Supersymmetry discovery potential of the LHC at s=\sqrt{s}=10 and 14 TeV without and with missing ETE_T

We examine the supersymmetry (SUSY) reach of the CERN LHC operating at $\sqrt{s}=10$ and 14 TeV within the framework of the minimal supergravity model. We improve upon previous reach projections by incorporating updated background calculations including a variety of $2\to n$ Standard Model (SM) processes. We show that SUSY discovery is possible even before the detectors are understood well enough to utilize either $E_T^{\rm miss}$ or electrons in the signal. We evaluate the early SUSY reach of the LHC at $\sqrt{s}=10$ TeV by examining multi-muon plus $\ge4$ jets and also dijet events with {\it no} missing $E_T$ cuts and show that the greatest reach in terms of $m_{1/2}$ occurs in the dijet channel. The reach in multi-muons is slightly smaller in $m_{1/2}$, but extends to higher values of $m_0$. We find that an observable multi-muon signal will first appear in the opposite-sign dimuon channel, but as the integrated luminosity increases the relatively background-free but rate-limited same-sign dimuon, and ultimately the trimuon channel yield the highest reach. We show characteristic distributions in these channels that serve to distinguish the signal from the SM background, and also help to corroborate its SUSY origin. We then evaluate the LHC reach in various no-lepton and multi-lepton plus jets channels {\it including} missing $E_T$ cuts for $\sqrt{s}=10$ and 14 TeV, and plot the reach for integrated luminosities ranging up to 3000 fb$^{-1}$ at the SLHC. For $\sqrt{s}=10$ TeV, the LHC reach extends to $m_{gluino}=1.9, 2.3, 2.8$ and 2.9 TeV for $m_{squark}\sim m_{gluino}$ and integrated luminosities of 10, 100, 1000 and 3000 fb$^{-1}$, respectively. For $\sqrt{s}=14$ TeV, the LHC reach for the same integrated luminosities is to m_{gluino}=2.4,\3.1, 3.7 and 4.0 TeV.Comment: 34 pages, 25 figures. Revised projections for the SUSY reach for ab^-1 integrated luminosities, with minor corrections of references and text. 2 figures added. To appear in JHE

Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleve

Changing geographical patterns and trends in cancer incidence in children and adolescents in Europe, 1991–2010 (Automated Childhood Cancer Information System): a population-based study

Background: A deceleration in the increase in cancer incidence in children and adolescents has been reported in several national and regional studies in Europe. Based on a large database representing 1·3 billion person-years over the period 1991–2010, we provide a consolidated report on cancer incidence trends at ages 0–19 years. Methods: We invited all population-based cancer registries operating in European countries to participate in this population-based registry study. We requested a listing of individual records of cancer cases, including sex, age, date of birth, date of cancer diagnosis, tumour sequence number, primary site, morphology, behaviour, and the most valid basis of diagnosis. We also requested population counts in each calendar year by sex and age for the registration area, from official national sources, and specific information about the covered area and registration practices. An eligible registry could become a contributor if it provided quality data for all complete calendar years in the period 1991–2010. Incidence rates and the average annual percentage change with 95% CIs were reported for all cancers and major diagnostic groups, by region and overall, separately for children (age 0–14 years) and adolescents (age 15–19 years). We examined and quantified the stability of the trends with joinpoint analyses. Findings: For the years 1991–2010, 53 registries in 19 countries contributed a total of 180 335 unique cases. We excluded 15 162 (8·4%) of 180 335 cases due to differing practices of registration, and considered the quality indicators for the 165 173 cases included to be satisfactory. The average annual age-standardised incidence was 137·5 (95% CI 136·7–138·3) per million person-years and incidence increased significantly by 0·54% (0·44–0·65) per year in children (age 0–14 years) with no change in trend. In adolescents, the combined European incidence was 176·2 (174·4–178·0) per million person-years based on all 35 138 eligible cases and increased significantly by 0·96% (0·73–1·19) per year, although recent changes in rates among adolescents suggest a deceleration in this increasing trend. We observed temporal variations in trends by age group, geographical region, and diagnostic group. The combined age-standardised incidence of leukaemia based on 48 458 cases in children was 46·9 (46·5–47·3) per million person-years and increased significantly by 0·66% (0·48–0·84) per year. The average overall incidence of leukaemia in adolescents was 23·6 (22·9–24·3) per million person-years, based on 4702 cases, and the average annual change was 0·93% (0·49–1·37). We also observed increasing incidence of lymphoma in adolescents (average annual change 1·04% [0·65–1·44], malignant CNS tumours in children (average annual change 0·49% [0·20–0·77]), and other tumours in both children (average annual change 0·56 [0·40–0·72]) and adolescents (average annual change 1·17 [0·82–1·53]). Interpretation: Improvements in the diagnosis and registration of cancers over time could partly explain the observed increase in incidence, although some changes in underlying putative risk factors cannot be excluded. Cancer incidence trends in this young population require continued monitoring at an international level. Funding: Federal Ministry of Health of the Federal German Government, the European Union's Seventh Framework Programme, and International Agency for Research on Cancer