Is the association of birth weight with premenopausal breast cancer risk mediated through childhood growth?

Several studies have found positive associations between birth weight and breast cancer risk at premenopausal ages. The mechanisms underlying this association are not known, but it is possible that it may be mediated through childhood growth. We examined data from a British cohort of 2176 women born in 1946 and for whom there were prospective measurements of birth weight and of body size throughout life. In all, 59 breast cancer cases occurred during follow-up, 21 of whom were known to be premenopausal. Women who weighed at least 4 kg at birth were five times (relative risk (RR)=5.03; 95% confidence interval=1.13, 22.5) more likely to develop premenopausal breast cancer than those who weighed less than 3 kg (P-value for linear trend=0.03). This corresponded to an RR of 2.31 (0.95, 5.64) per 1 kg increase in birth weight. Birth weight was also a predictor of postnatal growth, that is, women who were heavy at birth remained taller and heavier throughout their childhood and young adulthood. However, the effect of birth weight on premenopausal breast cancer risk was only reduced slightly after simultaneous adjustment for height and body mass index (BMI) at age 2 years and height and BMI velocities throughout childhood and adolescence (adjusted RR=1.94 (0.74, 5.14) per 1 kg increase in birth weight). The pathways through which birth weight is associated with premenopausal breast cancer risk seem to be largely independent of those underlying the relation of postnatal growth to risk

Does diet affect breast cancer risk?

The role of specific dietary factors in breast cancer causation is not completely resolved. Results from prospective studies do not support the concept that fat intake in middle life has a major relation to breast cancer risk. However, weight gain in middle life contributes substantially to breast cancer risk. Alcohol is the best established dietary risk factor, probably by increasing endogenous estrogen levels. Hypotheses relating diet during youth to risk decades later will be difficult to test. Nevertheless, available evidence is strong that breast cancer risk can be reduced by avoiding weight gain during adult years, and by limiting alcohol consumption

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Dietary fat and breast cancer risk revisited: a meta-analysis of the published literature

Animal experiments and human ecological studies suggest that dietary fat intake is associated with a risk of breast cancer, but individual-based studies have given contradictory results. We have carried out a meta-analysis of this association to include all papers published up to July 2003. Case-control and cohort studies that examined the association of dietary fat, or fat-containing foods, with risk of breast cancer were identified. A total of 45 risk estimates for total fat intake were obtained. Descriptive data from each study were extracted with an estimate of relative risk and its associated 95% confidence interval (CI), and were analysed using the random effects model of DerSimonian and Laird. The summary relative risk, comparing the highest and lowest levels of intake of total fat, was 1.13 (95% CI: 1.03-1.25). Cohort studies (N=14) had a summary relative risk of 1.11 (95% CI: 0.99-1.25) and case-control studies (N=31) had a relative risk of 1.14 (95% CI 0.99-1.32). Significant summary relative risks were also found for saturated fat (RR, 1.19; 95% CI: 1.06-1.35) and meat intake (RR, 1.17; 95% CI 1.06-1.29). Combined estimates of risk for total and saturated fat intake, and for meat intake, all indicate an association between higher intakes and an increased risk of breast cancer. Case-control and cohort studies gave similar results

A polymorphism at the 3'-UTR region of the aromatase gene defines a subgroup of postmenopausal breast cancer patients with poor response to neoadjuvant letrozole

<p>Abstract</p> <p>Background</p> <p>Aromatase (<it>CYP19A1</it>) regulates estrogen biosynthesis. Polymorphisms in <it>CYP19A1 </it>have been related to the pathogenesis of breast cancer (BC). Inhibition of aromatase with letrozole constitutes the best option for treating estrogen-dependent BC in postmenopausal women. We evaluate a series of polymorphisms of <it>CYP19A1 </it>and their effect on response to neoadjuvant letrozole in early BC.</p> <p>Methods</p> <p>We analyzed 95 consecutive postmenopausal women with stage II-III ER/PgR [+] BC treated with neoadjuvant letrozole. Response to treatment was measured by radiology at 4^thmonth by World Health Organization (WHO) criteria. Three polymorphisms of <it>CYP19A1</it>, one in exon 7 (rs700519) and two in the 3'-UTR region (rs10046 and rs4646) were evaluated on DNA obtained from peripheral blood.</p> <p>Results</p> <p>Thirty-five women (36.8%) achieved a radiological response to letrozole. The histopathological and immunohistochemical parameters, including hormonal receptor status, were not associated with the response to letrozole. Only the genetic variants (AC/AA) of the rs4646 polymorphism were associated with poor response to letrozole (p = 0.03). Eighteen patients (18.9%) reported a progression of the disease. Those patients carrying the genetic variants (AC/AA) of rs4646 presented a lower progression-free survival than the patients homozygous for the reference variant (p = 0.0686). This effect was especially significant in the group of elderly patients not operated after letrozole induction (p = 0.009).</p> <p>Conclusions</p> <p>Our study reveals that the rs4646 polymorphism identifies a subgroup of stage II-III ER/PgR [+] BC patients with poor response to neoadjuvant letrozole and poor prognosis. Testing for the rs4646 polymorphism could be a useful tool in order to orientate the treatment in elderly BC patients.</p

CMS Data Processing Workflows during an Extended Cosmic Ray Run

Peer reviewe

Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

Peer reviewe

Commissioning of the CMS high-level trigger with cosmic rays

This is the Pre-print version of the Article. The official published version of the paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)