Five European Union allies of the United States on Tuesday expressed opposition to President Donald Trump's recognition of the disputed Golan Heights as Israel's territory.
Belgium, Britain, France, Germany and Poland insisted that the European position had not changed and that the Golan remained Israeli-occupied Syrian territory, in line with worldwide law enshrined in United Nations resolutions.
"We raise our strong concerns about the broader consequences of recognizing illegal annexation and also about the broader regional consequences", it said.
CTGN quoted Chinese Foreign Ministry's spokesperson Lu Kang as saying "China opposes changing the status quo of Golan Heights through unilateral behaviour", calling for the avoidance of escalating regional tensions.
The US said "aggressive acts" by Iranian and Syrian terrorist groups, such as Hezbollah, threaten the security of Golan Heights.
According to him, the regime of Bashar al-Assad has never tried to politically defend the problem of the Golan on global scene and has not taken any action against Israel.
The document reverses more than a half-century of USA policy as Israeli Prime Minister Benjamin Netanyahu visited the White House.
Saudi Arabia, Bahrain, Qatar and Kuwait criticized the move by President Donald Trump to recognize Israel's 1981 annexation, and said the territory was occupied Arab land.
The Golan Heights, a high plateau that sits on the border between Israel and Syria, was part of Syria until Israeli forces seized it during the Six-Day War of 1967.
Indonesia, the ministry said, had based its position on the United Nations Charter principles of national sovereignty and territorial integrity, as well as previous UN resolutions, including the 1981 resolution that rendered Israel's annexation of the Golan Heights null and void and without worldwide legal effect.
Ever since Trump became President of the United States he has ignored both USA and global laws.
The Arab Parliament's rejection of the United States recognition of Golan Heights is totally justified.
Everybody in the Arab world already knows that Trump is completely loyal to Israel, if only because that is the best way to get the votes of US evangelical Christians.
The recognition of the Golan Heights showed that occupied territory can be held on to and occupying territory gained from a defensive war can be justified, the official told reporters. Lebanon maintains that the strip of land is a part of Lebanon, despite it having been under Syrian control from the 1950s until it was captured as part of the Golan Heights.
"No one could imagine that a person in America comes and gives land of a nation to another occupying country, against worldwide laws and conventions", President Hassan Rouhani was quoted as saying by state news agency IRNA.
The UAE Ministry of Foreign Affairs and International Cooperation (MoFAIC) is absolutely correct in stressing that there is no possibility of achieving stability and peace in the region as long as Israel continues its occupation of Palestinian and other Arab territories. In his phone conversation with U.S. State Secretary Mike Pompeo, Russian Foreign Minister Sergei Lavrov noted that the recognition of Israel sovereignty over the Golan Heights would lead to the violation of worldwide law, impede the settlement of the Syrian crisis, and aggravate the situation throughout the Middle East.
Turkey's foreign minister said that the USA had ignored worldwide law and that the decision would further increase tensions in the region.


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redpajama_set_name: RedPajamaGithub


This entry was posted in City Hall and tagged fire hall fiasco, Phil Sheegl, Sam Katz, whistle blower legislation.
Hmmm…..I am guessing that most of the guesses have involved Sam, Phil and Poppa Sandy. Seems to me that it could apply to the Federal Government as well. You'd just need more monkeys; the Senate has only coughed up a few of them, and Harper and his lackey should be in there too, along with the senators caught…..so far.
Here's an example of how internal reporting systems and investigations don't work.


text:
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The Power of 'Uluru'
Home » Articles » The Power of 'Uluru'
Lorraine Webb
Uluru in Central Australia was known by its western name of Ayers Rock until it was handed back to the original owners of that land and reverted to its known name of Uluru. People come to the Red Centre from countries all around the world just to see this powerful rock and to walk around or climb it. Of course we are asked by the local custodians, the Mutitjulu people to not climb the rock. Many people think this is because of the sacred significance but a few years ago I asked one of the elders why this was so and with a grin he told me that "We don't want these white people killing themselves, that is why. As the custodians we are responsible for the welfare of those at the rock and when people die at the rock we are responsible for their spirit." Many people do die at the rock that we don't hear about, it is not uncommon for someone to have a heart attack while climbing or for someone to fall. It is not a climb for the faint hearted and takes some effort, which many underestimate. I recall being at the base of the rock a few years ago with my healers group and we could not believe our eyes as we looked up and saw a man struggling down the rock with a baby of about three months in one arm and a young two or three year old by the hand. It was scary and we held our breath watching this struggle and at times this man had no choice but to let go of the toddler and let him do the best he could. As the elder told me "People do silly things."
My calling to the rock was back in early 2006 when Spirit told me that I was to now teach my course at Uluru, I had been teaching my Energetic Healers Course as a four-module course here in Adelaide since 2000. They told me that there was no time for this and that people needed to transform their lives and to get this information much faster than that and they assured me that the energy of the rock would help me to make this happen. I was very nervous about making this change as it didn't seem possible to me, however as always, I trusted what I had been told and prepared the first course for later that year. Once this was in place things really started to happen, I received a call from an Aboriginal lady elder who asked me what I was doing because she knew I was doing something that she wanted to be involved in, talking to this lady I felt I had known her for years, before that conversation ended she was coming with me on the first trip. I contacted Aboriginal elder Bob Randall from Mutitjulu and he knew I was coming as well. When the three of us met for the first time at Uluru we all looked into each other's eyes and knew we had much work to do together and we knew that we were now on a journey that had been planned for us, that continues today as our souls work together for the Divine Plan.
From that very first journey and group I could see amazing transformations taking place amongst each person that attended, not only did they take on new information but they dropped layers and layers of pain and allowed the wonderful power of the rock, the heart energy of Australia and the spiritual centre of the planet, to absorb their own heart pain and open their heart chakra to love.
We are so lucky to have this amazing site on our land, people will continue to be drawn to Australia seeking the knowledge and healing that is available here. I was shown in a vision ten years ago that Australia would be the spiritual centre of the world and that the Indigenous energy held the key to that power. I have connected to my ancestors and my Aboriginal heritage but as Australians black or white we are connected to this land and the power it holds and we can open to that power and knowledge and be proud that we have this ancient wisdom at our fingertips. The Indigenous people of this land are happy to share their amazing knowledge that is unique to this country yet so many Australians still seek out Indigenous cultures from other lands believing them to be somehow better, showing little or no respect for our own Indigenous wisdom. This is so sad for they don't know what they are missing out on. Times are changing however and people are awakening, if you would like to transform and awaken contact us and join us on the 'Uluru Experience', call 08 8342 4109 or email admin@adelaidehealingenergy.com.au
RELEASING ALL THAT NO LONGER SERVES YOU by Lorraine Webb
June 6, 2016 | adelaidehealing
PERSONAL RESPONSIBILITY by Lorraine Webb
April 1, 2016 | adelaidehealing
LET IT BE! by Lorraine
December 18, 2015 | adelaidehealing
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Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected Pc = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (Pc = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; Pc = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (Pc = 0.004) and in the Hispanic American sample from MESA (Pc = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations.
Genome-wide association studies (GWAS) have identified many loci associated with complex human traits or diseases. However, the fraction of heritable variation explained by these loci is often relatively low. Gene–gene interactions might play a significant role in complex traits or diseases and are one of the many possible factors contributing to the missing heritability. However, to date only a few interactions have been found and validated in GWAS due to the limited power caused by the need for multiple-testing correction for the very large number of tests conducted. Here, we used three types of prior knowledge, known GWAS hits, protein–protein interactions, and pathway information, to guide our search for gene–gene interactions affecting four lipid levels. We identified an interaction between HMGCR and a locus near LIPC in their effect on high-density lipoprotein cholesterol (HDL-C) and another pair of loci that interact in their effect on low-density lipoprotein cholesterol (LDL-C). We validated the interaction on HDL-C in a number of independent multiple-ethnic populations, while the interaction underlying LDL-C did not validate. The prior knowledge-driven searching approach and a locus-based validation procedure show the potential for dissecting and validating gene–gene interactions in current and future GWAS.
Funding: This work was supported in part by NIH grants GM065509, HL072904, and U01-HG005715. AK is an Alfred P. Sloan Research Fellow. ARIC, FHS, and MESA were supported by the National Heart, Lung, and Blood Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The catalog of genome-wide association studies (GWAS)  has collected to date over 1,194 publications since the end of 2008, for a total of over 5,697 single nucleotide polymorphisms (SNPs) that are associated with complex human diseases and other complex traits. However, most these associated SNPs exhibit a small effect size, and collectively only explain a relatively small fraction of additive variance , , , . Specifically, a recent meta-analysis of several GWAS, studying a combined sample size between ∼20,000 to ∼100,000 individuals, identified 95 loci associated with the level of one of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) . In aggregate, these loci explain only 25–30% of heritable variation for each trait . Many hypotheses aiming to explain the missing heritability of GWAS have been proposed, including structural variants, rare variants, gene-environment interactions, epigenetics, and complex inheritance , , , . Because gene-gene (epistatic) interactions may contribute to missing heritability to some extent , , , here we seek to find examples of pairs of loci that interact in their effects on any of the four lipid levels, which are important risk factors of coronary artery disease .
Epistasis has been investigated in order to understand the relationship between genotype and phenotype since Bateson  discovered in 1905 that some genes can suppress the effects of others. Thereafter, a number of epistatic interactions have been identified in QTL mapping studies or GWAS in humans ,  and other organisms , , . Studies of model organisms suggest that gene-gene interactions are a common phenomenon , , , . However, they have proven difficult to detect in humans, chiefly due to the limited statistical power associated with the large combinatorial number of tests and the skew towards low minor allele frequencies , . Hence, in order to increase power to detect gene-gene interactions in GWAS, a series of methods have been developed to prioritize candidate SNPs using prior knowledge of established GWAS hits , and recently also using knowledge of protein-protein interactions (PPIs) ,  and pathway information .
Although some interactions affecting complex diseases and traits have been reported in humans , , replication of these interactions in independent samples has proven difficult . He et al.  showed that this low replication is in part attributable to low power and small effect sizes of tag SNPs in GWAS. For two interacting causal loci, the observed interaction effect between two respective tag SNPs (each tagging one of the causal loci) is proportional to the underlying causal interaction effect multiplied by the product of the two linkage disequilibrium (LD) coefficients between each tag SNP and the respective causal variant. This decrease in the measured interaction effect reduces the statistical power of the interaction test and it also reduces the probability of replication of significantly identified interactions. This reduction is further exacerbated by heterogeneity in the LD structure between different populations and among population samples. These are the same problems that plague the power of single-marker GWAS tests, but they are exacerbated in interaction testing, with a quadratic dependence on LD between markers and causal loci, which lead to a much greater reduction in power. Motivated by this problem, Liu et al.  proposed a local validation analysis and successfully replicated the loci of a few interactions underlying common human diseases.
In this study, we aim to improve the power to detect gene-gene interactions in existing large-scale GWAS data sets by considering for interaction testing only a highly focused set of candidate SNPs extracted from prior information of known GWAS hits, PPIs, and pathway information. To improve the power of replicating gene-gene interaction signals in independent samples, we introduce an adaptive locus-based validation procedure that follows an approach similar to Liu et al. . Applying these procedures for testing for gene-gene interactions underlying lipid levels, we discovered a significant interaction affecting HDL-C levels, which provides new insights into the genetic architecture of this complex trait. Using the adaptive locus-based validation procedure, we also successfully replicated this novel interaction in four independent cohorts, including two cohorts of different ethnicity.
We tested the statistical significance of gene-gene interaction between each pair of SNPs among 125 SNPs from 95 loci that have been previously individually associated with any of the four lipid levels  for a total of 7,750 tests, out of ∼3 trillion possible tests between each pair of SNPs in our data. Tests of interaction were conducted using genotype data or imputed genotypes in a sample of 9,713 European Americans (EAs) from the Atherosclerosis Risk in Communities (ARIC) study  (Materials and Methods). We used an F-test with four degrees of freedom within a linear model framework for interaction testing , . This test considers the 3×3 table of genotype pairs for two SNPs and tests for significant interaction between the two SNPs on top of any additive or dominance effects that each of the SNPs might exhibit by itself. For consideration of statistical power and robustness, we discarded from testing pairs of SNPs for which one or more of the 9 genotype-by-genotype combinations appeared in fewer than 20 individuals in our sample (Materials and Methods).
Testing for interaction between 7,750 pairs of SNPs for each of four quantitative traits, we identified one significant interaction underlying each of LDL-C level and HDL-C level (Figure 1a). The interaction underlying LDL-C level is between rs2247056 and rs1030431 (Bonferroni corrected Pc = 0.003; Figure 1a). To explore the interaction between the two loci with better resolution, we tested for interaction between each SNP in the 100 kb surrounding rs2247056 and each SNP in the 100 kb surrounding rs1030431 and found that the interaction signal peaked between rs2853928 and rs1993453 (Pc = 0.01 after accounting for all additional pairs of SNPs tested; Figure S1). The discovery SNP pairs are in high LD with the fine-mapped SNP pairs, with an r2 value of 0.997 between rs2247056 and rs2853928 and 0.999 between rs1030431 and rs1993453. The former two reside near a pseudogene, LOC100133383, and the latter two are located near and in gene UBXN2B, respectively. However, this suggestive interaction underlying LDL-C did not replicate in independent cohorts.
Figure 1. QQ plots for gene–gene interaction tests.
A) Discovery in ARIC EA cohort by testing all possible pairs of SNPs among the 125 previously associated SNPs , for each of the four traits, showing deviation from expectation for two of them, and pointing in each of these two cases to a single pair of interacting SNPs (Table 1). B) Fine mapping in ARIC EA by testing all possible pairs of SNPs in the 100 kb surrounding rs12916 and rs1532085 that were found from panel A (HDL-C). C) Validation by testing SNP pairs surrounding rs3846662 and rs2043085 (found from panel B; see also Table 1) in four additional cohorts, each pointing to significant gene-gene interaction between the two regions. For all, stage (iii) of the adaptive locus-based validation procedure is shown, though replication has already been successful in stage (ii) in the MESA EA cohort.
Henceforth, we focus on the interaction between rs12916 and rs1532085 on HDL-C levels (Pc = 0.008), since its validation in additional cohorts is highly significant, as described below. We first tested for interaction between each SNP in the 100 kb surrounding rs12916 and each SNP in the 100 kb surrounding rs1532085. While many of these pairs show significant interactions (Figure 1b), as expected from LD, we observed the strongest signal between rs3846662 and rs2043085 (Pc = 0.002). The fine-mapped pair of SNPs is in high LD with the original pair of SNPs, with an r2 value of 0.88 between rs3846662 and rs12916 and an r2 value of 0.93 between rs2043085 and rs1532085 (Figure S2). rs3846662 is intronic in HMGCR (Table 1), which has not been previously associated with HDL-C, but has been associated with both TC and LDL-C levels . rs2043085 is upstream of LIPC (Table 1), which has been previously found to be associated with HDL-C .
Table 1. Significant interactions on HDL-C in multi-ethnic cohorts.
The interaction between rs3846662 and rs2043085 affects HDL-C twice as much as the effect of the polymorphism in LIPC alone: While individuals with TT genotype at rs2043085 already exhibit an average increase of 2.63 mg/ml in HDL-C (standard error (SE) = 0.014; Figure 2a), this genotype in combination with an AA genotype at rs3846662 leads to an average increase of 5.72 mg/ml (SE = 0.041; Figure 2b). The linear model with these two SNPs has an R-square value of 0.5% and the linear model with the two SNPs and their interaction has an R-square value of 0.8%, which indicates that the interaction explains additional 0.3% of the overall variation in HDL-C levels (Materials and Methods; Table S1). We tested whether rs3846662 and rs2043085 exhibit gene-gene interactions underlying any of the other lipid levels, and found a nominally significant interaction underlying LDL-C (P = 0.028), and almost significant interaction underlying TG (P = 0.08) in ARIC.
Figure 2. Marginal and interaction effect sizes on HDL-C level in ARIC EA cohort.
A) Boxplot of the effect sizes of rs2043085. Allele T of rs2043085 leads to increased HDL-C, with median levels of 45.8, 46.9 and 49.3 mg/ml for CC, CT, and TT (difference in mean levels reported in main text). B) Boxplot of the effect sizes of the SNP pair, rs3846662∶rs2043085. The genotype AA∶TT leads to a considerable increase of HDL-C. The median HDL-C level in the entire sample is 46.7 mg/ml, while the median level for AA∶TT is 52.7 mg/ml (rs2043085 is the only one of the two that is associated by itself with HDL-C, hence shown in panel A).
We performed a larger scale interaction analysis between all pairs of SNPs that (i) are found in interacting genes according to a curated human protein-protein interaction network (∼6 million pairs), or (ii) are involved in the pathway of metabolism of lipids and lipoproteins (∼27 million pairs). All SNPs in a gene were considered, as well as in the 5 kb regions upstream and downstream. This analysis detected no significant gene-gene interactions following Bonferroni correction (Pc≥0.58 for PPIs; Figure S3; Pc≥0.14 for pathway; Figure S4).
Considering the quadratic reduction in replication power as a function of LD between tag SNPs and causal loci, we aimed to increase power via an adaptive locus-based validation procedure that is related to that of Liu et al. . In considering a replication dataset, the procedure follows three sequential stages that leverage the signals of proxy markers: (i) test for interaction between the original SNP pair between which gene-gene interaction has been detected; (ii) test for interactions between each of the two original SNPs and each SNP in the proximate region containing the other original SNP; (iii) test for interactions between each pair of SNPs in each of the two respective proximate regions containing the two original SNPs. This validation procedure proceeds sequentially and stops at any stage when significant interactions were detected after multiple-testing correction. Both the method of Liu et al. and our adaptive locus-based validation method focus on replicating the interaction between a pair of loci, rather than between a pair of SNPs, due to the power limitations of replicating an interaction between SNPs. The null hypothesis of the entire three-stage procedure is that there is no interaction between the pair of loci, rather than just between the pair of SNPs, thus the procedure continues sequentially as described to consider proxy SNPs from the loci containing each original SNP. Replication is successful if an interaction between any SNP pair from the two loci is significant after multiple-testing correction. Similar locus-based approach has also been used in the context of gene-based GWAS tests for single-marker association, which use an entire gene or locus as the testing unit of association, rather than a single SNP , .
To validate the gene-gene interaction affecting HDL-C, we performed replication analyses in two additional GWAS datasets from the Framingham Heart Study (FHS)  and the Multi-Ethnic Study of Atherosclerosis (MESA) , as well as in the African American (AA) cohort from the ARIC study . Using our adaptive locus-based procedure, we tested for interaction sequentially between SNPs surrounding rs3846662 and SNPs surrounding rs2043085. We observed significant interactions in the two additional EA cohorts from FHS and MESA (Figure 1c), with Pc = 0.002 and Pc = 0.006 for the most significantly interacting SNP pair (Table 1). Replication was also significant in Hispanic Americans (HA) from MESA and AAs from ARIC (Figure 1c; Table 1). The R-square of linear model with the two interacting SNPs varies between 0.2–0.5% across the four replication cohorts, with the interaction term between the two explaining an additional 0.2–1.1% of the overall variation in HDL-C levels (Table S1). The replication procedure failed in a sample of AAs from MESA (Figure S5).
None of the successful replications were replicated at stage (i) of the adaptive locus-based validation procedure, which means that an interaction between the same SNP pair is not observed significantly in the additional samples. The interaction was successfully validated in stage (ii) of the three stages in the MESA EAs, with the same SNP in HMGCR (rs3846662) and a proxy SNP near LIPC exhibiting a significant gene-gene interaction after multiple-testing correction. The other three successful replications occurred at stage (iii) (Table 1), emphasizing the importance of a locus-based replication approach. The combined evidence from the discovery and four different validation cohorts for a gene-gene interaction between the two loci under study is overwhelmingly significant, even following a conservative Bonferroni correction (Pc = 9.0×10−8).
While the gene-gene interaction signal peaks for different pairs of SNPs across the different cohorts (Table 1), the type of interaction and effect patterns appear consistent across several sample sets (Figure S6). To test this formally, we partitioned the significant SNP-SNP interactions into the four possible interaction components on top of the marginal SNP effects, namely additive by additive (A×A), additive by dominance (A×D), dominance by additive (D×A), and dominance by dominance (D×D) components (Materials and Methods). Considering a nominal significance level of 0.01, D×A and D×D components are significant and underlie the significant interaction in the ARIC EA discovery set, between rs12916 and rs1532085 (Table S1). All four terms are significant between the pair of SNPs, rs3846662 and rs2043085, that resulted from fine mapping in the same discovery set, with D×A and D×D being of the same effect direction (sign) and similar effect sizes as between rs12916 and rs1532085 (Table S1). Examining the two replication cohorts of a similar (EA) ancestry, the interaction in the MESA cohort similarly shows significant D×A and D×D components, with same effect direction, though with larger effect sizes and a higher proportion of phenotypic variance explained (Table S1). None of the four terms is significant by itself in the EA FHS cohort. These results of consistent patterns of interaction across the EA cohorts support the possibility that they are all governed by the same (unobserved or partially unobserved) interacting variants.
To verify that our results are not an artifact of imputation errors, we compared imputed genotypes of the two SNPs (rs12916 and rs3846662) that were involved in significant interactions and for which we could obtain measured genotype data from an independent source, using the ITMAT/Broad/CARE (IBC) Vascular Disease 50 k SNP Array chip . For these two SNPs, r2 between imputed and actual genotypes is 0.914 and 0.921 and the genotype concordance rate is 94.5% and 94.7%, respectively. Although the imputation is not perfect, the two interaction tests involving these two SNPs are at least as significant when replacing imputed genotypes with measured IBC genotypes, consistent with imputation errors adding noise and masking some of the signal, rather than biasing the statistical test.
Tests of gene-gene interactions are not as powerful as tests of single-marker association, so a judicious strategy is essential for successful interaction analysis in GWAS , . The first step is to determine the size of the analysis, genome-wide or focusing on candidate SNPs. This step should consider the sample size, possible effect size of the underlying interaction, and the desired statistical power. Current single-marker GWAS have been successful in detection of single-marker associations for many complex diseases or traits using a stringent genome-wide significance level (P<5×10−8). To achieve a similar success for interaction analysis, we are limited to performing ∼1 million tests even if the interaction test and single-marker test had the same statistical power. This limitation means that we are not able to conduct an inclusive all-by-all pair-wise interaction analysis in current GWAS. Thus, in this study we only tested for interactions between candidate SNPs based on prior knowledge.
We used three types of prior knowledge, known GWAS hits, protein-protein interaction networks, and known functional pathways. These three analyses might be different in the enrichment of epistasis signals and are also different in the number of interaction tests, 7,750 based on known GWAS hits, ∼6.2 million using PPI, and ∼27 million with pathway information. We found significant interactions from the 7,750 interaction tests using known GWAS hits. As the sample size of ∼10,000 individuals is relatively large among existing GWAS, this indicates that the observed (tagged) effect size of any other underlying interactions is no larger than the marginal effects of single SNPs. It is also likely that the epistasis signals are better enriched between markers that are marginally associated with lipid traits such that testing interactions among known GWAS hits is more powerful in our study. Therefore, our results suggest that a small-scale interaction analysis of candidate SNPs driven by known marginal associations might be a good choice for detecting epistatic interactions in current GWAS.
Recently, the Population Architecture using Genomics and Epidemiology Study  found only ∼50% of the 125 reported associations with lipid levels  to replicate in three non-European cohorts. Due to the quadratic decrease in the interaction effect of tagged markers, gene-gene interactions are even less likely to replicate in diverse populations. Leveraging signals from proximate linked SNPs, our adaptive locus-based method successfully validated gene-gene interactions between HMGCR and LIPC in four additional, independent cohorts, including two of non-European ancestry. Although the most significant interaction in each cohort involves different SNPs, they are proximate across the cohorts, with stronger LD and smaller distances amongst the three EA cohorts and weaker LD and larger distances between them and the HA and AA cohorts (Figure S2 and Table 1). The differences in distance and LD between ethnicities could be due to differences in genetic background, demographic history, and natural selection, even if the different SNP pairs capture the same underlying causal interaction. However, the interaction shows similar patterns among some, but not all cohorts (Figure S6 and Table S1), while the different SNPs around HMGCR are in strong LD, and those around LIPC show weak LD (Figure S2). These results suggest that the five SNP pairs either capture separate causal interactions or are only in weak LD with the same pair of interacting, unobserved variants.
Another possibility is that the interaction is between relatively rare causal variants: Much like rare causal variants can lead to multiple independent associations of common variants, dubbed "synthetic associations" , an interaction between two rare causal variants can produce an even larger number of independent "synthetic interactions", which can in principle explain almost-independent, yet proximate gene-gene interactions. Another possibility is that the underlying interaction is more complex and involves more than a pair of SNPs. In that case, in our analysis of pairs of SNPs, each pair might tag only certain aspects of the underlying interaction.
Both HMGCR and LIPC are involved in metabolism of lipids and lipoproteins. HMGCR, which has been associated with TC and LDL-C , regulates the rate of cholesterol synthesis via a negative feedback mechanism mediated by sterols and non-sterol metabolites . LIPC encodes hepatic lipase which is an important enzyme in HDL metabolism  and has been previously associated with HDL-C levels . The interaction between variants in these genes as discovered in this study can be possibly explained by an indirect interaction between cholesterol synthesis and the metabolism of LDL and HDL particles. HGMCR is the rate-controlling enzyme in the mevalonate pathway for cholesterol synthesis . Much of this cholesterol will form cholesteryl esters that will be packaged into various lipoproteins including LDL, HDL, and TG-rich lipoproteins. There are a number of known lipoprotein interactions that result in the flow of cholesterol in the form of cholesteryl esters from LDL and VLDL to HDL-C . This cholesterol is later processed with the HDL particle by either reabsorbing into the liver or excretion in the urine .
The rs2043085 SNP in the LIPC gene region, where our strongest signal has been observed in fine mapping in the discovery panel, was recently associated with elevated HDL-C in an additional cohort of individuals with mixed dyslipidemia . Increased HDL-C may be related to modest inhibition of TG hydrolysis in the HDL particle by hepatic lipase, slowing its excretion in the urine along with its cholesterol content. Because HMGCR has a major effect on cholesterol synthesis, it will also indirectly affect the cholesterol content in the HDL particle through its interaction with LDL and TG-rich particles. In addition, LIPC has been reported to exhibit gene-gene interaction with other genes associated with lipid traits , , and HMGCR has been reported to interact with ABCA1 in Alzheimer's disease risk . While these results increase the plausibility of a biological interaction between these two genes, we note that a statistical gene-gene interaction does not necessarily entail an underlying epistatic interaction in the biological sense . We also note that while we refer to the interaction as being between HMGCR and LIPC, these two genes are implicated only by genomic proximity, and we presented no direct evidence that these genes are the interacting functional units.
We conclude that a focused study with higher enrichment of putative signals might have improved power to detect gene-gene interactions underlying complex diseases or traits. By focusing only on SNPs that were previously associated with the studied trait, HDL-C level, or any of a handful of related traits (other lipid levels), we successfully identified an interaction between SNPs in or near HMGCR and SNPs upstream of LIPC in European American samples. By using a locus-wide validation procedure to overcome the quadratic impact of partial SNP tagging on the observed interaction effect size, we further replicated the interaction between these loci in additional European American samples, as well as in African American and Hispanic American samples.
All work done in this paper was approved by local institutional review boards or equivalent committees.
Atherosclerosis Risk in Communities (ARIC) Study.
The ARIC Study is a multi-center prospective investigation of atherosclerotic disease . EA and AA individuals aged 45–64 years at baseline were recruited from four communities: Forsyth County, North Carolina; Jackson, Mississippi; suburban areas of Minneapolis, Minnesota; and Washington County, Maryland. A total of 15,792 individuals participated in the baseline examination in 1987–1989, with three triennial follow-up examinations. We conducted a discovery interaction analysis using 9,713 EAs from this study, for whom phenotype and genotype data were available, and considered 3,207 AAs from this study as one of the replication cohorts.
The FHS is a three generational prospective cohort . 5,209 EAs were initially recruited in 1948 in Framingham, Massachusetts to evaluate cardiovascular disease risk factors. The second generation cohort (5,124 offspring of the original cohort) was recruited between 1971 and 1975, and lipid measurements were obtained multiple times. The third generation cohort (4,095 grandchildren of the original cohort) was collected between 2002 and 2005, and one lipid measurement was obtained. We considered as one of the replication cohorts a sample of 6,575 individuals from FHS for whom genotypes and lipid measurements were available, while accounting for their relatedness (see Population stratification and relatedness).
Multi-Ethnic Study of Atherosclerosis (MESA).
MESA is a prospective cohort study of 8,296 men and women aged 45–84 years recruited from 6 US communities (Baltimore, MD; Chicago, IL; Forsyth County, NC; Los Angeles County, CA; northern Manhattan, NY; and St. Paul, MN) . MESA was designed to determine the characteristics of subclinical cardiovascular disease and its progression, hence adults were considered and individuals with symptoms or history of medical or surgical treatment for cardiovascular disease were excluded. Participants were enrolled between July 2000 and August 2002 and self-reported their race/ethnicity group as Caucasian or white, African American or black, Spanish/Hispanic/Latino, or Chinese American. We attempted replication in three cohorts from the first three of these ethnicities, with 2,685, 2,588, and 2,174 individuals, respectively, for which genotypes and lipid measurements were available. We discarded 777 Chinese Americans from our replication analysis because of the small sample size.
We obtained Affymetrix 6.0 SNP array genotyping of samples from the ARIC study . We obtained Affymetrix 6.0 SNP array genotyping of MESA samples and Affymetrix 500 K SNP array genotyping of FHS samples from the database of Genotypes and Phenotypes (dbGaP; MESA SHARe, downloaded in May 2011 and Framingham Cohort, downloaded in April 2010) , . Genotype quality control (QC) steps included the exclusion of individuals with >10% missing data, and the exclusion of SNPs with call rates <90%, minor allele frequencies (MAF)≤1%, or Hardy-Weinberg Equilibrium (HWE) test with P<10−6. For the pairwise interaction test of each pair of SNPs we also required (i) sample size of each of the nine possible genotype-by-genotype combinations of the two SNPs being >20 in the discovery analysis and >10 in the validation analysis; and (ii) LD of r2<0.1 between the two SNPs between which interaction is tested. The first requirement is a generalization of the MAF requirement in single-marker analysis.
We used IMPUTE2  with HapMap3  and 1000 Genomes  reference haplotypes to impute untyped SNPs, resulting in the same set of SNPs across cohorts. We did not impute untyped SNPs in MESA HA samples since no appropriate reference panel was available at the time we conducted our analysis. We discarded imputed SNPs with information score less than 0.6. Following this QC stage, we considered the genotype with the maximum posterior probability, and discarded SNPs for which this probability is <0.8.
We considered four lipid measurements: TC, LDL-C, TG, and HDL-C. All measurements were done in the fasting state using standard enzymatic methods. In all three studies, each lipid level is measured at multiple time points and we considered the average level per individual of each lipid in all our analyses. We applied a log transformation to TG levels to normalize them in face of the skewness in the original distribution, as previously proposed . We excluded individuals known to be taking lipid-lowering medications.
Gender, age, age squared, and body mass index (BMI) were included as covariates in all analyses, similarly to GWAS based on these phenotypes , . We averaged values for age and BMI whenever multiple measurements were available, in line with the averaging of lipid levels . The average age was also squared and included as a covariate. Plate is also included as a covariate in the ARIC data since it is correlated with some of the lipid levels ("plate effect"; data not shown).
Principal component (PC) analysis was conducted using EIGENSOFT . Top 10 PCs were included in the analysis as covariates to account for potential population stratification in each of the ARIC and MESA cohorts. For FHS, we applied a mixed model method to account for relatedness by performing the interaction test on the residuals after removing familial structure , .
As described in , , we tested for interaction between two SNPs on a quantitative trait as follows. Assume Y is the trait of interest and Gi is the genotype of SNP i (i = 1, 2). Gi denotes the number of copies of the reference allele (0, 1, or 2). Two indicator variables xi and zi are defined for each SNP as Two linear models were fitted. The first, model (1), allows for additive and dominance effects at each SNP, but is strictly additive (i.e. no interaction) over the two SNPs. The second, model (2), allows for the four possible forms of genotype-by-genotype interaction (additive×additive, additive×dominance, dominance×additive, and dominance×dominance) , as follows: (1) (2)Here, β0 denotes a vector of intercept and covariates as described above. ai and di denote the additive and dominance effects of SNP i, and iaa, iad, ida, and idd are the four interaction effects between the two SNPs.
We tested for the existence of an epistatic interaction of any type by an F-test with four degrees of freedom between models (1) and (2) . The F-test with four degrees of freedom tends to be more powerful when little is known about the underlying epistatic effect in terms of the possible directions of the deviation from independence of the additive effects. This test is similar to the "–epistasis" option in PLINK , except that only additive effects and their interaction are considered in PLINK, and an F-test with one degree of freedom is hence applied. We also considered a test for "physiological epistasis"  under the same model and obtained very similar results (data not shown). Throughout the results, we report P values following a conservative Bonferroni correction. To compare the effects of the different SNP pairs detected in our discovery and validation analyses, we also estimated and tested the four interaction terms in model (2) for each pair of SNPs from different cohorts using a t-test.
Although we only focus on pairwise interaction analysis, the total number of potential pairwise interaction tests across 2.5 million SNPs is still huge, about 3 trillion tests. Due to the huge reduction in power entailed by multiple-testing correction for such a large number of tests, it is crucial to restrict the number of tests a priori. We aimed to enrich possible interaction signals in the limited number of tests we considered through the following three strategies.
In total 95 loci were recently associated with TC, HDL-C, LDL-C, or TG in a GWAS meta-analysis . We exhaustively tested the pairwise interactions among all the significantly (P<5×10−8) associated SNPs in these 95 loci, for a total of 125 significant SNPs. For this approach, the total number of interaction tests is 7,750 for each trait.
We assembled over 3000 high-confidence human PPIs and for each exhaustively tested the pairwise interactions between each SNP in the first gene and each SNP in the second gene. For n1 and n2 being the numbers of SNPs in the first and second gene, respectively, the number of interaction tests is n1×n2 for this PPI. Repeating this process for the 3000 PPIs, we tested a total of ∼6.2 million SNP-SNP interactions. We obtained gene information (hg18) from UCSC genome browser (http://genome.ucsc.edu/) to map SNPs to genes, considering for each gene all SNPs from 5 kb upstream to 5 kb downstream of the gene. These PPIs, however, have no specific implications to lipid levels as they are not context-based, and were collected under different physiological conditions.
We tested for gene enrichment of the 96 genes reported in ref. 6 as associated with lipid levels. As expected, the metabolism of lipids and lipoproteins pathway (www.reactome.org) is the most significant pathway (P<10−20). There are a total of 228 genes in this pathway, to which we mapped a total of 12,716 SNPs similarly to above. We tested for pairwise interactions between each pair of these 12,716 SNPs, yielding a total of ∼27 million tests.
Liu et al.  developed a local validation strategy and validated a few interactions affecting common human diseases. This strategy attempts to replicate the interaction between two loci rather than the interaction between the original pair of SNPs. To further improve power, we extended this local validation strategy to an adaptive locus-based validation procedure: For a detected interaction between SNP A and SNP B in the discovery panel we followed three stages in each of the validation panels. (i) First, test for interaction between SNP A and SNP B; (ii) Second, if the interaction in (i) is not significant by itself, test for interaction between A and each SNP<200 kb away from B, and similarly between B and each SNP surrounding A; (iii) Last, if no test in the second stage is significant following multiple-hypothesis correction, test for interaction between each SNP<100 kb away from A and each SNP<100 kb away from B. Assuming n1 and n2 SNPs in the locus surrounding A and B, respectively, the number of interaction tests performed is 1, n1+n2, and n1×n2 in the three stages, respectively, with n1 and n2 in stage (iii) being smaller than those in stage (ii) due to considering only 100 kb. To maintain power in light of multiple-testing correction, the validation process proceeds sequentially and stops once we find significant results after multiple-testing correction. The interaction between rs3846662 and rs2043085 on HDL-C was successfully validated in stage (ii) for MESA EA samples and in stage (iii) for the MESA HA, FHS EA, ARIC AA cohorts. It did not validate significantly after multiple-testing correction in any of the three stages in the MESA AA samples. We used the same procedure as in step (iii) for fine mapping within the discovery panel.
Quantile–quantile (QQ) plots for gene–gene interaction tests of LDL-C in ARIC EA cohort. (A) Discovery analysis (reproduced from Figure 1a in main text); (B) Fine mapping by testing all possible pairs of SNPs in the 100 kb surrounding each of rs2853928 and rs1993453.
Linkage disequilibrium in data from the 1000 Genomes Project of all SNPs involving in significant interactions underlying HDL-C in any of the cohorts (i.e. all SNPs from Table 1). (A) and (C) are for SNPs in the locus on chromosome 5 in the CEU (European American) and YRI (West African) 1000 Genomes samples, respectively; similarly, (B) and (D) for SNPs on the interacting locus on chromosome 15. These figures were produced by Haploview . The numbers shown are R-square values with zeroes and dots omitted.
QQ plots for gene–gene interaction tests in ARIC EA cohort based on the PPI-based strategy for considering pairs of SNPs. (A) TC; (B) LDL-C; (C) TG; (D) HDL-C.
QQ plots for gene–gene interaction tests in ARIC EA cohort based on the pathway-based strategy for considering pairs of SNPs. (A) TC; (B) LDL-C; (C) TG; (D) HDL-C. We found a deviation in the QQ plot of the P values for interactions underlying TC levels and the strongest interaction signal appears between rs4804546 and rs914196, though it is not significant following correction for the ∼27 million tests (Pc = 0.14). The two genes from the pathway of metabolism of lipids and lipoproteins associated with this interaction are CARM1 and AGPAT3. AGPAT3 was previously found to be associated with the level of phospholipid , while CARM1 has not been associated to the best of our knowledge with any lipid levels.
QQ plots for stage (iii) of the adaptive locus-based validation tests in MESA African American cohort, which show no significant results.
Effect sizes on HDL-C level of the six SNP pairs from Table 1 in main text in the respective cohorts. The ARIC EA fine mapping panel is reproduced from Figure 2B in main text.
Effect estimates for significant interactions between SNPs surrounding HMGCR and LIPC on HDL-C in EA, AA, and HA cohorts.
We thank Haiyuan Yu and Jishnu Das for sharing with us their data on protein–protein interactions. We also thank the reviewers for their comments.
Conceived and designed the experiments: LM AGC AK. Performed the experiments: LM. Analyzed the data: LM. Contributed reagents/materials/analysis tools: AK AB EB CFS. Wrote the paper: LM AGC AK.
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For more information about Resort accomodations, real estate, vacation packages, and activities, please visit the official Sea Pines Resort web page or call 1-866-561-8802.
The Sea Pines Racquet Club is open to the general public (reserve and walk on rates do apply for court time). Already maintained and ready to play courts are free of charge to play on after hours which are currently 8:00AM - 5:00PM EST. Starting in March, the pro shop hours will be 7:45AM - 5:30PM EST.
Shirts and proper clay court tennis shoes are required - NO RUNNING SHOES ALLOWED.
Why no Running Shoes on the Clay?
- no lateral stability. Very poor support for quick cuts and stop and go type movements. You will likely roll your ankle.
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Belgium's Philippe Gilbert on Saturday picked up a second Tour of Lombardy crown as the one-day specialist landed the final classic race of the season.
The Omega Pharma rider made it back to back wins after he edged out Italian Michele Scarponi by a dozen seconds after the gruelling 260 kilometre event which required seven hours in the saddle in windy, wet conditions.
a minute off the pace with Dane Jakob Fuglsang leading in the next group of finishers ahead of Italian Tour of Spain winner Vincenzo Nibali and Spanish Olympic champion Samuel Sanchez.
Monaco-based Gilbert made it two wins in three days as Thursday he carried off the Tour of Piedmont, also for the second straight year, compensation in part for missing out on his main objective of the season, the world championships in Australia two weeks ago.
Saturday he strove from the outset to impose his superiority, explaining that "I decided I'd go out there and put the pressure on.".
And victory was assured once he had negotiated the tough 9.5km, 6.6 percent gradient Sormano climb at the 41km to go mark.
He went on to clinch victory after a 20km flat stretch on the shores of Lake Como, leading into the final climb at San Fermo della Battagila.
"I said the descent" – a spectacular one at that into Como – "would be even tougher than the (San Fermo) climb," said Gilbert, who had clearly done his homework.
Looking back to his Australian disappointment, Gilbert, who revealed that he had made winning the Liege-Bastogne-Liege race his chief 2011 ambition, said he had now digested that experience.
"When you give everything you can't be disappointed for too long," he insisted – expressing similar sentiments over an off colour showing in the Paris-Tour last week.
Liquigas all-rounder Nibali, who almost came to grief in sliding at one point on the Sormano climb, had hoped to give home fans their first classic win of the season – but instead this has been a barren vintage for the Italians.
Sanchez for his part had finished on the podium three times since 2006 but was just unable to pull off a repeat in the 104th edition of a race won by such luminaries as Fausto Coppi, Eddy Merckx, Bernard Hinault and Sean Kelly.


Anne Cochran continues to enjoy her soulful reunion with collaborator and producer Abe LaMarca. Coming off the smooth jazz radio hit, "Rise and Shine", she goes "Deeper" into her vocal and creative vocabulary and shows a more intense side of her style that her fans will love.
Anne will hit the road, again, on Jim Brickman's �Share The Love Tour� with stops in GA, IL, MI, PA, and TX.
Romantic Love Song Duets sung by powerhouse vocalists, Anne Cochran, ("After All These Years" ) and Super Bowl Champion Benjamin Utecht, who share their refreshing renditions of these 12 all-time favorites.
Anne will be singing with Jim Brickman and The Atlanta Symphony before their Valentine dates in Batavia, IL, Kalamazoo, MI, Pittsburgh, Pa, and York, PA.
See tour dates for details!
Thank you for setting a perfect example of how women can achieve ALL the desires in their heart.
The show was ABSOLUTELY spectacular! We loved every minute of it!
Ding dong, the bells did chime!


text:
Teen South Bank dad locked up after assault
A TEENAGE dad-of-two has been locked up after assaulting his mum and his ex-girlfriend in a night of violence and lurid threats.
Ben Taylor left his home shouting and screaming down the phone at his sister's partner, Ashley Readshaw.
He threatened to smash Mr Readshaw's face in and said: "You'd better say goodbye to your kids. I'm going to chop your head off."
His sister Natalie took the phone and tried to reason with her 18-year-old brother, but he threatened to smash her house up.
He said: "I'm going to burn your house down with the kids in it." This was the final straw and his sister called 999, prosecutor Sue Jacobs told Teesside Crown Court yesterday.
But Taylor then went to his mother's home on nearby Strauss Road, South Bank, on the evening of September 2 last year.
In the garden he attacked Lucy Thompson, from whom he'd just split up. He punched her to the nose and, as she tried to defend herself, punched the back of her head three times.
He pulled her to the ground, taking out a large clump of her hair, and tried to kick her to the face but missed, the court heard.
His mother Andrea came out, dragged her son off Ms Thompson and heard him threatening to chop up his ex. Taylor left but soon ran back waving a small Samurai sword.
He pinned his scared mother to the front door holding her neck and saying: "Don't let me have another charge against you."
Police found him in the loft of his home, where he lived with his uncle and gran.
Taylor, of Redcar Road East, South Bank, denied assault causing actual bodily harm, assault by beating and having an offensive weapon.
A jury convicted him. He had previous convictions for violence, including assaults on his mum and other family.
Andrew Teate, defending, said Taylor still denied some of the crimes. He said Taylor had difficulties including with his mental ability, education, drink, drugs and attention deficit hyperactivity disorder.
The two victims had repeatedly visited him in custody since the incidents.
He has mended his relationship with his mum. He sought help with courses inside and wanted to better himself, lead a lawful life, work in the building trade and be a good dad to his two children.
Judge Tony Briggs, inset, said the attack on Taylor's partner was nasty and sustained, the Samurai sword incident terrifying. He told Taylor: "Custody is inevitable in this case." He sentenced Taylor to 15 months' detention.


4th Armoured Division Launches Ground Attack Inside Daraa City (Map, Videos) 4.68 out of 5 based on 25 ratings. 25 user reviews.
On June 30, the Syrian Arab Army (SAA) 4th Armoured Division, backed by the Russian Aerospace Forces, launched a large attack on the positions of the US-backed Free Syrian Army (FSA) in the key district of al-Manishiyah in the city of Daraa. The FSA manged to capture most of the district after a successful attack back in 2017.
A source in the 4th Division told SouthFront that the SAA has captured a large area in al-Manishiyah so far. According to the source, the SAA is facing very little resistance from the remaining fighters of the FSA inside the city.
A day earlier, the 4th Armoured Division captured the hill of Zumaytiyah, thus imposed its fire control of the FSA's main supply route between the western and eastern countrysides of Daraa.
From it side, the FSA operations room in southern Syria known as "Tawhid al-Sufuf" reported that FSA fighters destroyed two battle tanks of the SAA with TOW anti-tank guided missiles (ATGMs) during clashes west of the city of Daraa. The joint operation room also announced that a soldier of the SAA was captured.
The SAA will likely step up its military operations around and inside the city of Daraa once the eastern Daraa countryside is secured. Elite units, including the Tiger Forces, will join the battle there, which will increase the pressure on the FSA.
Good to very good. I hope they dont lose their momentum and clear the scum out of their land, soon.
"Their" land? It is a Syrian land.
read again what I wrote and understand it as I say it not the way you transl;ate it in your mind.
It is Syrian land and the Zionist backed rebels will be exterminated.
The land is not of the scum or the trash, so, = to clear their land of the trash, or = to clear their land of the scum.
Not "rebels" but paid mercenaries.
That is what he said / inferred.
I'm amazed with your cool today for the kids, my spartan friend.
Ignore.I, like anyone with knowledge understood.
The great strength of the internet for us all are the different nationalities we can converse with every minute of every day. In previous conflicts this was not possible.
The use of words is a difficult path to follow at times but any misunderstanding can be debated and our new worldwide friends opinions give us hope in the knowledge that we are not alone.
They also give us a perspective of 'news' as broadcast in far off lands.
Yes, their land, because they are Syrians.They have help from the outside, but that does not change the fact that they are Syrians, they fight for Syria, they fight for their land!
Michal, don't bother Promitheas, bother yourself, because you deserve it. If not, you haven't passed in the test, and you can't go anywhere without risk, just like a little kid.
Damn right it is. The Golan to the Syrians.
That is exactly what he said. THE SAA ARE CLEARING THEIR LAND.
With a little help hand from their friends.
"almost very good" ??. I reckon we will have lots of good news for months.
Bravo Syria, Russia, Iran and dont forget the Palestinians.
Will UK back street workshop's be turning out weapons and munitions as they were easily in Syria ?
only the second vid shows a hit. in the first the missile hits the ground short of the target. but who cares.
Please just let me vent. It really p1sses me when we receive a WAR report and all we see "non-stop", is a tank or armed vehicle in the desert being blown up…… Christ the Hollywood films are going to be crap.
Yes it is noticeable that often these videos are cut short so we do not get to see the after effects due to clouds of dust.
when they cut them, it's because the hit didn't attain the intended results. Ex. – the first vid. The atgm is clearly seen hitting the ground and not the tank.
Tough luck for the ragheaded propagandists, next time the US should provide them with TOWs with a non-visible IR light.
btw, the failure rate of this sort of equipment is astounding, idk if it's due to jihadists being untrained of if they received discarded or expired equipment but the percentage of atgms falling in front of their targets is way beyond acceptable.
I find it difficult to identify the vehicles in these videos, but the second one did not look like a tank. May be others have better analysis skills than me and can identify what is shown.
In second video, it was a car. See the back of the car (SUV), with a spare wheel on the rear door.
Thanks. Yes it did not look right.
the fsa little resistance!! no!!
Antoun, write on french or on english— brrrrrr!
Russian planes must be striking from Astral plane as they have supposedly been evacuated.
"evacuate" is the word i'd use about Syria doing it all over the heads of zio-scum.
Russia did not sent home ALL their planes.
SAA will soon get rid of these terrorists, and I hope Russia aerospace force continue given its strong, fast, and effective support and protection to ground troops.
Humm, it is hard to identify those claimed tanks. These are not convinced videos about tanks, maybe other things.
Obama's legacy of arming jihadis in Syria (with TOW missiles), and murdering Syrian soldiers continue to this day.
Urban fighting is Hell when the foe is determined, like Daesh in Mosul and Raqqa. These Green Daesh Orcs are on their last legs though.
First hit ugly miss, hit the ground.
Second hit, looks like it hitted some straw pile.


text:
The 420-acre Washington County Convention Center complex can accommodate a wide variety of meetings and events. The complex encompasses not only the popular 25,000 square-foot Exhibit Hall with a 4200-square-foot four-way convertible meeting room, but an Expo Center, Outdoor Arena, Stock Car Racing Track, and Legion Baseball Field
The 38,400 -square-foot enclosed Exposition Building has been the scene of livestock and other agricultural exhibits and circuses and can accommodate a crowd of 2500 attendees. Stockcar races use the Convention Center's 500- x 1000-foot track. The bleachers will hold 3500 enthusiasts, with the convenience of four women's restrooms and three men's restrooms. The complex also features Legion Field, featuring four Dixie Baseball fields with bleachers that will seat 500 fans each.
Convention Center Features
The most dominating feature of the Convention Center Complex is its 25,000 square-foot indoor Exhibit Hall, which will seat an audience of 3500 for a concert or 100 tables for a banquet. It can be transformed into an athletic event with a portable hardwood floor and bleacher seating for 500.
Concerts given at the arena take advantage of its 1500-square foot stage, audio system (four microphone hook-ups; cordless microphone, Samsung Cassette Deck, and CD changer), and lighting system (spotlights and stage lights with dimmer switches).
Organizers of smaller conferences can use the convertible room, with a total capacity of 4200 square feet that can be partitioned into four smaller rooms.
The Convention Center also boasts an industrial kitchen, qualifying the Center as a Red Cross Emergency Shelter. The kitchen features three industrial-sized sinks, two ovens, six-burner commercial stove, two freezers, two refrigerators, two deep-fat fryers, stove grill and warmer, commercial ice maker, microwave oven, and two tables. Also on the premises are eight bathrooms.
Emphasizing its flexibility, the Washington County Convention Center has been the venue for the following events, some of which take place annually:
Delta Ag Expo
Junior Auxiliary Ball
Local High School Commencement exercises
Mississippi Delta Community College Commencements
Red Cross Dinner Theater
Wildlife Seminar & Tasting Buffet
Community and Private Parties and Receptions
Fashion shows, using a runway
Red Cross Emergency Shelter/Crisis Center
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Phone the County Convention Center office at 662-332-0488 to reserve spots at other venues in Washington County, which include:
Race Track & Cars
Paul Love Park
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Floorplans (pdf file)


October 15, 2014 by Elizabeth Girard, MS, L.Ac.
I was diagnosed at age 4 with severe asthma. Unfortunately for me as I grew older my asthma grew worse. I was often hospitalized for not being able to breathe. It's one of the worse feelings in the world not knowing if you are going to be able to breathe your next breath. I carried my fast acting inhaler with me everywhere and still do. I hate the feeling of having an asthma attack. Now that I have a child I hate it even more. It makes me feel like I can't care for my daughter as well as I should because I just can't breathe. I can't imagine being the parent of an asthmatic. The fear of not knowing if your child is going to be able to breathe is unimaginable for me. There was a point that I went over 3 weeks without an asthma attack which is still a miracle for me. That was my first real experience with acupuncture and Chinese medicine.
If you know me you know how passionate I am about what I do for work. I am an acupuncturist and Chinese herbalist. Very early in my career I realized that this was my true life purpose to be able to help people. To help people in a very real way. A natural way that works with their body, correcting what is wrong and supplementing what is weak. I not only have experienced myself the immediate change in acute lung symptoms of asthma but long term changes as well. I have seen allergies almost disappear and patients with COPD living healthy lives. According to research provided by the NIH (National Institute of Health) Acupuncture can reduce shortness of breath, chest tightness, cough and wheezing in patients with chronic obstructed pulmonary disorder. Acupuncture helps to relax the chest muscles and dilate the bronchioles allowing more air flow. Chinese medicine practitioners use acupuncture to "supplement" or "tonify" the lungs. It is believed that certain acupuncture points are needled in ordered to boost the "qi" (energy of the lungs). By supplementing the energy of lungs you can treat and prevent diseases. Chinese herbs and acupuncture together provides the most relief. There are certain formulas that treat shortness of breath, colds, sinus infections, bronchitis and many other conditions. Just like acupuncture there are also formulas that help to strengthen your immune system and lung "qi". Adults and children of all ages can benefit from Chinese medicine.
If you or your child suffer from asthma or other chronic pulmonary conditions, please feel free to contact me.


text:
Paul Holt ready for ring return this weekend
Boxen247.com Boxing News	BCB Promotions, Paul Holt	0
Paul Holt is ready to pour everything that he has left into the rest of his boxing career as he prepares for a ring return.
His route back begins on home turf at the H Suite in Edgbaston, Birmingham, during a weekend double-header of shows staged by BCB Promotions, set for October 16 and 17.
Holt features on Saturday night, where he will be in pro action for the 18th time, with a chequered record of 10 wins and seven losses to look back on.
The second-generation fighter, as son of former pro Mark Holt, has adopted a fearless approach ever since he first laced on a pair of gloves.
He racked up 48 amateur bouts for Nechells Green Boxing Club, with 26 victories, before turning pro in late 2013, where he would match his dad's achievements.
Holt Jnr, a fellow southpaw, followed in his footsteps with Midlands title glory in 2016, halting Louis Fielding by sixth round stoppage.
That was in the super featherweight division, after a crack at the featherweight crown his father once held proved unsuccessful, against Bobby Jenkinson, a year earlier.
He relinquished the strap and was defeated challenging for it again, going down in three to Lyon Woodstock, and has only won once in seven outings since.
That success did come over another Midlands title contender, Luke Jones, and all of those setbacks came at the hands of highly-rated opponents, who were undefeated.
Holt, who has just turned 31, insists he's not content with just making up the numbers, with 2021 so far containing TKO losses to Louie Lynn and Sean Gerard Duffy.
He said: "Being a former Midlands champion does give you a bit of credibility, but I don't want to be someone who is going out there and can't hack the pace anymore.
"Coming into this year, I knew the only way to get fights was to box on the TV, against unbeaten prospects. I've been in twice, with two top lads. I'm just trying to keep busy.
"I got stopped, in both of them, but I felt like I could have continued in the first one. I'd come through a tough spell, early on, and I was determined to see the final bell.
"The second time, fair enough. He got me with a good body shot and I can tell you that it hurt! It was a great punch, so you have to respect that.
"I've lost a few as a pro, but I've never backed down from anyone. You only have to look at my record to see that. I was the same as an amateur.
"I really want to get back in the mix for the Midlands title. It doesn't seem like five years ago when I won it. The buzz I got from that night was unreal, I still can't even describe it.
"I never lost the title, it just sort of got away from me, which was a bit of a wounder and left me feeling pretty low. I'd worked so hard to get there and I'd love to do it all again.
"Originally, I was supposed to defend it against Sam Bowen (before he became the British champion), but I needed more notice than they were prepared to give me.
"The belt was vacant when me and Lyon Woodstock boxed for it. I was doing alright, then he caught me with a long-range hook and I felt my ear pop. Maybe I've lost my way since then.
"I'm 31 now, so I reckon I've got another two to three years left in boxing. I've just got to go for it, no messing about, and leave everything in the ring."
Tickets for the Birmingham bills are available now, priced at £40 standard or £75 VIP ringside with buffet per day, directly from the boxers or by visiting myfighttickets.com.
Subscribe to our new YouTube Channel (latest video below) with the latest boxing news and results, gossip and information from around the world. Just click the image below or any of the images for all our social media:
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Probellum sign Lewis Ritson, Darius Fulghum & Sam Jones joins team	Nonito Donaire signs with Probellum


text:
Home News Va. Beach manufacturing facility sells for $21.7M
Va. Beach manufacturing facility sells for $21.7M
Industrial building fully leased to World Distribution Services
Published November 16, 2020 by Sydney Lake
1537 Air Rail Drive. Photo courtesy Cushman & Wakefield | Thalhimer Capital Markets Group
A 320,000-square-foot industrial building in Virginia Beach sold for nearly $21.7 million, Cushman & Wakefield | Thalhimer Capital Markets Group announced late last week.
The property located at 1537 Air Rail Drive is fully leased to World Distribution Services, an affiliate of The World Group, which offers logistics services through more than 10 warehousing locations in the U.S. The property, which sits on approximately 18 acres, is located 15 miles from the Port of Virginia.
Richmond-based Lingerfelt CommonWealth Partners sold the property to Manchester Capital Management LLC, a Charlottesville-based wealth management and real estate advisory firm, in a transaction that closed on Nov. 12, according to Lingerfelt.
Lingerfelt purchased the building in December 2018 for $8 million and invested $7 million in renovations, including interior office space renovations, warehouse flooring repair, electrical upgrades, adding exterior tailgate doors and repairing the 300,000-gallon water tank, according to Lingerfelt.
Cushman & Wakefield | Thalhimer's Capital Markets Group represented Lingerfelt in the transaction. Senior Vice President Eric Robison led the brokerage team that handled the transaction.
"Single-tenant industrial assets remain highly sought after by investors seeking yield in buildings leased to strong, high-growth companies like World Distribution Services," Robison said in a statement. "In addition to the strength of the tenant and long-lease term, the location of the property and health of the industrial market in Hampton Roads made this an attractive investment for the buyer."


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La Batalla del Campo de Krbava (croata: Bitka na Krbavskom polju o Krbavska bitka; húngaro: Korbávmezei csata; en turco Krbava Muharebesi) se libró entre el Imperio Otomano de Bayezid II y un ejército del Reino de Croacia, en aquel entonces en unión personal con el Reino de Hungría, el 9 de septiembre de 1493, en el campo de Krbava, en la región de Lika en la moderna Croacia.

Las fuerzas otomanas estaban bajo el mando de Hadım Yakup Pasha, sanjak-bey de los sanjacados de Bosnia. En cambio, el ejército croata estaba dirigido por Emerik Derenčin, ban de Croacia, que sirvió bajo el rey  Vladislaus II Jagiello.

A principios del verano de 1493, los turcos emprendieron una incursión a través de Croacia en Carniola y Estiria. Alrededor de esa misma época, se habían producido enfrentamientos en Croacia entre la Casa de Frankopan y el ban croata, pero las noticias de la incursión otomana los obligaron a hacer las paces. Los nobles croatas reunieron un gran ejército e interceptaron a las fuerzas otomanas que regresaban al sanjacado de Bosnia. Las malas tácticas y la elección de una batalla abierta con la caballería otomana más experimentada, resultaron en una derrota total para el ejército croata.

No hubo ganancias territoriales inmediatas para el Imperio otomano, pero en las décadas siguientes se expandió gradualmente hacia el sur de Croacia.

Antecedentes

Situación previa

Tras la caída del Reino de Bosnia en manos otomanas en 1463, los turcos se expandieron rápidamente hacia el oeste, amenazando las partes sur y central del Reino de Croacia.

Desde entonces, sus incursiones se hicieron más frecuentes, siendo llevadas a cabo por la akıncı, la caballería ligera irregular. Cabalgaban por el territorio cristiano y saqueaban el campo durante la primavera y el verano, evitando las ciudades fronterizas fortificadas y los conflictos militares directos. De esta forma, sus continuas incursiones obligaron a la población local a abandonar sus tierras, dejando los castillos fronterizos sin suministros. Una de estas comenzó en septiembre de 1491, con la caballería turca cruzando el río Kupa y llegando a Carniola. A su regreso, fueron interceptados cerca de Udbina por el ejército del ban croata Ladislav de Egervár y el conde Bernardin Frankopan, acabando derrotados en la batalla de Vrpile. Esta derrota obligó a los otomanos a detener sus ataques durante 1492. Solo después de que Hadım Yakup Pasha se convirtiera en el sanjak-bey del sanjacado de Bosnia, reanudaron sus incursiones.

Preparativos
En el verano de 1493, Hadım Yakup Pasha levantó un ejército de 8000 jinetes ligeros o akıncı y atacó a Jajce, pero no logró capturar su fortaleza. Desde allí giró hacia el noroeste y entró en Carniola y Estiria, saqueando la campiña. Ese mismo año, estalló una guerra entre el recién nombrado ban de Croacia, Emerik Derenčin (húngaro: Imre Derencsényi) y los Frankopan, aliados con Karlo Kurjaković (de la familia Gusić), por el control de Senj y varias otras ciudades. A mediados de julio, los condes Bernardin Frankopan e Iván VIII Anž Frankopan, estaban ganando la guerra y estaban sitiando Senj. El asedio se levantó después de que un ejército de 4000 jinetes y 2000 infantes liderados por Derenčin fue enviado para ayudar a los defensores, y el ejército de los Frankopan se retiró a Sokolac. Mientras tanto, los Frankopan fueron acusados de cooperar con los otomanos, aunque sus propiedades también fueron devastadas. Las noticias del ejército otomano entrante los obligaron a hacer la paz.

A su regreso, los turcos saquearon a los Modruš, en el norte de Lika, entonces propiedad de la familia noble de los Frankopan. Los Frankopan y el ban Derenčin querían interceptar a los otomanos, y reunieron un ejército de alrededor de 3000 de caballería y 8000 de infantería de todas las partes de Croacia, sin embargo, una parte del ejército consistía en campesinos de los alrededores de Krbava. Por iniciativa de Derenčin, los comandantes croatas decidieron presentar una batalla abierta en el campo de Krbava, cerca de la ciudad de Udbina, en el centro de Croacia, aunque Iván Frankopan Cetinski argumentó que una emboscada en los cañones y barrancos sería una mejor opción.

Fuerzas enfrentadas
El historiador croata Krešimir Kužić estima que el ejército cristiano se componía de 11.600 soldados distribuidos en 9.200 infantes y 2.400 jinetes, aunque él mismo reconoce que son solo aproximaciones. El mal desempeño de sus fuerzas se debió a las malas formaciones, la falta de disciplina y experiencia y armas insuficientes, téngase en cuenta que se utilizaron principalmente espadas o lanzas y muy pocas armas de fuego, y aunque las fuentes turcas mencionan la captura de algunas, probablemente estaban reservadas a los oficiales. Según Borislav Grgin, el ejército croata se compondría de unos 5.000 hombres organizados en tres cuerpos de unos 1.500 soldados cada uno, destacando 2.000 venidos de Hungría y 2.400 de Eslavonia. Sin embargo, sólo la crónica de Tomašić da a entender que los cristianos estaban en inferioridad numérica, de ahí la cautela demostrada. Vjekoslav Klaić dice que eran 3000 jinetes y 8000 infantes.

Casi todos los historiadores estimarían a los otomanos en 8000 jinetes ligeros, excepto Klaić, que los eleva a 10 000.

Combate

Los otomanos entraron en el campo de Krbava a través del más bajo y estrecho paso de montaña local de Gorica, a diferencia de los dos años anteriores a través del paso de Vrpile donde sufrieron una gran derrota. Antes de la batalla, Hadım Yakup Pasha ordenó la ejecución de los cautivos cristianos cerca de Jelšani (actual Jošan) para que no pudieran ayudar a los croatas en medio del combate. Después de una reunión con los comandantes, envió una parte de su ejército, alrededor de 3000 caballeros, para ocultarse en un bosque cerca del campo de batalla.

Aunque el plan era luchar contra los turcos en las llanuras abiertas, el ejército croata se desplegó inicialmente en las laderas de la parte oriental de Krbava, cerca del pueblo de Visuć. Estaba formado para enfrentar al enemigo frontalmente en tres cuerpos: la derecha estaba compuesta por soldados de Eslavonia comandados por Franjo Berislavić, el centro estaba bajo el mando de Iván Frankopan Cetinski, y la izquierda estaba comandado por Nikola VI Frankopan y Bernardin Frankopan. La infantería y la caballería croatas se distribuyeron por igual entre estas secciones. El comandante principal era el ban Emerik Derenčin.

Su contraparte otomana también estaba organizada en tres cuerpos: el primero estaba comandado por Ismail Bey, sanjak-bey del sanjacado de Kruševac, y ocupaba el ala derecha; el segundo por Mehmed Bey del sanjacado de Üsküp (Skopje), ocupaba su izquierda; mientras, el cuerpo central estaba bajo el mando del propio Hadım Yakup Pasha. Ishak Bey Kraloğlu (nacido Segismundo de Bosnia), hijo del rey Tomás de Bosnia (muerto en 1461), también participó en la batalla del lado musulmán.

El plan turco era atraer a las fuerzas cristianas más al oeste, junto al bosque donde les habían tendido una emboscada. El ala derecha de Ismail hizo el primer movimiento, dirigiéndose hacia el flanco izquierdo croata. El ejército cristiano dejó las laderas y se precipitó hacia los musulmanes, comenzando una batalla en campo abierto. La lucha fue peleada cuerpo a cuerpo con espadas, sin usar arcos. Los otomanos fueron al principio empujados hacia atrás y comenzaron una retirada fingida, atrayendo a los croatas a una persecución que los llevó a la trampa.

Los 3000 jinetes otomanos situados en la zona boscosa del campo de Krbava cruzaron el río homónimo y atacaron la retaguardia enemiga. Entonces las principales fuerzas otomanas de Hadım Yakup Pasha, también esperando escondidas en los bosques, comenzaron un ataque frontal. Así, el ejército cristiano fue atacado por el frente, el flanco derecho y la retaguardia. El flanco izquierdo croata de Bernardin Frankopan no pudo soportar los ataques de la caballería ligera turca y comenzó a retirarse. Sin embargo, la mayoría de la infantería croata estaba rodeada y no podía moverse. Los croatas sufrieron una derrota total y sólo un pequeño número de hombres logró alcanzar la seguridad en la cercana ciudad fortificada de Udbina.

La batalla comenzó alrededor de las 09:00 horas y terminó por la tarde. El ban Derenčin fue capturado en la batalla y murió en cautiverio, mientras que su hijo Pavao y su hermano murieron en la batalla. Nikola VI Frankopan Tržački también fue capturado, pero fue rescatado y liberado. Entre los nobles croatas asesinados estaban Ivan Frankopan Cetinski, Petar II Zrinski, Juraj Vlatković, y el ban de Jajce, Mihajlo Pethkey. El conde Bernardin Frankopan y Franjo Berislavić se las arreglaron para sobrevivir al combate.

Consecuencias

Las cifras de soldados involucrados y bajas dadas en fuentes históricas más antiguas son en su mayoría exageradas. Como las noticias de la derrota se propagaron rápidamente, los informes escritos inmediatamente después de la batalla se hicieron bajo la impresión de la gran pérdida. Kužić estima que las bajas cristianas fueron de 9.600 muertos, 1.700 prisioneros y apenas 300 sobrevivientes que lograron escapar. Las musulmanas bordearían los 1.000 fallecidos.

Aunque la nobleza croata sufrió una dura derrota, descrita por los antiguos historiadores y cronistas como la «primera disolución del Reino de Croacia y allí pereció toda la nobleza», según el cronista Ivan Tomašić en el siglo XVI, el Imperio otomano no tuvo ganancias territoriales como resultado de la victoria. Dado que las pérdidas fueron cuantiosas, en la tradición local el campo de Krbava se conoció como el «Campo de la Sangre» (en croata: Krvavo polje). La paz entre los reinos de Croacia y Hungría y el Imperio otomano se firmó en abril de 1495. Las siguientes grandes incursiones musulmanas ocurrieron en 1512 y 1513, y resultaron en la victoria croata de la batalla de Dubica. Después de la batalla, y en décadas posteriores, debido a los constantes ataques otomanos, las poblaciones croatas locales se trasladaron a áreas más seguras; el noroeste de Croacia, la costa y las islas, y también fuera del país. Franjo Berislavić se convirtió en el ban de Jajce en 1494.

Registros históricos
Se han registrado relatos del campo de batalla de Krbava en varias fuentes históricas modernas y antiguas. Entre las más antiguas se encuentran el informe del delegado papal Antonio Fabregues escrito el 13 de septiembre de 1493 en Senj, un registro del viajero bohemio Jan Hasištejnský el 23 de septiembre de 1493 en su libro de viajes, el relato del sacerdote glagolita Martinac en el breviario Novi Vinodolski en 1493, y el relato de la batalla escrito en una carta al papa Alejandro VI por el obispo de Nin, Juraj Divnić, el 27 de septiembre de 1493. En 1561, la batalla fue descrita por el cronista Ivan Tomašić en su «Crónica breve del Reino de Croacia», Chronicon breve Regni Croatiae, y en 1696, Pavao Ritter Vitezović la describió en Kronika aliti szpomen vszega szvieta vikov.

Referencias

Bibliografía

Enlaces externos
 Ottoman Wars: Battles of Otranto 1480 and Chaldiran 1514 Documentary. Video del canal de YouTube Kings and Generals. Publicado el 7 de octubre de 2018. En inglés. En el video también se muestra el desarrollo de la batalla en Krbava.

Croacia en el siglo XV
Imperio otomano en el siglo XV
Batallas de Croacia
Guerra otomano-croata de los cien años
Batallas del Imperio otomano en el siglo XV

redpajama_set_name: RedPajamaWikipedia