeedulis.The Açaí Palm Germplasm Bank (Banco de Germoplasma de Açaizeiro - BAG-Açaí), from Embrapa Amazônia Oriental in Belém-PA, Brazil, provided seeds from five specimens of PageBreakRoots originating from germinated seeds were pre-treated with 2 mM 8-hydroxyquinoline for 7 h at 4 °C. Slides were prepared by the squashing technique following cell wall digestion with pectinase/cellulase (100/200U) solution at 37 °C for 1.5 h. Staining was performed with 1% propionic carmine for the analysis of the mitotic metaphases and 5% Giemsa for the evaluation of the interphase nuclei. The images were acquired in a bright-field microscope (Leica DMLS) equipped with a digital camera .HCTL = ∑Lti), the centromeric index (CI=[SA/(SA+LA)]×100) were calculated. The chromosomes were classified based on their centromere position according to The short and long arms  of chromosomes were measured using the IMAGE TOOL 3.00 program from UTHSCA . The mean lengths of SA and LA of each chromosome were obtained from measurement of five different metaphases from each species and were used to prepare the ideograms. The chromosome total length (TL = SA + LA), the haploid complement total length , similar chromosome sizes and differ regarding chromosome morphology  and one submetacentric chromosome (13). Chromosome pair 17 is the only one in the complements that differs regarding centromere position in all three species; it is metacentric in Euterpeoleracea, submetacentric in Euterpeprecatoria and acrocentric in Euterpeedulis  in Euterpeoleracea and on the long arm of pair two (submetacentric) in Euterpeprecatoria  in ria Fig. .Euterpeprecatoria showed HCTL and DNA content significantly higher than that of Euterpeedulis and Euterpeoleracea (Table coefficient of variation (CV) of flow cytometry data was 0.52%, which demonstrates the reliability of DNA amount estimation, since only CVs up to 2% indicate high quality analysis . The hypothesis is that starting from 2n=36 (basic number x=18) different and independent reduced dysploid series diverged not only in Arecoideae (2n=28 to 2n=36), but also in Coryphoideae (2n=28 to 2n=36) and Calamoideae (2n=26 to 2n=36)  .Euterpe species studied, these data indicate that the rearrangements may be responsible for karyotype variation among the three Euterpe species studied.The analyzed karyotypes showed differences in centromere and secondary constriction position. The chromosomes may differ in terms of centromere position, according to Coryphoideae subfamily, describing the presence of secondary constrictions in 10 of them. The author found a single pair of chromosomes bearing secondary constriction in eight species: Livistonachinensis Brown, 1810, Pritchardiathurstonii Mueller & Drude, 1887, Braheaedulis Wendland ex Watson, 1876, Coperniciamacroglossa Wendland, 1907, Washingtoniarobusta Wendland, 1883, Sabalminor , Bismarckianobilis Hildebrandt & Wendland, 1881 and Phoenixcanariensis Chabaud, 1882. The other studied species showed two pairs or no pairs of chromosomes with secondary constriction.Most karyotype studies on palm trees do not include data on the number and location of secondary constrictions. The study performed by Arecaceae subfamilies, mainly based on plant morphological characteristics, with the characterization based on the interphase nuclei and karyotypes  has shown to be highly correlated with Feulgen densitometry ones. However, despite of being a well stablished method for DNA quantification, Feulgen densitometry has some critical points in the procedure that can affect its precision  should be used to unravel the mechanisms involved.Differences in genome size and chromosome morphology among the three


Although resistance can occur among separate populations of a species across the landscape, the spatial scale of resistance in many weeds is often left unexamined. We assessed the potential that resistance to the herbicide glyphosate in the agricultural weed Ipomoea purpurea has evolved independently multiple times across its North American range. We examined both adaptive and neutral genetic variations in 44 populations of I. purpurea by pairing a replicated dose–response greenhouse experiment with SSR genotyping of experimental individuals. We uncovered a mosaic pattern of resistance across the landscape, with some populations exhibiting high-survival postherbicide and other populations showing high death. SSR genotyping revealed little evidence of isolation by distance and very little neutral genetic structure associated with geography. An approximate Bayesian computation (ABC) analysis uncovered evidence for migration and admixture among populations before the widespread use of glyphosate rather than the very recent contemporary gene flow. The pattern of adaptive and neutral genetic variations indicates that resistance in this mixed-mating weed species appears to have evolved in independent hotspots rather than through transmission of resistance alleles across the landscape.Strong human-mediated selection  The evolution of herbicide resistance in weedy plants is an excellent example of adaptation to strong human-mediated selection , then it is inferred that populations are independently evolving resistance across the landscape. In this case, a pattern of high neutral genetic structure across populations would suggest rather limited gene exchange among populations, supporting the possibility that populations are independent evolutionary units. Hence, pairing an assessment of the level of resistance across the landscape with investigation of the genetic structure of a weed can allow us to identify the evolutionary units of herbicide resistance  Is there a geographic mosaic pattern of glyphosate resistance in I. purpurea, indicating that resistance has evolved independently in separate populations across the landscape, or is there a pattern of isolation by distance suggesting a single origin? (ii) Does the pattern of neutral genetic structure across this species' range provide evidence that populations are genetically isolated or that gene flow, whether historical or contemporary, has occurred or is occurring? and (iii) Is there evidence for migration between populations of the southeastern USA after glyphosate was put into widespread use across the landscape, indicating that contemporary gene flow is responsible for the spread of resistance? While the majority of studies that assess neutral genetic variation in herbicide-resistant weeds have investigated either predominantly outcrossing, wind-pollinated species, or alternatively highly selfing species, the work presented herein considers a species that exhibits a mixed-mating system, and one that, by all indications, is in the early stages of glyphosate-resistant evolution across the landscape.Defelice . This spDefelice , which iDefelice . AdditioDefelice . AlthougDefelice , we currI. purpurea located within soya, cotton, corn or alfalfa fields selected at random from six states across the Midwestern and Southeastern USA . Ten seeds from each population  were scarified and then planted in pine bark soil in SC10 super containers  in each of six experimental treatments, described below. Individual plants were randomly assigned to racks that were then randomly assigned to flow trays (four racks per flow tray). Pots were watered daily, and flow trays were filled with water to prevent desiccation. Only plants that germinated prior to June 26, 2013, were included in the experiment—however, germination was high  in both experiments and ranged from 50 to 100% among populations. A total of 4614 plants were used in our resistance assays, with 1995 and 2619 individuals planted in each experiment. The number of individuals per population and treatment combination used in the experiment can be found in 2-pressurized sprayer . The same applicator treated each of the two replicate experiments. We sprayed plants at a rate of 187 liters/ha at 30 psi with a stride pace of 90 paces per minute at 1.5 meters above the plants. Three weeks after glyphosate application, we scored survival and the height of the living stem of each plant.We measured the height of the stem and number of leaves of each individual 3 weeks after planting, when the majority of individuals were at the 5-leaf stage. Average height of the plants prior to herbicide application was 13.1 ± 0.3 cm. Plants were then sprayed with RoundUp PowerMax  at rates around the recommended field rate (1.54 kg ai/ha) of 0, 0.21, 0.42, 0.84, 1.70, and 3.40 kg a.i./ha (the 0 kg a.i./ha treatment was used as a water control) using a handheld, COμl for subsequent PCR. We identified 15 SSR loci that showed compatibility for multiplexing and were easily scorable of 20 that were previously described for I. purpurea . All DNA samples were quantified by spectrophotometry and diluted to 20 ng/purpurea . Forwardμm of IP8, IP2, IP27, 0.20 μm of IP31, and 0.25 μm of IP34, IP18, and IP1. The second multiplex consisted of 0.05 μm IP36, 0.10 μm of IP47, 0.15 μm of IP6, and 0.25 μm of IP12, IP21, IP45, IP26, and IP42. Ten microlitre PCRs were run with Qiagen Master Mix . Thermocycler conditions consisted of 95°C for 3 min, 35 cycles of 94°C for 30 s, 50°C for 90 s, 72°C for 60 s, and a final extension at 72°C for 10 min on an Eppendorf  MasterCycler Pro thermacycler. One microliter of PCR product was used for fragment detection using an Applied Biosystems 3730 DNA Analyzer  at the Cornell Life Sciences Core Facility . An ABI GS500 for multiplex 1 and GS600 for multiplex 2 size standards were used for fragment length comparison. All sample genotypes were analyzed using Applied Biosystems PeakScanner 1.0 analytical software . A PP (Primer Peaks adjustment) sizing default was used for the analysis.Because fragment size and dye incompatibilities precluded running all 15 loci in one multiplex, we split loci into two multiplex PCRs. One multiplex consisted of 0.15 We included populations with at least 10 germinants per experiment  in the analyses of spatial variation of herbicide resistance. We first report a species dose–response curve and then follow with patterns of survival across populations at doses above the recommended field rate.R = 0.480, P = 0.004), showing that although we identify differences in the survival of plants in separate greenhouse experiments, the populations performed similarly relative to one another in the different experiments. To estimate the dose–response curve, we first fit the residuals by regressing a general linear model of survivorship on experiment with a binomial distribution to account for the effect of replicate. The residual data were then fit to a Weibull 2.4 parameter model (Weibull 50) was expressed as:Preliminary analysis showed a significant effect of replicate experiment on the proportion that died. Thus, we used residual values after accounting for the effect of greenhouse experiment to estimate our dose–response curves. The use of residual is recommended by Kelly and Rice  to smoot Weibull  using th Weibull  in R (R  Weibull . The WeiY is the response (survivorship), c is the upper limit of the curve, d is the lower limit of the curve, e is the ED50, and b is the relative slope around e. We first estimate a species-level ED50 using all individuals, followed by a regional (Southeastern and Midwestern USA) ED50 value, and ED50 values per state. We included state in the models because we hypothesized that management policies and herbicide procedures might vary at the state level, and this could influence the level of resistance among states.where We assessed survival at the 1.7 and 3.4 kg a.i./ha treatment levels (a rate that is similar to the suggested field rate of 1.54 kg a.i./ha and a dose that is twice that) to determine whether there was a significant effect of population, state, and/or region of origin on survival postherbicide. To do this, survival was modeled as a binary character (1/0) in a generalized linear model with a binomial distribution using the lmer option of the lme4 package Bates  in R R . Fixed eWe calculated Moran's I to determine whether there was a correlation between survival following herbicide application and geographic distance. Specifically, we calculated the correlation between survivorship and its spatial lag using the Spatial Autocorrelation Analysis in Macroecology . We used MicroChecker .We assessed patterns of neutral genetic variation across this species' range using a variety of metrics to determine whether genetic diversity and population structure were influenced by recent selection kerham's  θ using kerham's . A confiamova to test the level of genetic differentiation across regions , states within regions , and populations nested within states using GenAlEx v. 6.1 ), were assessed from five runs using a range of k values from 1 through 35. We used the delta-k method , and Cavalli-Sforza distance over the natural log of geographic distance using ISOLDE, Option 6 in GenePop  and a third scenario assumed admixture after the use of glyphosate (time t5) within NC and TN regions.We next used a Bayesian coalescent approach , which is the year that RoundUp was approved for chemical weed control (Duke and Powles t3), from an initial effective population (Ne) size ranging between 250 and 1000 individuals, which encompasses the range of previously estimated Ne for I. purpurea  had previously been described in Defelice , which is similar to the manufacturer's recommended field dose of 1.54 kg a.i./ha. Twelve populations, all of which were from VA, SC, NC, and TN, exhibited a proportion survival that was significantly higher than the species average, that is, resistance values that were greater than the species 95% CI  and state on survival , but we observed no isolation by geographic distance across all sampled populations in survival . The Southeastern USA exhibits greater diversity in the proportion survival per population than the Midwestern USA; although the most resistant populations do not, in general, cluster together in a PCoA  and observed (Ho) heterozygosity ranged between 0.230–0.372 (mean = 0.304) and 0.191–0.400 (mean = 0.294), respectively , and allelic richness per multilocus genotype × population combination ranged between 1.23 and 1.37 (mean = 1.30). Expected , and populations within states . The majority of genetic variation in I. purpurea is found within populations .The FST across the species' range to be 0.127, (95% CI: 0.071–0.183), which is lower than a previous estimate using floral color . One hundred and eight (21%) of 595 pairwise-FST values between populations were significantly greater than 0, and ranged from 0.035 . Of the significant FST values among states, the majority were observed between populations in TN and NC (15%) and SC (15%)—interestingly, these were states in which we observed highest levels of resistance. There was, however, no indication that resistant populations exhibited more or less differentiation compared to other populations, as the majority (64%) of the significant pairwise-FSTs were among populations that exhibited resistance values within the species' 95% CI, and, less than 2% of the significant pairwise-FSTs were between resistant and susceptible populations.We estimated Weir and Cockerham's  FST acroI. purpurea was k = 3 (ln(P(D) = −8265.7). All 3 genotypic clusters were found within individuals sampled from North Carolina suggesting that populations within this state are either the source of introduction for other weedy populations or this state has had multiple introductions of different seed lots.Further, although we found a moderate level of genetic differentiation across populations sampled from North America, our STRUCTURE analysis uncovered a pattern of widespread migration and admixture among individuals within populations Fig. . The mosamova result for regional genetic differentiation . However, these populations were contained within the range of variation across the Southeastern US populations  or ‘susceptible’  in PC1 or PC2 mean scores . Hence, there was no indication that the neutral genetic variation of this species clustered according to resistance status rather than geography, as would be expected if propagules from, for example, resistant TN populations had migrated to the resistant Carolina populations and established and/or admixed. We did not uncover evidence of isolation by distance using linearized FST over geographic distance , nor did we uncover significant isolation by distance measured as the Cavalli-Sforza Edwards chord distance . Pairwise estimates of Nei's genetic distance similarly did not correlate with geographical distance , reinforcing our finding of either widespread gene flow across populations or colonization following a recent bottleneck.Our PCoA of neutral genetic variation revealed a slight clustering of Midwestern US populations, which had similarly been found in the ons Fig. , and theWe found overwhelming support for admixture prior to glyphosate use  and that it is unlikely increased resistance is due to contemporary gene flow between populations, but rather, results from independent regimes of selection via the herbicide. We discuss each of these main points below.Our comprehensive analysis of herbicide resistance and neutral genetic variation in the weed that is, resistant populations were located near susceptible populations—suggesting that resistance has independently evolved across disparate areas of this species' distribution. This pattern of potentially independent resistance hotspots has been shown in other resistant weed species  , we uncovered populations that exhibited very high or very low survivorship postherbicide application. Populations that exhibited high survival and thus high resistance did not appear to cluster in one region of the landscape—50 estimates and survivorship compared to Midwestern US populations. Because management practices are often regulated at the state level, it is possible that the difference in resistance between regions may result from differences in the recommended dose across areas. For example, TN has the highest recommended application rate in corn  as does survival postherbicide , we find little evidence for a geographic pattern to that structure beyond the slight clustering of Midwestern US populations identified in the PCoA. In particular, we found no isolation by distance within the species, suggesting a scenario of either widespread gene flow between populations or their relatively recent colonization.With some notable exceptions , but still historical gene flow is responsible for the low genetic differentiation. Populations then went through rapid adaptation of increased resistance across separate areas within the past ∼20 years due to the prevalent use of Roundup herbicide. To conclusively rule out the possibility that rare gene flow events may have introduced resistance alleles across disparate areas, however, we will need to determine whether the genetic basis of resistance across populations differs, and perform an analysis of the phylogeographic history of resistance alleles.An interesting and remaining question is whether or not the potential independent evolution of resistance is due to selection on pre-existing and hence similar genetic variation, or due to novel mutations in the same or different genomic architecture. Previous work in this species has identified genetic variation for glyphosate defense in accessions of


Introduction. A family history of Alzheimer's disease is a significant risk factor for its onset, but the genetic risk associated with possessing multiple risk alleles is still poorly understood. Methods. In a sample of 95 older adults , we constructed a genetic risk score based on the accumulation of risk alleles in BDNF, COMT, and APOE. A neuropsychological evaluation and consensus determined cognitive status . Logistic regression was performed to determine whether the genetic risk score predicted cognitive impairment above and beyond that associated with each gene. Results. An increased genetic risk score was associated with a nearly 4-fold increased risk of cognitive impairment  when including the individual gene polymorphisms as covariates in the model. Discussion. A risk score combining multiple genetic influences may be more useful in predicting late-life cognitive impairment than individual polymorphisms.  TS) of AD . In the 4 allele , and ε4  decline , 7. APOE, other genetic variants have been identified as risk factors for cognitive decline because they influence biological pathways involved in memory and executive function, which exhibit the earliest deficits during the progression of AD [ BDNF gene codes for brain-derived neurotrophic factor, a protein secreted by neurons that promotes neurogenesis and synaptic plasticity and transmission in the central nervous system; BDNF is particularly critical for learning and memory processes because it facilitates long-term potentiation in hippocampal neurons [ BDNF gene, variation in the protein's function has been attributed to a single nucleotide polymorphism  resulting in a valine  to methionine (Met) substitution at codon 66. The Met-substituted product is associated with impaired intracellular trafficking and secretion of BDNF, poorer performance in declarative memory [ Met allele confers an increased risk of AD [In addition toon of AD . For exa neurons . AD has  neurons . BDNF al neurons . Age-rel neurons . In the e memory  and exece memory , and rede memory –16. Despe memory  and candsk of AD , 19, sug APOE and BDNF, the catechol-o-methyltransferase (COMT) gene codes for an enzyme responsible for catalysis and inactivation of catecholamine neurotransmitters such as dopamine, norepinephrine, and epinephrine [ COMT  involves a substitution of Val by Met at codon 158, the product of which is four times less metabolically active than the homozygous Val allele product [ Met carriers relative to Val homozygotes [ COMT polymorphism and AD has not been confirmed by GWAS or meta-analysis [ Val allele is associated with characteristics of cognitive decline and dementia such as poorer performance on tasks of executive functioning and working memory [ Val66Met, the COMT Val158Met SNP is likely an under-recognized contributing genetic risk factor in the development of AD.In addition tonephrine . A commo product . Slower ozygotes . Althouganalysis , studiesg memory , declarag memory , and slog memory . As in tAPOE genetic variants  identified by GWAS of AD risk, with each allele weighted by its AD risk odds ratio. Although the weighted genetic risk score was not significant, the authors found that subjects who possessed a total of six or more risk alleles progressed from MCI to AD twice as quickly as those who possessed fewer than six risk alleles. While the accumulation of risk alleles was a significant predictor for rate of progression to AD , each individual genetic polymorphism did not have significant predictive power by itself, with the exception of one marginally significant gene . Similar risk scores have been employed to predict other pathologies such as age-related macular degeneration, multiple sclerosis, and type II diabetes [These and other genetic polymorphisms likely contribute relatively small independent effects to collectively predispose one to develop a complex disease such as AD. Studies have begun to investigate how multiple genetic influences can be aggregated into a single risk profile to predict the prevalence or course of a given pathology, either by summing the total number of risk alleles possessed or by obtaining a weighted sum including each risk allele multiplied by its associated effect size. Rodríguez-Rodríguez et al.  construcdiabetes –30. Thes APOE) or that have an important role in cognitive and brain functions in late adulthood and have a relatively common minor allele frequency  but may have been previously undetected by GWAS due to small individual effect sizes. To test whether the combination of these three risk genotypes was collectively predictive of late-life cognitive impairment, we created a cumulative genetic risk score by summing the possession or absence of each SNP's risk allele. We predicted that a higher genetic risk score would correspond to an increased risk of cognitive impairment above and beyond that of the individual gene polymorphisms.In this genetic risk score study, we took a candidate gene approach by targeting genetic variants that have either been identified as having a clear link with risk for AD  offices , 32. ParOne participant was removed due to incorrectly recorded cognitive data. Since distributions of allelic frequencies differ between races, 4 African American participants were removed from the analysis to minimize confounding by genetic admixture. Age, gender, and years of education were self-reported. All participants signed a consent form approved by the University of Pittsburgh Institutional Review Board and were remunerated $20 for participation.Each participant completed a comprehensive neuropsychological test battery assessing five primary cognitive domains: memory, executive function, spatial ability, language, and attention/psychomotor speed. Measures of memory were the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Learning Test with delayed recall , the Wecn = 44), Mild Cognitive Impairment , or dementia (n = 4). Because of the low number of individuals with dementia, those with either Mild Cognitive Impairment or dementia were combined into a single group labeled “cognitive impairment” (n = 51).A clinical adjudication panel of three expert neuropsychologists  determined cognitive status: normal, mild cognitive impairment (MCI), or dementia. Classifications were done according to the criteria from the University of Pittsburgh Alzheimer's Disease Research Center , 45. DemμL and stored at −20°C.Genomic DNA was collected with the Oragene-DNA Self-Collection Kit OG-500 . Extraction and purification of DNA were completed using the laboratory protocol from Oragene-DNA. DNA was diluted with TE buffer to 10 ng/Val66Met) in BDNF, rs4680  in COMT, and rs429358/rs7412 in APOE . Genotype analysis was performed by high-resolution melting (HRM) analysis. Each polymerase chain reaction (PCR) was performed on a CFX96 real-time PCR system  using 1x Precision Melt Supermix . The reaction volume was 20 μL and contained 50 ng of genomic DNA. See  BDNF were 1 cycle of 95°C for 2 min and 65 cycles of 95°C for 10 s, and 56.6°C for 30 sec. The running conditions for COMT were 1 cycle of 95°C for 2 min and 65 cycles of 95°C for 10 s, and 60.1°C for 30 sec. The conditions for APOE were 1 cycle of 95°C for 2 min and 60 cycles of 95°C for 10 s, 63.8°C for 30 s, and 72°C for 30 sec. The melting range varied per SNP . The demographic variables, consisting of age, gender, and years of education, comprised the 1st block whileP values below 0.05.Hierarchal logistic regression was then performed to determine whether the composite genetic risk score variable (entered as the 3rd block) predicted cognitive status (nonimpaired versus impaired) above and beyond the individual genotypes  and the demographic variables (the 1st block). We report odds ratios (OR) and confidence intervals (C.I.) resulting from these analyses and report  APOE genotype, resulting in an overall failure rate of 7.37% and error rate of 0%). Our final sample size of n = 95 was 64.2% female with a mean age of 75.1 years. Allelic frequencies did not significantly differ from Hardy-Weinberg equilibrium for any of the three genes. P = .025, and 95% C.I. = 1.014, 1.222) and years of education  such that higher age and fewer years of education were associated with a higher risk of impairment. Gender was not significantly associated with an increased risk of impairment , but there were a higher proportion of men in the cognitively impaired group and there is evidence of sexual dimorphism of both BDNF and APOE on risk for AD [ BDNF, COMT, and APOE genotype or the genetic risk score on cognitive status. See Nine participants were excluded  after controlling variation from age, gender, and education. Neither BDNF nor COMT genotype was related to cognitive status .Consistent with the literature,P = .013, and 95% C.I. = 1.333, 10.973) even after including all of the individual gene polymorphisms in the model  while the individual genotypes remained nonsignificant in the full model, with the exception of COMT which reached nominal significance .Follow-up analyses were performed to determine whether the 4 individuals with dementia were driving the association between the genetic risk score and cognitive impairment. After removing the 4 individuals with dementia from the analysis, the risk score remained significant  when controlling individual polymorphisms in BDNF, COMT, and APOE . These results demonstrate that the aggregation of multiple risk genotypes into one total risk score predicted the presence or absence of impairment to a higher degree than any of the individual polymorphisms.We created a genetic risk score to represent the accumulation of risk genotypes of polymorphisms inAPOE) as well as in processes known to present the earliest deficits in AD such as learning, memory, and executive function (BDNF and COMT). Polymorphisms in these genes  have been associated with differential protein function, with possession of each SNP's risk allele  associated with poorer cognitive performance. Our findings support the use of a single genetic risk score to represent the accumulation of genetic influences affecting multiple domains of cognition and brain health in relation to AD, which may be more important in determining cognitive decline than testing individual genotypes. When considered individually, these same genetic polymorphisms contribute small or negligible effects and remain largely undetected by previous GWAs (except APOE) but may still represent influential aspects of AD pathology. These results beg the question of the importance of other risk genotypes not assessed here that could also contribute to risk of AD. Additionally, our results complement previous reports of significant interaction between COMT Val158Met and APOEε4 on risk for AD [ BDNF Val66Met and APOEε4 on hippocampal activity in healthy older adults [ BDNF Val66Met and APOEε4 on episodic memory in cognitively healthy older adults [The genes under consideration for this study were chosen due to their involvement in general neural function . In genetic association studies, hundreds of subjects are genotyped in order to achieve sufficient power to reliably test specific genetic interactions or confirm epistatic effects between genes. However, we still detected an association between higher risk scores and increased odds of being cognitively impaired  significantly predicted late-life cognitive impairment. The risk score was significant above and beyond the effects of each individual genotype. Our findings demonstrate the effectiveness of genetic risk scores and their potential utility as predictors of more genetic variation in cognitive outcomes such as AD than polymorphisms considered individually.In summary, we found that a cumulative genetic risk score across three genes related to cognition, brain function, and risk for dementia (


Global gene expression analysis of tumor samples has been a valuable tool to subgroup tumors and has the potential to be of prognostic and predictive value. However, tumors are heterogeneous, and homogenates will consist of several different cell types. This study was designed to obtain more refined expression data representing different compartments of the tumor.Formalin-fixed paraffin-embedded stroma-rich triple-negative breast cancer tumors were laser-microdissected, and RNA was extracted and processed to enable microarray hybridization. Genes enriched in stroma were identified and used to generate signatures by identifying correlating genes in publicly available data sets. The prognostic implications of the signature were analyzed.C1Q genes and the one associated with good prognosis contained HLA genes. This association with prognosis was seen for other cancers as well as in other breast cancer data sets.Comparison of the expression pattern from stromal and cancer cell compartments from three tumors revealed a number of genes that were essentially specifically expressed in the respective compartments. The stroma-specific genes indicated contribution from fibroblasts, endothelial cells, and immune/inflammatory cells. The gene set was expanded by identifying correlating mRNAs using breast cancer mRNA expression data from The Cancer Genome Atlas. By iterative analyses, 16 gene signatures of highly correlating genes were characterized. Based on the gene composition, they seem to represent different cell types. In multivariate Cox proportional hazard models, two immune/inflammatory signatures had opposing hazard ratios for breast cancer recurrence also after adjusting for clinicopathological variables and molecular subgroup. The signature associated with poor prognosis consisted mainly of Our data indicate that the molecular composition of the immune response in a tumor may be a powerful predictor of cancer prognosis.The online version of this article (doi:10.1186/s13058-015-0530-2) contains supplementary material, which is available to authorized users. Gene expression profiling has enabled novel classification of breast cancer into different subgroups. At least five molecular subgroups  have been identified ,2 and adGene expression analyses of tumor samples are generally performed on whole tumor homogenates and thereby represent a pattern that reflects the expression from all cell types present in the tumor. The tumor microenvironment, comprising a large variety of cells, such as fibroblasts, immune cells, and endothelial cells, can constitute a significant part of the tumor and substantially contribute to observed expression patterns. Cells in the microenvironment can influence cancer progression -11 and hFor routine histological diagnosis of surgically removed tumors, formalin-fixed paraffin-embedded (FFPE) tissue is normally used and thus a wide range of FFPE tumors are available for gene expression analyses. However, fixation and embedding have a detrimental effect on RNA quality, resulting in fragmentation and chemical modifications and making it of less use for expression analyses . In thisTumor specimens, from subjects that had given informed consent, were obtained from Skåne University Hospital, Malmö. Ethical permission has been obtained from the local Research Ethics Committee in Lund (Dnr 2009/658). Information about the tumors was obtained from the pathology reports. All tumors were negative for estrogen and progesterone receptors and had no ERBB2 (HER2) amplification. Tumors with sufficient amount of cells in the stromal compartment to allow conclusive microarray analyses were selected. Two of the tumors used for microarray analysis were high-grade, grade III , and one was low-grade, NHG  grade I (1 + 3 + 1 according to the NHG grading system). Two of the tumors were invasive ductal carcinomas, whereas one was reported as a medullary carcinoma.Five consecutive sections (5 μm) of each tumor were prepared on a microtome and mounted onto polyethylene terephtalate (PET) membrane slides . When indicated, 30% ethanol was included. Mounted tissue sections were allowed to dry for 30 minutes in room temperature prior to incubation in −20°C for 24 hours for optimal adhesion. To preserve the RNA quality in the archived FFPE tissue specimens, the blocks used for biomarker analysis during the routine prognostic procedure were stored in 4°C.During method development, staining of the tissue sections with either a cresyl violet LCM staining kit  or standard hematoxylin-and-eosin staining was evaluated. For further analysis, cresyl violet staining was used. Tissue sections were initially rinsed 2 × 1 minute with xylene for deparaffinization and rinsed in 100%, 75%, and 50% ethanol for 30 seconds. Rehydration of the tissue with diethylpyrocarbonate (DEPC)-treated water was performed prior to 40-second incubation in staining solution, followed by additional rinsing with DEPC-treated water for 30 seconds and dehydration with 100% ethanol twice for 30 seconds. Sections were thereafter dried in room temperature and immediately used for LCM or stored at 4°C for up to 1 week.LCM to isolate tumor compartments was performed on a Leica LMD6500. After microdissection, the tissue was collected in 0.5-mL polymerase chain reaction (PCR) tube caps containing Allprep RNA/DNA FFPE kit lysis buffer  with Proteinase K.RNA was extracted by using Allprep RNA/DNA FFPE kit (Qiagen) and evaluated with Nanodrop and Bioanalyzer  in accordance with standard procedures, including calculation of RNA integrity number (RIN) values as previously described . IsolateTCGA expression data were downloaded November 2013 (breast cancer), January 2014 (kidney and lung cancer), and March 2014 (head and neck cancer) from the TCGA database . The datAll analyses were done with R by using the limma, survival, and cluster packages. Breast cancer subtypes were determined by using the nearest correlations with the PAM50 centroids . For anaTo obtain RNA of sufficient quality from tumor compartments isolated with LCM, sectioning, mounting, deparaffinization, and staining steps were performed with the highest possible purity to avoid RNase contamination. Adhesion of the tissue section to the membrane slide was obtained with 30% ice-cold ethanol  and by applying a variance filter, which removed probes with variance of less than 0.15. The remaining 5,971 probes were analyzed for difference in expression between stroma and cancer cells by using the limma package in R.P value of less than 0.05, that had higher levels in stroma and 48 probes  and decorin (DCN). There was also enrichment of genes related to an immune response such as chemokines (CXCL12 and CCL19) along with their receptors (CXCR4 and CCR7), matrix metalloproteases (MMP2 and MMP9), the T cell-specific genes CD4 and granzyme K (GZMK), and the B cell-specific immunoglobulin genes such as both heavy  and light  chain-encoding genes. This indicates that the analysis has worked technically and that it identifies genes that are essentially stroma-specific in their expression. On the other hand, several of the genes in the cancer cell compartment are epithelial, such as the cadherin family member desmoglein (DSG2), intracellular junction protein desmoplakin (DSP), the epithelium-specific transcription factors (ELF3 and 5), keratin 7 (KRT7), claudin 4 and 7 (CLDN4 and 7), and integrin beta 8 (ITGB8).Even if only three tumors were analyzed, this approach identified 107 probes , indicating that a multivariate model may be more appropriate. Therefore, we performed both forwards and backwards selection to identify an optimal model. The P value of the likelihood ratio test of the model was used as an indicator of the quality of the model. This resulted in an optimal model that contained four signatures. A multivariate analysis with these signatures indicated that two (1 and 13) were associated with an increased and two (5 and 12) with a decreased risk for new tumor event , ARHGEF15, ROBO4, and ELTD1 and other endothelial markers such as CD34, CLEC14A, and ESAM. Several (7/12) of the genes in gene sets 4 and 5 were identified in the angiogenesis signature obtained from 1,250 tumors from different cancer types [Sets 4 and 5 contain genes typical of endothelial tissue, both actual angiogenic regulators er types .CD3 , CD4, ZAP70, GIMAP and granzymes (GZMA/GZMK and GZMM), major histocompatibility complex (MHC) II-encoding HLAs, and more general lymphocyte-associated genes such as LAIR1 and LST1.The remaining gene sets contain genes typical of immune and inflammatory cells, such as T cell-associated Cox proportional hazard analyses revealed only limited value of the gene signatures in univariate models, which suggest that neither the amount of stroma nor the extent of vascularization or the magnitude of inflammatory components has prognostic information as isolated variables. However, in a multivariate model, four of the gene signatures were significant. Sets 1 and 13 are associated with an increased risk for new tumor event, whereas gene sets 5 and 12 negatively influenced the HR.FAP) was identified in gene set 1 together with fibroblast-expressed extracellular matrix-associated genes, such as collagens, whereas gene set 13 contained complement factor C1Q. FAP has been identified as a prognostic marker in various cancer studies, including breast and lung cancer, and has been suggested to be a potential target in solid tumors [A typical fibroblast marker  and angiogenesis-regulating genes, such as TEK and ELTD1 (gene set 5). ELTD1 expression has previously been shown to be associated with an improved outcome [HLA-DR have been shown to predict better prognosis of invasive ductal carcinomas [The gene sets with negative HR contain several MHC-II-encoding  outcome  which marcinomas . The sigA more limited Cox model based on only the immune gene signatures 12 and 13, with or without lymph node status and stratification for subtype in the model, could also predict recurrence. The opposing effects by these signatures on the risk indicate that the composition of the immune response in the tumor is of importance for the progression. This conclusion is further supported by the fact that the signatures are predictive in a multivariate Cox model in several other tumor forms and other breast cancer data sets. It suggests that the importance of specific components of the immune response for progression of the disease may be a general phenomenon applicable to several cancer forms.C1Q and HLA genes, respectively. C1Q genes have been shown to be produced by a number of cells, including monocytes, macrophages, and dendritic cells [C1Q has previously been reported to be highest in immature immune cells that are known to reflect a state of immune paralysis in cancer immunology [HLA genes may be indicative of a more active immune response. This assumption is further supported by the screen  and macrophage genes . On the other hand, genes that were associated with a lower risk in a multivariate model with the C1Q signature , CD8A, CD27, CD52, CD96, PYHIN1, SLAMF6, and IL12RB1). The number of genes with both high correlation of their expression and similar prognostic value indicates that it may be possible to identify fairly large gene sets that could be used as markers for the profile of an intra-tumor immune response. It thereby highlights potential factors determining this profile.The prognostic signatures contain mainly ic cells . Howevermunology ,48. Theren Table  for immu+ T cells, namely follicular helper T cells, predicts breast cancer survival [The results support the idea that the molecular profile of an immune response, rather than the amount of immune or inflammatory cells, is an important prognostic marker in breast cancer and in other cancer forms. Such a hypothesis is further supported by other results, including the finding that the amount of a specific set of CD4survival .We have developed a methodological procedure for isolation and characterization of compartment-specific genes by using LCM on FFPE triple-negative breast cancers. Through expansion of the gene list with data from TCGA of correlating genes, we could identify two immune/inflammatory signatures with prognostic information. The results further underscore the importance of the composition rather than the extent of the immune response as a prognostic indicator in cancer. It also provides novel signatures that are stable indicators of prognosis and valid for some other cancer types as well and highlights genes that may be of particular importance when analyzing the composition of an immune response in a tumor.


Asphodelus aestivus floral nectar and in its typical herbivorous bug Capsodes infuscatus, along an aridity gradient. Bacteria were sampled from floral nectar and bugs at four sites, spanning a geographical range of 200 km from Mediterranean to semi-arid conditions, under open and bagged flower treatments. In agreement with the niche assembly hypothesis, the differences in bacterial community compositions were explained by differences in abiotic environmental conditions. These results suggest that microbial model systems are useful for addressing macro-ecological questions. In addition, similar bacterial communities were found in the nectar and on the surface of the bugs that were documented visiting the flowers. These similarities imply that floral nectar bacteria dispersal is shaped not only by air borne bacteria and nectar consumers as previously reported, but also by visiting vectors like the mirid bugs.Identifying the processes that drive community assembly has long been a central theme in ecology. For microorganisms, a traditional prevailing hypothesis states that “everything is everywhere, but the environment selects”. Although the bacterial community in floral nectar may be affected by both atmosphere (air-borne bacteria) and animals as dispersal vectors, the environmental and geographic factors that shape microbial communities in floral nectar are unknown. We studied culturable bacterial communities in  Identifying processes that drive community assembly have long been a central theme in ecology Until recently, most of our knowledge of the mechanisms that govern species composition and diversity emerged from studies focusing on macro-organisms such as plants and animals One possible mechanism of bacterial dispersal among plant hosts across space is transfer by animal vectors. Most plant species on earth are animal-pollinated Asphodelus aestivus along a 200 km climatic gradient in Israel. The plants' environment may affect nectar production rates, sugar content and chemistry by mechanisms mediated via the plant Capsodes infuscatus bugs attacking A. aestivus. By manipulating the access of nectar consumers to the flower, we constructed a unique experimental system that revealed the role of a potential insect vector versus airborne-origin bacterial sources, in shaping the composition of bacterial communities in floral nectar.In this study, we examined the effects of the plants' environmental conditions across sites and herbivory on the nectar bacterial community composition in floral nectar. To that end, we studied the composition of communities of culturable bacteria in floral nectar of No specific permission was required for plant samplings since the field studies did not involve endangered or protected species. The exact location of sampling points for this study is indicated in Asphodelus aestivus, also known as Asphodelus ramosus [Liliaceae]  attack Asphodelus aestivus with their piercing-sucking mouthparts. These mirid bugs feed on A. aestivus leaf cells, apical meristem of new inflorescences, buds, flowers and fruits Asphodelus aestivus inhabits each of these sites which are also characterized by different temperature, precipitation, soil type, and elevation  integrated in a mobile phone. All sampled plants were distinct individuals, separated by at least 2 m We collected floral nectar from Sugar in floral nectar was analyzed by means of a hand-held refractometer . The mean (± SE) sugar equivalent concentration was 33.3%±1.5% (n = 40 flowers).A. aestivus individual, we also aseptically collected Capsodes infuscatus adults (5.3±0.9 bugs per site). Each mired bug was collected from a distinct individual of A. aestivus, separated by at least 2 m Open flowers (hereinafter 'open') from different plants , were aseptically sampled . DirectlThe dislodgement of bacteria from the surface of the bugs ('out') was performed by sonication according to Aizenberg-Gershtein et al. http://eztaxon-e.ezbiocloud.net/) As nectar inoculation on agar plates was performed in the field, plates were kept at room temperature (25 °C) for up to seven hours until they reached the laboratory where they were incubated at 30 °C in the dark. Bug cultures were kept at 30 °C. Forty-eight hours after incubation, few colonies of each phenotypically distinct microbial type  were picked and streaked on an R2A plate containing 20% sucrose to yield axenic cultures. In cases where only few colonies grew on a plate (10 or less) all the colonies where picked and streaked as described. This action was repeated four times for each clone. To avoid mixed colonies, these were also streaked on Luria–Bertani (LB) agar, at least once. All bacterial isolates were kept in LB with 30% glycerol (−80°C). Representative isolates of each morphotype were identified by amplifying and sequencing a 1501-bp internal fragment of the 16S rRNA gene using 11F and 1512R primers as described in Senderovich et al. We used rarefaction analysis to estimate the total expected culturable bacterial species richness in floral nectar (bagged and open flowers) and on bugs (in and out treatments), using the average of three nonparametric estimators for presence/absence data: Chao2, Jackknife1 and Incidence-Based Coverage Estimator of species richness (ICE) based on 100 randomizations without replacement. Nonparametric estimators for species richness present the least biased option, but because no particular estimator has consistently performed best P<0.05.To visualize the difference among bacterial communities at the different sites and with different treatments, we performed a cluster analysis using R Bacilli, Gammaproteobacteria, Actinobacteria and Alphaproteobacteria classes were found to account 46.5%, 24%, 23.5% and 6% of the nectar isolates, respectively . Bacillus (34%) and Pseudomonas (18%) (Gammaproteobacteria) were the two most common bacterial genera recovered; both were found in all the examined sites.A total of 161 representative isolates recovered from 52 nectar samples and from 28 distinct individual plants, were identified by amplifying and sequencing the 16S rRNA gene . The meaectively . RepreseF3 = 1.36, P<0.05; F1 = 1.07, NS). Canonical Correspondence Analysis (CCA) revealed that bacterial community composition differed along environmental gradients in temperature, precipitation and elevation and that different bacteria species were associated with different sites and environmental conditions .Cluster analysis revealed that OTUs differed across sites, and that in all cases except Goral community similarity across treatments (open versus bagged), community similarity within sites was greater than community similarity across sites . There wnditions ; Table 2Bacilli, Gammaproteobacteria, Actinobacteria and Alphaproteobacteria classes accounted for 48.7%, 45.2%, 5.2% and 0.9% of the bug's bacterial isolates, respectively (Actinobacteria and Alphaproteobacteria were identified mostly inside the bugs. Bacillus (43%) and Pantoea (17%) were the two most common bacterial genera recovered; both were found in the in and out treatments. However, OTUs from the genus Pantoea were identified only at Nadiv.A total of 115 representative isolates recovered from 34 mirid bug samples collected from 21 distinct individual plants, were identified based on 16S rRNA gene sequences . The estectively . RepreseF1 = 1.87, P<0.05) and between the in and bagged treatments . There was no significant variation in OTUs composition between the in and out treatments , between out and open treatments  and between out and bagged treatments .There was significant variation in OTUs composition between the in and open treatments  that were occasionally found in the bagged flowers in all sites. Moreover, we documented adult C. infuscatus bugs inserting their piercing-sucking mouthparts through the bag and into the flower and extracting their waste on the covering bag  and are also characterized by similar environmental conditions. However, according to cluster analysis, their community compositions as determined by the OTUs were less similar than were those at Bashan and Goral, which are distant geographically (∼200 km) and in terms of environmental factors , were found only at these two remote locations. To our knowledge, this is the first study on bacterial communities in floral nectar and its herbivores, conducted at sites located along a geographical and environmental gradient. This is also the first study of bacterial communities on mirid bugs.Here we have demonstrated that bacterial communities in nectar collected from  factors . For exaet al. Acinetobacter. Acinetobacter isolates were also the dominant fraction when the culturable method was used cinetobacter species were identified  the identification is accurate only up to the genera level C. infuscatus bugs to penetrate the bag with their piercing-sucking mouthparts  and within each treatment (open or bagged). In the table, number of isolates and (in parentheses) coverage and percentage of the 16S rRNA gene similarities to the closest known species, respectively.(PDF)Click here for additional data file.Table S2List of bacterial isolates from Capsodes infuscatus in the four sites  and within each treatment (in or out). In the table, number of isolates and (in parentheses) coverage and percentage of the 16S rRNA gene similarities to the closest known species, respectively.(PDF)Click here for additional data file.


Because the adequacy of micronutrient intake correlates positively with energy intake , a varied diet that includes cereals, fish and fruits is especially important for players with low levels of energy intake. Supplements may be a possible solution if adequate micronutrient intake cannot be achieved through regular dietary intake alone. However, dietary analyses should be conducted on a regular basis throughout the year to improve the nutritional knowledge of the athletes and assure adequate micronutrient intake.Wheelchair basketball has evolved into a high-performance sport over several years, and small variations in player performance can determine the difference between winning and losing. Therefore, adequate micronutrient intake may influence this difference if performance-promoting macronutrient intake and physical fitness are equal between teams. Seventeen elite male wheelchair basketball players belonging to the Spanish National Team participated in this study. Macro- and micronutrient intake were determined using a food-weighing diary over three consecutive days during three training camps in two consecutive years. Current Dietary Reference Intake levels were used to determine the adequacy of intake of seventeen micronutrients of particular interest for athletes. After categorizing the consumed foods into fourteen food groups according to the National Nutrient Database for Standard References (USDA) these groups were used to identify the best predictors of the adequacy of intake for each micronutrient. Total energy intake correlated positively with the adequacy of all micronutrient intake levels, except for vitamins A and E. Five B vitamins and phosphorus, selenium, and iron showed 100% adequacy. All other micronutrient intake levels were found to be inadequate, e.g., vitamin E (51% adequacy) and calcium (73%). The fruit, fish and cereal food groups were found to be predictors of adequate intake of most micronutrients. Together with energy intake ( In high-performance sports, differences in the factors that determine winning and losing can be small . Hence, 6, folic acid and vitamin B12) and minerals  facilitate the conversion of macronutrients into energy and are therefore essential to athletes because of their high levels of energy expenditure  values. Significance was accepted at p < .05, and all tests were performed using SPSS version 22 .Normal distributions were tested for using the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Pearson and Spearman correlations were computed for parametric and non-parametric data, respectively, to determine the linear relation between energy and micronutrient intake. Stepwise multiple linear regressions were conducted for each micronutrient intake as a dependent variable, and food groups were used as independent variables so that we could determine the relationship between micronutrient intake and dietary variation. Differences in micronutrient intake between all three evaluations were tested via analyses of variance (ANOVA) with repeated measurements for parametric data or via Friedman tests for non-parametric data. For post hoc tests we used paired Student’s t-tests for parametric data and Wilcoxon tests for non-parametric data, using Bonferroni corrections with partial eta-squared  are shown in Overall, 37 food diaries were examined. Mean energy intake was 2,673±485 kcal/d  and 36.8±10.5 kcal/kg . Macronutrient intake relative to body mass was 3.9  g/kg for carbohydrates and 1.7±0.6 g/kg for protein, excluding supplements. The percentage of energy derived from fat was 33.7±5.5%.6 and vitamin B12 and for various minerals  for all the players. No player exceeded the UL for any micronutrient. AdequacySUM was found to be 13.2±2.0, with no player achieving adequate intake levels for all 17 micronutrients but with 35% taking in adequate levels for 16 micronutrients.The estimated adequate intake probabilities at the group level are shown in One player used supplements on all three occasions, achieving adequate calcium and vitamin D levels for Training Camp T1 and adequate intake levels for all micronutrients and calcium for Training Camp T2. Two players used mineral supplements on one occasion, achieving levels of calcium above adequacy.SUM and micronutrient intake adequacy is shown in The correlation of total energy intake with adequacySUM levels consumed more fruit, dairy, fat, oil, and cereals  and T2 (p = .046). Similar results were found for fruit  and egg intake levels , although significant post hoc test results were not found.Anthropometric data and diet compositions for the eight players who took part in all three evaluations are shown in p = .008, W = 0.61; T1-T2 n.s., T2-T3 p = .035, T1-T3 p = .045) and magnesium  showed significant differences, with three players over the EAR for iodine at T1, one over at T2 and seven over at T3 and with three over the EAR for magnesium at T1, two over at T2 and three over the RDA at T3.The probabilities of adequate micronutrient intake for the three evaluations are shown in SUM values were 12.5±2.4 at T1, 12.3±1.8 at T2 and 14.0±1.7 at T3 .The adequacyOur study reveals a relationship between total energy intake and adequate micronutrient intake in male wheelchair basketball players. Additionally, it shows that a variety of food groups are needed for one to achieve adequate micronutrient intake.Although a higher total energy intake among able-bodied athletes should result in adequate micronutrient intake , 5, it iHowever, total energy intake is not the only factor that affects the adequacy of micronutrient intake. For example, similar energy intake levels of 2,558 kcal/d and 2,479 kcal/d were found in our study between two players and resulted in the adequate intake of ten micronutrients for one player and sixteen for the other, with only vitamin D showing inadequate intake levels, which will be discussed later. Consequently, a varied diet is also important [Compared with the levels found in the study by Krempien and Barr  on male The dietary intake levels of our participants showed a high adequacy for 13.3±2.1 of the 17 micronutrients examined. Micronutrients involved in bone health, such as calcium, magnesium and vitamin D, showed low adequacy levels, and the levels of phosphorus were high in relation to those of calcium , which cHowever, the DRI for vitamin D represents intake levels under minimal sun exposure conditions, and in the summer, the endogenous synthesis of vitamin D in Madrid, Spain, (40° in latitude) is achieved with 10 minutes of daily sunlight exposure. Nonetheless, limited sun exposure can occur because of the season and at latitudes higher than 35°. In such cases, calcium and vitamin D supplements should be considered during fall and winter and especially for athletes presenting low total energy intake levels.6, and B12, as well as folic acid, iron and zinc should be of great concern [6 and vitamin B12 intake levels were found to be adequate as animal food groups were well represented and no player followed a vegetarian diet. Vitamin A, vitamin C, iron and zinc intake levels were above their EAR. Various food groups served as significant sources of vitamin A and iron, although only fruits served as sources of vitamin C, and only cereals served as sources of zinc. Regarding the low adequacy levels of vitamin E and folic acid intake, a higher intake of nutrient-dense legumes may prove beneficial, as legumes are good sources of these micronutrients. However, due to the low legume intake in this study, legumes were not found to serve as a significant source of any micronutrient. Although digestion is slower in players with SCI [In addition to improve performance, micronutrients play an important role in enhancing immune function, and illness can result in players being absent from training and competition , 33. To  concern , 35. In with SCI  and certNutritional advice was found to increase the overall adequacy of micronutrient intake after one year, which can be attributed to a higher total energy intake and to a more varied diet characterized by the higher fruit and egg intake of our participants. Considering the marginal differences found after the second training camp (T2), which was only four weeks after the first (T1), it appears that eating habits take time to change and that advice should be given more frequently than it was in our study to achieve adequate micronutrient intake. Even a nutrition education program involving three sessions over four months did not improve micronutrient intake among able-bodied professional handball players , despiteAlthough the DRI values were used to study the intake adequacy of all micronutrients, our analysis conducted over three consecutive days may have been too short to fully analyze the requirements for some micronutrients . Other pThe adequacy of the micronutrient intake by elite male Spanish wheelchair basketball players is positively related to their total energy intake. However, a variety of food groups must be included in one’s diet to achieve adequate levels for the most important micronutrients, and nutrient-dense food groups such as fruit are associated with more micronutrients than less nutrient-dense groups. As some micronutrients showed inadequate intake levels, additional nutritional advice should be provided to avoid adverse effects resulting from personal dislike of certain food groups, and the consumption of beneficial foods  should be promoted as some of these groups, legumes in particular, were only consumed in minimal amounts. In addition, shorter time frames between nutritional advice are more successful than longer periods, such as one year.Food variety with special attention to nutrient-dense foods is especially important in players with low energy intake. Consequently, it might be necessary to use supplements for players with SCI, especially for micronutrients involved in bone health. Nutritional monitoring in Paralympic athletes should be incorporated into the regular routine of their training periods throughout the year so that a short time frame between repeated sessions of receiving nutritional advice can be used to raise their knowledge of the benefits of sports nutrition.S1 Table(DOCX)Click here for additional data file.