Transabdominal ultrasonographic measurement of caudal vena cava to aorta derived ratios in clinically healthy neonatal foals

Background: Ultrasonographic measurement of the vena cava and aorta (Ao) diameters and their ratios have been suggested to be a reliable way of quantifying hypovolemia. Objective: To evaluate the feasibility and reliability of an ultrasonographic technique for measurement of Ao and caudal vena cava (CVC) and derived ratios using three different acoustic windows in a population of healthy neonatal foals. Correlation between Ao and CVC measurements and ratios and foals' age or bodyweight were also investigated. Methods: In 14 healthy foals aged less than 7 days, the diameters of the Ao and of the CVC in long and short axis were measured by two observers from images obtained using three different ultrasonographic imaging planes (left dorsal, left ventral and right views). The Ao and CVC cross-sectional area and the CVC/Ao diameter and area ratios were calculated. Image quality was subjectively assessed. Intraobserver and interobserver reliabilities for image quality scores and measurements were evaluated between the two observers. Simple linear regression models were used to identify correlations between the CVC/Ao measurements and ratios and the age and bodyweight of the foals. Results: The left ventral view showed the highest reliability. A correlation between bodyweight and the short axis measurement of the CVC was found (R2 = 0.385; p = 0.018). Age was positively correlated with the long axis of measurement of the CVC (R2 = 0.426; p = 0.011) and CVC/Ao diameter ratio (R2 = 0.625; p = 0.001). Conclusions: The left ventral view allows the Ao and CVC cross sections to be easily visualized and measured in neonatal foals in right lateral recumbency

Equine asthma: current understanding and future directions

The 2019 Havemeyer Workshop brought together researchers and clinicians to discuss the latest information on Equine Asthma and provide future research directions. Current clinical and molecular asthma phenotypes and endotypes in humans were discussed and compared to asthma phenotypes in horses. The role of infectious and non-infectious causes of equine asthma, genetic factors and proposed disease pathophysiology were reviewed. Diagnostic limitations were evident by the limited number of tests and biomarkers available to field practitioners. The participants emphasized the need for more accessible, standardized diagnostics that would help identify specific phenotypes and endotypes in order to create more targeted treatments or management strategies. One important outcome of the workshop was the creation of the Equine Asthma Group that will facilitate communication between veterinary practice and research communities through published and easily accessible guidelines and foster research collaboration

Additional file 1: of eQTL discovery and their association with severe equine asthma in European Warmblood horses

Figure S1. Minimum D-statistics determine mean read count cutoffs. Figure S2. PCA plots of normalized variance stabilized RNAseq counts after KS test filter. Figure S3. PCA plots of 1,056,195 SNP genotypes and colored by cohort. Figure S4. Matrix eQTL histograms and QQ-plots for all p-values for all cis and trans eQTL analyses using tag SNPs for the MCK1 treatment. Figure S5. Low confidence cis eQTLs. Figure S6. Joint modeling with eQTLBMA with possible overestimation of shared eQTLs across all PBMC treatments. Figure S7. Distance between eSNPs with the lowest FDR values per gene is small. Figure S8.. Enrichment of SNPs in trans regulatory hotspots genome wide. Figure S9. GWAS for RAO. Figure S10. Loss of DEXI gene expression regulation in HDE. Figure S11. Cis trans eQTL plot for all eQTLs for treatment HDE9. Table S1. High confidence additive linear cis eQTLs from the MCK treatment. Table S2. Low confidence additive linear cis eQTLs from the MCK treatment. Table S3. High confidence additive linear trans eQTLs from the MCK treatment. Table S4. Low confidence additive linear trans eQTLs from the MCK treatment. Table S5. High confidence additive linear cis eQTLs from the LPS treatment. Table S6. Low confidence additive linear cis eQTLs from the LPS treatment. Table S7. High confidence additive linear trans eQTLs from the LPS treatment. Table S8. Low confidence additive linear trans eQTLs from the LPS treatment. Table S9. High confidence additive linear cis eQTLs from the RCA treatment. Table S10. Low confidence additive linear cis eQTLs from the RCA treatment. Table S11. High confidence additive linear trans eQTLs from the RCA treatment. The eQTLs reported are limited to one eQTL per gene, representing the eSNP with the lowest FDR value for each gene. Table S12. Low confidence additive linear trans eQTLs from the RCA treatment. Table S13. High confidence additive linear cis eQTLs from the HDE treatment. Table S14. Low confidence additive linear cis eQTLs from the HDE treatment. Table S15. High confidence additive linear trans eQTLs from the HDE treatment. Table S16. Low confidence additive linear trans eQTLs from the HDE treatment. Table S17. Two proportion z-test calculation. Table S18. 4157 significant eQTLs discovered with eQTLBMA. Table S19. Trans eQTL results for the trans regulatory hotspot on chromosome 11 (SNP MNEc.2.11.60892596.PC). Table S20. Trans eQTL results for the trans regulatory hotspot on chromosome 13 (SNP MNEc.2.13.18333037.PC). Table S21. Panther gene enrichment GO process results for genes regulated by the trans regulatory hotpot on chromosome 11 (MNEc.2.11.60892596.PC). Table S22. Panther gene enrichment GO process results for genes regulated by the trans regulatory hotpot on chromosome 13 (MNEc.2.13.18333037.PC). Table S23. GWAS results. Table S24. All significant cis eQTLs for the MCK treatment. Table S25. All significant cis eQTLs for the LPS treatment. Table S26. All significant cis eQTLs for the RCA treatment. Table S27. All significant cis eQTLs for the HDE treatment. Table S28. Linkage disequilibrium and allele frequencies between RAO associated SNPs on chromosome 13 positions 32,843,309 – 33,502,488. Table S29. Sample information for 82 individuals used in eQTL analyses. Table S30. Sample information for all 379 individuals. (ZIP 51963 kb