Search for Flavoured Multiquarks in a Simple Bag Model

We use a bag model to study flavoured mesonic $(Qq\bar q\bar q)$ and baryonic $({\overline Q}qqqq)$ states, where one heavy quark $Q$ is associated with light quarks or antiquarks, and search for possible stable multiquarks. No bound state is found. However some states lie not too high above their dissociation threshold, suggesting the possibility of resonances, or perhaps bound states in improved models.Comment: REVTEX, VERSION 3.

Dissociation constants and thermodynamic properties of amino acids used in CO2 absorption from (293 to 353) K

The second dissociation constants of the amino acids βalanine, taurine, sarcosine, 6-aminohexanoic acid, DL-methionine, glycine, L-phenylalanine, and L-proline and the third dissociation constants of L-glutamic acid and L-aspartic acid have been determined from electromotive force measurements at temperatures from (293 to 353) K. Experimental results are reported and compared to literature values. Values of the standard state thermodynamic properties are derived from the experimental results and compared to the values of commercially available amines used as absorbents for CO 2 capture.

Mathematical Modelling of Optical Coherence Tomography

In this chapter a general mathematical model of Optical Coherence Tomography (OCT) is presented on the basis of the electromagnetic theory. OCT produces high resolution images of the inner structure of biological tissues. Images are obtained by measuring the time delay and the intensity of the backscattered light from the sample considering also the coherence properties of light. The scattering problem is considered for a weakly scattering medium located far enough from the detector. The inverse problem is to reconstruct the susceptibility of the medium given the measurements for different positions of the mirror. Different approaches are addressed depending on the different assumptions made about the optical properties of the sample. This procedure is applied to a full field OCT system and an extension to standard (time and frequency domain) OCT is briefly presented.Comment: 28 pages, 5 figures, book chapte

Prostate Cancer Risk by BRCA2 Genomic Regions.

A BRCA2 prostate cancer cluster region (PCCR) was recently proposed (c.7914 to 3') wherein pathogenic variants (PVs) are associated with higher prostate cancer (PCa) risk than PVs elsewhere in the BRCA2 gene. Using a prospective cohort study of 447 male BRCA2 PV carriers recruited in the UK and Ireland from 1998 to 2016, we estimated standardised incidence ratios (SIRs) compared with population incidences and assessed variation in risk by PV location. Carriers of PVs in the PCCR had a PCa SIR of 8.33 (95% confidence interval [CI] 4.46-15.6) and were at a higher risk of PCa than carriers of other BRCA2 PVs (SIR = 3.31, 95% CI 1.97-5.57; hazard ratio = 2.34, 95% CI 1.09-5.03). PCCR PV carriers had an estimated cumulative PCa risk of 44% (95% CI 23-72%) by the age of 75 yr and 78% (95% CI 54-94%) by the age of 85 yr. Our results corroborate the existence of a PCCR in BRCA2 in a prospective cohort. PATIENT SUMMARY: In this report, we investigated whether the risk of prostate cancer for men with a harmful mutation in the BRCA2 gene differs based on where in the gene the mutation is located. We found that men with mutations in one region of BRCA2 had a higher risk of prostate cancer than men with mutations elsewhere in the gene

Arrhythmia Caused by a Drosophila Tropomyosin Mutation Is Revealed Using a Novel Optical Coherence Tomography Instrument

Background: Dilated cardiomyopathy (DCM) is a severe cardiac condition that causes high mortality. Many genes have been confirmed to be involved in this disease. An ideal system with which to uncover disease mechanisms would be one that can measure the changes in a wide range of cardiac activities associated with mutations in specific, diversely functional cardiac genes. Such a system needs a genetically manipulable model organism that allows in vivo measurement of cardiac phenotypes and a detecting instrument capable of recording multiple phenotype parameters. Methodology and Principal Findings: With a simple heart, a transparent body surface at larval stages and available genetic tools we chose Drosophila melanogaster as our model organism and developed for it a dual en-face/Doppler optical coherence tomography (OCT) instrument capable of recording multiple aspects of heart activity, including heart contraction cycle dynamics, ostia dynamics, heartbeat rate and rhythm, speed of heart wall movement and light reflectivity of cardiomyocytes in situ. We applied this OCT instrument to a model of Tropomyosin-associated DCM established in adult Drosophila. We show that DCM pre-exists in the larval stage and is accompanied by an arrhythmia previously unidentified in this model. We also detect reduced mobility and light reflectivity of cardiomyocytes in mutants. Conclusion: These results demonstrate the capability of our OCT instrument to characterize in detail cardiac activity i

Common ataxia telangiectasia mutated haplotypes and risk of breast cancer: a nested case–control study

INTRODUCTION: The ataxia telangiectasia mutated (ATM) gene is a tumor suppressor gene with functions in cell cycle arrest, apoptosis, and repair of DNA double-strand breaks. Based on family studies, women heterozygous for mutations in the ATM gene are reported to have a fourfold to fivefold increased risk of breast cancer compared with noncarriers of the mutations, although not all studies have confirmed this association. Haplotype analysis has been suggested as an efficient method for investigating the role of common variation in the ATM gene and breast cancer. Five biallelic haplotype tagging single nucleotide polymorphisms are estimated to capture 99% of the haplotype diversity in Caucasian populations. METHODS: We conducted a nested case–control study of breast cancer within the Nurses' Health Study cohort to address the role of common ATM haplotypes and breast cancer. Cases and controls were genotyped for five haplotype tagging single nucleotide polymorphisms. Haplotypes were predicted for 1309 cases and 1761 controls for which genotype information was available. RESULTS: Six unique haplotypes were predicted in this study, five of which occur at a frequency of 5% or greater. The overall distribution of haplotypes was not significantly different between cases and controls (χ(2 )= 3.43, five degrees of freedom, P = 0.63). CONCLUSION: There was no evidence that common haplotypes of ATM are associated with breast cancer risk. Extensive single nucleotide polymorphism detection using the entire genomic sequence of ATM will be necessary to rule out less common variation in ATM and sporadic breast cancer risk

Risks of breast or ovarian cancer in BRCA1 or BRCA2 predictive test negatives: findings from the EMBRACE study.

Purpose BRCA1/BRCA2 predictive test negatives are proven noncarriers of a BRCA1/BRCA2 mutation that is carried by their relatives. The risk of developing breast cancer (BC) or epithelial ovarian cancer (EOC) in these women is uncertain. The study aimed to estimate risks of invasive BC and EOC in a large cohort of BRCA1/BRCA2 predictive test negatives. Methods We used cohort analysis to estimate incidences, cumulative risks, and standardized incidence ratios (SIRs). Results A total of 1,895 unaffected women were eligible for inclusion in the BC risk analysis and 1,736 in the EOC risk analysis. There were 23 incident invasive BCs and 2 EOCs. The cumulative risk of invasive BC was 9.4% (95% confidence interval (CI) 5.9-15%) by age 85 years and the corresponding risk of EOC was 0.6% (95% CI 0.2-2.6%). The SIR for invasive BC was 0.93 (95% CI 0.62-1.40) in the overall cohort, 0.85 (95% CI 0.48-1.50) in noncarriers from BRCA1 families, and 1.03 (95% CI 0.57-1.87) in noncarriers from BRCA2 families. The SIR for EOC was 0.79 (95% CI 0.20-3.17) in the overall cohort. Conclusion Our results did not provide evidence for elevated risks of invasive BC or EOC in BRCA1/BRCA2 predictive test negatives. Genetics in Medicine advance online publication, 22 March 2018; doi:10.1038/gim.2018.44

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management