No evidence of BRCA2 mutations in chromosome 13q-linked Utah high-risk prostate cancer pedigrees

<p>Abstract</p> <p>Background</p> <p>Germline mutations in the <it>BRCA2 </it>gene have been suggested to account for about 5% of familial prostate cancer; mutations have been reported in 2% of early onset (i.e., ≤ 55 years) prostate cancer cases and a segregating founder mutation has been identified in Iceland (999del5). However, the role of <it>BRCA2 </it>in high risk prostate cancer pedigrees remains unclear.</p> <p>Findings</p> <p>We examined the potential involvement of <it>BRCA2 </it>in a set offive high-risk prostate cancer pedigrees in which all prostate cases were no more distantly related than two meioses from another case, and the resulting cluster contained at least four prostate cancer cases. We selected these five pedigrees from a larger dataset of 59 high-risk prostate cancer pedigrees analyzed in a genome-wide linkage screen. Selected pedigrees showed at least nominal linkage evidence to the <it>BRCA2 </it>region on chromosome 13q. We mutation screened all coding regions and intron/exon boundaries of the <it>BRCA2 </it>gene in the youngest prostate cancer case who carried the linked 13q segregating haplotype, as well as in a distantly related haplotype carrier to confirm any segregation. We observed no known protein truncating <it>BRCA2 </it>deleterious mutations. We identified one non-segregating <it>BRCA2 </it>variant of uncertain significance, one non-segregating intronic variant not previously reported, and a number of polymorphisms.</p> <p>Conclusion</p> <p>In this set of high-risk prostate cancer pedigrees with at least nominal linkage evidence to <it>BRCA2</it>, we saw no evidence for segregating <it>BRCA2 </it>protein truncating mutations in heritable prostate cancer.</p

Pennsylvania Folklife Vol. 39, No. 1

• An Overview of Travel and Transportation in Pennsylvania • Floretta Emma Warfel: A Folk Artist in Embroidery Paint on Cloth • Robacker, Earl F. and Ada F.: A Bibliography • The Modernizing Effect of the Marketplace on Old Order Society, 1727 to 1987 • Aldes un Neies (Old and New)https://digitalcommons.ursinus.edu/pafolklifemag/1125/thumbnail.jp

Association of FGFR4 genetic polymorphisms with prostate cancer risk and prognosis

The fibroblast growth factor receptor 4 (FGFR4) is thought to be involved in many critical cellular processes and has been associated with prostate cancer risk. Four single nucleotide polymorphisms within or near FGFR4 were analysed in a population-based study of 1458 prostate cancer patients and 1352 age-matched controls. We found no evidence to suggest that any of the FGFR4 SNP genotypes were associated with prostate cancer risk or with disease aggressiveness, Gleason score or stage. A weak association was seen between rs351855 and prostate cancer-specific mortality. Subset analysis of cases that had undergone radical prostatectomy revealed an association between rs351855 and prostate cancer risk. While our results confirm an association between FGFR4 and prostate cancer risk in radical prostatectomy cases, they suggest that the role of FGFR4 in disease risk and outcomes at a population-based level appears to be minor

Challenges for a CBR framework for argumentation in open MAS

[EN] Nowadays, Multi-Agent Systems (MAS) are broadening their applications to open environments, where heterogeneous agents could enter into the system, form agents’ organizations and interact. The high dynamism of open MAS gives rise to potential conflicts between agents and thus, to a need for a mechanism to reach agreements. Argumentation is a natural way of harmonizing conflicts of opinion that has been applied to many disciplines, such as Case-Based Reasoning (CBR) and MAS. Some approaches that apply CBR to manage argumentation in MAS have been proposed in the literature. These improve agents’ argumentation skills by allowing them to reason and learn from experiences. In this paper, we have reviewed these approaches and identified the current contributions of the CBR methodology in this area. As a result of this work, we have proposed several open issues that must be taken into consideration to develop a CBR framework that provides the agents of an open MAS with arguing and learning capabilities.This work was partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022 and by the Spanish government and FEDER funds under TIN2006-14630-C0301 project.Heras Barberá, SM.; Botti Navarro, VJ.; Julian Inglada, VJ. (2009). Challenges for a CBR framework for argumentation in open MAS. Knowledge Engineering Review. 24(4):327-352. https://doi.org/10.1017/S0269888909990178S327352244Willmott S. , Vreeswijk G. , Chesñevar C. , South M. , McGinnis J. , Modgil S. , Rahwan I. , Reed C. , Simari G. 2006. Towards an argument interchange format for multi-agent systems. In Proceedings of the AAMAS International Workshop on Argumentation in Multi-Agent Systems, ArgMAS-06, 17–34.Sycara, K. P. (1990). Persuasive argumentation in negotiation. Theory and Decision, 28(3), 203-242. doi:10.1007/bf00162699Ontañón S. , Plaza E. 2006. Arguments and counterexamples in case-based joint deliberation. In AAMAS-06 Workshop on Argumentation in Multi-Agent Systems, ArgMAS-06, 36–53.Sadri F. , Toni F. , Torroni P. 2001. Dialogues for negotiation: agent varieties and dialogue sequences. In Proceedings of the 8th International Workshop on Agent Theories, Architectures, and Languages, ATAL-01, Intelligent Agents VIII 2333, 405–421. Springer.Fox J. , Parsons S. 1998. Arguing about beliefs and actions. In Applications of Uncertainty Formalisms, Lecture Notes in Computer Science 1455, 266–302. Springer.Dung, P. M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77(2), 321-357. doi:10.1016/0004-3702(94)00041-xAulinas M. , Tolchinsky P. , Turon C. , Poch M. , Cortés U. 2007. Is my spill environmentally safe? Towards an integrated management of wastewater in a river basin using agents that can argue. In 7th International IWA Symposium on Systems Analysis and Integrated Assessment in Water Management. Washington DC, USA.Amgoud L. 2003. A formal framework for handling conflicting desires. In Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Computer Science 2711, 552–563. Springer.Armengol E. , Plaza E. 2001. Lazy induction of descriptions for relational case-based learning. In European Conference on Machine Learning, ECML-01, 13–24.Sørmo, F., Cassens, J., & Aamodt, A. (2005). Explanation in Case-Based Reasoning–Perspectives and Goals. Artificial Intelligence Review, 24(2), 109-143. doi:10.1007/s10462-005-4607-7RAHWAN, I., RAMCHURN, S. D., JENNINGS, N. R., McBURNEY, P., PARSONS, S., & SONENBERG, L. (2003). Argumentation-based negotiation. The Knowledge Engineering Review, 18(4), 343-375. doi:10.1017/s0269888904000098Brüninghaus S. , Ashley K. D. 2001. Improving the representation of legal case texts with information extraction methods. In 7th International Conference on Artificial Intelligence and Law, ICAIL-01, 42–51.Parsons, S. (1998). Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8(3), 261-292. doi:10.1093/logcom/8.3.261Atkinson, K., Bench-Capon, T., & Mcburney, P. (2005). A Dialogue Game Protocol for Multi-Agent Argument over Proposals for Action. Autonomous Agents and Multi-Agent Systems, 11(2), 153-171. doi:10.1007/s10458-005-1166-xBrüninghaus S. , Ashley K. D. 2003. Predicting the outcome of case-based legal arguments. In 9th International Conference on Artificial Intelligence and Law, ICAIL-03, 233–242.Modgil S. , Tolchinsky P. , Cortés U. 2005. Towards formalising agent argumentation over the viability of human organs for transplantation. In 4th Mexican International Conference on Artificial Intelligence, MICAI-05, 928–938.Tolchinsky P. , Atkinson K. , McBurney P. , Modgil S. , Cortés U. 2007. Agents deliberating over action proposals using the ProCLAIM model. In 5th International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS-07, 32–41.Prakken, H., & Sartor, G. (1998). Artificial Intelligence and Law, 6(2/4), 231-287. doi:10.1023/a:1008278309945Gordon T. F. , Karacapilidis N. 1997. The Zeno argumentation framework. In International Conference on Artificial Intelligence and Law, ICAIL-97, ACM Press, 10–18.Tolchinsky P. , Modgil S. , Cortés U. 2006a. Argument schemes and critical questions for heterogeneous agents to argue over the viability of a human organ. In AAAI Spring Symposium Series; Argumentation for Consumers of Healthcare, 377–384.Aleven V. , Ashley K. D. 1997. Teaching case-based argumentation through a model and examples, empirical evaluation of an intelligent learning environment. In 8th World Conference of the Artificial Intelligence in Education Society, 87–94.Rahwan, I. (2005). Guest Editorial: Argumentation in Multi-Agent Systems. Autonomous Agents and Multi-Agent Systems, 11(2), 115-125. doi:10.1007/s10458-005-3079-0RISSLAND, E. L., ASHLEY, K. D., & BRANTING, L. K. (2005). Case-based reasoning and law. The Knowledge Engineering Review, 20(3), 293-298. doi:10.1017/s0269888906000701Tolchinsky, P., Cortes, U., Modgil, S., Caballero, F., & Lopez-Navidad, A. (2006). Increasing Human-Organ Transplant Availability: Argumentation-Based Agent Deliberation. IEEE Intelligent Systems, 21(6), 30-37. doi:10.1109/mis.2006.116McBurney, P., Hitchcock, D., & Parsons, S. (2006). The eightfold way of deliberation dialogue. International Journal of Intelligent Systems, 22(1), 95-132. doi:10.1002/int.20191Rissland, E. L., Ashley, K. D., & Loui, R. P. (2003). AI and Law: A fruitful synergy. Artificial Intelligence, 150(1-2), 1-15. doi:10.1016/s0004-3702(03)00122-xSoh, L.-K., & Tsatsoulis, C. (2005). A Real-Time Negotiation Model and A Multi-Agent Sensor Network Implementation. Autonomous Agents and Multi-Agent Systems, 11(3), 215-271. doi:10.1007/s10458-005-0539-5Capobianco, M., Chesñevar, C. I., & Simari, G. R. (2005). Argumentation and the Dynamics of Warranted Beliefs in Changing Environments. Autonomous Agents and Multi-Agent Systems, 11(2), 127-151. doi:10.1007/s10458-005-1354-8Tolchinsky P. , Modgil S. , Cortés U. , Sànchez-Marrè M. 2006b. CBR and argument schemes for collaborative decision making. In Conference on Computational Models of Argument, COMMA-06, 144, 71–82. IOS Press.Ossowski S. , Julian V. , Bajo J. , Billhardt H. , Botti V. , Corchado J. M. 2007. Open issues in open MAS: an abstract architecture proposal. In Conferencia de la Asociacion Española para la Inteligencia Artificial, CAEPIA-07, 2, 151–160.Karacapilidis, N., & Papadias, D. (2001). Computer supported argumentation and collaborative decision making: the HERMES system. Information Systems, 26(4), 259-277. doi:10.1016/s0306-4379(01)00020-5Aamodt A. 2004. Knowledge-intensive case-based reasoning in Creek. In 7th European Conference on Case-Based Reasoning ECCBR-04, 1–15.Jakobovits H. , Vermeir D. 1999. Dialectic semantics for argumentation frameworks. In Proceedings of the 7th International Conference on Artificial Intelligence and Law, ICAIL-99, ACM Press, 53–62.Díaz-Agudo, B., & González-Calero, P. A. (s. f.). An Ontological Approach to Develop Knowledge Intensive CBR Systems. Ontologies, 173-213. doi:10.1007/978-0-387-37022-4_7Reed C. , Walton D. 2005. Towards a formal and implemented model of argumentation schemes in agent communication. In Proceedings of the 1st International Workshop in Multi-Agent Systems, ArgMAS-04, 173–188.Sycara K. 1989. Argumentation: planning other agents’ plans. In 11th International Joint Conference on Artificial Intelligence, 1, 517–523. Morgan Kaufmann Publishers, Inc.Bench-Capon, T. J. M., & Dunne, P. E. (2007). Argumentation in artificial intelligence. Artificial Intelligence, 171(10-15), 619-641. doi:10.1016/j.artint.2007.05.001Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence, 13(1-2), 81-132. doi:10.1016/0004-3702(80)90014-4Amgoud L. , Kaci S. 2004. On the generation of bipolar goals in argumentation-based negotiation. In 1st International Workshop on Argumentation in Multi-Agent Systems, ArgMAS, Lecture Notes in Computer Science 3366, 192–207. Springer.CHESÑEVAR, C., MCGINNIS, MODGIL, S., RAHWAN, I., REED, C., SIMARI, G., … WILLMOTT, S. (2006). Towards an argument interchange format. The Knowledge Engineering Review, 21(4), 293-316. doi:10.1017/s0269888906001044Rahwan I. , Amgoud L. 2006. An argumentation-based approach for practical reasoning. In Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS-06, ACM Press, 347–354.Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155-169. doi:10.1007/bf01405730Soh L.-K. , Tsatsoulis C. 2001b. Reflective negotiating agents for real-time multisensor target tracking. In International Joint Conference on Artificial Intelligence, IJCAI-01, 1121–1127.Eemeren, F. H. van, & Grootendorst, R. (1984). Speech Acts in Argumentative Discussions. doi:10.1515/9783110846089Rissland E. L. , Skalak D. B. , Friedman M. T. 1993. Bankxx: a program to generate argument through case-based search. In International Conference on Artificial Intelligence and Law, ICAIL-93, 117–124.Sycara K. 1987. Resolving Adversarial Conflicts: An Approach Integrating Case-Based and Analytic Methods, PhD thesis, School of Information and Computer Science. Georgia Institute of Technology.Ontañón S. , Plaza E. 2007. Learning and joint deliberation through argumentation in multi-agent systems. In International Conference on Autonomous Agents and Multiagent Systems, AAMAS-07, 971–978.Rissland, E. L., & Skalak, D. B. (1991). CABARET: rule interpretation in a hybrid architecture. International Journal of Man-Machine Studies, 34(6), 839-887. doi:10.1016/0020-7373(91)90013-wDaniels J. J. , Rissland E. L. 1997. Finding legally relevant passages in case opinions. In 6th International Conference on Artificial Intelligence and Law, ICAIL-97, 39–47.Brüninghaus S. , Ashley K. D. 2005. Generating legal arguments and predictions from case texts. In 10th International Conference on Artificial Intelligence and Law, ICAIL-05, 65–74.Simari G. R. , García A. J. , Capobianco M. 2004. Actions, planning and defeasible reasoning. In Proceedings of the 10th International Workshop on Non-monotonic Reasoning, NMR-04, 377–384.Soh L.-K. , Tsatsoulis C. 2001a. Agent-based argumentative negotiations with case-based reasoning. 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Case-control study of the parkin gene in early-onset Parkinson disease

Background: Mutations in parkin are estimated to account for as much as 50% of familial Parkinson disease (PD) and 18% of sporadic PD. Single heterozygous mutations in parkin in both familial and sporadic cases may also increase susceptibility to PD. To our knowledge, all previous studies have been restricted to PD cases; this is the first study to systematically screen the parkin coding regions and exon deletions and duplications in controls. Objective: To determine the frequency and spectrum of parkin variants in early-onset PD cases (aged 50 years) and controls participating in a familial aggregation study. Patients and Methods: We sequenced the parkin gene in 101 cases and 105 controls. All cases and controls were also screened for exon deletions and duplications by semiquantitative multiplex polymerase chain reaction. Results: Thirteen (12.9% [95% confidence interval, 7%-21%]) of the 101 cases had a previously described parkin mutation: 1 was homozygous, 11 were heterozygous, and 1 was a compound heterozygote. The mutations Arg42Pro (exon 2) and Arg275Trp (exon 7) were recurrent. The previously reported synonymous substitution Leu261Leu (c.884A>G) was identified in 4 (3.9%) of 101 cases and 2 (2%) of 105 controls (P = .44). Excluding the synonymous substitution Leu261Leu (heterozygotes), 10 (9.9% [95% confidence interval, 4.6%-17.5%]) carried mutations. Conclusions: The frequency of mutations among cases that were not selected based on family history of PD is similar to what has previously been reported in sporadic PD. The similar frequency of Leu261Leu in cases and controls suggests it is a normal variant rather than a disease-associated mutation. We confirmed that heterozygous parkin mutations may increase susceptibility for early-onset PD

Emotional Substrates of White Racial Attitudes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91203/1/j.1540-5907.2011.00561.x.pd

Pennsylvania Folklife Vol. 37, No. 3

• Folk Artist Jacob Maentel of Pennsylvania and Indiana • Up Another River: Fourteen Days on the St. Johns • An Appreciation of Russell Wieder Gilbert • Holy Images: A Brief Study of Folk Religious Belief • Lamont Alfred Old Ironsides Pry, Contemporary American Folk Artist • Synopsis of the Penburne Quintethttps://digitalcommons.ursinus.edu/pafolklifemag/1119/thumbnail.jp

Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

BACKGROUND: Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. METHODS: We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis ( 10 years). The false discovery rate (q value) was used to account for multiple testing. RESULTS: The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). CONCLUSIONS: Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk

What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research

Genome-wide association study identifies the GLDC/IL33 locus associated with survival of osteosarcoma patients

Survival rates for osteosarcoma, the most common primary bone cancer, have changed little over the past three decades and are particularly low for patients with metastatic disease. We conducted a multi‐institutional genome‐wide association study (GWAS) to identify germline genetic variants associated with overall survival in 632 patients with osteosarcoma, including 523 patients of European ancestry and 109 from Brazil. We conducted a time‐to‐event analysis and estimated hazard ratios (HR) and 95% confidence intervals (CI) using Cox proportional hazards models, with and without adjustment for metastatic disease. The results were combined across the European and Brazilian case sets using a random‐effects meta‐analysis. The strongest association after meta‐analysis was for rs3765555 at 9p24.1, which was inversely associated with overall survival (HR = 1.76; 95% CI 1.41–2.18, p = 4.84 × 10−7). After imputation across this region, the combined analysis identified two SNPs that reached genome‐wide significance. The strongest single association was with rs55933544 (HR = 1.9; 95% CI 1.5–2.4; p = 1.3 × 10−8), which localizes to the GLDC gene, adjacent to the IL33 gene and was consistent across both the European and Brazilian case sets. Using publicly available data, the risk allele was associated with lower expression of IL33 and low expression of IL33 was associated with poor survival in an independent set of patients with osteosarcoma. In conclusion, we have identified the GLDC/IL33 locus on chromosome 9p24.1 as associated with overall survival in patients with osteosarcoma. Further studies are needed to confirm this association and shed light on the biological underpinnings of this susceptibility locus