Improved Surgical Outcomes for Breast Cancer Patients Receiving Neoadjuvant Aromatase Inhibitor Therapy: Results from a Multicenter Phase II Trial

Background: Neoadjuvant aromatase inhibitor therapy has been reported to improve surgical outcomes for postmenopausal women with clinical stage II or III hormone receptor-positive breast cancer. A multicenter phase II clinical trial was conducted to investigate the value of this approach for US surgical practice. Study Design: One hundred fifteen postmenopausal women with >2 cm, estrogen receptor (ER) or progesterone receptor (PgR)-positive breast cancer were enrolled in a trial of 16 to 24 weeks of letrozole 2.5 mg daily before operation. Results: One hundred six patients were eligible for primary analysis, 96 underwent operations, 7 received chemotherapy after progressive disease, and 3 did not undergo an operation. Baseline surgical status was marginal for breast-conserving surgery (BCS) in 48 (45%), 47 were definitely ineligible for BCS (44%), and 11 were inoperable by standard mastectomy (10%). Overall Response Evaluation Criteria In Solid Tumors clinical response rate in the breast was 62%, with 12% experiencing progressive disease. Fifty percent underwent BCS, including 30 of 46 (65%) patients who were initially marginal for BCS and 15 of 39 (38%) patients who were initially ineligible for BCS. All 11 inoperable patients successfully underwent operations, including 3 (27%) who had BCS. Nineteen percent of patients undergoing mastectomy had a pathologic T1 tumor, suggesting that some highly responsive tumors were overtreated surgically. Conclusions: Neoadjuvant aromatase inhibitor improves operability and facilitates BCS, but there was considerable variability in responsiveness. Better techniques to predict response, determine residual tumor burden before operation, and greater willingness to attempt BCS in responsive patients could additionally improve the rate of successful BCS

Synchronous communication in PLM environments using annotated CAD models

The connection of resources, data, and knowledge through communication technology plays a vital role in current collaborative design methodologies and Product Lifecycle Management (PLM) systems, as these elements act as channels for information and meaning. Despite significant advances in the area of PLM, most communication tools are used as separate services that are disconnected from existing development environments. Consequently, during a communication session, the specific elements being discussed are usually not linked to the context of the discussion, which may result in important information getting lost or becoming difficult to access. In this paper, we present a method to add synchronous communication functionality to a PLM system based on annotated information embedded in the CAD model. This approach provides users a communication channel that is built directly into the CAD interface and is valuable when individuals need to be contacted regarding the annotated aspects of a CAD model. We present the architecture of a new system and its integration with existing PLM systems, and describe the implementation details of an annotation-based video conferencing module for a commercial CAD application.This work was supported by the Spanish Ministry of Economy and Competitiveness and the FEDER Funds, through the ANNOTA project (Ref. TIN2013-46036-C3-1-R).Camba, JD.; Contero, M.; Salvador Herranz, GM.; Plumed, R. (2016). Synchronous communication in PLM environments using annotated CAD models. Journal of Systems Science and Systems Engineering. 25(2):142-158. https://doi.org/10.1007/s11518-016-5305-5S142158252Abrahamson, S., Wallace, D., Senin, N. & Sferro, P. (2000). Integrated design in a service marketplace. Computer-Aided Design, 32(2):97–107.Ahmed, S. (2005). Encouraging reuse of design knowledge: a method to index knowledge. Design Studies, 26:565–592.Alavi, M. & Tiwana, A (2002). Knowledge integration in virtual teams: the potential role of KMS. Journal of the American Society for Information Science and Technology, 53:1029–1037.Ameri, F. & Dutta, D. (2005). Product lifecycle management: closing the knowledge loops. Computer-Aided Design and Applications, 2(5):577–590.Anderson, A.H., Smallwood, L., MacDonald, R., Mullin, J., Fleming, A. & O'Malley, C. (2000). Video data and video links in mediated communication: what do users value? International Journal of Human-Computer Studies, 52(1):165–187.Arias, E., Eden, H., Fischer, G., Gorman, A. & Scharff, E. (2000). Transcending the individual human mind–creating shared understanding through collaborative design. ACM Transactions on Computer-Human Interaction (TOCHI) 7(1): 84–113.Barley, W.C., Leonardi, P.M., & Bailey, D.E. (2012). Engineering objects for collaboration: strategies of ambiguity and clarity at knowledge boundaries. Human Communication Research, 38:280–308.Boujut, J.F. & Dugdale, J. (2006). Design of a 3D annotation tool for supporting evaluation activities in engineering design. Cooperative Systems Design, COOP 6:1–8.Camba, J., Contero, M., Johnson, M. & Company, P. (2014). Extended 3D annotations as a new mechanism to explicitly communicate geometric design intent and increase CAD model reusability. Computer-Aided Design, 57:61–73.Camba, J., Contero, M. & Salvador-Herranz, G. (2014). Speak with the annotator: promoting interaction in a knowledge-based CAD environment built on the extended annotation concept. Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 196–201.Chudoba, K.M., Wynn, E., Lu, M. & Watson-Manheim, M.B. (2005). How virtual are we? Measuring virtuality and understanding its impact in a global organization. Information Systems Journal, 15(4):279–306.Danesi, F., Gardan, N. & Gardan, Y. (2006). Collaborative Design: from Concept to Application. Geometric Modeling and Imaging—New Trends, 90–96.Durstewitz, M., Kiefner, B., Kueke, R., Putkonen, H., Repo, P. & Tuikka, T. (2002). Virtual collaboration environment for aircraft design. Proceedings of the IEEE 6th International Conference on Information Visualisation, 502–507.Fisher, D., Brush, A.J., Gleave, E. & Smith, M.A. (2006). Revisiting Whittaker and Sidner’s email overload ten years later. Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work. ACM, BanffFonseca, M.J., Henriques, E., Silva, N., Cardoso, T. & Jorge, J.A. (2006). A collaborative CAD conference tool to support mobile engineering. Rapid Product Development (RPD’06), Marinha Grande, Portugal.Frechette, S.P. (2011). Model based enterprise for manufacturing. Proceedings of the 44th CIRP International Conference on Manufacturing Systems.Fu, W.X., Bian, J. & Xu, Y.M. (2013). A video conferencing system for collaborative engineering design. Applied Mechanics and Materials, 344:246–252.Fuh, J.Y.H. & Li, W.D. (2005). Advances in collaborative CAD: the-state-of-the art. Computer-Aided Design, 37:571–581.Fussell, S.R., Kraut, R.E. & Siegel, J. (2000). Coordination of communication: effects of shared visual context on collaborative work. Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, 21–30.Gajewska, H., Kistler, J., Manasse, M.S. & Redell, D. (1994). Argo: a system for distributed collaboration. Proceedings of the ACM Second International Conference on Multimedia, San Francisco, CA, USA. 433–440.Gantz, J., Reinsel, D., Chute, C., Schlichting, W., Mcarthur, J., Minton, S., Xheneti, I., Toncheva, A. & Manfrediz, A. (2007). The expanding digital universe: a forecast of worldwide information growth through 2010. IDC, Massachusetts.Gowan, Jr. J.A. & Downs, J.M. (1994). Video conferencing human-machine interface: a field study. Information and Management, 27(6):341–356.Gupta, A., Mattarelli, E., Seshasai, S. & Broschak, J. (2009). Use of collaborative technologies and knowledge sharing in co-located and distributed teams: towards the 24-h knowledge factory. The Journal of Strategic Information Systems, 18:147–161.Hickson, I. (2009). The Web Socket Protocol IETF, Standards Track.Hong, J., Toye, G. & Leifer, L.J. (1996). Engineering design notebook for sharing and reuse. Computers in Industry, 29:27–35.Isaacs, E.A. & Tang, J.C. (1994). What video can and cannot do for collaboration: a case study. Multimedia Systems, 2(2):63–73.Karsenty, L. (1999). Cooperative work and shared visual context: an empirical study of comprehension problems in side-by-side and remote help dialogues. Human Computer Interaction, 14(3): 283–315.Lahti, H., Seitamaa-Hakkarainen, P. & Hakkarainen, K. (2004). Collaboration patterns in computer supported collaborative designing. Design Studies, 25:351–371.Leenders, R.T.A., Van Engelen, J.M. & Kratzer, J. (2003). Virtuality, communication, and new product team creativity: a social network perspective. Journal of Engineering and Technology Management, 20(1):69–92.Levitt, R.E., Jin, Y. & Dym, C.L. (1991). Knowledge-based support for management of concurrent, multidisciplinary design. Artificial Intelligence for Engineering, Design, Analysis and Manufacturing, 5(2):77–95.Li, C., McMahon, C. & Newnes, L. (2009). Annotation in product lifecycle management: a review of approaches. Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2009. Vol. 2. New York: ASME, 797–806.Li, W.D., Lu, W.F., Fuh, J.Y. & Wong, Y.S. (2005). Collaborative computer-aided design-research and development status. Computer-Aided Design, 37(9):931–940.Londono, F., Cleetus, K.J., Nichols, D.M., Iyer, S., Karandikar, H.M., Reddy, S.M., Potnis, S.M., Massey, B., Reddy, A. & Ganti, V. (1992). Coordinating a virtual team. CERC-TR-RN-92-005, Concurrent Engineering Research Centre, West Virginia University, West Virginia.Lubell, J., Chen, K., Horst, J., Frechette, S., & Huang, P. (2012). Model based enterprise/technical data package summit report. NIST Technical Note, 1753.May, A. & Carter, C. (2001). A case study of virtual team working in the European automotive industry. International Journal of Industrial Ergonomics, 27(3):171–186.Olson, J.S., Olson, G.M. & Meader, D.K. (1995). What mix of video and audio is useful for small groups doing remote real-time design work? Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press, Addison-Wesley Publishing Co.Ping-Hung, H., Mishra, C.S. & Gobeli, D.H. (2003). The return on R&D versus capital expenditures in pharmaceutical and chemical industries. IEEE Transactions on Engineering Management, 50:141–150.Sharma, A. (2005). Collaborative product innovation: integrating elements of CPI via PLM framework. Computer-Aided Design, 37(13):1425–1434.Shum, S.J.B., Selvin, A.M., Sierhuis, M., Conklin, J., Haley, C.B. & Nuseibeh, B. (2006). Hypermedia support for argumentation-based rationale: 15 Years on from Gibis and Qoc. Rationale Management in Software Engineering, 111–132.Siltanen, P. & Valli, S. (2013). Web-based 3D Mediated Communication in Manufacturing Industry. Concurrent Engineering Approaches for Sustainable Product Development in a Multidisciplinary Environment, 1181–1192. Springer London.Stark, J. (2011). Product Lifecycle Management. 1–16. Springer London.Tavcar, J., Potocnik, U. & Duhovnik, J. (2013). PLM used as a backbone for concurrent engineering in supply chain. Concurrent Engineering Approaches for Sustainable Product Development in a Multi-Disciplinary Environment, 681–692.Tay, F.E.H. & Ming, C. (2001). A shared multi-media design environment for concurrent engineering over the internet. Concurrent Engineering, 9(1):55–63.Tay, F.E.H. & Roy, A. (2003). CyberCAD: a collaborative approach in 3D-CAD technology in a multimedia-supported environment. Computers in Industry, 52(2):127–145.Toussaint, J. & Cheng, K. (2002). Design agility and manufacturing responsiveness on the web. Integrated Manufacturing Systems, 13(5):328–339.Tsoi, K.N. & Rahman, S.M. (1996). Media-on-demand multimedia electronic mail: a tool for collaboration on the web. Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing.Upton, D.M. & Mcafee, A. (1999). The Real Virtual Factory. Harvard Business School Press, 69–89.Vila, C., Estruch, A., Siller, H.R., Abellán, J.V. & Romero, F. (2007). Workflow methodology for collaborative design and manufacturing. Cooperative Design, Visualization, and Engineering 42–49, Springer Berlin Heidelberg.Wasiak, J., Hicks, B., Newnes, L., Dong, A., & Burrow, L. (2010). Understanding engineering email: the development of a taxonomy for identifying and classifying engineering work. Research in Engineering Design, 21(1):43–64.Wasko, M.M. & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly: Management Information Systems, 29:35–57.Yang, Q.Z., Zhang, Y., Miao, C.Y. & Shen, Z.Q. (2008). Semantic annotation of digital engineering resources for multidisciplinary design collaboration. ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 617–624. American Society of Mechanical Engineers.You, C.F. & Chao, S.N. (2006). Multilayer architecture in collaborative environment. Concurrent Engineering Research and Applications, 14(4):273–281.Yuan, Y.C., Fulk, J., Monge, P.R. & Contractor, N. (2010). Expertise directory development, shared task interdependence, and strength of communication network ties as multilevel predictors of expertise exchange in transactive memory work groups. Communication Research, 37: 20–47

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Measurement of the inclusive production cross sections for forward jets and for dijet events with one forward and one central jet in pp collisions at sqrt(s) = 7 TeV

The inclusive production cross sections for forward jets, as well for jets in dijet events with at least one jet emitted at central and the other at forward pseudorapidities, are measured in the range of transverse momenta pt = 35-150 GeV/c in proton-proton collisions at sqrt(s) = 7 TeV by the CMS experiment at the LHC. Forward jets are measured within pseudorapidities 3.2<|eta|<4.7, and central jets within the |eta|<2.8 range. The double differential cross sections with respect to pt and eta are compared to predictions from three approaches in perturbative quantum chromodynamics: (i) next-to-leading-order calculations obtained with and without matching to parton-shower Monte Carlo simulations, (ii) PYTHIA and HERWIG parton-shower event generators with different tunes of parameters, and (iii) CASCADE and HEJ models, including different non-collinear corrections to standard single-parton radiation. The single-jet inclusive forward jet spectrum is well described by all models, but not all predictions are consistent with the spectra observed for the forward-central dijet events.Comment: Submitted to the Journal of High Energy Physic

Measurement of the charge ratio of atmospheric muons with the CMS detector

This is the pre-print version of this Article. The official published version can be accessed from the link below - Copyright @ 2010 ElsevierWe present a measurement of the ratio of positive to negative muon fluxes from cosmic ray interactions in the atmosphere, using data collected by the CMS detector both at ground level and in the underground experimental cavern at the CERN LHC. Muons were detected in the momentum range from 5 GeV/c to 1 TeV/c. The surface flux ratio is measured to be 1.2766 \pm 0.0032(stat.) \pm 0.0032 (syst.), independent of the muon momentum, below 100 GeV/c. This is the most precise measurement to date. At higher momenta the data are consistent with an increase of the charge ratio, in agreement with cosmic ray shower models and compatible with previous measurements by deep-underground experiments

Observation of a new Xi(b) baryon

The first observation of a new b baryon via its strong decay into Xi(b)^- pi^+ (plus charge conjugates) is reported. The measurement uses a data sample of pp collisions at sqrt(s) = 7 TeV collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 5.3 inverse femtobarns. The known Xi(b)^- baryon is reconstructed via the decay chain Xi(b)^- to J/psi Xi^- to mu^+ mu^- Lambda^0 pi^-, with Lambda^0 to p pi^-. A peak is observed in the distribution of the difference between the mass of the Xi(b)^- pi^+ system and the sum of the masses of the Xi(b)^- and pi^+, with a significance exceeding five standard deviations. The mass difference of the peak is 14.84 +/- 0.74 (stat.) +/- 0.28 (syst.) MeV. The new state most likely corresponds to the J^P=3/2^+ companion of the Xi(b).Comment: Submitted to Physical Review Letter

Alignment of the CMS silicon tracker during commissioning 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 silicon tracker, consisting of 1440 silicon pixel and 15 148 silicon strip detector modules, has been aligned using more than three million cosmic ray charged particles, with additional information from optical surveys. The positions of the modules were determined with respect to cosmic ray trajectories to an average precision of 3–4 microns RMS in the barrel and 3–14 microns RMS in the endcap in the most sensitive coordinate. The results have been validated by several studies, including laser beam cross-checks, track fit self-consistency, track residuals in overlapping module regions, and track parameter resolution, and are compared with predictions obtained from simulation. Correlated systematic effects have been investigated. The track parameter resolutions obtained with this alignment are close to the design performance.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)

Commissioning and performance of the CMS pixel tracker with cosmic ray muons

This is the Pre-print version of the Article. The official published verion of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe pixel detector of the Compact Muon Solenoid experiment consists of three barrel layers and two disks for each endcap. The detector was installed in summer 2008, commissioned with charge injections, and operated in the 3.8 T magnetic field during cosmic ray data taking. This paper reports on the first running experience and presents results on the pixel tracker performance, which are found to be in line with the design specifications of this detector. The transverse impact parameter resolution measured in a sample of high momentum muons is 18 microns.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)