Skin autografts are in great demand due to injuries and disease, but there are challenges using live tissue sources, and synthetic tissue is still in its infancy. In this study, an electrocompaction method was applied to fabricate the densely packed and highly ordered collagen/sulfated xylorhamnoglycuronan (SXRGlu) scaffold which closely mimicked the major structure and components in natural skin tissue. The fabricated electrocompacted collagen/SXRGlu matrices (ECLCU) were characterized in terms of micromorphology, mechanical property, water uptake ability and degradability. The viability, proliferation and morphology of human dermal fibroblasts (HDFs) cells on the fabricated matrices were also evaluated. The results indicated that the electrocompaction process could promote HDFs proliferation and SXRGlu could improve the water uptake ability and matrices’ stability against collagenase degradation, and support fibroblast spreading on the ECLCU matrices. Therefore, all these results suggest that the electrocompacted collagen/SXRGlu scaffold is a potential candidate as a dermal substitute with enhanced biostability and biocompatibility. Skin is the largest organ of the human body and it acts as a physical barrier against the external environment. Compromised wound healing is a major issue in the treatment of massive skin lesions. Currently, widely used strategies to treat skin wounds include wound dressing, skin autografts and allografts . HoweverSkin tissue engineering alleviates the issue associated with donor shortage and prompts wound management via the use of bioactive cell-material complex scaffolds . CurrentIn skin tissue, collagen is the most abundant component in the extracellular matrix, providing integrity, rigidity and elasticity . CollageIn natural skin, apart from collagen, polysaccharides are also important native components with functions including maintaining moisture environment, promoting angiogenesis, offering binding sites for drugs or growth factors . RecentlN-hydroxysuccinimide (EDC–NHS). Physiochemical properties of the fabricated matrices including micromorphology, SXRGlu content and distribution, mechanical property, water uptake ability and degradability were evaluated. In addition, HDFs were cultured on the scaffolds to assess the cell viability, proliferation and morphology. The aim of this project is to fabricate biomimicry dermal substitutes using electrochemically aligned collagen (ECL) matrix and SXRGlu for wound healing applications. SXRGlu was introduced to the ECL matrices by chemical crosslinking, using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and The fabrication process of traditional collagen gel (GEL), electrocompacted and crosslinked collagen (ECLC) as well as SXRGlu-conjugated ECLC (ECLCU) matrices is illustrated in N-morpholino) ethanesulfonic acid (MES) buffer for 4 h at room temperature [To enhance the mechanical property and stability of the collagen matrices, the ECL matrices were crosslinked using 20 mM EDC and 20 mM NHS in 50 mM 2- with 10 × PBS (1 part) and adjusting the pH to 7.0–7.5 using 0.1 N NaOH (1 part). The mixture was then cast into molds and allowed to gel at 37 °C for 24 h followed by crosslinking using 20 mM EDC and 20 mM NHS in 50 mM MES buffer. Strips or circle membranes were then cut from these gels and processed as mentioned above for subsequent tests. An equal amount of collagen was used for fabrication of both compacted and uncompacted sheets.To mimic the more complex scaffold structure of skin matrices and investigate the functions of SXRGlu in wound healing applications, an SXRGlu rich extract, obtained from the cell wall of a DNA barcoded green macroalgae , was crosslinked to the ECL matrices by soaking the freeze-dried ECL matrices in 1% SXRGlu, 20 mM EDC and 20 mM NHS in 50 mM MES buffer for 4 h at room temperature. After that, the SXRGlu conjugated-ECL (ECLCU) were rinsed thoroughly with PBS, freeze dried and stored at 4 °C for further application.w/v) SXRGlu into 0.1 M MES buffer (pH 6.0) and incubating under gentle stirring at room temperature for 24 h. Extra dyes were removed by dialyzing against distilled water for 7 days. Then the Fluo-SXRGlu was crosslinked to the ECL using the same procedures mentioned above.To quantify the amount of SXRGlu in the ECLCU matrices, the ECLCU matrices were dissolved in 1 N HCl and incubated at 37 °C for 72 h. The dimethylmethylene blue (DMMB) assay  was usedScanning electron microscopy  inspections were conducted on GEL, ECL, ECLC and ECLCU to investigate the effect of electrocompaction process on the microstructure of collagen. Samples used for SEM imaging were hexamethyldisilazane  dehydrated. The fixing and dehydration process are as following : freshly−1. Before testing, samples were washed with deionized water, dehydrated using a series of ethanol washes, and air dried. The dried bundles were glued onto transparency sheets of both ends using a UV curable glue  and rehydrated with PBS [Tensile mechanical properties of the traditional collagen GEL, ECLC and ECLCU were tested using a Shimadzu EZ-L universal mechanical tester at wet state with a 10 N load cell at a crosshead speed of 10 mm·minwith PBS . The You2 were weighed in the dry state and were recorded as (Wd). Following this, samples were soaked in PBS for 24 h for complete hydration and then the wet weight (Ww) was recorded after removing excess water on sample surface using Kimwipe. The swelling ratio of collagen matrices were calculated using the formula below [To evaluate the effect of electrocompaction and SXRGlu incorporation on the water up take behavior of collagen matrices, samples of 0.5 × 0.5 cmla below :SwellingW0). Following this, the collagen matrices were immersed in the digest solution which contained 100 μg/mL (28 units) collagenase  in PBS (pH 7.4) and incubated in water bath at 37 °C for desired time points. The digest solution was replaced every 2 h. At t = 2 and 4 h, the matrices were removed from the digest solution and freeze-dried. Then the residual mass at each time point was calculated.The stability of electrocompacted collagen matrices was determined by assessing the resistance of the matrices to collagenase treatment. The collagen matrices were freeze-dried and the initial weight of the matrices prior to collagenase treatment was recorded (v/v) fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin under 5% CO2 at 37 °C. Before cell seeding, scaffolds in 24 well plate were sterilized firstly by UV irradiation for 1 h, immersion in 70% ethanol for 3 h and washing for five times with PBS for 12 h. To saturate the scaffold with cell culture medium and facilitate cell attachment onto the collagen matrices, the sterilized scaffolds were incubated in 1 mL of culture medium at 37 °C overnight before cell seeding. Human dermal fibroblast  cells at passage 8 were seeded onto the fabricated collagen scaffolds to assess the influence of electrocompaction and incorporation of SXRGlu on cell proliferation and morphology. The HDFs were cultured in Dulbecco’s Modified Eagle’s medium (DMEM) supplemented with 10%  assay according to the manufacturer’s instruction. Briefly, at day 1, 3, 5 and 7, three HDFs-scaffold constructs were incubated with PrestoBlue™ mix for 1 h at 37 °C. Following this, for each sample, 100 μL aliquots of supernatant were transferred to a 96-well plate in triplicate and measured using a microplate reader .The HDFs were then seeded at the density of 1.0 × 10Live/dead assays were performed to inspect the HDFs cell viability on the scaffolds. Briefly, at each time point, HDFs-scaffold complexes were incubated with Calcein AM  at 37 °C for 10 min. Then, after a media change, propidium iodides  were added into the HDF-scaffold complexes and incubated for 5 min followed by a further media change. Images were acquired using a confocal microscope  and the 3D projection tools in the Leica application suite X (LAS X) software  were used for depth coding. −1 4′,6-diamidino-2-phenylindole  for 10 min at RT to visualize the nuclei. Finally, samples were washed and imaged using a confocal microscope .Alexa Fluor 488-Phalloidin cell cytoskeleton staining  were conducted to assess the cell morphology. To do this, collagen matrices with cells at day 7 were washed in PBS and fixed in 3.7% paraformaldehyde in PBS for 10 min at room temperature. Then, samples were washed with PBS and permeabilized with 0.1% Triton-X 100 in PBS for 5 min at room temperature. Samples were subsequently stained with Alexa Flour 488-Phalloidin (1:40 in PBS) for 1 h at room temperature, washed with PBS, and then incubated with 10 μg·mLSEM images of the electrocompacted collagen A–D showeSherman et al.  reportedTo mimic the typical matrix structure of natural skin, SXRGlu was conjugated to the ECL matrices. After SXRGlu conjugation, the final content of SXRGlu confirmed by the calibration curve in the ECLCU was 2.1 ± 0.2%. Confocal images of electrocompacted collagen conjugated with Fluo-labelled SXRGlu  confirmeHowever, with the current EDC/NHS crosslinking method, the amount of SXRGlu that can be introduced into the ECLC matrices is limited, well below the composition of polysaccharides in native skin, among which collagen and polysaccharides account for 75% and 20% dry weight respectively. An alternative approach to improve SXRGlu loading is to develop SXRGlu derivatives that can carry both positive charge and negative charge, sharing the same isoelectric point with collagen . In thisThe Young’s modulus A, ultimaYet, electrocompaction and crosslinking significantly decreased the extensibility of collagen matrices as shown by the ultimate tensile strain results. This might be due to the crosslinking and SXRGlu incorporation procedure reducing the mobility of collagen chains within the matrices, thus leading to a more rigid molecular structure which finally resulted in weaker elasticity . This coThe swelling ratio of GEL, ECLC and ECLCU were compared to evaluate the influence of the electrocompaction process and SXRGlu incorporation on the water uptake behavior of the matrices. As shown in Apart from fiber-forming structural molecules, components in skin ECM can be divided into “matricellular proteins”, and “nonfiber-forming structural molecules” . MatriceCollagenase treatment to the collagen matrices was conducted to evaluate the influence of electrocompaction and SXRGlu inclusion on matrix stability. As shown in ® suggested that cell numbers on ECLCU and ECLC were higher than that on GEL on day 5 and day 7, which confirmed that the electrocompacted collagen matrices could promote the proliferation of fibroblasts. This is probably because the electrocompaction process increased the mechanical property of the matrix and this is in accordance with reports that fibroblasts responds to improved matrix stiffness by enhanced proliferation, collagen secretion, and smooth muscle α-actin (αSMA) stress fibers expression [Cell studies were conducted to evaluate the viability, proliferation and cell morphology of HDFs cells cultured on the fabricated collagen matrices. The proliferation of HDFs on collagen matrices were assessed using PrestoBlue™ assay A. Quantipression . Especiapression . Over th2/cell (n = 100) respectively. HDFs on ECLCU resulted in most significantly increased F-actin area, indicative of most enlarged and spread out morphology of the HDFs. This might because the abundant rhamnose groups in SXRGlu could trigger skin fibroblast recognition and attachment to the ECLCU through the mediation of a unique rhamnose recognizing lectin-site on fibroblasts as receptor [The morphology of HDFs on different matrices and the arrangement of the actin cytoskeleton were visualized by SEM inspection and fluorescent staining of cytoskeletal F-actin filaments after 7 days’ cell culture . F-actinreceptor . BesidesTogether, these results demonstrated firstly that electrocompaction of collagen improved the mechanical property of the collagen matrices and promoted HDFs proliferation; secondly, the incorporation of SXRGlu facilitated HDFs spreading and enlargement on the electrocompacted collagen matrices; also, the incorporation of SXRGlu increased the stability of the matrices against collagenase degradation. Herein we presented the fabrication and in vitro characterization of a biomimicking skin scaffold using collagen and SXRGlu. Electrocompacted collagen matrices were successfully fabricated. SEM inspection confirmed the presence of highly ordered, densely packed collagen fibers, mimicking the alignment and structure of collagen fibers in natural skin tissue more closely than the non-compacted matrix. Moreover, electrocompacted collagen matrices exhibited increased tensile strength and the mechanical properties of ECLC and ECLCU are comparable to that of natural skin. Incorporation of SXRGlu significantly improved the water uptake ability and stability of the electrocompacted collagen matrices. Cell proliferation studies showed the electrocompacted collagen matrices promoted the proliferation of HDFs, and SXRGlu facilitated HDFs spreading. Together, these results implied the potential of this SXRGlu incorporated electrocompacted collagen film as skin scaffold substitute.In future work, polysaccharides including hyaluronic acid and SXRGlu will be aminated and co-electrocompacted with collagen and elastin to fully mimic the components and structure of natural skin ECM. Co-culture of keratinocytes and fibroblasts will be performed to do a reconstruction of a full thickness skin model.


Habitat loss and fragmentation causes a decline in insect populations. Odonata (both dragonflies and damselflies) are especially threatened by the destruction of both aquatic and terrestrial environment. Moreover, effects of large-scale habitat heterogeneity on Odonata assemblages are poorly studied. In a two years study along East-European lowland watercourses both aquatic and terrestrial environment were studied to reveal the importance of local  and landscape-scale  variables to Odonata (as well as to dragonflies and damselflies separately) through increasing spatial sampling scales. The specimens were sampled using 500 m long transects from May to September. Results, both on local and landscape scales emphasized the importance of terrestrial environment on Odonata. Local variables influence damselflies, while dragonflies are more sensitive to landscape variables. Damselfly’s diversity decreased with increasing macrovegetation cover, while dragonfly’s diversity decreased with the increasing degree of land use intensification, but increased with the length of watercourses. It is thus vital to stress the importance of partial watercourse clearing, and moderate maintenance of traditional farm management based on small parcel farming near watercourses to maintain diverse and healthy Odonata assemblages. Their high diversity, complex life history, rapid development and their essential role in food webs3 make them ideal model insects for ecological surveys. Healthy aquatic habitats are crucial for the development of Odonata; beside this, adults also need resource-rich terrestrial habitats for maturation, feeding, resting, and mating4. Furthermore, Odonata are also sensitive to the landscape composition and configuration; their sensitivity to landscape quality can even exceed those of water hydrography and chemistry or other local ecological parameters describing the aquatic environment5. The presence and abundance of Odonata along watercourses are also affected by several conditions like water quality6, competition between larvae7, competition between adults8, dispersal ability of adults9, and the surrounding landscape10.Odonata are real flagship taxa of freshwater ecosystems, and often used as indicator species to assess the quality of their close environment11. While several studies explore the influence of habitat loss on terrestrial populations and communities14, relatively few studies focus on the relationship between landscape changes and aquatic invertebrates such as Odonata. However, a remarkable rise in the number of studies regarding terrestrial effects on Odonata communities have emerged during the last ten years17.Human-caused habitat loss and fragmentation has become the major threatening factor during the last few decades for several taxa20. Other studies address the relationship of Odonata and forests, underlying the importance of trees and shrubs for these insects22. Another group of studies reveal the major importance of connectivity between water bodies for Odonata25. Only a small number of studies targets Odonata assemblages using both local and landscape variables as predictors to understand their occurrence, abundance and community structure26.The literature on Odonata-environment relationship is largely restricted to single or few species, and usually consider only a few landscape variables. The majority of the existing studies are focusing on the influence of bankside and riparian vegetation, analysing the presence of buffer strips or the extent of shading canopyThe purpose of the study was to explore the effect of local (i.e. aquatic) and landscape variables  on Odonata assemblages along lowland watercourses in two Central-Eastern European countries. Considering both the features of local habitat, and the surrounding landscape, the variables that were essential for the maintenance of rich Odonata assemblages were identified. The importance of local and landscape variables was also assessed by considering the two major Odonata groups separately (Zygoptera and Anisoptera) to explore taxa-specific sensitivities to the studied variables. The aim of this study was to conclude: (i) Which local biotic variables affect Odonata species diversity? (ii) Which landscape variables affect Odonata species diversity? (iii) Is there any difference in the sensitivity of the two suborders regarding the local and landscape variables?2 = 3.54, df = 1, p = 0.06, Table 2 = 1336.2, df = 10, p < 0.001) and Anisoptera  showed significant differences (site-specific mean abundances).Over the two-year period the number of specimens counted was 10,884 belonging to 34 species . The width of watercourses varied between 1.9 and 10.4 meter, with an average of 4.2 meter (±2.2). The watercourses were found to have a relatively high-water surface macrovegetation cover: it varied from 6% to 95%, with an average of 72% (±27%). Eight sites out of eleven had higher than 75% vegetation cover, and only one had a lower than 10%. The percentage of banksides tree cover varied between 1.6 and 65% with an average of 37% (±23%). The average bankside cover of herbs was relatively high: 70% (±18), and it varied between 41% and 98%. The average plant height of the banksides was 60 cm (±23), varying between 24−93 cm.Significant negative correlation was found between the percentage of water surface macrovegetation cover and Odonata diversity: with increasing surface cover the diversity of Odonata decreased Table . This coResults regarding other diversity indices had the same outcome as detailed above  towards intermediate (0.97 ± 0.23) and large scales (1.11 ± 0.19). The total length of watercourses (km) within the landscape also showed an increasing trend . The forest patch proportion increased from large (9.85 ± 5.67) to middle (12.96 ± 13.13) and small scale (15.87 ± 13.91). The farmland patch size (ha) decreased only from large (25.06 ± 11.31) to middle (15.87 ± 7.25) and small scale (14.89 ± 7.95). The mean distance to the nearest forest patch was 174.46 (±253.45) meters.Two variables showed significant correlation with Odonata diversity from the five tested variables on landscape scale. The total length of watercourses at the largest scale showed significant positive correlation with the diversity of Anisoptera Table . The corThe farmland patch size showed significant negative correlations with species diversity at various landscape scales Fig. . CorrelaAt the smallest landscape scale (radius = 1.25 km) we also found a marginally significant correlation between the forest patch proportion and the diversity of Zygoptera Table  and the Results regarding other diversity indices than Shannon index showed the same relationships  and landscape-scale  in explaining the Odonata species diversity; it was followed by the farmland patch size on the 5 km scale Table . The tot27. Furthermore, the quality of the terrestrial environment is also important for the populations because it provides habitats for mating, egg laying, feeding, resting and facilitates dispersal28. The results show that both local and landscape variables were important for the occurrence and abundance of Odonata. However, it is stressed that the two groups showed different sensitivities to the local and landscape variables.The influence of water body attributes and the surrounding landscape on the Odonata assemblages along lowland watercourses were tested. The studied watercourses were the most stable aquatic environments from the whole hydrographic basin, because they persisted even in extreme dry summer periods. The short term stability of the aquatic ecosystems is of crucial importance for the breeding success and generational continuity of populations in most of species2. Rouquette and Thompson19 report the importance of emergent vegetation in the case of Coenagrion mercuriale; it is underlined that high percentage of water surface cover is not favoured, at the same time open water positively affects the density of C. mercuriale.Only one out of the six analysed local variables (the cover of emergent vegetation), had significant influence on the species richness and diversity of Odonata. Especially the Zygoptera showed significant sensitivity to this variable. Furthermore, Zygoptera diversity decreased with the increase of the cover of emergent vegetation. However, a relatively high cover of emergent vegetation on almost all sites was observed. A high open water surface cover may hamper the movement of Zygoptera, which has weaker flying and dispersal ability than the Anisoptera species18. The explanation for the inconsistence between the findings and the previously cited results is regarded to water surface cover variability, namely that in this case the water surface cover was rather high which may have hindered the movement of Zygoptera. Most of the Zygoptera species are perchers, and detect intruders, or females sitting on different surfaces  by watching around2. Shade of surveyed habitats had no significant effects on the Odonata assemblages, a result which is adverse to several reported relationships30. The findings regarding shade may be due to the relatively reduced shade in all selected habitats.In another study, where both Zygoptera and Anisoptera species were analysed from the perspective of water surface cover, Anisoptera species were more affected than Zygoptera species31. This assumption was also confirmed in other studies, where it was reported that the more mobile Anisoptera were more sensitive to landscape variables at large scales, while Zygoptera were sensitive to local variables (i.e. water body related)10.The relationship between the landscape variables and Odonata was significant only for the Anisoptera species, and this result supported the expectation. As expected from published literature, Anisoptera due to their higher dispersal ability are more sensitive to the landscape structure than Zygoptera32, and thus better flying abilities. A longer watercourse network provides an extended habitat which provides more food, more oviposition site and more conspecific females, and higher survival chance. It was reported that in England the number of ponds in the surrounding area had no effect on species richness of dragonflies28. However, their largest spatial scale was of a 1600-meter-long radius, contrary to the 5 km long radius scale used in this study. In another study4 authors found that the distance to the nearest possible pond is a crucial factor in species occurrence: species richness decreased with increasing distance to the nearest suitable pond. In an experimental study where cattle tanks were used, the results show that both the distance to the nearest tank and the connectivity between artificial ponds affected significantly the species richness15. With increasing isolation, the dispersal between tanks decreased, and thus species richness declined.This difference in habitat sensitivity between the two Odonata suborders can explain the finding that total length of watercourses on a 5 km scale has a positive significant effect on Anisoptera diversity. Anisoptera have larger size, bigger muscle mass, and better thermoregulation than ZygopteraThe farmland patch size showed a significant negative effect on Odonata species diversity at a large scale (5 km), and on Anisoptera species diversity at the small (1.25 km) scale. The trend was the same for Anisoptera at the middle scale (2.5 km). The farmland patch size alludes to landscape fragmentation: increasing patch size results in landscape homogenization, with fewer buffer strips, bushes, forest patches, and presumably high fertilizer input. In the agriculturally intensified landscapes this means less space for maturation, feeding, and resting for the dragonflies.33. A similar effect on Odonata species richness was described in another study where the species richness increased with larger areas of land under Higher Level Scheme28. The Higher Level Scheme, an agri-environmental scheme included pond-specific options that could potentially beneficial for Odonata, by assuring buffering in-field ponds in improved grassland or farmland, maintenance of high quality ponds, and pond creation and restoration.The negative effects of the intensified land use on a large number of Odonata was presented by Ott34. In a study of the threatened dragonfly species Sympetrum depressiusculum Dolný et al.35 and Hykel et al.36 suggest that the heterogeneous terrestrial habitat structure is essential for the development of juveniles, and movement of adults, which preferred habitat patches with abundant vegetation. When the importance of land cover types per se and landcover heterogeneity was studied, authors showed that from nine land cover types, farmland percentage had positive effect on 9 species, and negative effect on 31 species. They also found that in the case of 73 species abundance increased with the increasing of landcover heterogeneity21. The landscape composition surrounding habitats was found to be one of the main determinants of Odonata diversity17. Habitat heterogeneity can be considered as the main reason for increasing species richness and diversity and has stronger impact than habitat size alone37. For some Odonata species the landscape heterogeneity is of great importance, while for others seems to be of less38.Habitat structure and landscape configuration effect on species diversity was demonstrated in a study . They showed that the habitat structure and other landscape variables calculated at increasing scales  was more important than boating pressure both for adults and for larvae28. Although the role of forests for Odonata has a voluminous literature39 the results showed that for the lowland Zygoptera species the increased amount of woodland could be an obstructive factor.Species diversity of Zygoptera showed a marginally significant decreasing trend with the increasing forest patch proportion in the surrounding habitat at the small scale (1.25 km). This relationship was underlined in a study where Odonata species richness decreased with increasing amounts of forest, especially on a 200 m scale42. For preservation of species-rich Odonata assemblages future policies should take the landscape context into consideration and management actions should be directed toward regions where availability of extensively used areas is high.It was demonstrated that Odonata show different responses to local and landscape variables. While the Zygoptera species were mostly affected by local variables, the Anisoptera species were more sensitivity to landscape variables. This study further highlighted the need for simultaneous consideration of local (aquatic habitat) and landscape variables to understand fully the habitat use of Odonata. The findings suggest that an extensive land use management is necessary for a successful conservation management of Odonata assemblages. This kind of management supports species-rich Odonata assemblages and may also be beneficial for several other taxa such as amphibians, butterflies and farmland birds2 and that of Romania had 127 km2. The two survey years were dry43; in this context, it was identified in the studied area all the possible watercourses with substantial amount of water in order to implement our sampling design, and selected 11 study sites (4 in Hungary and 7 in Romania). The chosen watercourses were characterised by the presence of Carex sp., Glyceria maxima, Mentha aquatica, Nuphar lutea, Sparganium erectum, Stratiotes aloides, Phragmites australis, Typha latifolia, T. angustifolia. Banksides had rich herbaceous vegetation, with scarce shrub and tree cover. Watercourses were usually exposed to direct sunlight. Surveyed watercourses were at different distances from forest patches. All watercourses were at least on one bankside adjacent to agricultural fields, mostly farmlands. All surveyed watercourses were outside of urban areas. These watercourses are characterized by a slow water flow, with abundant still zones. The great majority of species are developing in these watercourses, even the species which require still water; thus, there are no vagrant species here or their occurrence is very unlikely.Lowland watercourses and their neighbouring habitats of North East Hungary (Szatmári Plain) and North West Romania (North-Partium) were surveyed in 2015 and 2016 , water width (m), water surface macrovegetation cover (percentage cover), bankside cover with trees and bushes (percentage cover), bankside cover with herbs (percentage cover), and average height of the bankside vegetation (cm). These variables were measured or estimated by the same person at every single sample event. The bankside cover with trees and bushes, and the average height of the bankside vegetation incorporates the shade characteristic of the habitats. Local abiotic variables were measured once at every sample site. These abiotic variables include: air temperature, wind speed, humidity, and the distance of visibility.http://earth.google.com/; © 2016 Google; © 2016 Geoeye; © 2016 DigitalGlobe). The maps were constructed from manually digitised cover type boundaries at a resolution ratio of 1:250 in Quantum GIS . Cover types were delimited as farmland, pastures, orchards, urban areas, broad-leaved forests, bushy areas, embankments, dry riverbeds, rivers and lakes. The area (ha) of each cover type was calculated using Quantum GIS.Landscape level variables were recorded in a circle with radii 1.25 , 2.5  and 5 km  around the midpoint of the sampled transects. These areas were digitised from the highest spatial resolution satellite images possible, acquired from Google Earth™  circles. Total length of watercourses contained length of creeks and rivers. Landscape diversity, forest patch proportion, and farmland patch size, were calculated using the package LecoS46. We calculated rarefied species richness46, Shannon diversity, Simpson diversity and Pielou’s evenness46 for Anisoptera, Zygoptera and all Odonata. Then Goodness of Fit (GOF) tests were utilised to verify the normality assumption for each analysed outcome variable. Collinearity between the explanatory variables was assessed with Pearson correlation; no collinearity was detected (r < 0.5); therefore, we used all variables in the modelling47. For assessing correlations between local or landscape level environmental variables and assemblage diversities, Pearson’s correlation coefficients were calculated. Environmental variables that showed significant or marginally significant correlations were used to build linear models with Gaussian error distributions (using function ‘lm’). Backward stepwise selection procedure (using function ‘update’) were used selecting important variables. From all models, AICs and Akaike weights were calculated (ω) (using function ‘akaike.weights’ from package ‘qpcR’). Based on ω values, relative importance was calculated from the used environmental variable sets as described in Rhodes et al.47.The R programming language was used during the statistical calculations . To assess Odonata assemblage characteristics Shannon diversity was calculated for each sampling site using function’diversity’ from package’vegan’ Supplementary material Table S1.Supplementary material Table S2.


Nanorods based on ZnO for surface enhanced Raman spectroscopy are promising for the non-invasive and rapid detection of biomarkers and diagnosis of disease. However, optimization of nanorod and coating parameters is essential to their practical application. With the goal of establishing a baseline for early detection in biological applications, gold-coated ZnO nanorods were grown and coated to form porous structures. Prior to gold deposition, the grown nanorods were 30–50 nm in diameter and 500–600 nm in length. Gold coatings were grown on the nanorod structure to a series of thicknesses between 100 and 300 nm. A gold coating of 200 nm was found to optimize the Rhodamine B model analyte signal, while performance for rat urine depended on the biomarkers to be detected. These results establish design guidelines for future use of Au-ZnO nanorods in the study and early diagnosis of inflammatory diseases. As a final step, Au was deposited on the grown ZnO nanorod substrate in an amount equivalent to 100 nm of thin film thickness [A porous ZnO nanorod substrate was fabricated in the following manner to obtain an amplified Raman signal: (1) Si wafers were diced to an appropriate size  was used to control the amount of gold deposited on SERS substrates that had already been subject to the equivalent of 100 nm gold deposition by thermal evaporation. The amount of gold deposition was controlled by quantifying the deposition current and time and by measuring the cross section after deposition on a bare Si wafer. The deposition conditions were 0.1 mbar of bare pressure and 25 mA deposition current, for deposition at a rate of 50 nm per 11 min. The structural and morphological properties of the samples with gold deposited in various amounts were observed using a field emission scanning electron microscope (FE-SEM)  at 10 kV beam voltage.Rhodamine B was used to evaluate the characteristics of the SERS substrate dependent upon the thickness of the Au deposited on the ZnO nanorod. Rh B  in powder form was diluted into a 1 mM concentration solution, and one drop (5 µL) of this solution was dropped onto SERS substrate and air-dried. Using a metabolic cage, we also collected urine in a 50-mL tube from a healthy 10-week-old female Sprague–Dawley rat, which was used to further identify potential bio applications.−1, covering the range of 600–1570 cm−1, with an integration time of 50 s. The spectra of healthy rat urine samples were measured from 15 points at room temperature and at a spectral resolution of 1 cm−1, covering the range of 465–1475 cm−1, with an integration time of 50 s. Using Neutral Density (ND) filters, Rh B and healthy rat urine were irradiated with 0.1 mW and 1 mW of excitation light, respectively. After obtaining Raman measurements, all spectra were post-processed by applying third-order polynomial fitting to remove the background, and by applying the Savitzky–Golay smoothing method using the RAON-Spec program provided by NOST. Spectral image visualizations were processed using the Origin program .Raman measurements  were performed using a 0.6 NA, 40× objective lens with a focal spot diameter of approximately 2.4 μm as measured on a CCD. In addition, a 785-nm diode laser was used. The spectra of Rh B samples were measured from 7 points at room temperature and at a spectral resolution of 1 cmTo determine the optimal SERS substrate, gold was deposited on ZnO nanorods at thicknesses of 100–300 nm in 50-nm intervals. Rhodamine B was selected as a model analyte to investigate the SERS effect of Au-deposited ZnO nanorod substrates. Rh B is a molecule frequently used as a dye in biotechnology, has no optical absorption in the near-infrared region, and is widely used in SERS due to its good adsorption ability with gold nanoparticles ,22,23. F−1, which correspond to the C–C–ring in-plane bend, C–O–C stretching, aromatic ring vibrations, and C–C stretching, respectively [−1 peaks, respectively.A SERS intensity graph of the Rh B peaks as a function of gold deposition is shown in ectively ,25,26. T−1. The rat urine used was unfiltered urine that contained approximately 25 metabolites. Its Raman spectrum was measured on the SERS substrates using samples that had been fully diffused and dried, and several peaks were observed, as shown in −1 (CH3CH2 wagging mode of collagen) [−1 (C–S stretch) [To confirm the bio-applicability of the SERS substrate, rat urine was measured via Raman spectroscopy on ZnO nanorod substrates deposited with amounts of gold equivalent to a thin film thickness of 100 and 200 nm. In life sciences, studies are also underway to diagnose various diseases using the SERS method in urine, blood, and tissues ,28,29,30ollagen) . The redollagen)  and 735 Gold-coated ZnO nanorods show promise for the early optical detection and diagnosis of biomarkers via SERS due to their low cost, LSPR-based signal enhancement, and biocompatibility. Raman spectroscopy experiments were conducted with Rhodamine B as a model analyte, which show optimization at a 200 nm thickness of Au coating due to increased LSPR without local fill. Intensity of high sensitivity peaks showed standard deviations between four and five percent, indicating high substrate uniformity. Surprisingly, the SERS substrates optimized for Rh B showed reduced relative detection for most biomarkers in rat urine, although this reduced detection did not hold for all chemical signatures. These results suggest that future Au/ZnO nanorod SERS substrates will benefit from optimization to a subset of individual biomarkers. Nanoscale biomarkers are well dispersed in samples of urine and blood, and despite the benefits of more targeted optimization, the substrates demonstrate the high potential of ZnO nanorods based on SERS for early disease diagnosis.


Ascomycota representing the dominant taxon. Basidiomycota and Zygomycota are also well represented, dominated by species of the genus Sebacina and Mortierella respectively, mainly distributed in the semi-natural plots (woodland and grassland). Most of the species are reported as first records for Colombia. Some of them are particularly interesting for their conservation significance such as Geoglossum fallax, which is the dominant species in the unimproved grassland plot. The bootstrap-based clustering analysis showed a different distribution of the species in orchards and non-cultivated areas as a possible response of the fungal community to different use of soil in the agro-environment.Colombia is a country for which one of the highest biodiversity rates is reported, and one of the first in the tropical areas where an effort was made to gather information on indigenous fungi. Nevertheless, mycological data are still scarce and discontinuous, above all on soil fungi. The present study wanted to contribute to unveil the large soil fungal biodiversity in the upper Andean Colombian agro-ecosystems. The studied area is located in the department of Boyacà, considered with a notable economical value, partly devoted to subsistence agriculture. More than 150 described species were revealed in this study, belonging to 5 phyla with  In the Dictionary of Fungi2, the entry “number of Fungi” results in a total of 97,330 species. This number raises to about 99,000 with the addition of the 1300 Microsporidia species listed by Hibbett et al.3. Even with this, the gap with the estimated number of species ‒ 1.5–5.1 million4 ‒ remains relevant5. However, in the last two decades culture-independent methods based on sequence-specific identification have deeply reshaped research in the field, especially with reference to uncultivable species, becoming invaluable tools for their ability to effectively lead to new species discovery in a shorter time7. This applies also to soil, one of the most complex habitats and richest reservoir of bacteria and fungi of the biosphere. Our knowledge on the fungal biodiversity in soil has been continuously increasing, largely thanks to the cited molecular techniques9, comprised, in the last years, those based on metagenomics, metabarcoding and next-generation sequencing platforms10. For example, in a recent paper Tedersoo et al.11 analyzed 365 soil samples from natural locations all over the world, using pyrosequencing, to correlate fungal biodiversity to the most various environmental factors. Their data depicted a soil fungal biodiversity highly influenced by mean annual precipitations and distance from equator. The highest fungal diversity, as well as the highest rates of endemism were found to be strongly linked to the tropical band12.The assessment of the global diversity of soil fungi is often demanding due to the microscopic dimension of many species and to the fact that most of them are hidden13. In the particular case of agricultural soils, unraveling the composition of their mycobiota provides the basis for better understanding functions exerted by the microbial component (fungi and bacteria), also in view of a more effective managing of the agroecosystems themselves. Metagenomics and metabarcoding-based analyses of myco-microbiota of various agricultural soils have been faced by several authors, in South America16, Europe19 and other locations20. Data are consistent with the conclusion that agricultural activities, together with other external stimuli, influence taxonomic composition as well as the metabolic activities of microbial communities. Metagenomic characterization, on the other hand, has allowed to address the influence of agricultural interventions on the soil ecosystem and potentially represents precious tools for defining plant protection strategies21.The main contributions of soil mycobiota to the functioning of ecosystems are linked to soil stabilization and nutrient cycling, and thus to the concept of soil qualityet al.16 that analyzed the fungal phyla inhabiting “paramos” ecosystems of the Andean mountains.The present work focuses on the mycobiota of Colombian soils by a metabarcoding analysis, in the furrow of the work recently initiated by Alvarez-Yela 22, it can be assumed that, in Colombia, fungal species must be >210,000. Even if this country was one of the first in the tropical area where an effort was made to gather information on the mycological flora, also in association to agroecosystems, data still appear scarce and discontinuous. The work of Fuhrmann and Mayor23 on Colombian parasitic fungi dates back to 1914 and the publication of Chardon and Toro24 was the first which referred comparative results of large explored areas as reported by Dumont et al.25. Gradually, the characterization of Colombian fungal species was enriched thanks to serial publications on the New or noteworthy fungi from Panama and Colombia, mainly coming from the Sierra Nevada of Santa Marta, in the department of Magdalena29. In 1974, the cooperative program Mycological Flora of Colombia was launched, and more than 2,000 fungi in the departments of Cundinamarca, Antioquia, Valledel Cauca and Boyacá were recorded25.Colombia is one of the countries for which the highest biodiversity rates are reported. 35,000 plant species have been recorded and, according to the association between plants and fungi proposed by Hawksworth39.The attention to microfungi has increased more recently, but knowledge on their diversity and ecology is still to its infancyThe present research wants to contribute to uncover the soil fungal diversity of the upper Colombian Andean agro-environment of the Boyacá department Fig. .Figure 1The study area is located on a high plateau  (Cundiboyacense region) in the Eastern Cordillera of the Colombian Andes.This area belongs to Colombian paramos, covers part of Cundinamarca and Boyacá departments and belongs to the altitudinal vegetation belt of the upper Andean forest (upper mountain cloud forest). Since approximately 50 years, human activities have transformed the native forest into a grassland, mostly devoted to subsistence agriculture (potatoes and onions). On the other hand, this area is now knowing important changes and becoming a potential flywheel of socio-economic rescue. Since 2012, in the context of improving the economic picture, some scientific and economic projects aim to introducing economically relevant cultures, such as fine varieties of peaches and apples. In view of this, an important piece in the puzzle of the conceivable forthcoming evolution is, for sure, to acquire a deep knowledge of the microbiological condition of this land, to guide choices aimed at its sustainable use and management.Table 5 (in Peach B plot). Differences recorded for CFU values are difficult to be explained by soil physico-chemical data of soil samples which are similar, as already evidenced above; whereas the low value of CFU observed in the resting grassland could be explained by a shortage of water; on the contrary the orchards are irrigated artificially  to 29% of the woodland sample. Zygomycota represent the 15%, with a range from 9% (resting grassland) to 13–14% (cultivated areas). Least, Glomeromycota and Chytridiomycota sequences have been mostly recorded in the resting grassland, at low frequencies (<0.7% and 0.1% respectively).Taxonomic analyses assigned sequences to five fungal phyla Fig. . As expeEurotiales (Ascomycota) results the most represented order (20%), followed by Mortierellales (Zygomycota) (about 15%), and by three orders always belonging to Ascomycota: Hypocreales (ca 13%), Trichosporales (ca 7%), and Sordariales (ca 5%). Other orders resulted less represented, with values <5%.Figure Trichocomaceae  results the most represented (14%), even if with remarkable differences: the lowest prevalence is retrieved in the apple orchard (5–6%) and the highest (30%) in the woodland soil. Mortierellaceae  is the second most abundant family, representing on average 10% of fungal families in the whole sampling area with an opposite behavior with respect to Trichocomaceae. Indeed, the lowest prevalence (6%) is here observed in an uncultivated soil (grassland) and the highest in the two orchards: apple A and peach B. It is noteworthy that these are the soils in which the phosphorous concentration was higher  also appears quite abundant with a prevalence reaching 3%, mainly recorded in the cultivated sites (4% in average) and the lowest value in the woody site .In Fig. er Table . The twoAscomycota and Basidiomycota are the most represented phyla, OTUs belonging to these taxa have been considered only if representing ≥1% of total diversity in at least one sample, or in any case if exclusively retrieved in one sampling site. On the contrary, all OTUs belonging to other, rarer, phyla  have been considered and analyzed.A finer, manual, bioinformatic analysis on the most abundant and/or significant OTUs was performed to allow resolution at the species level. This was functional to obtaining a clearer and more comprehensive picture of the diversity and of the differences among orchards, grassland, and woodland. Since In each plot, diversity and richness indexes were investigated at the level of OTUs considered as above. The results are reported in Table Ascomycota, Basidiomycota and Zygomycota) where the genus Mortierella is present with the highest number of species. Peach plot harbors the highest number of exclusive species mainly belonging to Ascomycota, followed by the apple and the uncultivated grassland (resting) plots. Most of the basidiomicetous fungi are restricted to woodland plot , consistently with their mycorrhizal association with trees.A Venn’s diagram is reported in Fig. Supplementary Tables Ascomycota is represented by 77 species, listed in Supplementary Table Penicillium is the most represented genus and resolves into 13 species, followed by Acremonium (6 species) and Sarocladium (3 species). The most abundant species are Penicillium virgatum, Penicillium scabrosum, Chaetomium udagawae.Geoglossum fallax (7%). Together with Chaetomium udagawae (see below), G. fallax is one of the most abundant fungi in the study area. This species belongs to a group of fungi named waxcap which includes genera of grassland fungi that are restricted to soils low in enriching nutrients41. Many of these species are typical members of ‘unimproved grassland’, non-intensively managed semi-natural grassland habitats that have not been treated with nitrogen fertiliser42. Taxa assigned to this group are considered to be of conservation significance in several European countries. In this study. G. fallax presence is exclusively associated to the grassland site, an 10 year-abandoned area that can be considered a semi-natural habitat, and its finding is consistent with the literature. This species is considered as a bioindicator of habitat worth to be conserved.Uncultivated grassland, for its part, is characterized by the dominance and exclusively presence of Microsphaeropsis arundinis (4%), Phomopsis columnaris (2%), Ascochyta medicaginicola (1%). The listed species are often associated to plants as pathogens or endophytic fungi43.Notable differences, in comparison with other sites, have also been recorded for Oidiodendron tenuissimum (2%), and Penicillium catenatum (1%). Relevant differences are recorded for Pochonia chlamydosporia  and Penicillium simplicissimum (ca. 2%).The following ascomycetous species result instead exclusive of the woody site: Oidiodendron in the woody site is consistent to its ecology. This is a cosmopolitan genus whose members can usually be found colonizing different cellulose substrates, i.e. litter, wood pulp, bark, and mosses44.The presence of Chaetomium udagawae (10%), C. globosum (3%), C. leptoderma (ca. 1%), Pseudeurotium zonatum , and Mycochlamys macrospora (ca. 1%). Basing on our knowledge, ecological data on Chaetomium udagawae are completely lacking in the literature. In the present study C. udagawae is the most abundant and its dominance in the area is worth to be investigated in a future research. The species recorded (mainly C. globosum and C. udagawae) are dominant in the cultivated areas. The authors assume that their presence is probably due to the high level of soil fertilization  appear notably different in the distribution of the fungal species (the peach A soil hosts 24% more species than peach B), although this difference is difficult to be explained basing on the site characteristics, e.g. sun exposure. Moreover Peach A and Peach B sites are very similar in the agronomic management and other reasons must be found, e.g. the proximity of rich propagule fungal source areas could explain such data.Cephalotrichiella penicillata (3%), and Pyrenochaeta lycopersici (ca. 1%). Moreover, the following species are recorded with relevant differences in abundance compared to the other sites: Penicillium scabrosum (12%), Stachylidium bicolor (3%), Pseudogymnoascus pannorum (3%), Penicillum brevicompactum , Epicoccum nigrum (ca. 3%), Acremonium furcatum , Cladosporium cladosporioides (1%).The peach A site is characterized mainly by the presence of the following species, exclusive of this site: Beauveria caledonica (3%) and Saccobolus globuliferellus (2%). The latter is a fungus strongly associated to dung and its presence is consistent with the organic fertilization occurring in the orchards48.On the other hand, the site named peach B mainly harbors the following species exclusive of this area: Basidiomycota. The peach A site results twofold richest in basidiomycetous species compared to the other sites. Many species are exclusively retrieved in this site, although with very low abundance, e.g. Agaricus bisporus, Conocybe inopinata, Coprinopsis luteocephala, Coprinopsis radiate, Filobasidium magnum, Hannaella oryzae, Naganishia diffluens, Erythrobasidium hasegawianum. The only exclusive species with a relative abundance of at least 1% is Filobasidium floriforme (ca. 2%) often reported in literature associated to fruits and leaves and frequently used as biocontrol agent against plant diseases49.Supplementary Table Agaricus campestris which is the most abundant , and yeasts mainly represented by Solicoccozyma terreus, S. aeria, Saitozyma podzolica (3–4%), species frequently isolated from soil50.Other basiomycetous species are rarely recorded in cultivated sites except Laccaria lateritia (ca. 2%), Ramaria abietina (1%), and Sebacina highly frequent (5%); their presence can be due to the particular habitat of the woody area. In fact, these genera are reported forming mycorrhizae with trees, and orchid species (Sebacina in particular).The woodland site harbors the exclusive presence of Zygomycota, 31 species were recognized (Supplementary Table Mortierella (15 species) and Mucor (8 species) and reach the highest prevalence in both samples belonging to the apple orchards and in the peach A site. The uncultivated grassland and woodland sites harbor about half number of species (11 and 10 respectively). The apple sites are characterized by the exclusive presence of Mortierella exigua, Mortierella wolfii, Absidia cylindrospora, and Actinomucor elegans.For Absidia repens, Mucor gigaspora, Mucor hiemalis, and Mucor zychae var. linnemanniae are exclusive of peach A.Glomeromycota, have been resolved at the species rank , probably favored by the presence of the organic fertilizer  seems to explain the difference observed in the taxonomic diversity of fungi clearly underlined by the presence of the two sub-clusters (apple and peach plots) in Figs 19 for the soil mycobiota associated with soils subjected to different soil managements.Samples were also compared and clustered with respect to their composition in fungal OTUs. From the bootstrap-based clustering analysis Fig. , it cleaAscomycota phylum, in agreement with the international literature55. Basidiomicetous species are mainly recorded in the woodland area, consistently to the fact that many of them, as saprotrophic or symbiontic , show preferences for lignocellulosic material. Zygomycota appear homogenously distributed, although with a slightly higher abundance in cultivated areas probably due to their common association to organic fertilization56. Among families, Trichocomaceae results the most abundant followed by Mortierellaceae, and Nectriaceae. The finer, manual, bioinformatics analysis on OTUs many taxa were identified at species level: 77 species were identified belonging to Ascomycota, 28 to Basidiomycota, 31 to Zygomycota. Only Glomus mosseae and Entrophospora infrequens were identified for the Glomeromycota phylum; for Chytridiomycota only Olpidiaster brassicae was identified. The low numbers obtained for Glomeromycota species, compared to what expectable from previous studies is likely ascribable to known limits of universal primers targeting the ITS1 barcode17. Other gene sequences could be helpful to obtain a major resolution of taxa such as Glomeromycota and Chytridiomycota.Based on the picture emerging from the species composition and from the structure of fungal communities as depicted by the population analysis, some conclusive remarks might be drawn. Both cultivated and not cultivated appear dominated by species belonging to the Ascomycota, and Basidiomycota . Particularly important for conservation, is the exclusive presence of Geoglossum fallax, the dominant species in the grassland plot; this species is considered as a bioindicator of habitats worth to be conserved.The uncultivated areas (grassland and woodland) are characterized by the abundant presence of some exclusive species belonging to Chaetomium udagawae and C. globosum: this is another interesting aspect that is worth addressing in future studies. From the bootstrap-based clustering analysis, fungal communities split into two main macro-clusters: the woodland-grassland and the orchards. This result seems to indicate a response of microbial community to different use of soil in the agro-environment. The influence of land use and managements on microbial communities were already reported in the literature and our findings confirmed this results also for the particular habitats of upper Colombia.Many basidiomicetous species, different from those retrieved in the woodland, characterized the peach orchards. This result needs to be deeply investigated with respect to the environmental and management conditions. These cultivated areas result particularly rich in Retrieved differences in fungal species composition are consistent with the bootstrap-based clustering analysis based on class composition. Considering the study area as a whole, the results obtained seem to draw a taxonomic gradient with the woodland as the most different site compared to cultivated sites and the uncultivated grassland in an intermediate position. Other areas in upper Andean Colombian agro-environments are worth to be investigated in order to confirm the main structure of soil fungal community here reported.Area of Study and sampling sites. The study area is located in the department of Boyacá Fig. , in Sora2, South East-exposed, in which peach trees var. “Dorado” have been planted since 2011. Hereafter named “peach A”;A plot, with an area of 7,454.53 mA second plot, with an area of 6,690.61 m2, North West-oriented, planted with peach trees “Dorado”. Hereafter named “peach B”;A plot (4405.95 m2), North West oriented, in which apples (var. “Anna”) are planted. Two different subplots have been sampled named “apple A” and “apple B”.A control plot (2500 m2) represented by an uncultivated field, North West-oriented, abandoned for 10 years, dominated by graminaceous plants. Hereafter named “resting grassland” (“resting” in the table and graphs).Eucalyptus globulus, Pinus spp., Acacia spp.) and autochthonous plants . This area spans 500 m2 and is adjacent to the edges of the experimental farm.A further control plot, named “woodland” (“wood” in the tables and graphs), represented by a woodland, South East-oriented, planted 10 years ago with alloctonous . For soil fungal charge, metabarcoding, and physico-chemical analyses, three soil samples were collected in each plot on the vertices of a triangle with a sampling point placed as far as possible from the others, but at least 10 m away from field edges. Soil samples (500 g each) were aseptically collected at 3 cm depth with a sterile spoon, after removing vegetation cover, debris, and stones, and put in sterile polyethylene bags. Samples were maintained at low temperatures until processed: −20 °C for metabarcoding and +4 °C for fungal counts. For metabarcoding, samples referring to the same plot or subplot were pooled before freezing.TOT), organic carbon (CORG), C/N ratio, plant-available phosphorous (P), calcium (Ca), magnesium (Mg), potassium (K), soil composition in sand, silt, and clay.Chemical properties of soils were determined by Labanalysis, Casanova Lonati , according to the Italian standard protocols (DM 13/09/99). The following parameters were evaluated: pH, organic matter, total nitrogen , 0.5 µM of each primer. The cycling program, performed on a MJ Mini thermal cycler , included an initial denaturation (95 °C for 3 min), followed by 25 cycles at 94 °C for 30 s, 55 or 60 °C C for 30 s, 72 °C for 30 s, and final extension (72 °C for 5 min). Clean-up of amplicons was performed using Agencourt AMPure XP SPRI magnetic beads (ThermoFisher Scientific). Illumina sequencing libraries were finally constructed through the link of indexes , quantified using a Qubit 2.0 Fluorometer (ThermoFisher Scientific), normalized and pooled. Libraries were subjected to paired-end sequencing  on an Illumina MiSeq sequencer at BMR Genomics . The sequencing data were deposited in The European Nucleotide Archive (ENA) under the Accession Number PRJEB32659.Total DNA was extracted starting from 350 mg of each sample with the NucleoSpin Soil kit  according the manufacturer’s specifications and quantified using a Qubit fluorometer . For amplicon production, the ribosomal ITS1 region  was targeted, by using primers BITS and B58S340. Raw data were demultiplexed and barcodes and primers were trimmed off. Quality filters were applied, including a length threshold (100 bp) and removal of singletons. High-quality reads were clustered into operational taxonomic units (OTUs) at 97% similarity using VSEARCH58 and chimaeras excluded using UCHIME59. OTUs were finally annotated using the UNITE fungal ITS reference data set within RDP classifier (http://rdp.cme.msu.edu) and the Worcup ITS reference as training dataset.Data analysis was performed using the pipeline PIPITShttps://rdp.cme.msu.edu/) and using the specialized fungal pages within GenBank. Finally, relative abundances of microbial taxa in each sample were calculated and compared.Species were assigned on selected OTUs against mycobank (mycobank.org), RDP (60. Diversity in composition among samples (β-diversity) was compared, at all taxonomic ranks, through: (i) bootstrap-based clustering analysis, using the R function pvclust61; (ii) double clustering analysis, through the R function heatmap.2 of the R library G plots62, setting the pvclust output as sample dendrogram; (iii) Principal Coordinates Analysis (PCoA) analysis based on Bray-Curtis dissimilarity matrix, performed using the R library Vegan60.α-diversity matrices were assessed by computing Chao 1, Abundance Coverage Estimator (ACE) and Shannon indexes at the level of OTUs using the R library Vegan63 to detect, quantitatively, cultivable microfungi. According to previous studies65, 10 g of each soil sample was suspended 1:10 (w/v) in sterile water + agar (0.15%) and shaken for 20 min. Suspensions were further diluted 1:10 and 1 ml aliquots of the 10−4 suspension were homogeneously distributed with a sterile blent rod onto 16 cm diameter Petri dishes containing MEA medium  and antibiotics . Five replicates of each sample were prepared, and incubated at 25 °C in the dark. Inoculated plates were observed continuously during 2 weeks by means of a stereomicroscope, and the number of developed colonies was expressed as CFU (Colonies Forming Units) per gram of soil (dry weight). Soil dry weight was measured by an infrared moisture balance .After collection, soil samples were processed within 15 days, using the Dilution Plate TechniqueLegends of supplementary tablesData set 1Data set 2Data set 3Data set 4Data set 5Data set 6


This article provides data related to different activities in the hydrocarbon supply chain (HCSC). HCSC structures from Crude oil and natural gas supply chains. There are three main sectors in the HCSC related to activities in the production areas, processing plants, and demand terminals. The considered activities comprise the upstream sector of the crude oil and all sectors of the natural gas. The data were collected from Saudi Arabia, considering the main production and processing plants. The provided data are useful in tactical planning of crude oil, natural gas, and natural gas products of the HCSC. These data support the research article entitled “A Multi-Objective Optimization Model for Tactical Planning of Upstream Oil & Gas Supply Chains” [1]. Figure 1 presented in Ref. [1.•Gas-oil ratio (GOR) corresponding to crude oil type for different reservoir streams.•Crude oil composition; yield of main components  at each entity.•2, H2S, methane, and ethane.Natural gas composition, for instance, the yield of COStream composition and yield at each plant:2.The demand for crude oil and gas by-products by local customer, local industry, and international customer and the corresponding selling prices.3.The capacity of each entity, the capacity of routes connecting the entities, and the transportation modes utilized through these routes.4.Cost elements: production and processing costs at each entity, and transportation costs.The provided data can be classified as four groups, as follows:2This article includes quantitative data collected from puplished reports, official and government websites of Saudi Arabia, and Google Maps web. Cost of transportation via the pipelines has been estimated based on that it costs US$0.6 to transport and pump an oil barrel from Ras Tanura to Yanbu. It is estimated that the pipeline transportation cost per barrel is SR0.0016466/Km (US$l = SR3.75). To estimate the transshipment cost of each barrel, the Google Maps web  was usedThe local demand for crude oil and gas products have been estimated based on the population size of Saudi Arabia as per 2016 (32.28 Million) . Then thThe gas oil ratio (GOR) and yiels of by-products were collected from puplished article  Plants c


A higher density of infiltrating CD20+ B lymphocytes was associated with tumours of the right colon (P = 0.025) and of lower stages (P = 0.009). Furthermore, patients whose tumours were highly infiltrated by CD20+ B lymphocytes had a significantly improved disease-specific survival , which remained significant in multivariable analysis. CD20+ B lymphocytes were highly and positively associated with CD8+ T lymphocytes (P < 0.001), and part of the prognostic role was found to be a cooperative effect between these lymphocyte subsets. Our results support a favourable prognostic value of tumour-infiltrating CD20+ B lymphocytes in CRC. Furthermore, a cooperative prognostic effect between CD20+ B lymphocytes and CD8+ T lymphocytes is suggested.The anti-tumour immune response is critical to patient prognosis in colorectal cancer (CRC). The aim of this study was to investigate infiltration of B lymphocytes into CRC tumours, and their clinical relevance, prognostic value and relation to other immune cell subsets. We used multiplexed immunohistochemistry and multispectral imaging to assay the amount of infiltrating CD20 Curative treatment is based on surgical resection, but still almost half of the patients will die of their disease due to tumour metastasis. Immune infiltration has been proven to be of powerful prognostic value in CRC2. In the era of immunotherapy, a more detailed understanding of how the immune response is organised to counteract tumour growth and spread, may lead to important prognostic clues and new targets for therapy.Despite medical advances, CRC remains one of the most deadly cancers worldwide3. The prognostic importance of infiltrating subsets of T lymphocytes in CRC has been widely accepted, and subsequently led to a joint task force to introduce the Immunoscore, based on immunohistochemical (IHC) evaluation of T cell markers, into clinical practice4. The role of infiltrating B lymphocytes is less explored and in matters of prognostic importance consensus has yet to be reached5. In addition to the adaptive immune response, cells of innate immunity are found at the tumour site. Macrophage infiltration has been linked to an improved prognosis in CRC6, while the prognostic importance of neutrophils is still uncertain10.The adaptive immune response is orchestrated by antigen-specific T and B lymphocytes. T lymphocytes are known combaters in anti-tumour immunity and can inhibit tumour growth by direct killing (cytotoxic T lymphocytes)11, while most other immune cell subsets mainly reside in the tumour stromal compartment. Infiltration of regulatory T lymphocytes is somewhat surprisingly also associated with an improved prognosis in CRC, but a higher ratio of CD8+ to FOXP3+ cells does appear to improve prognosis13. Similar trends have been seen when comparing the ratio of tumour infiltrating M1 to M2 subsets of macrophages14. In the Th1/Th2 paradigm, the activity of the cytotoxic T cells is supported by the Th1 lineage and M1 macrophages, while in contrast regulatory T lymphocytes, B lymphocytes and M2 macrophages are more closely related to the tumour promoting Th2 response15. However, coordinated T and B lymphocyte responses are well established in both autoimmunity and allograft rejection17. In addition, small lymphoid organizations that contain both T and B lymphocytes - called tertiary lymphoid structures (TLS) - are detected in tumours and linked to a potent lymphocyte response and a good prognosis, suggesting that the B lymphocytes may collaborate with T lymphocytes in anti-tumour immunity18. Towards the goal of developing more efficient therapies, understanding the role of B lymphocytes in the immune response to CRC is critical.Both the intratumoural localisation and functional orientation of immune cells have been shown to carry prognostic information. For instance, the strongest prognostic value of the cytotoxic T lymphocytes in CRC is found within the tumour epithelium+ B lymphocytes, CD8+ cytotoxic T lymphocytes, and FOXP3+ T regulatory cells,) and the innate (CD68+ macrophages and CD66b+ neutrophils) immune system, in CRC tissue specimens. By this we could study the individual clinical relevance and prognostic importance of B lymphocytes, but also the interrelation with other immune cell subsets and their combined prognostic value.In this study, we have used multiplexed IHC and multispectral imaging to analyse the degree of infiltration of five different immune cells belonging to both the adaptive , CD8 (cytotoxic T lymphocytes), CD20 (B lymphocytes), CD68 (macrophages) and FoxP3 (T regulatory cells). Pan-Cytokeratin was used to identify tumour tissue, and DAPI was used for nuclear counterstaining. Spectral unmixing resulted in a composite image displaying the different immune markers Fig. . Machine2 Fig. . The exc2 Fig. . Immune + cells were more often highly infiltrating tumours of the right colon (Table P = 0.025) and tumours of lower stages (Table P = 0.009). This pattern closely follows that seen for most other immune cell subsets , which remained significant in a multivariable Cox regression model including age, localisation, stage, and stratified by sex (Table P = 0.045). The prognostic value of CD8, CD68 and FoxP3, previously demonstrated in literature, was confirmed by our study  to that of CD8 (high or low) in the stromal compartment. The best prognosis was found in patients whose tumours were highly infiltrated by CD8+ cells . CD20 is expressed throughout the different stages of B cell development, but is down-regulated upon differentiation into plasma cells19. CD20 is thus a marker for naive B cells, germinal center B cells, and memory B cells. The multiplex IHC method is advantageous for studies of interrelationships between different immune cell subsets, since it allows immunostaining of multiple markers within one image. Multiplex IHC and multispectral imaging has been validated as a good method to study tumour immune infiltration in two independent studies, showing reliable data and a good overlap with conventional IHC staining and evaluation21. The method is not optimal for use on whole tissue sections for a large patient cohort, so instead the study was performed using TMA. This together with the chosen digital approach has the disadvantage of not being able to assess the often heterogenic distribution of immune cells and to avoid e.g. necrotic areas. These problems were partly controlled for by manually inspecting each scanned image and when necessary excluding parts or whole images. Furthermore, tumour immune infiltration was calculated as a mean value from two individual TMA cores for most patients. An advantage of using a digital approach is, however, to overcome observer variability. A weakness of this study is that a large percentage of cases are rectal cancers, and that part of these have received preoperative radiotherapy, which may impact immune cell infiltration. Both reduced and enhanced immune responses are shown in response to irradiation24. For this reason, irradiated rectal cancers were excluded from the survival analyses. However, the effect of irradiation on immune infiltration in rectal cancer and the relation to prognosis is interesting, and a topic for further investigation. The well-established prognostic value of the different T lymphocyte subsets13 and macrophages25, as previously reported in literature using conventional IHC, could be identified also in this study, further strengthening the validity of the method used.We used multiplexed IHC and multispectral imaging to score five different tumour-infiltrating immune cells in CRC using well-established markers  and in accordance with relevant guidelines and regulations. The National Supervisory Authority of Welfare and Health gave us permission to use tissue samples without the individual informed consent of the patients in this retrospective study . For construction of tissue microarray (TMA) blocks an experienced gastropathologist annotated representative tumour areas on H&E slides. The TMA blocks were constructed using a TMA Grand Master 3D instrument  by punching 1 mm cores from archived formalin-fixed and paraffin-embedded (FFPE) tissue samples. The TMA used for this study included two 1 mm cores taken within the tumour mass, one more central and one more peripheral to avoid systematic heterogeneityTM 7 Solid Tumour Immunology Kit , but optimized for colorectal FFPE TMA tissue sections. In brief, tissue TMA slides were sequentially stained using antibodies against CD66b, CD8, CD20, FoxP3, CD68 and pan-Cytokeratin. The CD4 antibody used in the kit was exchanged by CD66b . The CD8 antibody in the kit was exchanged by CD8 . Concentrations of antibodies and Opal dyes were adjusted . All standard epi-flourescent filters were used; DAPI, FITC, CY3, Texas Red, and CY5. Whole slide scans were acquired using x10 magnification. The Phenochart software (PerkinElmer) was subsequently used to mark TMA cores from the whole slide scans for subsequent multispectral imaging using x20 magnification. A spectral library was collected by single stainings of colorectal FFPE tissue sections with the CD20 antibody and the individual Opal dyes and subsequent imaging. An unstained sample was used as autofluorescence control and utilized together with the spectral library for spectral unmixing in the inForm software (PerkinElmer). Composite images were compared to single stained slides and inspected for crosstalk and interference.Images were quantified using the inForm software in two steps. Firstly, 15 TMA cores representing the heterogeneous nature of CRC, were selected to train machine-learning algorithms for tissue segmentation, cell segmentation and cell phenotyping, that were later applied on the whole TMA cohort. The software was first trained to segment tissue by manually annotating tumour tissue, stromal tissue, and no tissue, according to manufacturer´s recommendations. Cell segmentation was based on the nuclear DAPI stain, but assisted using nuclear FoxP3, and membrane CD8, CD66b, CD20 and CD68 staining. For classification of cell phenotypes, the software was trained by manually annotating 34–72 cells identified by each marker. Each scanned image was examined by one observer under the supervision of an experienced gastropathologist. Exclusion criteria for whole TMA cores were; loss of large part or whole core (n = 33), lack of tumour or stromal tissue (n = 32), bad quality of staining (e.g. weak pan-Cytokeratin stain) (n = 42), and heavy necrosis (n = 24). In total, this lead to the exclusion of 5 patients due to large part or whole cores lost, 3 patients due to lack of tumour or stromal tissues, 10 patients due to bad quality of staining, 5 patients due to heavy necrosis, and 13 patients were excluded for a mixture of the above described exclusion criteria. Four of the remaining patients had duplicate TMA sets, and for these patients the immune infiltration was calculated from all available TMA cores. One patient was excluded due to lack of clinical information. After exclusions, 275 patients remained in the study, of which 209 had immune data from two or more cores, and 66 had immune data from one TMA core.2 . For patients with data on two TMA cores, an average number of cells per mm2 was calculated from the total number of cells divided by the total tissue area. Infiltrating immune cells, as identified by the different markers, were further divided into groups of high and low infiltration by the median number of infiltrating cells.We inspected each TMA core for areas of disinterest, which were manually drawn and subtracted from the image. Exclusion areas included; cellular debris, mucus, large vessels, areas of necrosis, large lymphoid aggregates and normal epithelial tissue. After exclusion of cores and regions, cell segmentation summary data was collected for each TMA core, and converted to number of individual cell types per mmP < 0.05 was considered statistically significant.Statistical analyses were performed using PASW Statistics 25 . The χ2 test was used for cross-tabulations and the linear-by-linear association test for linear relationships. Correlations between continuous variables were analysed using the Spearman´s rank correlation test. Disease-specific survival was estimated using Kaplan-Meier survival analysis, and comparisons of differences in outcome between groups were analysed using the log-rank test. Multivariable survival analyses were performed using Cox proportional hazard models. Testing of the Cox model assumption of constant hazard ratios over time involved the inclusion of a time-dependent covariate separately for each testable variable. There was weak indication that gender did not follow the assumption, therefore, in multivariable analyses, a stratified analysis for gender was performed. Interaction terms were considered, but no significant interaction was found after the Bonferroni correction for multiple testing. Supplementary Information


In recent years, deletion and insertion polymorphisms (DIPs) were treated as a novel complementary tool with huge potential for forensic applications. In this study, we utilized 30 DIP loci to make a comprehensive research of allele frequency distribution and compute forensic parameters to evaluate the efficiency of forensic applications in the 295 unrelated healthy individuals of Kyrgyz group, and in addition, infer the genetic relationships between Kyrgyz group and 24 other previously studied groups. No significant departures from Hardy-Weinberg equilibrium and linkage disequilibrium were observed at these 30 DIP loci. The combined power of discrimination and the combined probability of exclusion for all 30 DIP loci in Kyrgyz group were 0.9999999999989 and 0.9939, respectively. Furthermore, the results of the interpopulation differentiations, phylogenetic reconstruction, population genetic structure and principal component analyses suggested that Kyrgyz group had relatively close genetic relationships with Kazakh and Uygur groups. However, it was also important to stress that 15 loci were selected out from these 30 DIP loci using the method of selecting ancestry markers, which could be utilized for further ancestry inference study relatively. DIPs could in turn be split into those with multiple alleles  and with only two alleles 1. Nearly all of the multiallelic DIPs were based on tandem repeats, mostly short tandem repeats (STRs)1, however, the 30 DIP loci chosen in this study were diallelic.The majority of human genome sequence variation could be attributable to nucleotide substitution polymorphisms, with the rest attributable to deletion and insertion polymorphisms (DIPs)2; (ii) an abundance of distributions in human genome with the density ranking only second to that of SNPs3; (iii) small amplicon size improving the probabilities of successfully analyses for highly degraded DNA4; (iv) lower rates of mutations, which made them more stable than STRs2; (v) PCR amplification without the generation of stutter peaks, making the allelic genotyping results more concise and precise5; (vi) the marked differences of allele frequencies in some loci between diverse populations from geographically separated regions, therefore they had potential to be applied in biogeographic ancestry analyses7.Further, it was particularly noteworthy that DIPs possessed the desirable properties of both STRs and single nucleotide polymorphisms (SNPs), which could be summarized as followings: (i) length polymorphisms allowing them amenable to analyze through simple capillary electrophoresis in common forensic DNA laboratories8, which are mainly found in the southwestern part of the Xinjiang Uygur Autonomous Region, China8. Now we use Qiagen Investigator DIPplex reagent , a commercial kit, to analyze 30 DIP loci distributed on 19 pairs of chromosomes and in addition, this kit was put into use in the previous population studies which were already published11. We gathered the bloodstain samples of Kyrgyz group in Xinjiang Uygur Autonomous Region and used the kit mentioned above to obtain population data to acquire more information about the Kyrgyz ethnic minority’s genetic background.The Kyrgyz ethnic minority with the population totaling over 0.18 million belongs to the 56 ethnic groups officially published by the People’s Republic of Chinap = 0.05/30 = 0.0017). Allele frequencies and forensic efficiency parameters of 30 DIPs in Kyrgyz group were depicted in Fig. 12) implying that the panel of 30 DIP loci could be a complementary tool for STR typing system in forensic paternity cases. We also detected the power of discrimination (PD) ranging from 0.4967 (HLD39) to 0.6451 (HLD40), and combined power of discrimination (CPD) reached 0.9999999999989, which was able to meet the satisfactory levels for the individual identification of forensic demands13. Among these forensic parameters, it was significantly pronounced that the lowest values of He, Ho, PD, PE, PIC were obtained at HLD39 locus, indicating that HLD39 locus showed relative low forensic efficiency in the studied Kyrgyz ethnic group.The systematically experimental operations and analyses of the samples had been conducted under the laboratory stringent criteria before the data of Kyrgyz group obtained. There were no significant departures from Hardy-Weinberg equilibrium (HWE) in the 30 DIPs after applying a Bonferroni correction  of 0.0700 to 0.2000 were found at 12 loci (Supplementary Table Linkage disequilibrium (LD) tests among these 30 DIP loci in Kyrgyz group were performed using the SNPAnalyzer program. As shown in the Supplementary Figure p values were shown in Supplementary Table p < 0.05) between Kyrgyz and the 24 reference populations were presented intuitionally in bar diagram format combined with the result of structure analysis (K = 4) in Fig. 11 at two loci; Uygur group11 at seven loci; Bai group15 at ten loci; Tibet Tibetan and Qinghai Tibetan group16 at 12 loci; Beijing Han11 and Uruguayan group17 at 15 loci; Central Spanish group18 at 16 loci; Tujia19 and Xibe group20 at 17 loci; Basque18 and Dane group21 at 18 loci; Hungarian group22 at 19 loci; Guangdong Han23 and South Korean group24 at 20 loci; Shanghai Han25 and She group25 at 21 loci; Yi group26 at 22 loci; and six Mexican groups27 at 21–26 loci, respectively. According to the diagram, the Kyrgyz group had the lowest genetic divergence with Kazakh group (significant differences found at two loci) in contrast with Mexican Amerindian group (significant differences found at 26 loci). Furthermore, some loci with high ethnic diversities could be observed: two loci (HLD81 and HLD111) all showed significant differences at 21 compared groups, on the contrary, HLD101 and HLD88 at four and six respectively. It was suggested that the abilities of some DIP loci to distinguish ethnic groups were at different levels3. Note that, studies of more DIP loci in more ethnic populations should be required for the different application purposes in forensic science.To explore the hereditary similarities and differences, the studied Kyrgyz group was compared with previously published groups at these 30 DIP loci utilizing the analysis of molecular variance (AMOVA) method on the basis of Arlequin software version 3.1. The locus-by-locus R statistical software. Based on 30 DIP loci, one heat map of pairwise fixation index (Fst) values  utilizing the SPSS 18.0 software . As shown in Fig. 30. Since Western Han Dynasty to the middle of the Qing Dynasty, mainly from the Yenisai River to the Tianshan Mountains and Central Asia, Kyrgyz group experienced five westward migrations which were basically facilitated by warfare29. The studied Kyrgyz group which inhabits the southwestern region of Xinjiang broadly assimilated Western Regions culture after the long term of mixed dwelling with the Uygurs, Kazakhs, Hans and Mongolians etc29. In contrast, the ancestry of Xinjiang Xibe is different from Kyrgyz group. Xibe traditionally resided in northeast China and immigrated to Xinjiang during the middle of the eighteenth century. Thus, Xinjiang Xibe group had the same pattern with other East Asian groups as shown in structure analysis of Fig. 31. That was the reason why the Xinjiang Xibe group came from the same region as Kyrgyz group was treated as a member of East Asian groups in Fig 8.As presented in Fig. Fst values calculated by GENEPOP program. As shown in Fig. For further investigation of genetic correlations among 25 populations, multidimentional scaling (MDS) analysis was performed using SPSS 18.0 software  and provided a two-dimensional representation of genetic relationships based on pairwise DA values, phylogenetic reconstruction tree encompassing two main branches was performed to verify the genetic relationships between the Xinjiang Kyrgyz and 24 reference populations, which was reconstructed utilizing neighbor joining method by MAGA software v5.0. As shown in Fig. In order to estimate the studied population affiliations, based on the 11, while Kyrgyz group partially mixed the genetic component of Mongol, Khitan, Turkic, Uygur and Han groups since the ancient time32. Furthermore, Kyrgyz, Kazakh and Uygur groups almost possessed the same religious belief and the close geographic distance, more likely leading to the cultural exchange among these three groups29.In long-term development of Chinese history, the Kazakh group was formed as a combination of the Turkic, Wusun, Khitan and Mongolian people, and Uygur group was stemmed from a branch of Turkic peopleK that represented the number of hypothetical ancestral populations33. As shown in Supplementary Figure 34. At K = 2, the East Asian groups were distinguished from both European groups  and Mexican groups , with the constitution of entirely red components. At the same time, the Central Asian groups, including Kyrgyz, Kazakh and Uygur groups, shared obviously mixed memberships in red and green color. Five European groups and six Mexican groups were almost filled with green components; therefore, European and Mexican groups could not separate from each other at K = 2. Whereas, the Central Asian groups were separated from other populations evidently with the combination of red, green and yellow components in different proportions at K = 4  that discrepant values of average insertion allele frequencies among the clusters  could be over 0.2937. After that, we again performed structure analyses of the studied Kyrgyz group and 24 reference populations with the result (K = 4) showing in the Supplementary Figure 38. However, in the Fig. Based on the analyses mentioned above, we have a sufficient reason to insist that some loci with great genetic divergence were existed in these 30 DIP loci, which were valid for detecting population structure and distinguishing Kyrgyz ancestry information from other populations distributed in different administrative divisions. However, abilities of these 30 DIP loci appeared to be diverse at the power of describing population clusters. In order to pinpoint the loci that more contributed to population discrimination, 15 loci among these 30 DIP loci, including HLD39, HLD45, HLD48, HLD56, HLD58, HLD70, HLD64, HLD81, HLD83, HLD111, HLD114, HLD118, HLD122, HLD125 and HLD128, were selected out based on population-specific allele frequencies In brief, to explore the genetic background and genetic structure of the studied Kyrgyz and other populations further, we could choose efficient AIMs with reference to the method mentioned above to acquire more comprehensive and accurate population genetic information and to lay a solid foundation for the ancestry inference study in the future.In this study, the allele frequencies and statistically forensic parameters of the autosomal 30 DIP loci were obtained for the researches of population genetics and forensic applications. The panel, as a useful forensic tool, was suit for individual identification, but could barely be treated as supplementary markers for STR loci in paternity testing. The results of interpopulation differentiations, genetic distances, principal component, multidimentional scaling, phylogenetic and structure analyses indicated close genetic relationships between Kyrgyz and the two Central Asian groups (Kazakh and Uygur groups). Furthermore, we selected out 15 loci with sufficient capacity of ancestry inference from these 30 DIP loci, which could be implemented in ancestry inference study. For the sake of better understand the origin and genetic evolution of Kyrgyz group, further study should be performed in later research.The bloodstain samples of 295 unrelated healthy individuals were collected from Kyrgyz group residing in Xinjiang Uygur Autonomous Region, China. During the course of collecting samples, we excluded the samples gathered from two individuals who had blood relationships within three generations. All participants concerned to this study provided the written informed consents. The research was in accordance with the human and ethical research principles and approved by the ethics committee of Xi’an Jiaotong University Health Science Center.On GeneAmp PCR System 9700 thermal cycler , a multiple PCR amplification with five-color fluorescence of autosomal 30 DIPs was performed with Investigator DIPplex reagent on the basis of manufacturer’s instructions. Genotyping of DIPs was analyzed by capillary electrophoresis on ABI 3500 Genetic Analyzer  and processed by GeneMapperv3.2 software .39.The study was conducted following ISFG recommendations on the analysis of the DNA polymorphisms as described by Schneider40 was chosen to evaluate locus-by-locus p values using AMOVA method. The heat maps were performed by R statistical software v3.0.241 based on Fst and DA values which were calculated by allele frequencies and raw population data, respectively. The SNPAnalyzer 42 was selected to test LD for all pairwise DIP loci. Three plots of PCA and a plot of MDS analysis were carried out by SPSS 18.0 software . Population genetic structure analyses were conducted by STRUCTURE v2.2 program33. The phylogenetic tree was described using MAGA v6.06 software based on DA values calculated by DISPAN program43.Forensic statistical parameters of 30 DIP loci in Kyrgyz group, such as the values of HWE, Ho, PE, PD, PIC and allele frequency distributions were calculated by modified Powerstate (version1.2) spreadsheet , and He values were calculated based on allele frequencies. Arlequin software (version3.0)The datasets analyzed during the current study are available from the corresponding author upon reasonable request.Supplementary Information