Saccharum spp.) and other members of Saccharum spp. are attractive biofuel feedstocks. One of the two World Collections of Sugarcane and Related Grasses (WCSRG) is in Miami, FL. This WCSRG has 1002 accessions, presumably with valuable alleles for biomass, other important agronomic traits, and stress resistance. However, the WCSRG has not been fully exploited by breeders due to its lack of characterization and unmanageable population. In order to optimize the use of this genetic resource, we aim to 1) genotypically evaluate all the 1002 accessions to understand its genetic diversity and population structure and 2) form a core collection, which captures most of the genetic diversity in the WCSRG. We screened 36 microsatellite markers on 1002 genotypes and recorded 209 alleles. Genetic diversity of the WCSRG ranged from 0 to 0.5 with an average of 0.304. The population structure analysis and principal coordinate analysis revealed three clusters with all S. spontaneum in one cluster, S. officinarum and S. hybrids in the second cluster and mostly non-Saccharum spp. in the third cluster. A core collection of 300 accessions was identified which captured the maximum genetic diversity of the entire WCSRG which can be further exploited for sugarcane and energy cane breeding. Sugarcane and energy cane breeders can effectively utilize this core collection for cultivar improvement. Further, the core collection can provide resources for forming an association panel to evaluate the traits of agronomic and commercial importance.Sugarcane ( Saccharum spp.) is a perennial grass, belonging to the Poaceae family and Andropogoneae tribe, which is grown widely in tropical and subtropical regions. It is the highest yielding crop worldwide Saccharum. Sugarcane cultivars are selected primarily for high sucrose content and energy cultivars for high biomass and fiber with low sucrose content. Biomass level of energy cane cultivars out-performs many other grasses cultivated for biofuel production, including switchgrass, elephant grass, Miscanthus, and sorghum in the southern US Sugarcane  which is characterized by high sugar and low fiber content S. spontaneum , which is resistant to biotic and abiotic stresses S. officinarum and 15% from S. spontaneumSaccahrum spp. has made sugarcane and energy cane breeding cumbersome. The genotypes utilized over decades in earlier breeding programs are a limited number of S. spontaneum and S. officinarum clones, which has resulted in a narrow genetic base of sugarcane cultivars The origin of modern sugarcane cultivars is from inter-specific hybridizations of domesticated species Saccharum spp. based on morphology, chromosome numbers and geographic distribution has been a matter of debate for a long time. The Saccharum genus was believed to consist of six major species, including two wild species S. spontaneum and S. robustum and four cultivated species, S. officinarum, S. barberi, S. sinense and S. eduleSaccharum species: viz. S. officinarum and S. SpontaneumSaccharum genus together with related genera, such as Erianthus, Miscanthus, Narenga, and Sclerostachya were referred to as the “Saccharum Complex” Saccharum complex using molecular markers Saccharum spp by extensive molecular dissection. Two duplicated “Saccharum Complex” germplasm collections known collectively as the “World Collection of Sugarcane and Related Grasses” (WCSRG) were utilized. One WCSRG is maintained in Coimbatore, India and the other in Miami, FL, USA. The National Germplasm Repository located at the USDA-ARS Subtropical Horticulture Research Station in Miami, FL maintains the WCSRG in the USA The classification of the Saccharum spp. would provide a subset of representative accessions and can facilitate extensive examination at phenotypic, physiological and genetic levels. Thus, it could substantially utilize the contributions of the WCSRG in sugarcane and energy cane breeding programs.With its large number and genetically complex accessions, it is a formidable task to fully characterize and use the WCSRG in breeding programs. A core collection that is a condensed assembly of the entire collection with maximized genetic diversity and minimized redundancy is essential for its utilization Zea maysSorghum bicolorSolanum lycopersicumOryza sativaVitisTriticum aestivumHordeum vulgareEucalyptusGenetic markers are widely applied for diversity analysis, genetic trait mapping, association studies and marker assisted selection http://www.ars-grin.gov/npgs/index.html). The NPGS caters the need of researchers by acquiring, preserving, evaluating, documenting and distributing crop germplasm. There were 1002 non-redundant accessions in the WCSRG maintained at the USDA-ARS Subtropical Horticulture Research Station, Miami, FL, and made available for free distribution. These accessions were mostly survivors from Hurricane Andrew in 1992 with some curated new accessions. The S. spontaneum accessions are maintained in 7-gallon pots on a concrete pad and not allowed to flower as they are considered invasive. The rest of the accessions are planted in the field and rotated to new field plots every 4 years. The mature plants are cut to the ground every year in the early spring until replanting. The accessions represent collections from 45 different countries  . The selected SSR markers were then used for genotyping each accession in the WCSRG.In total, 191 SSR primer pairs selected from different publications  were scr3) according to the modified protocol of Creste et al. Two genotyping platforms, polyacrylamide gel electrophoresis (PAGE) with silver staining and capillary electrophoresis with an ABI 3730 sequencer were used to separate/visualize the PCR products. For the PAGE system, a C.B.S. electrophoresis unit  was used for the PCR product separation. The amplified products were loaded in non-denaturing 6% polyacrylamide gel electrophoresis , 1.33 mL 10% APS (ammonium persulfate), and 66.5 µl TEMED]. The electrophoresis was conducted in 0.5 X TBE running buffer at 350 V for approximately 1 hour 45 minutes and SSR amplicons were visualized by silver staining (0.2% AgNOhttp://www.ars-grin.gov/), which has an open free access to scientists in the world-wide community, and will be available upon request.For the ABI 3730 sequencer system, forward primers were labeled with fluorescent dyes, 6-FAM, VIC, NED or PET, allowing subsequent multiplexing. PCR reactions of the four primer pairs were performed independently, and the amplified PCR products were checked on a 1% agarose gel. The optimized amounts of four different fluorescence dye-labeled PCR products of the same genotype were multiplexed. Combined PCR products were denatured at 95 °C for 5 min and mixed with GeneScan™ 600 LIZ™ size standard  and Hi-Di formamide for separation on ABI 3730 Genetic Analyzer . The GeneScan files generated were analyzed using GeneMarker V2.4.0 . The peak sizes were automatically calibrated against the 600 LIZ™ size standards with default module settings. The alleles were mainly called by the GeneMarker software in couple with manual rechecking. The presence of a peak was scored as “1” and its absence was designated as “0”. The genotypic data are made publically available through the Germplasm Resources Information Network (GRIN) database (He) The binary data matrix of alleles for each SSR locus was constructed from evaluation of all the accessions in the WCSRG. PowerMarker V3.25 software was used to calculate allele frequency, number of alleles per locus, percentage of polymorphic bands, PIC, and gene diversity  was set from 1 to 15, and at least ten runs per K were conducted separately with 100,000 generations of ‘burn-in’ and 100,000 Markov chain Monte Carlo (MCMC). The best K value was determined based on ad hoc quantity (ΔK) analysis The population structure and number of subpopulations present in the WCSRG was assessed by model-based clustering algorithms using STRUCTURE V2.2 Saccharum accessions belonging to different species. These markers yielded 276 alleles with 2–13 alleles per primer pair and their PIC value ranged from 0.195 to 0.375. To screen WCSRG, 36 SSR markers with high PIC values were selected to genotype each accession in the WCSRG. Out of 36 SSR markers, 14 primer pairs could be located on eight different sorghum chromosomes and the other 22 could not be mapped on sorghum genome (A pilot experiment was carried out for screening 191 sugarcane SSR markers  with eigm genome . In totam genome . In totam genome . Of the I) was low in most cases. It ranged from 0.012 (UGSM667) to 0.395 (SEGM2dot) with an average of 0.132. For the majority of primer pairs, the power of exclusion (Q) was moderate ranging from 0.178 (SEGM2dot) to 0.840 (UGSM667) with an average of 0.515  and S. robustum (85.65%)  followed by S. robustum (0.263), with an average of 0.276  between S. officinarum and S. hybrid and other S. spp. with unknown accessions  . The aveectively  indicatiof 0.276 . Based ocessions .S. spontaneum clustered in group 1, S. hybrids clustered with S. officinarum, S. robustum, S. barberi, S. edule and S. sinense in group 2 while the majority of accessions of unknown speciation and the species in other genera such as Erianthus, Miscanthus, and Sorghum  of uncertain species name, which are likely Spontaneum spp. Subpopulation 2 consisted of 218 S. officinarum accessions, 101 S. hybrid accessions, 66 accessions from other Saccharum species, 4 Miscanthus hybrid accessions, and 55 unknown/pending accessions. Seventy-six accessions were identified in subpopulation 3 including two major non-Saccharum species existing in the WCSRG such as Miscanthus and Erianthus, which show high genetic divergence compared with subpopulations 1 and 2.The population structure of the WCSRG was analyzed by STRUCTURE V2.2. The ad hoc quantity (ΔK) analysis Saccharum species, which were pre-defined by the germplasm curators. However, based on the AMOVA analysis, the фst (0.160) among the three major subpopulations inferred by the structure analysis was higher than the фst (0.108) among the six major species.The distance-based AMOVA analysis revealed genetic variance among and within the populations were highly significant (P<0.001) and the variation within subgroups (89%) was significantly higher than that among subgroups (11%) . SignifiTo construct a core collection representing most of the genetic diversity in the WCSRG, the maximum length sub-tree for disequilibrium was calculated using DARwin. From this, a core collection of 300 accessions representing most of the genetic diversity was identified . GeneticGenotypic evaluation of the sugarcane germplasm as a potential breeding material provides essential information so that cane breeders can utilize more genetically diverse parents in their breeding programs. In this study, we evaluated all 1002 accessions available in the WCSRG using SSR markers to estimate the genetic diversity and select accessions for the core collection. The WCSRG is currently not widely used but is potentially a great resource for sugarcane and energy cane breeders to improve commercial cultivars. We report here the results of the first extensive genetic diversity study on all accessions available in the WCSRG maintained in USA. With this information, sugarcane and energy cane breeders will now have information on the WCSRG that will allow them to make long-term improvements of commercial cultivars with important agronomic traits.Because sugarcane is extremely heterozygous and highly polyploid, polymorphisms are high among the accessions. Analysis of SSR markers on the WCSRG indicated 1 to 17 robust polymorphic alleles with an average of 5.8 alleles per locus, comparable to other studies, where the allele number per locus was 7.35 I) is an individual identification estimator which explains the probability of two different accessions having the same genotypes at one specific locus in a population by chance rather than through inheritance. It was calculated based on the allele frequencies for each marker from the WCSRG. The I values ranged between 0.012 (UGSM667) and 0.395 (SEGM2dot)  indicates the probability of excluding an accession from the possibility of parentage if the accession was not involved in any parentage. The Q values were moderate for most SSR primers, ranging from 0.178 (SEGM2dot) to 0.840 (UGSM667) (The probability of identity (EGM2dot) . For mosUGSM667) . The comS. spontaneum and S. officinarum suggests genomic differences, which could act as gene flow barriers between them. The species-specific alleles were also found Erianthus, S. spontaneum and S. officinarum. These alleles can be used to detect genome components of S. spontaneum in the hybrids.The presence of 20 significantly different alleles between Saccharum species has been a topic of debate for many years. The Saccharum genus was traditionally divided into six species: S. spontaneum, S. officinarum, S.robustum, S. edule, S. barberi and S. sinense, which were defined by some highly variable characters with many uncertainties S. spontaneum and S. officinarum with the other four species and hybrids being considered as S. officinarum based on the morphological, cytological and genotypic analysis. In this study, phylogenetic analysis based on genetic diversity indicated that accessions of S. spontaneum clustered into a major group/subpopulation. S. officinarum along with other Saccharum species such as S. sinense, S. barberi, S. robustum, S. hybrids and other genus Narenga were clustered into another distinctive group/subpopulation  did not group closely with any of the Saccharum species and there was no evidence of division of Saccharum into Erianthus and NarengaSaccharum complex” and indicated Saccharum spp. are grouped together and are apart from non-Saccharum spp. Similar results were observed in WCSRG in this study  including major Saccharum spp.In summary, 1002 accessions in the WCSRG maintained by the USDA in Miami, FL, USA were evaluated with 209 polymorphic alleles from 36 SSR markers. Diversity analysis showed that the WCSRG has a gene diversity of 0.304. The result from phylogenetic and structure analysis of the 1002 accessions revealed three major groups with significant differentiation among them. Based on the genotypic data, a core collection of 300 accessions was selected representing the majority of diversity in the WCSRG. The core collection developed and the data from this study provide valuable breeding resources to the sugarcane and biomass feedstock communities. These clones can be utilized for creating mapping populations that will be useful to develop QTLs and to understand the genetic basis. The information can be exploited in mapping of genes and QTLs for marker assisted introgression of traits into elite breeding lines. This characterized diverse genetic resource can be further exploited by breeders to improve both sugarcane and energy cane in Table S1Numerical distribution of the different species in the World Collection of Sugarcane and Related Grasses (WCSRG). Note: Asterisk (*) indicate the genus name of each accession in the WCSRG was listed based on the curator’s records. However, they are supposed to be named as non- Saccharum species according to our experiment results.(XLSX)Click here for additional data file.Table S2Summary information of 191 simple sequence repeat (SSR) markers used to genotype 1002 accessions in the World Collection of Sugarcane and Related Grasses in Miami, FL, USA.(XLSX)Click here for additional data file.Table S3Sample name, species, group assignment, and subpopulation assignment of 1002 accessions genotyped in the World Collection of Sugarcane and Related Grasses in Miami, FL, USA.(XLSX)Click here for additional data file.


A growing base of genetic testings is now available for clinicians and its results could improve the quality of care and its outcomes. In addition, these testings are also helpful for predictive medicine and early detection of diseases. Genetic testings could further personalize the care processes based on the patient individual genetic makeup. Genetic testing methods are diverse and span from testing for known germline mutations in the context of single-gene disorders, to full sequencing of genes in tumor tissues looking for somatic variations in cancer cells, and on to whole-exome sequencing in cases of predictive medicine or unknown diagnosis. As a consequence of that diversity and the constantly growing number of techniques yielding new result formats less familiar to clinicians, existing report formats attempt to contain rather detailed descriptions of the tests performed, but that approach makes it hard to understand the interpretations of the testing results and given recommendations. Genetic testing reports should be both human readable to its users, and at the same time also be processable to computerized algorithms computing the interpretation of the genetic testing results. Thus, it is equally important to standardize the way genetic testing interpretations are represented  as an inGiven the above considerations, it is important to streamline the utilization of genetic testing reports by standardizing its format. The GTR (Genetic Testing Report) standard was published in February 2013 [The GTR standard can facilitate true semantic interoperability among all personalized healthcare stakeholders, e.g., genetic labs, EHR systems, patients, clinical trials and research, public health agencies, etc. The GTR is flexible enough to be further constrained for more specific usages, e.g., requirements in different countries, research vs. clinical environments, professional societies recommended-formats, specific omics technologies / methodologies, or special use cases such as tissue typing or whole-exome sequencing report.The GTR has been developed using MDHT  - an open source effort that is used worldwide to develop specialized standards based on UML models of common and generic standards like the CDA . The MDH


Aptenodytes patagonicus, return rates of post-fledging chicks to their natal sub-colony are remarkably high. Empirical studies have shown that adults return year after year to their previous breeding territories within a radius of a few meters. Yet, little reliable data are available on intra- and inter-colonial dispersal in this species. Here, we present the first fine-scale study of the genetic structure in a king penguin colony in the Crozet Archipelago. Samples were collected from individual chicks and analysed at 8 microsatellite loci. Precise geolocation data of hatching sites and selective pressures associated with habitat features were recorded for all sampling locations. We found that despite strong natal and breeding site fidelity, king penguins retain a high degree of panmixia and genetic diversity. Yet, genetic structure appears markedly heterogeneous across the colony, with higher-than-expected inbreeding levels, and local inbreeding and relatedness hotspots that overlap predicted higher-quality nesting locations. This points towards heterogeneous population structure at the sub-colony level, in which fine-scale environmental features drive local philopatric behaviour, while lower-quality patches may act as genetic mixing mechanisms at the colony level. These findings show how a lack of global genetic structuring can emerge from small-scale heterogeneity in ecological parameters, as opposed to the classical model of homogeneous dispersal. Our results also emphasize the importance of sampling design for estimation of population parameters in colonial seabirds, as at high spatial resolution, basic genetic features are shown to be location-dependent. Finally, this study stresses the importance of understanding intra-colonial dispersal and genetic mixing mechanisms in order to better estimate species-wide gene flows and population dynamics.How genetic diversity is maintained in philopatric colonial systems remains unclear, and understanding the dynamic balance of philopatry and dispersal at all spatial scales is essential to the study of the evolution of coloniality. In the King penguin,  How colonial systems are maintained in non-cooperative species remains an important question in evolutionary biology ,2. Philoet al. )Aptenodytes patagonicus, which breeds in large colonies all around the sub-Antarctic area, is an ideal model to investigate these aspects of coloniality. It is known to choose and defend a breeding territory within the colony, even though it does not build a nest [The King penguin, d a nest ,31. Breed a nest ,31. Retud a nest ,33. Howed a nest ,35). Howd a nest ; therefod a nest .(i) global homogeneous processes or (ii) local heterogeneous processes whose effect varies across the area [(i) The predictions associated with strong and consistent philopatric behaviour belong to the former class. Without taking spatial distribution of individuals into account, a skew in global population inbreeding descriptors may be expected [(ii) If, on the other hand, philopatric behaviour is a more variable trait dependent on local ecological conditions, the processes involved in colony structure are expected to belong to the second class. Local heterogeneous signatures should therefore be found, such as divergent population parameters for different areas of the colony [When considering the genetic structure of a species, expected patterns may be analysed according to the area . (i) Theexpected , with anexpected ,41. Alteexpected . (ii) Ife colony . Althouge colony ,43. Paire colony ,44.In this study, we use a combined approach including genetic, spatial and local ecological data to investigate the mechanisms of genetic mixing inside a seabird colony. We focus in particular on how fine-scale habitat heterogeneity patterns may influence local dispersal behaviour, and how lack of genetic structuring can emerge from small-scale heterogeneity in ecological parameters.All animals in this study were handled only once in order to mark them with an external plastic pin tag (Floytag(r)) and to conduct morphological measurements. All procedures employed during this field work were approved by the Ethical Committee of the French Polar Institute (Institut Paul Emile Victor—IPEV) and conducted in accordance with its guidelines, also complying with French laws including those relating to conservation and welfare. Authorizations to enter the breeding site (permits n°2009–57 issued on August 26th 2009) and handle birds (permits n°2009–59 issued on August 29th 2009) were delivered first by the French “Ministère de l’Aménagement du Territoire et de l’Environnement” and then by the Terres Australes et Antarctiques Françaises (TAAF).Handled animals were removed from the colony in order to minimize the disturbance to neighbouring birds and taken to a shelter a few meters away for manipulation. They were hooded to reduce their stress and manipulations lasted between 5 and 10 minutes. All blood-sampling and tagging material was sterilized . Moreover, Vétédine soap and alcoholic antiseptic solutions were used to disinfect the skin before bleeding and tagging. Flesh wounds did not seem infected thereafter .ca. 10×10m cells). King penguins are monogamous during a reproductive season and lay a single egg each year [Our study was conducted during the summer season 2009/2010 in the king penguin colony of “La Baie du Marin”, on Possession Island, Crozet Archipelago , which comprises around 16,000 breeding pairs [ach year ,47, thus-1.DNA was extracted using a DNeasy(r) Blood and Tissue Kit (Qiagen) with a modified protocol. A prolonged initial incubation of the impregnated Whatman(r) paper in PBS buffer (24 h) was used to dissolve dried blood cells, and a final elution in 50 μL instead of 100 μ L was made to obtain higher DNA concentration. The final DNA concentration was assessed by spectrometry and adjusted to 25 ng.μL2, in a total reaction volume of 12.5 μL . Amplification followed a touchdown protocol, with a 5-minute denaturation at 95°C, 12 amplification cycles of a 30 second denaturation at 95°C, 30 seconds of annealing beginning at 63°C in the first cycle and decreasing one degree at each cycle until 52°C, and 30 seconds of elongation at 72°C, followed by 23 cycles of 30 seconds at 95°C, 30 seconds at 52°C, and 30 seconds at 72°C. Amplification was finished with 10 minutes at 72°C. The same protocol was used for all primers. FAM and HEX fluorochrome-labelled primers were used for sequencing: several microsatellite loci could be multiplexed in the same reaction , and 100,000 random permutations.However, heterogeneous spatial processes may not always be detected by global spatial autocorrelation analyses . Heterogadegenet [Coancestry [Coancestry: 50 independent simulated datasets were generated. For each of them, both observed and simulated individuals were pooled, and 100,000 randomly redistributed partitions were generated. Group-averaged inbreeding difference was computed for each of these partitions, and significance of the observed result was checked against this random distribution. Observed individual inbreeding was then mapped onto the colony to identify potential high-inbreeding clusters using Quantum GIS .Individual inbreeding coefficients and pairwise relatedness were also taken as an index of local genetic structure. If potential mates are more related to each other in some areas, then offspring sampled in that area are expected to be more inbred, and potentially related to each other. Inbreeding was studied both at population and individual levels. At population level, Ballou’s maximum likelihood method was preferred , since iadegenet . Individancestry . As expeGenepop  and Fstat using chi-square assessment of genotypic frequencies. Pairwise divergence in inbreeding and relatedness distribution between clusters was also assessed. Pairs of individuals belonging to one cluster were compared to pairs of individuals belonging to different clusters, and significance of distribution divergence was tested in Coancestry .If our second hypothesis (heterogeneous structuring processes) holds true, we expect these processes to apply differently in specific areas of the colony depending on local characteristics. We therefore performed the following analyses on the discrete natural clusters defined in the sampling area , as oppo(i) For 3 consecutive breeding seasons (2010–2012), chick survival rate between hatching (January/February t) and fledging (November/December t) was measured as the proportion of marked chicks still alive at fledging [(ii) Parasite infestation has been shown to influence breeding success and adult survival rate in king penguins [(iii) Finally, as early breeders lay eggs in November/December, and late breeders after January [To measure breeding site quality, several ecological variables were used as proxies. fledging . (ii) Papenguins . Thus, f January ,64, an er test performed between successive years with all grid zones), and spatial autocorrelation of the data was assessed in spdep . Each vOf the 10 microsatellite loci tested for genotyping, only 8 were successfully amplified, and were used in the subsequent analyses. Ech011 amplified irregularly in king penguins under the tested PCR conditions, and Ech081 was repeatedly scored as more than 2 alleles per genotype. Only Ech030, Ech036, Ech051, Ech071, AM13, B3–2, Emm4 and RM3 were therefore retained for genotyping. For these, scoring repeatability was of 100% across our random replicates.P-values: Ech030 = 1; Ech036 = 0.9997; Ech051 = 0.3880; Ech071 = 1; AM13 = 1; B3–2 = 0.4948; Emm4 = 1; RM3 = 0.0697). FIT was not found to be significantly different from zero for the whole sample (FIT = 0.0259), although it was significantly higher for one locus (Ech071: FIT = 0.1275). Considering this might be a sign of weak linkage to a region under selective pressure, subsequent analyses were therefore tested both including and excluding this locus. No locus was found to be under linkage disequilibrium. Allele frequencies, counts, and genetic diversity are given in The total population was found to be in Hardy-Weinberg equilibrium. After 100,000 randomisations, no locus showed significant departure from Hardy-Weinberg equilibrium . At the individual level, MME inbreeding coefficients were found to deviate from a random distribution. In 80% of our simulations, the empirical data fell outside the 95% interval of the random distribution, and in all cases the difference was clearly positive . It is noteworthy that these individuals were clustered in two groups that strongly overlapped with the higher-inbreeding regions identified previously . However, pairwise FST comparisons did not yield any significant result.Cluster differentiation analyses performed in Coancestry : cluster C1 was found to have significantly (PC1 < 0.05) less inbreeding than clusters C2, C3, C5 and C6 (but not C4). Most significant was the comparison between C1 and C5 . Chick survival was found to be correlated between 2010 and 2011 (c = 1.548 P = 0.0427), sampling did not overlap sufficiently between years 2011 and 2012 for comparison. All 3 variables showed a markedly structured, gradient-driven distribution across our sampling range [P-values < 0.01). Occupancy timing and chick survival distributions appeared to largely overlap, and to be partly complementary to tick infestation distribution. Comparison between C1 and C5 was significant for all variables: tick infestation varied from 0.188 ± 0.095 in C1 to 0.083 ± 0.019 in C5, while averaged chick survival ranged from 0.208 ± 0.058 in C1 to 0.398 ± 0.130 in C5, and occupancy timing index from 0.303 ± 0.206 in C1 to 0.488 ± 0.056 in C5  inbreed example , our res example . Moreove example . Not surOur pairwise cluster analysis supports the hypothesis of genetic clustering within the colony. Genotypic differentiation points towards structural divergence between the centre and the extremities of our sampling range. Yet, the genotypic structure detected is globally weak. This is an expected result, as Waples and Gaggiotti  showed tTogether, these different elements outline an underlying structure in which the north-western end of the colony (cluster C1 in particular) appears more outbred, with lower pairwise-relatedness levels, and the south-eastern end  is more inbred, with higher relatedness levels. Such a structure implies that the probability for a breeder to mate with a related individual is not constant across the colony. Potential mates are therefore more likely to share identical alleles (either by descent or by state) at the south-eastern end of the colony than at the north-western end. This result is in accordance with the findings of Steiner and Gaston , who shoInterestingly, the observed heterogeneity in genetic structure we found within this king penguin colony appeared to be related to the quality of the breeding sites. Tick infestation has a local maximum around C1, i.e. at the north-western end of the range, and lower values elsewhere. In contrast, chick survival has local maxima around C5 and C6, and very low values in C1. The chronology of settlement-site occupancy also appeared to be strongly associated with the quality of the breeding sites. Indeed, preferred areas at the south-eastern end of the colony were occupied first, and less-favoured spots at the north-western end were occupied by late breeders. The fact that no significant correlation could be found between habitat descriptors and genetic parameters may be a consequence of our small sample size, as our sampling area is not large enough to allow for replicate situations. Some other constraints, such as flooding, fine-scale variations in predation pressure, or inter-annual climate variability, were not monitored and may also interact to define high- and low-quality habitat.Overall, principal component analysis revealed a gradient from higher habitat quality at the south-eastern end of the colony, around clusters C5 and C6, to lower quality at the north-western end (clusters C1 and C2). This pattern suggests that habitat quality may be one of the drivers shaping the observed differences in relatedness and inbreeding across sampled individuals. This may be a consequence of differences in fine-scale philopatric behaviour. Indeed, while king penguins have been shown to select their breeding location according to site-specific characteristics at the breeding-season scale , our resMacronectes spp.) {[Stercorarius antarcticus), are not more common in the peripheral areas than in the centre of the colony, which is consistent with our field observations. Finally, the overall breeding success has been shown to be independent of central or peripheral location [Peripheral territories in a king penguin colony are generally characterized by higher tick loads and later settling dates compared to central areas, thus the weak genetic signal may be explained by our peripheral sampling design (required in order to minimize colony disturbance). Nevertheless, central areas do suffer from specific pressures, such as higher density and associated stress levels . Predatis spp.) {, when chs spp.) { that suclocation , which sAnother possible explanation of the weakness in the genetic signal may arise from our sampling of pre-dispersal chicks and the analysise of nuclear autosomal markers (as opposed to sex-specific ones). Indeed, a constant bias such as sex-specific dispersal may lead to more genetic structure in one sex than the other, a phenomenon which may be blurred by our sampling of pre-dispersal individuals of undetermined sex. Yet, although sex-specific dispersal is a common phenomenon in birds , on a muA more likely explanation of the weak genetic signal may lie in inter-annual habitat variability. If local philopatric maxima are conditioned by the past breeding experience of individuals, they may be subject to medium time-scale variations: higher-quality breeding sites may change every few generations, depending on flooding variations, ground erosion, or parasite pressures. These very fine-scale shifts may be sufficient to weaken genetic structure at the colony level on longer time scales.Moreover, at the individual scale, it may be difficult for a breeder to retain its breeding site consistently across all breeding seasons. Indeed, the complex breeding cycle of the king penguin extends for more than a year, implying that birds are alternately early or late breeder ,47, regaFinally, king penguin population genetic structure may still bear the imprint of recent demographic history. Most of the king penguin colonies suffered a drastic reduction at the turn of the nineteenth century, as sealers slaughtered them to near-extinction on most of the archipelagos for oil production. They recovered, but recently ,86. SimiThe convergence of genetic and ecological indicators we observed outlines the structural heterogeneity inherent to penguin colonies, and probably to other colonial seabirds . How


HI) strongly up‐regulates Signal Transducer and Activator of Transcription 3 (STAT3) in the immature brain. Our aim was to establish whether STAT3 up‐regulation is associated with neonatal HI‐brain damage and evaluate the phosphorylated STAT3‐contribution from different cell types in eliciting damage. We subjected postnatal day seven mice to unilateral carotid artery ligation followed by 60 min hypoxia. Neuronal STAT3‐deletion reduced cell death, tissue loss, microglial and astroglial activation in all brain regions. Astroglia‐specific STAT3‐deletion also reduced cell death, tissue loss and microglial activation, although not as strongly as the deletion in neurons. Systemic pre‐insult STAT3‐blockade at tyrosine 705 (Y705) with JAK2‐inhibitor WP1066 reduced microglial and astroglial activation to a more moderate degree, but in a pattern similar to the one produced by the cell‐specific deletions. Our results suggest that STAT3 is a crucial factor in neonatal HI‐brain damage and its removal in neurons or astrocytes, and, to some extent, inhibition of its phosphorylation via JAK2‐blockade reduces inflammation and tissue loss. Overall, the protective effects of STAT3 inactivation make it a possible target for a therapeutic strategy in neonatal HI.Hypoxic‐ischaemic encephalopathy is a leading cause of child death, with high mortality and morbidity, including cerebral palsy, epilepsy and cognitive disabilities. Hypoxia‐ischaemia (Current data show that neuronal and astroglial STAT3 molecules are involved in the pathways underlying cell death, tissue loss and gliosis following neonatal hypoxia‐ischaemia, but differ with respect to the target of their effect. Y705‐phosphorylation contributes to hypoxic‐ischaemic histopathology. Protective effects of STAT3 inactivation make it a possible target for a therapeutic strategy in neonatal hypoxia‐ischaemia. BWbody weightDMSOdimethyl sulfoxideGFAPglial fibrillary acidic proteinHIEhypoxic ischaemic encephalopathyHIhypoxia ischaemiai.p.intraperitonealJAKJanus KinaseNEneonatal encephalopathyOLVoptical luminosity valuesPBSphosphate buffered salinepSTAT3phosphorylated Signal Transducer and Activator of Transcription 3SDstandard deviationSEMstandard error of the meanSTAT3Signal Transducer and Activator of Transcription 3SVsubventricularTHtherapeutic hypothermiaTUNELterminal deoxynucleotidyl transferase dUTP nick end labellingNeonatal hypoxic ischaemic encephalopathy affects 1–3 per 1000 live term births in high‐income countries, with rates 5–10 times higher in low‐income settings. About 40% of affected infants die in the neonatal period and an additional 30% have lifelong neurological deficits, including cerebral palsy, epilepsy and cognitive disabilities causing substantial socio‐economic burden to the individual, family and healthcare system , a member of the STAT family, is strongly up‐regulated by hypoxia ischaemia (HI) in the immature brain . Mice carrying floxed STAT3 allele (STAT3F/F) on SVJ129 background  by crossing them with C57/Bl6 obtained from Charles River . Animals expressing cre recombinase driven by synapsin promoter  were provided by Dr Axel Behrens from the Mammalian Genetics Laboratory, Cancer Research UK, and animals expressing cre recombinase under the control of glial fibrillary acidic protein promoter  were from Jackson Labs . The wild‐type littermate controls in the cell type‐specific STAT3 deletion experiments were thus on mixed C57/Bl6 and SVJ129 background for the neuron‐specific STAT3 deletion or on mixed C57/Bl6 and FVB background for the astroglia‐specific deletion.The animals used in the STAT3F/F mice . To prevent germline STAT3 deletion due to testicular expression of the synapsin promoter  and male cre‐negative STAT3F/F mice were used for breeding to generate STAT3∆S mutants and STAT3F/F littermate controls with Mendelian distribution. A similar approach was used for the generation of animals with homozygous astroglia‐specific deletion of STAT3 (STAT3∆G), by crossing GFAP::Cre mice twice with STAT3F/F animals.For cell type‐specific STAT3 deletion studies, Syn::Cre animals were crossed twice with DNA extraction was performed with the ‘Wizard’ Genomic DNA purification system according to manufacturer's instructions , using tail tips taken before the perfusion. Specific oligonucleotide primers  were used for genotyping.STAT3 flox forward primer: 5′‐CCTGAAGACCAAGTTCATCTGTGTGAC‐3′STAT3 flox reverse primer: 5′‐CACACAAGCCATCAAACTCTGGTCTCC‐3′GFAP‐cre forward primer: 5′‐ACTCCTTCATAAAGCCCT‐3′GFAP‐cre reverse primer: 5′‐ATCACTCGTTGCATCGACCG‐3′Synapsin‐cre forward: 5′‐AGCTTCAGCACCGCGGACAGT‐3′Synapsin‐cre reverse: 5′‐TCGTTGCATCGACCGGTAATG‐3′All animal experiments and care protocols were carried out according to the UK Animals (Scientific Procedures) Act 1986 and approved by the Home Office. The ARRIVE guidelines were followed. All experiments involved postnatal day 7 mice (P7) bred in house.et al. The surgical procedures were performed as previously described  was dissolved in 100% dimethyl sulfoxide (DMSO) and administered intraperitoneally at two doses of 40 mg/kg body weight (BW) . The brains were then removed, post‐fixed in 4% paraformaldehyde in PBS for 1 h at 4°C, and cryoprotected for 24 h in phosphate‐buffered 30% sucrose solution as described before . αX immunoreactivity was enhanced with Co/Ni. Overall, GFAP immunoreactivity was detected with the rabbit polyclonal anti‐GFAP antibody. However, for the double immunofluorescence with pSTAT3 in Fig. Five cryosections from each brain (400 μm apart), obtained at 48 h post‐HI, were rehydrated in distilled water and stained using immunohistochemistry as previously described  . The staining procedure followed the manufacturer protocol with Co/Ni enhancement.Five more sections per brain with the same spacing were stained with cresyl violet (Nissl).For the double immunofluorescence with pSTAT3 in Fig. et al. The cresyl violet‐stained sections were scanned and imported into Optimas 6.5 image analysis software . The areas of intact staining in cortex, pyriform cortex, hippocampus, striatum, thalamus and external capsule were outlined and measured bilaterally. The percentage tissue loss was then calculated by converting the measured injured and uninjured areas into square millimetres and then converting the volume by multiplying by 400 μm. The sum of these volumes was then used to calculate the percentage of surviving brain tissue as injured/uninjured volume × 100 . The counts were then averaged per animal and per group.To analyse the pSTAT3 immunoreactivity following HI, we counted the number of positive cells bilaterally in three different optical fields at × 40 magnification in cortex and hippocampus at 0, 15 min, 1, 2, 4, 8, 16, 24, 48, 72, and 96 h following HI , treating region as the repeated measure. For each outcome, several regions of the brain were examined. With repeated measures such as these, it is likely that the observations from a single subject will be correlated, therefore the first stage of the analysis included the observations from all the regions tested in a single mixed model with a random subject effect, to produce an estimate of the treatment effect and associated inference that accounts for the correlations in the data arising from the repeated measures. Further The protein levels of pSTAT3 (Y705) were assessed through western blot analysis. Compared to littermate controls , postnatal day 7 (P7) mouse pups (C57/Bl6) demonstrated bilateral pSTAT3 (Y705) up‐regulation in cortex and hippocampus, at 1 h following a 60 min HI‐insult  increase was also observed through immunohistochemistry. Figures n = 4 animals per time point). Cortical pSTAT3 +  counts , to obtain animals with homozygous CNS neuron‐specific deletion of STAT3 (STAT3∆S) and STAT3F/F littermate controls, on a mixed C57/Bl6xSVJ129 background.To explore the functional role of HI‐induced STAT3 activation, animals expressing one gene copy of cre recombinase under the control of the synapsin promoter were crossed twice with mice carrying 2 copies of floxed STAT3 gene (STAT3∆S) strongly reduced western blot levels of pSTAT3 (Y705) in hippocampus and cortex compared to STAT3F/F littermate controls at 1 h following a 60 min HI‐insult  markedly reduced the number of TUNEL+ cells compared to STAT3F/F littermate controls . The Syn::cre‐mediated reduction was observed across all six examined forebrain regions : cerebral isocortex, pyriform cortex, hippocampus, striatum, thalamus and external capsule. Individually, all six regions revealed a significant, 70–90% decrease in the number of TUNEL+ cells in STAT3∆S animals compared to their STAT3F/F littermates (p < 0.05 in t‐test).To determine the biological impact of neuron‐specific STAT3 deletion, we next examined the effects on TUNEL+ cell death and brain volume loss, on reactive astrogliosis and on different markers or microglial activation at 48 h following a 60 min HI‐insult. Figures STAT3F/F animal , with individual significant decrease of 80–90% in isocortex, striatum and total forebrain area (p < 0.05 in t‐test).A similar effect of the Syn::cre‐mediated deletion of STAT3 was also observed for forebrain tissue loss, i.e. the reduction of the volume on the ipsilateral versus the non‐occluded contralateral side. Figure mal Fig. c and itsate Fig. d. Quantiate Fig. f revealeSTAT3F/F animals, their STAT3∆S littermates revealed less overall polyclonal GFAP‐immunoreactivity , with individual significant decrease of 40–65% in ipsilateral isocortex and thalamus, and of 32% in contralateral hippocampus (p < 0.05 in t‐test).In addition to cell death and brain tissue loss, Syn::cre‐mediated deletion of STAT3 also decreased HI‐induced and predominantly ipsilateral reactive astrogliosis and microglial activation. Compared to ity Fig. i and j, ity Fig. k and l. STAT3F/F group 48 h following a 60 min HI‐insult revealed the round, phagocytic phenotype shown in the inserts of Fig. STAT3∆S group mainly displayed resting to activated, but still ramified morphology , with individual decreases of 50–90% in all brain regions apart from external capsule (p < 0.05 in t‐test). Although the non‐occluded, contralateral side showed much fewer αX+ cells, Syn::cre‐mediated deletion of STAT3 also led to significant contralateral reduction of the number of αX+ microglia , with individual decrease of 90% in the contralateral pyriform cortex (p < 0.05 in t‐test).While the microglial cells in the control ogy Fig. s‐insert.STAT3∆S group , with significant decrease of 65–90% in all six individual ipsilateral brain regions (p < 0.05 in t‐test).A similar effect was also observed for microglial activation score Fig. q based oSTAT3F/F control animals, deletion of both STAT3 gene copies with cre recombinase driven by astroglia‐specific GFAP promoter (STAT3∆G) significantly reduced the extent of TUNEL+ cell death and astrogliosis. The effect on TUNEL+ cells is shown in Fig. p = 0.02), with individual significant decrease of 30–87% in hippocampus, thalamus and external capsule (p < 0.05 in t‐test). However, despite the apparently consistent lower average tissue loss values across the examined brain regions . Likewise, microglial activation based on the αM integrin immunoreactivity .Compared with STAT3∆S .In contrast, astroglial pSTAT3 deletion strongly reduced HI‐induced up‐regulation of GFAP‐immunoreactivity in both ipsi‐ and contralateral brain regions  . Microglial activation , with individually significant decrease of 51% in ipsilateral hippocampus (p < 0.05 in t‐test). The insert in Fig. Pre‐ and post‐insult treatment with 80 μg/g WP1066 did not have significant effect on ipsilateral brain tissue loss at 48 h post‐HI in Mixed Linear Model, treating region as a repeated measure (STAT3ΔS) clearly reduced forebrain cell death and tissue loss, as well as microglial and astroglial activation. Astroglia‐specific STAT3 deletion (STAT3ΔG) blocked reactive astrogliosis and attenuated cell death, but had a more moderate effect on tissue loss and active microgliosis. A combined pre‐insult and immediate post‐insult blockade of JAK2 with systemically applied WP1066 inhibited the HI‐induced forebrain STAT3(705)‐phosphorylation and reduced HI‐brain damage based on some evidence for astroglial and microglial post‐HI response. However, this effect was weak and did not lead to a statistically significant reduction in brain tissue loss. Overall, our data suggest a critical role for STAT3, and possibly also a contribution in neonatal HI‐brain damage via Tyr705 phosphorylation.As shown in the current study, in a Rice‐Vannucci model of severe HI insult in postnatal (P7) mice, neuronal deletion of STAT3  in the current study, was specific for HI, peaking at 1–4 h following insult , implying that the functional effect of STAT3 is probably elicited by some post‐translational modification and/or translocation, cytoplasmic translation and nuclear transcription (Nicolas STAT3ΔS), in GFAP+ astroglia (STAT3ΔG) and blocking JAK2‐mediated Y705‐phosphorylation with WP1066. The pharmacological inhibition produced a relatively moderate effect. Compared to vehicle (DMSO)‐treated controls, the combined pre‐HI and immediate post‐HI intraperitoneal injection of WP1066 significantly reduced the levels of pSTAT3 in cortex and hippocampus  through which STAT3 activation is involved in HI‐brain damage would considerably improve the therapeutic potential of interfering with STAT3 in a clinical setting.


Juglans regia L) is an economically important species cultivated worldwide for its wood and nuts. It is generally accepted that J. regia survived and grew spontaneously in almost completely isolated stands in its Asian native range after the Last Glacial Maximum. Despite its natural geographic isolation, J. regia evolved over many centuries under the influence of human management and exploitation. We evaluated the hypothesis that the current distribution of natural genetic resources of common walnut in Asia is, at least in part, the product of ancient anthropogenic dispersal, human cultural interactions, and afforestation. Genetic analysis combined with ethno-linguistic and historical data indicated that ancient trade routes such as the Persian Royal Road and Silk Road enabled long-distance dispersal of J. regia from Iran and Trans-Caucasus to Central Asia, and from Western to Eastern China. Ancient commerce also disrupted the local spatial genetic structure of autochthonous walnut populations between Tashkent and Samarkand , where the northern and central routes of the Northern Silk Road converged. A significant association between ancient language phyla and the genetic structure of walnut populations is reported even after adjustment for geographic distances that could have affected both walnut gene flow and human commerce over the centuries. Beyond the economic importance of common walnut, our study delineates an alternative approach for understanding how the genetic resources of long-lived perennial tree species may be affected by the interaction of geography and human history.Common walnut ( Juglans regia L.) is a wind-pollinated, monoecious, long-lived, perennial tree cultivated throughout temperate regions worldwide for its timber and edible nuts  or [Dest /(1-Dest)] and the natural logarithm of geographic distances (straight-line distances in km) among sampling sites were significantly correlated (r (FST) = 0.6248, P = 0.0002; r (Dest) = 0.6521, P = 0.0002). Space  and human interactions may act simultaneously on gene flow, however, influencing the genetic structure of common walnut populations. Simple Mantel tests  and [Dest / (1- Dest)] pairwise values against the corresponding natural logarithm of geographic distances. Because geographically distant human populations are often also separated by linguistic boundaries, leading to spurious correlations, we performed a partial Mantel test to calculate the partial correlation between linearized FST/Dest values and human linguistic diversity after controlling for straight-line geographic distance. We caution that simple and partial Mantel tests have been questioned recently for showing inflated type-1 error rate in the presence of spatial autocorrelation, even when a geographic distance matrix is included in the analysis [FST/Dest calculated among J. regia populations was evaluated with a multiple regression on distance matrices approach [r2 were estimated using 5,000 permutations.We tested the effect of geographic distances , Uzbekistan (10–26), China (27–32), Pakistan (33–34), Tajikistan (35), Iran (36), Turkey (37) and Georgia (38–39). The Silk Road (solid red line) and other trade routes (dotted red line) across the Asian continent were reported as proposed by Francis et al. .(TIF)Click here for additional data file.S2 FigUPGMA cluster analysis based on unbiased Nei’s  genetic (TIF)Click here for additional data file.S3 FigGEN) computed as FST [Dest [LAN) calculated on the basis of Ruhlen’s classification of languages [P ≤ 0.05 according to the post hoc Tukey’s test.Mean genetic distances Click here for additional data file.S4 FigSolid red line indicates statistically significant genetic boundaries. The classification of languages into four phyla spoken by human communities in the geographic sampling sites were also reported.(TIF)Click here for additional data file.S1 TableNumber of samples (N), and geographic description for 39 common walnut populations collected across the species’ Asian range  and Ruhl(DOCX)Click here for additional data file.S2 TableQi) of each predefined common walnut population in each of the four (K = 4) clusters and four (K’ = 4) sub-clusters of cluster 2 inferred by STRUCTURE [Q-values greater than 0.80 are reported in bold. The number and percentage of walnut genotypes from each population assigned (Qi ≥ 0.80) to each of four clusters (K = 4) and four sub-clusters (K’ = 4) were also reported below Q-values. Populations and/or individuals with 0.20 < Qi < 0.80 were classified as admixed populations and /or genotypes.Mean percentage of membership Click here for additional data file.


Background. Provincial maternal mortality surveillance systems (PMMSS) have been set up in nearly all the provinces in China to monitor local maternal mortality and provide the evidence for maternal health interventions suited to local conditions. However, till now little is known outside of China about the characteristics of PMMSS. Methods. A systematic review of the literature contained in PubMed and China Academic Journal Network Publishing database was carried out. The current situation on PMMSS was described. Provincial disparities on PMMR in six provinces were analyzed by Poisson regression analysis. Results. A total of 35 studies met the inclusion criteria, of which 31 were published in Chinese. PMMSS were set up and adjusted by the provincial government based on their own financial resources and demand. Provinces from remote region had the highest risk of maternal mortality, followed by provinces from inland region and coast region. Conclusions. PMMSS may be the most reliable data source for measuring provincial level MMR in each province. Great provincial disparities on PMMSS and PMMR do exist within the country; more emphasis should be placed on improving PMMSS and reducing PMMR particularly in the provinces with high maternal death burden. China endorsed the United Nations Millennium Development Goals (MDGs) in 2000, which include a reduction of the maternal mortality ratio (MMR) by 2015 from 89 maternal deaths per 100 000 live births in 1990 to 22/100 000. During the past ten years, China has placed great emphasis on the maternal health, and MMR in China has declined in some degree . HoweverNational Maternal and Child Mortality Surveillance System (NMCMSS), representing all 31 provinces and covering 60 million people, has been the principal data source for estimating national MMR in China . NeverthGiven the size and diversity of China, reducing maternal deaths in the whole of China under the same policies is a great challenge in particular. In order to monitor local maternal mortality levels and to provide scientific evidence for mother and child health (MCH) interventions suitable to the local situation, provincial maternal mortality surveillance systems (PMMSS) have been set up in nearly all the provinces in China. Throughout China, the PMMSS is uniform in the basic structure and operation procedure . In ChinHowever, till now, performances and characteristics of PMMSS in China are not widely known outside of China, since most provincial maternal mortality ratio (PMMR) data were published in Chinese and only five English literatures reported PMMSS and PMMR data in four of 31 provinces –14. The Searches of publications were performed in the China Academic Journal Network Publishing (CAJNP) database and PubMed. Both searches were limited to literatures reported from January 1982 to May 2013. We searched CAJNP database using keyword combinations of “yun chan fu si wang”  and “province name” and PubMed using a combination of “maternal mortality or maternal death” and “province name” for all 31 provinces.Studies were eligible for inclusion if they reported PMMSS and PMMR of any province in China. Studies were excluded if they reported (i) data concerning PMMSS without requisite data (surveillance mode and sampling method) or (ii) data on PMMR only in graphs or percentage.The quality of included studies was evaluated based on study design and data integrity. A study detailing PMMSS, reporting year-by-year PMMR, cause of maternal death, and results of maternal death review, and analyzing possible factors related to maternal death was considered a high-quality study. A study describing PMMSS in detail and only reporting year-by-year PMMR and cause of maternal death was considered of average quality. Studies that we considered to have unclear or poor design and studies that we judged to present unreliable or conflicting data were regarded to be of poor quality and were excluded from the review.Two authors independently applied the inclusion criteria (screening) to all identified studies and made decisions on which studies to include.Two authors did the data extraction independently, and the discrepancies between the authors were resolved by consensus.Using a classification system developed by the information and statistics centre of the Ministry of Health, which was based on a range of indicators  per capita), China's 31 provinces, autonomous regions, and municipalities were classified into three regions: coast region , inland region , and remote region  , 16.The data were extracted from each study that qualified for the inclusion in the review including information about the setup, surveillance mode, sampling percentage, and operation procedures of PMMSS. If two or more studies presented data for the same province in different years, the data were combined.The PMMR data  were retrieved, pooled, and analyzed. Long and continuous year-by-year PMMR data were prerequisite for the time trend and provincial disparities analysis. However, in the published studies, in most provinces, only discontinuous or short-time PMMR data were available. Six provinces, which had a complete time series of PMMR data, two from coastal region (Shanghai and Liaoning), two from inland region (Henan and Chongqing), and two from remote region (Gansu and Qinghai), were included in the analysis of time trends and provincial disparities on PMMR from 1999 to 2008.α was set at 0.05.Statistical analyses were performed using Stata version 11.0 software . Poisson regression was used for the test of time trends and provincial disparities on PMMR. The statistical significance level for On a region level, coast region perform better than the other two regions in terms of data density and integrity on PMMSS and PMMR. Most provinces from coast region had a nearly complete time series of PMMR data from the late 1990s to 2000s; by contrast, most provinces in inland and remote region just reported 3–5 years' PMMR data continuously or intermittently, let alone the five provinces without any data on PMMSS or PMMR  .Following the national guide on data collection, maternal death review, and quality control, provincial governments established and adjusted their own PMMSS, respectively, based on their finance resources to monitor local maternal mortality level.County/district is taken as both the basic unit for data collection and the smallest sampling unit for maternal death surveillance in PMMSS. There were generally two types of surveillance modes for PMMSS: complete maternal death registration and stratified random sampling surveillance. In provinces adopting the former mode, maternal deaths in all counties/districts were reported and audited, whereas, in provinces adopting the latter mode, only the maternal deaths in the sampled counties/districts were under strict monitoring and careful review.The surveillance mode and the sampling percentage of the PMMSS varied among provinces . Of the There was a paucity of data over the time of establishment of PMMSS in most provinces. Only 6 provinces reported the setup times of their PMMSS, which from early to late were Hubei in 1987, Jilin in 1990, Hainan and Henan in 1996, Sichuan in 2001, and Xinjiang in 2004.P < 0.01). PMMR in Shanghai did not vary significantly from 1999 to 2008 (P > 0.05).Provincial variation in maternal mortality was substantial, especially among the provinces from different regions. Shanghai, with the lowest PMMR, was taken as the reference province. There was no significant difference on PMMR between the two provinces from coast region at all three time spots.P > 0.05). However, provincial disparities among provinces from different regions were substantial. Impressively, the RR of Qinghai to Shanghai was as high as 8.32 , 9.36 , and 7.32  in 1999, 2004, and 2008, respectively. Similarly, the RR of Gansu to Shanghai reached up to 6.71  and 7.96  in 1999 and 2004, respectively.This is the first English-language review of PMMSS and PMMR in China. With large population coverage and thorough quality control, PMMSS plays an important role in monitoring maternal mortality at provincial level. The surveillance mode and sampling percentage of PMMSS differ widely across the provinces. In addition, wide provincial disparities on PMMR were found after pooled analysis of the PMMSS data from six provinces. The results of the present review will help medical workers, the government, and international organizations understand the current status of provincial level maternal mortality surveillance systems in China.China has begun using NMCMSS from 1989 to track and estimate maternal mortality at national level . HoweverAs a system self-financed by provincial governments, PMMSS are limited to a great degree by the local socioeconomic development level. Consequently, although following the unified national outline for basic structure and data collection, the surveillance mode and sampling percentage of PMMSS differ widely across the provinces. As shown in the results, in the better-off region (coast region), nearly all the provinces realized complete registration of maternal deaths which is certainly effective, but undoubtedly more expensive and logistically challenging, while in inland and remote regions, most provinces adopted stratified random sampling surveillance. However, after experiencing remarkable economic growth, three provinces adjusted their maternal death surveillance mode from sampling surveillance to complete registration of maternal deaths, which also shows clearly the great importance to maternal death surveillance and reduction attached by the provincial governments.The comparison among PMMSS, NMCMSS, and NMCHRS could easily make clear the superiority of PMMSS in monitoring provincial maternal mortality. To some degree, PMMSS fosters strengths and circumvents weaknesses of the two other systems. On one hand, with the same thorough quality control and careful review of the maternal death with NMCMSS, PMMSS have substantially larger population coverage than NMCMSS. Within the country, PMMSS in 40% provinces adopt complete maternal deaths registrations; in most provinces adopting sampling surveillance mode, the sampling percentage varies from 14.6 to 34.8%, which is obviously higher than the sampling percentage of the NMCMSS about 5%) , 5. On t% , 5. OnSeveral papers have highlighted the problem of regional disparities on MMR in China. Feng et al.  and LianTibet, the province with the most underdeveloped economies and the highest MMRs around the country , definitMany studies have drawn attention to underreporting of births in national vital registration systems and fertility surveys, and the PMMSS is probably no exception. Underreporting of births is higher in remote areas or provinces, and the missing births are at higher risk of death; then we may have underestimated the maternal mortality ratio in remote areas or provinces and the gap between remote areas or provinces and coast areas or provinces. However, the same biases are likely to apply to maternal deaths over time, so this should not have influenced the observed disparities in the MMR over time.Several limitations to our review should be acknowledged here. First, there is obvious lack of information from the literatures. In China, maternal mortality surveillance findings usually are regarded as “internal report,” “confidentiality” were applied by restricting “outsider” access to the details . For a lSecond, generalizing conclusions about the national level MMR or regional level MMR from the PMMSS data has inherent limitation, since the different surveillance modes among the different provinces lead to big differences in the surveillance population, which necessarily hinders the pooled analysis.Although it may be ambitious, our conclusion is that PMMSS may be the most reliable data source for measuring provincial level MMR in each province. Given the size and diversity of China, it would be advantageous to keep the national surveillance systems as well as the provincial system. Great provincial disparities on PMMSS and PMMR do exist within China. More emphasis should be placed on improving PMMSS and reducing PMMR, particularly in the provinces with high maternal death burden, in order to ensure that all of the PMMSS are robust and adequate and provide comparable and complete information and that MMR could have a balanced decrease across the whole of China. In addition, the publication and wide spread of PMMSS data should be encouraged.


There are substantial phenotypic differences between the male and female human. Several complex traits have recently been tested to see whether these phenotypic differences are explained by differences in genetic control between males and females. While some differences in genetic control between males and females are detected, overall the results demonstrate that the genetic control of complex traits in humans is largely the same across the sexes.http://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1025-xPlease see related Research article:  Sexual dimorphism is pervasive in complex traits and diseases, with sex differences observed in, for example, the risk, incidence, prevalence and age-at-onset of cardiovascular disease, cancer, autoimmune disease and neurological and psychiatric disorders . These pA typical approach to study sex-specific genetic effects has been to perform either a sex-stratified GWAS or genotype-by-sex analysis. With few notable exceptions e.g. , 4), the, the4]),Rawlik and colleagues take an alternative approach to detecting genotype-by-sex interaction by treating the genetic architecture of the complex trait on a genome-wide scale separately for males and females, and then estimate the genetic correlation (rG) across the sexes. This approach has been widely used to look at genetic control of sexual dimorphism in a range of animals . The genn = 44,126 unrelated individuals  of European descent from seven GWAS cohorts [A genetic correlation of 1 occurs when the genetic control of the complex trait is the same in both sexes. A genetic correlation of less than 1 shows that the genetic control of the trait of interest differs across the sexes and is consistent with a certain amount of sex-specific genetic architecture. In general, the estimates of genetic correlation are subject to large sampling errors and are, therefore, very seldom precise unless performed in very large samples. This approach has previously been applied to height and body mass index (BMI) using a combined sample of Rawlik and colleagues address the question of sex-specific genetic architecture of human complex traits by examining the genetic correlation of 19 complex traits using 319,038 common autosomal SNPs across 54,040 unrelated males and 59,820 females from the UK Biobank cohort [There is an assumption when a complex trait has large differences between males and females that these differences are being driven by differences in the genetic control of the trait across the sexes. This assumption appears to be unsubstantiated by the data, with no clear relationship observed between the level of difference between the sexes and their genetic correlation Fig. . In partThis study demonstrates that most high-level complex traits have very high genetic correlations across the sexes. It follows that individual genotype-by-sex interactions are relatively unimportant, will on average have effect sizes that are much smaller than the main genetic effects on the trait and will thus require very large sample sizes to detect them. On a cautionary note, there is a need for reported genotype-by-sex interaction studies to be held to the high standards already required by GWAS studies, including substantial replication, to prevent the literature being flooded with false-positive results.BMI, body mass index; GWAS, genome-wide association study; LRS, life-time reproductive success; SNP, single-nucleotide polymorphism.


Gunnera tinctoria population from Ireland, we evaluated the potential of using plants derived from seeds associated with different soil layers to track genetic variation through time. This species and site were chosen because (1) G. tinctoria produces a large and persistent seed bank; (2) it has been present in this locality, Sraheens, for ∼90 years; (3) the soil is largely undisturbed; and (4) the soil's age can be reliably determined radiometrically at different depths. Amplified fragment length polymorphic markers (AFLPs) were used to assess differences in the genetic structure of 75 individuals sampled from both the standing population and from four soil layers, which spanned 18 cm (estimated at ∼90 years based on 210Pb and 137Cs dating). While there are difficulties in interpreting such data, including accounting for the effects of selection, seed loss, and seed migration, a clear pattern of lower total allele counts, percentage polymorphic loci, and genetic diversity was observed in deeper soils. The greatest percentage increase in the measured genetic variables occurred prior to the shift from the lag to the exponential range expansion phases and may be of adaptive significance. These findings highlight that seed banks in areas with long-established invasive populations can contain valuable genetic information relating to invasion processes and as such, should not be overlooked.Most research on the genetics of invasive plant species has focused on analyzing spatial differences among existing populations. Using a long-established  Invasive non-native species are estimated to cost the world economy hundreds of billions of dollars every year Pimentel  and are After initial colonization, a lag phase is frequently observed prior to the rapid range expansion of introduced plants Mack , and it Ambrosia artemisiifolia populations. The results suggested that current invasive populations have arisen from active gene flow and the subsequent admixture of historical populations, incorporating new alleles from multiple introductions. This study showed that including a temporal element in population genetic studies can provide useful information on the evolutionary processes involved in forming invasive populations. However, herbarium material of past populations that are amenable to genetic analyses is rarely available.Recently, Chun et al.  used herSoil seed banks play an important role in determining the structure of plant communities Harper , providiGunnera tinctoria seeds were germinated from soil obtained at varying depths at a site in Sraheens, Ireland. G. tinctoria is a native of Chile, but has become invasive in a number of countries worldwide, including Ireland, the United Kingdom, the Azores, the USA, and New Zealand, and it produces a persistent seed bank  markers . The soil in this area is a fine minerotrophic peaty gley (Hickey G. tinctoria at this site was estimated to be in the 1920s (Hickey Three soil cores were extracted from a heavily invaded unimproved grassland area (80 × 70 m) at Sraheens, Co Mayo, Ireland, where y Hickey  consistiy Hickey . Based os Hickey . The locG. tinctoria plants that were growing adjacent to each soil core were sampled by removing approximately 5 cm2 of leaf material. Samples from aboveground were preserved on site by drying using silica gel (Environogel), following the method described by Chase and Hill  with a relative efficiency of 22.5% and a resolution of 0.546 keV and 1.69 keV (FWHM) at energies of 5.9 keV and 1.33 MeV, respectively. Energy and efficiency calibrations were established using a mixed radionuclide standard solution (SRM 4276) containing 154Eu and 155Eu, supplied by the National Institute of Standards and Technology (US), a mixed radionuclide standard solution (7081/4) containing 241Am, 137Cs, and 60Co, supplied by CERCA Framatone ANP (France), and a 210Pb standard solution (S6/19/110) supplied by Amersham International (UK). Self-absorption of low-energy γ-rays within the sample was corrected for after the method of Yang and Ambats  as those used for the seed bank analysis (collected in 2010). One dating core was collected in 2002 and one in 2006. The cores, 50 cm long and 10 cm in diameter, were sealed with tape at both ends and transported back to the laboratory. After careful removal of soil from the cores, the outer ∼1 cm of soil was removed in case of contamination. The inner part of the core was then cut into 1-cm discs and air dried at approximately 35°C for at least a week. These samples were then passed through a 2-mm sieve to remove all large particles and stones. Subsamples (∼10 g) of the dried sections were then finely ground and homogenized before placing them in low background plastic counting vials prior to d Ambats .210Pb activity concentrations were measured via its gamma ray emission at 46.5 keV, while 226Ra, used to establish “supported” 210Pb concentrations, was determined by assuming equilibrium with its daughter nuclides, 214Pb (gamma emission at 351 keV) and 214Bi (gamma emission at 609 keV), following an appropriate equilibration period of at least 3 weeks in a sealed container. Unsupported (excess) 210Pb was calculated as the difference between the measured total 210Pb and the estimated 226Ra content. Concentrations of 137Cs and 241Am were measured via their gamma emissions at 661.7 and 59.5 keV, respectively. Chronologies and sediment accumulation rates were established by applying the CIC and CRS hypotheses to the measured 210Pb excess data  or absent (0) using the band-matching component of GelCompar2 3.0  and transformed into a binary 1/0 character matrix showing the presence or absence of each fragment for each sample. Fragments with a band frequency below 5% were excluded from the analysis as they are generally considered to be artifacts , the number of private alleles (Np), and the percentage of polymorphic alleles (Ppl) were calculated for each soil layer within each soil core using GENALEX 6.2. Using the distance component of GENALEX 6.2, the level of genetic diversity for each soil layer within each soil core was calculated based on the Shannon index of diversity (I)  were not included as there was no deeper soil layer for comparison.The total allele count  was performed using the PCO component of PAST 1.94b , and within soil layers (ϕPT), was calculated using a squared Euclidean distance matrix (9999 permutations). AMOVA was also performed within each soil core so that differences between ϕPR and ϕPT within soil cores could be characterized and compared.An analysis of molecular variation (AMOVA) was performed using GENALEX 6.2  was identified between germination rates and soil depth, with fewer seeds germinating in soils obtained from deeper soil core layers  of 210Pb and 137Cs distribution indicated that the soil was relatively undisturbed.Based on P < 0.0001) of the total genetic variation was partitioned within soil layers and 97% (P < 0.0001) of total genetic variation was partitioned within soil cores (data not shown). This confirms that the patterns of genetic variation observed are due to differences between layers and not between cores.An analysis of molecular variance (AMOVA) revealed that 72% (Nl) (Table pl) . For the standing population, Nl, Ppl, and I were higher than those in deep soil, but lower than those in shallow soil .When data were aggregated for each soil layer, it was observed that seeds germinated from deeper layers had a lower total allele count (l) Table , Fig. 2,l) Table , and a ll) Table . IncreasNl correlated linearly with increases in the percentage of polymorphic alleles (Ppl) and population genetic diversity (I) . There was a strong linear relationship between I and Ppl .For the aggregated data, increases in Np) fluctuated between 0 and 9 .Private allele counts  soil layer  soil layer  of the presence/absence allelic data grouped the samples into three clusters Fig. . PrincipG. tinctoria seeds germinated from different soil depths  and compared them with plants from a standing population. There was a general pattern of increasing genetic diversity in the seed bank with time, with the greatest increase relative to deeper soils occurring before the transition between lag and expansion phases. Germination rates were lower in seeds recovered from deeper soils, and total allele counts (Nl), percentage polymorphic alleles (PPL), and the level of genetic diversity (I) decreased with increasing depth; however, based on PCO analysis, there were no clear population structure differences between the different layers. Four main nonmutually exclusive influences, which could have contributed to the observed allelic patterns, have been identified. These influences are as follows: differences in seed mortality/viability at different depths; seed movement through the soil; sample size; environmental conditions in the growth environment; errors determining soil accretion rates; and evolutionary processes . The evidence indicates that evolutionary processes play the most significant role in influencing the observed patterns. To explain how this conclusion was reached, and to assess the role of other factors, the various possibilities are considered sequentially and evaluated against the available evidence.To test the feasibility of using plant material derived from seed bank soil cores to track changes in population genetic structure through time, this study investigated differences in the pattern of genetic variation between The mechanisms that govern seed viability are not fully understood; however, seed longevity is believed to be influenced by a combination of genetic, physiological, and environmental factors    Hickey . The pat°C) and, due to its high water content, would be low in oxygen . However, unless this loss of seeds had a genetic basis, that is, certain genotypes had an enhanced viability, selecting those individuals that remained in the soil for genetic analysis would be no different than randomly selecting the same number of individuals from the original intact seed population. Furthermore, as AFLPs are neutral markers, the genetic variation observed in this study would not be linked to the fitness of the organism and, therefore, would not be affected by natural selection ) were variable. If the soil depths in the different cores did not correspond to the same dates, then we would not expect to see definitive population structure differences between layers. However, samples from sequentially deeper layers from each individual core would still have been sequentially older, and changes through time could still have been observed for Nl, PPL, and I. In future, however, soil age profiles should preferably be obtained for each individual core and be examined independently.The lack of definitive population structure differences between soil layers could be explained if the ages of analogous soil layers in different cores were not uniform. The soil dates used in this study are from averages obtained from data originating from cores collected on two previous studies. The accretion rates obtained , the subsequent increases of the values with decreasing depth, and the higher levels observed in the shallowest soil layer  would be indicative of a population that had previously undergone genetic bottlenecking and subsequently experienced gene flow influenced increases in allelic content through time. The higher number of private alleles in the standing population and the trend of increasing private allele counts with decreasing depth would also be indicative of new alleles arriving through time. Finally, from the PCO analysis, individuals from the deepest soil layer were distinct from the standing population. The results from this study, therefore, support the findings of Fennell et al. (On the basis of this assessment of the possible confounding factors associated with estimates of genetic differences in soil seed populations at varying depths, it is unlikely that seed loss, seed migration, and experimental error can explain the depth-dependent changes in l et al. .G. tinctoria indicates that increases in genetic diversity may be associated with a shift from the lag to the exponential growth expansion phase. Although, owing to the use of neutral genetic markers, no specific inferences can be made, this could imply that adaptive evolution, benefitting from a larger gene pool, has played a role in the expansion of this introduced species.An examination of the relationship between percentage changes in genetic variables and the invasion curve for The general utility of the approach used in this study is not limited to AFLP analysis. If such an approach was combined with an analysis of epigenetic variation, MS-AFLP (Hazen et al. The use of seedlings germinated from sequentially deeper and datable soil layers can be used to track changes in the population genetic structure of an invasive species through time. The success of this approach is likely to depend on the chosen species and location. A species with highly persistent seeds is required, as is a location with soil that has the appropriate characteristics and that can be reliably dated. Neutral genetic markers can be used effectively. An equal number of samples should be randomly selected from all soil layers.Nl, PPL, and I between deep soil, shallow soil, and the standing population indicate that existing invasive populations of G. tinctoria have arisen from an initial genetic bottleneck, followed by active gene flow from other locally occurring populations. As a result, the population allelic content has increased over time. This increase in genetic diversity may have counterbalanced any potentially fitness-reducing effects of genetic bottlenecking, thereby contributing to range expansion and, ultimately, invasive success.Changes in the pattern of variation in If this approach is adopted and used to examine temporal changes in the population genetic structure of many invasive species across many environments, then invaluable insight could be gained into the genetic processes that lead to the success of invasive populations.


Vasculogenic mimicry (VM) formation is important for invasion and metastasis of tumor cells in gastric adenocarcinoma (GAC). The present study aimed to investigate the association between signal transducer and activator of transcription-3 (STAT3), phosphor-STAT3 (p-STAT3), hypoxia-inducible factor-1α (HIF-1α) and VM formation in GAC, and discuss their clinical significance and correlation with the prognosis of patients with GAC. The expression levels of STAT3, p-STAT3, HIF-1α and VM were assessed in 60 cases of patients with GAC and 20 cases of patients with gastritis on tissue microarrays by immunohistochemical methods. The expression levels of STAT3, p-STAT3, HIF-1α and VM were higher in patients with GAC (particularly in poorly differentiated GAC) than in those with gastritis (P<0.05). The expression levels of STAT3, p-STAT3 and HIF-1α were higher in VM tissues compared with non-VM tissues (P<0.05). Positive correlations existed between STAT3, p-STAT3, HIF-1α and VM expression (P<0.05). The expression levels of STAT3, p-STAT3 and HIF-1α, VM, status of lymph node metastasis and tumor differentiation degree were associated with the overall survival time of patients with GAC (P<0.05). However, only p-STAT3 and VM expression were identified as the independent risk factors of GAC OS when analyzed with multivariate analysis. p-STAT3 and VM play a significant role in indicating the prognosis of patients with GAC. STAT3 activation may play a positive role in VM formation of GAC by the STAT3-p-STAT3-HIF-1α-VM effect axis. STAT3ynthesis . Pawlus s /PAS double-staining method. Subsequently, combining VM existence with the expression levels of STAT3, p-STAT3 and HIF-1α, the association was assessed between them and the possible formation mechanism of VM was investigated. Additionally, prognosis was assessed by Kaplan-Meier survival analysis for univariate analysis and by Cox proportional hazards model for multivariate analysis.A total of 80 cases of paraffin-embedded specimens were collected in the Department of Pathology at the Qilu Hospital of Shandong University . These cases included 60 GAC specimens  and 20 gastritis specimens . Primary gastric cancer in these patients was diagnosed and treated at the Qilu Hospital between July 2005 and December 2006. The patients with GAC had well-documented clinical histories and follow-up information. None of the patients underwent preoperative chemotherapy and/or radiation therapy. The follow-up time ranged between 6 and 72 months until July 2012, although the follow-up data of one case was lost. Overall survival (OS) time was defined as the interval between the dates of surgery and mortality. The gastritis cases were derived from gastritis biopsy specimens. All the cases were reviewed by two highly qualified pathologists. The study was approved by the ethics committee of Shandong University School of Medicine  and written informed consent was obtained from the patients or their family.A tissue microarray instrument  was used to construct a blank receptor wax block of six rows and seven columns. Marked and collected tissues from the paraffin-embedded specimens were inserted into the holes of the receptor wax block. From each case, two specimens were acquired to overcome the loss of tissue. The first two holes on the first line were filled with ash, which served as a ‘blank’ specimen-positioning reference. Each receptor wax block accommodated 40 specimens, which represented a total of 20 cases. The GAC specimens were built into the three tissue microarrays. Each was subjected to repeated wax melting at 56°C to become a whole specimen. The tissue microarrays and gastritis tissue specimens were sectioned into 4-μm-thick slices that served as a continuous backup source.The slices were dewaxed in xylene and then rehydrated through a graded series of alcohols. For antigen retrieval, the slides were heated in 10 mmol/l EDTA buffer (pH 8.0). Subsequent to washing with phosphate-buffered saline (PBS) three times, the endogenous peroxidase activity was blocked by 3% hydrogen peroxidase for 10 min of incubation at room temperature. Following washing with PBS again, the sections were incubated with polyclonal rabbit anti-human STAT3 , polyclonal rabbit anti-phospho-STAT3  and monoclonal rabbit anti-human HIF-1α  primary antibodies at 4°C overnight separately. The slides were washed with PBS and incubated with biotinylated horseradish peroxidase-conjugated secondary antibody, polyclonal goat anti-rabbit immunoglobulin G , at room temperature for 30 min. Subsequent to washing, the slides were colored with 3,3-diaminobenzidine and counterstained with hematoxylin  and the proportion of positive cells estimated in an average of 100 cells counted in 10 high-magnification fields. The staining intensity was subjected to the following numerical scoring: Specimens were colorless, 0 points; pale yellow, 1 point; yellow, 2 points; or brown, 3 points. The proportion of positive cells was scored as follows: The number of positive cells was <5%, 0 points; 5–25%, 1 point; 26–50%, 2 points; 51–75%, 3 points; and >75%, 4 points. Immunostaining was considered positive when the product of the two types of scores was multiplied and was ≥4 . The count column was analyzed by the χVM , arrow, Positive expression levels of STAT3, p-STAT3 and HIF-1α were significantly increased in the GAC specimens compared with the gastritis specimens, respectively . Notably, STAT3-, p-STAT3- and HIF-1α-positive expression and VM formation in tissues from patients with lymph node metastasis were significantly higher than those from patients without lymph node metastasis, respectively . In addition, STAT3- and p-STAT3-positive expression and VM formation were increased in poorly differentiated GAC tissues compared with those in well-differentiated GAC tissues, separately . The various expression levels of STAT3, p-STAT3 and HIF-1α were detected in VM GAC and non-VM GAC tissues, and it was found that STAT3 , p-STAT3The results showed that the expression levels of VM exhibited a positive correlation with those of STAT3 (r=0.480 and P=0.001), p-STAT3 (r=0.480 and P=0.001) and HIF-1α (r=0.480 and P=0.001), separately. The expression levels of HIF-1α were also positively associated with those of STAT3 (r=0.480 and P=0.001) and p-STAT3 (r=0.480 and P=0.001), separately .Using Kaplan-Meier univariate analysis, six factors were found to have statistically significant associations with the OS time of patients with GAC following curative surgery, including STAT3, p-STAT3 , HIF-1α,All the aforementioned six variables were analyzed by a multivariate Cox proportional hazards model (forward stepwise procedure). In this model, VM , and p-STAT3  showed significant correlations with the OS times of patients with GAC following curative surgery, which indicated that VM and p-STAT3 were the independent risk factors of the OS time of patients with GAC .et al . Additionally, STAT3 expression was positively correlated with p-STAT3, HIF-1α and VM expression, respectively, in GAC tissues. By univariate and multivariate survival analysis, patients with both negative expression of p-STAT3 and VM were found to be more likely to have a longer median OS time compared with those with p-STAT3- and (or) VM-positive expression (P<0.05), and p-STAT3 was an independent risk factor of the OS time of patients with GAC. These indicated a specific type of association between STAT3, p-STAT3, HIF-1α and VM in GAC tissues.Combining the aforementioned studies with the results of the present study, it was deemed that STAT3 may be a novel positive factor of VM formation in GAC tissues through the effect of p-STAT3. STAT3 and p-STAT3 were positive factors of HIF-1α expression and VM formation in GAC tissues. STAT3 was significantly associated with progression and prognosis of GAC. Combining the previous studies with the present study results, it can be concluded that STAT3 may promote the formation of VM to affect the invasion and metastasis in GAC tissue by a specific type of mechanism (STAT3-p-STAT3-HIF-1α-VM).In conclusion, it was found that p-STAT3 and VM played a significant role in indicating the prognosis of patients with GAC. STAT3 activation may play a positive role in VM formation of GAC tissues by the STAT3-p-STAT3-HIF-1α-VM effect axis. These results provide opportunities to develop potential novel therapeutic targets for GAC.