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This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, |GE | and |GM|, using the ¯pp → μ+μ− reaction at PANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at PANDA, using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is ¯pp → π+π−,due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distribuations of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented.
The inclusive charged particle transverse momentum distribution is measured in proton–proton collisions at s=900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region (|η|<0.8) over the transverse momentum range 0.15<pT<10 GeV/c. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for |η|<0.8 is 〈pT〉INEL=0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉NSD=0.489±0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger 〈pT〉 than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
Aims: Heart failure (HF) leads to repeat hospitalisations and reduces the duration and quality of life. Pulmonary artery pressure (PAP)‐guided HF management using the CardioMEMS™ HF system was shown to be safe and reduce HF hospitalisation (HFH) rates in New York Heart Association (NYHA) class III patients. However, these findings have not been replicated in health systems outside the United States. Therefore, the CardioMEMS European Monitoring Study for Heart Failure (MEMS‐HF) evaluated the safety, feasibility, and performance of this device in Germany, The Netherlands, and Ireland.
Methods and results: A total of 234 NYHA class III patients (68 ± 11 years, 22% female, ≥1 HFH in the preceding year) from 31 centres were implanted with a CardioMEMS sensor and underwent PAP‐guided HF management. One‐year rates of freedom from device‐ or system‐related complications and from sensor failure (co‐primary outcomes) were 98.3% [95% confidence interval (CI) 95.8–100.0] and 99.6% (95% CI 97.6–100.0), respectively. Survival rate was 86.2%. For the 12 months post‐ vs. pre‐implant, HFHs decreased by 62% (0.60 vs. 1.55 events/patient‐year; hazard ratio 0.38, 95% CI 0.31–0.48; P < 0.0001). After 12 months, mean PAP decreased by 5.1 ± 7.4 mmHg, Kansas City Cardiomyopathy Questionnaire (KCCQ) overall/clinical summary scores increased from 47.0 ± 24.0/51.2 ± 24.8 to 60.5 ± 24.3/62.4 ± 24.1 (P < 0.0001), and the 9‐item Patient Health Questionnaire sum score improved from 8.7 ± 5.9 to 6.3 ± 5.1 (P < 0.0001).
Conclusion: Haemodynamic‐guided HF management proved feasible and safe in the health systems of Germany, The Netherlands, and Ireland. Physician‐directed treatment modifications based on remotely obtained PAP values were associated with fewer HFH, sustainable PAP decreases, marked KCCQ improvements, and remission of depressive symptoms.
Background: Genome-wide association studies (GWAS) have identified new candidate genes for the occurrence of acute coronary syndrome (ACS), but possible effects of such genes on survival following ACS have yet to be investigated.
Methods: We examined 95 polymorphisms in 69 distinct gene regions identified in a GWAS for premature myocardial infarction for their association with post-ACS mortality among 811 whites recruited from university-affiliated hospitals in Kansas City, Missouri. We then sought replication of a positive genetic association in a large, racially diverse cohort of myocardial infarction patients (N = 2284) using Kaplan-Meier survival analyses and Cox regression to adjust for relevant covariates. Finally, we investigated the apparent association further in 6086 additional coronary artery disease patients.
Results: After Cox adjustment for other ACS risk factors, of 95 SNPs tested in 811 whites only the association with the rs6922269 in MTHFD1L was statistically significant, with a 2.6-fold mortality hazard (P = 0.007). The recessive A/A genotype was of borderline significance in an age- and race-adjusted analysis of the entire combined cohort (N = 3095; P = 0.052), but this finding was not confirmed in independent cohorts (N = 6086).
Conclusions: We found no support for the hypothesis that the GWAS-identified variants in this study substantially alter the probability of post-ACS survival. Large-scale, collaborative, genome-wide studies may be required in order to detect genetic variants that are robustly associated with survival in patients with coronary artery disease.