Prognostic Value of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancers From Two Phase III Randomized Adjuvant Breast Cancer Trials: ECOG 2197 and ECOG 1199

Purpose Recent studies suggest that tumor-infiltrating lymphocytes (TILs) are associated with disease-free (DFS) and overall survival (OS) in operable triple-negative breast cancer (TNBC). We seek to validate the prognostic impact of TILs in primary TNBCs in two adjuvant phase III trials conducted by the Eastern Cooperative Oncology Group (ECOG). Patients and Methods Full-face hematoxylin and eosin–stained sections of 506 tumors from ECOG trials E2197 and E1199 were evaluated for density of TILs in intraepithelial (iTILs) and stromal compartments (sTILs). Patient cases of TNBC from E2197 and E1199 were randomly selected based on availability of sections. For the primary end point of DFS, association with TIL scores was determined by fitting proportional hazards models stratified on study. Secondary end points were OS and distant recurrence–free interval (DRFI). Reporting recommendations for tumor marker prognostic studies criteria were followed, and all analyses were prespecified. Results The majority of 481 evaluable cancers had TILs (sTILs, 80%; iTILs, 15%). With a median follow-up of 10.6 years, higher sTIL scores were associated with better prognosis; for every 10% increase in sTILs, a 14% reduction of risk of recurrence or death (P = .02), 18% reduction of risk of distant recurrence (P = .04), and 19% reduction of risk of death (P = .01) were observed. Multivariable analysis confirmed sTILs to be an independent prognostic marker of DFS, DRFI, and OS. Conclusion In two national randomized clinical trials using contemporary adjuvant chemotherapy, we confirm that stromal lymphocytic infiltration constitutes a robust prognostic factor in TNBCs. Studies assessing outcomes and therapeutic efficacies should consider stratification for this parameter

Development of 2nd generation aminomethyl spectinomycins that overcome native efflux in Mycobacterium abscessus

Mycobacterium abscessus (Mab), a nontuberculous mycobacterial (NTM) species, is an emerging pathogen with high intrinsic drug resistance. Current standard-of-care therapy results in poor outcomes, demonstrating the urgent need to develop effective antimycobacterial regimens. Through synthetic modification of spectinomycin (SPC), we have identified a distinct structural subclass of N-ethylene linked aminomethyl SPCs (eAmSPCs) that are up to 64-fold more potent against Mab over the parent SPC. Mechanism of action and crystallography studies demonstrate that the eAmSPCs display a mode of ribosomal inhibition consistent with SPC. However, they exert their increased antimicrobial activity through enhanced accumulation, largely by circumventing efflux mechanisms. The N-ethylene linkage within this series plays a critical role in avoiding TetV-mediated efflux, as lead eAmSPC 2593 displays a mere fourfold susceptibility improvement against Mab ΔtetV, in contrast to the 64-fold increase for SPC. Even a minor shortening of the linkage by a single carbon, akin to 1st generation AmSPC 1950, results in a substantial increase in MICs and a 16-fold rise in susceptibility against Mab ΔtetV. These shifts suggest that longer linkages might modify the kinetics of drug expulsion by TetV, ultimately shifting the equilibrium towards heightened intracellular concentrations and enhanced antimicrobial efficacy. Furthermore, lead eAmSPCs were also shown to synergize with various classes of anti-Mab antibiotics and retain activity against clinical isolates and other mycobacterial strains. Encouraging pharmacokinetic profiles coupled with robust efficacy in Mab murine infection models suggest that eAmSPCs hold the potential to be developed into treatments for Mab and other NTM infections

Bifidobacterium infantis strains with and without a combination of Oligofructose and Inulin (OFI) attenuate inflammation in DSS-induced colitis in rats

BACKGROUND: Pathogenesis of inflammatory bowel disease is thought to be through different factors and there is a relationship between the gut flora and the risk of its development. Probiotics can manipulate the microflora in chronic inflammation and may be effective in treating inflammation. Bifidobacterium are saccharolytic and their growth in the gut can be promoted by non-absorbable carbohydrates and its increase in the colon appears to be of benefit. METHODS: Oligofructose and inulin (OFI) alone and the two B. infantis DSM 15158 and DSM 15159 with and without OFI, were fed to Sprague-Dawley rats for 7 days prior to colitis induction and administrations continued for another 7 days with the DSS. Colitis severity assessed using a Disease Activity Index. Samples were collected 7 days after colitis induction, for intestinal bacterial flora, bacterial translocation, short chain fatty acids (SCFAs), myeloperoxidase (MPO), cytokines (IL-1β, TNF-α, IL-10 and TGF-β) and malondialdehyde (MDA). RESULTS: OFI alone or the B. infantis strains with and without OFI improved significantly the DAI and decreased colonic MPO activity. Colonic tissue IL-1β decreased significantly in all treated groups except B. infantis DSM 15158. MDA decreased significantly in B. infantis DSM 15159 with and without OFI compared to colitis control. Succinic acid increased significantly in OFI group with and without DSM 15159 compared to all groups. Sum values of propionic, succinic acid and butyric acid increased significantly in all groups compare to the colitis control. Bacterial translocation to mesenteric lymph nodes decreased significantly in all groups compared to colitis control. Translocation to the liver decreased significantly in all groups compare to the colitis control and OFI + B. infantis DSM 15158 groups. CONCLUSION: Administrations of OFI and Bifidobacterium improve DSS-induced acute colitis and have an anti-inflammatory effect. Major differences in effect were observed between the two B. infantis strains as indicated in MDA and succinic acid concentration as well as bacterial translocation rate in synbiotic combinations

Exploring the potential of phone call data to characterize the relationship between social network and travel behavior

[EN] Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. Part C 18, 45–54 (2010)Arentze, T.,Timmermans, H. J.: social networks, social interactions and activity-travel behavior: a framework for micro-simulation. Paper presented at the 85th annual meeting of the Transportation Research Board, Washington, D. C., Jan 2006 (2006)Arentze, T., Timmermans, H.: Social networks, social interactions, and activity-travel behavior: a framework for microsimulation. Environ. Plan. 35, 1012–1027 (2008)Axhausen, K.W.: Social networks and travel: some hypotheses. In: Donaghy, K.P., Poppelreuter, S., Rudinger, G. (eds.) Social Aspects of Sustainable Transport: Transatlantic Perspectives, pp. 90–108. Ashgate, Aldershot (2005)Bagrow, J.P., Lin, Y.-R.: Mesoscopic structure and social aspects of human mobility. PLoS One 7(5), 1–11 (2012)Bar-Gera, H.: Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: a case study from israel. Transp. Res. Part C 15(2007), 380–391 (2007)Becker, R.A., Cáceres, R., Hanson, K., Loh, J.M., Urbanek, S., Varshavsky, A., Volinsky, C.: A tale of one city: using cellular network data for urban planning. Pervasive Comput. IEEE 10(4), 18–26 (2011)Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439, 462 (2006)Caceres, N., Wideberg, J.P., Benitez, F.G.: Deriving origin–destination data from a mobile phone network. IET Intell. Transp. Syst. 1(1), 5–26 (2007)Caceres, N., Wideberg, J.P., Benitez, F.G.: Review of traffic data estimations extracted from cellular networks. IET Intell. Transp. Syst. 2(3), 179–192 (2008)Caceres, N., Romero, L.M., Benitez, F.G., Castillo, J.M.D.: Traffic flow estimation models using cellular phone data. IEEE Trans. Intell. Transp. Syst. 13(3), 1430–1441 (2012)Calabrese, F., Pereira, F. C., Lorenzo, G. D., Liu, L., Ratti, C.: The geography of taste: analyzing cell-phone mobility and social events. In: Proceedings of IEEE International Conference on Pervasive Computing (2010)Calabrese, F., Smoreda, Z., Blondel, V.D., Ratti, C.: Interplay between telecommunications and face-to-face interactions: a study using mobile phone data. PLoS One 6(7), e20814 (2011a). doi: 10.1371/journal.pone.0020814Calabrese, F., Lorenzo, G.D., Liu, L., Ratti, C.: Estimating origin-destination flows using mobile phone location data. Pervasive Comput. IEEE 10(4), 36–44 (2011b)Carrasco, J.A., Miller, E.J.: Exploring the propensity to perform social activities: social networks approach. Transportation 33, 463–480 (2006)Carrasco, J.A., Hogan, B., Wellman, B., Miller, E.J.: Collecting social network data to study social activity-travel behaviour: an egocentric approach. Environ. Plan. B 35(6), 961–980 (2008a)Carrasco, J.A., Hogan B., Wellman B., Miller E. J.: Agency in social activity and ICT interactions: The role of social networks in time and space, Tijdschrift voor Economische en Sociale Geografie (J. Eco. Soc. Geogr.), 99(5), 562–583 (2008b)Carrasco, J.A., Miller, E.J., Wellman, B.: How far and with whom do people socialize? Empirical evidence about the distance between social network members. Transp. Res. Rec. 2076, 114–122 (2008b)Carrasco, J.A., Miller, E.J.: The social dimension in action: a multilevel, personal networks model of social activity frequency. Transp. Res. Part A 43(1), 90–104 (2009)Chen, C., Mei, Y.: Does distance still matter in facilitating social ties? The roles of mobility patterns and the built environment. Presented at 93rd TRB annual meeting (2014)Cho E., Myers S.A., Leskovek J.: Friendship and mobility: user movement in location-based social networks. In: KDD ‘11 Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1082–1090 (2011)Clifton, K.J.: The social context of travel behavior. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 441–448. Emerald Press, London (2013)Do T., Gatica-Perez D.: Contextual conditional models for smartphone-based human mobility prediction. In: Proceedings ACM International Conference on Ubiquitous Computing, Pittsburgh, Sept (2012)Doyle, J., Hung, P., Kelly, D., Mcloone, S., Farrell, R.: Utilising mobile phone billing records for travel mode discovery. ISSC 2011, Trinity College Dublin, June (2011)Dubernet, T., Axhausen K. W.: Solution concepts for the simulation of household-level joint descision making in multi-agent travel simulation tools, paper presented at the 14th Swiss Transport Research Conference (STRC), Ascona (2014)Dugundji, E., Walker, J.: Discrete choice with social and spatial network interdependencies: an empirical example using mixed GEV models with field and “panel” effects. Transp. Res. Rec. 1921, 70–78 (2005)Eagle, N., Pentland, A., Lazer, D.: Inferring social network structure using mobile phone data. Proc. Natl. Acad. Sci. (PNAS) 106(36), 15274–15278 (2009)González, M.C., Hidalgo, C.A., Barabási, A.-L.: Understanding individual human mobility patterns. Nature 453(2008), 779–782 (2008)Gould, J.: Cell phone enabled travel surveys: the medium moves the message. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 51–70. Emerald Press, Bingley (2013)Habib, K.N., Carrasco, J.A.: Investigating the role of social networks in start time and duration of activities: a trivariate simultaneous econometric model. Transportation Research Record: Journal of the Transportation Research Board 2230, 1–8 (2011)Hackney, Jeremy K., Kay W. Axhausen: An agent model of social network and travel behavior interdependence. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Hackney, J., Marchal, F.: A model for coupling multi-agent social interactions and traffic simulation, in: TRB 2009 annual meeting (2009)Hackney, J., Marchal, F.: A coupled multi-agent microsimulation of social interactions and transportation behavior. Transp. Res. Part A 45, 296–309 (2011)Horni, A.: Destination choice modeling of discretionary activities in transport microsimulations, Ph.D. Thesis, ETH Zurich, Zurich (2013)Isaacman, S.,Becker, R., Caceres, R., Kobourov, S., Martonosi, M., Rowland, J., Varshavsky, A.: Identifying important places in people’s lives from cellular network data. In: Procedings International Conference on Pervasive Computing, San Francisco, June (2011)Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. Commun. Mag. IEEE 48(9), 140–150 (2010)Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., Van Alstyne, M.: Computational Social Science. Science 323, 721 (2009)Ma, H., Ronald, N., Arentze, T.A., Timmermans, H.J.P.: New credit mechanism for semicooperative agent-mediated joint activity-travel scheduling. Transp. Res. Rec. 2230, 104–110 (2011)Ma, H., Arentze, T. A., Timmermans, H. J. P.: Incorporating selfishness and altruism into dynamic joint activity-travel scheduling. Paper presented at the 13th international conference on Travel Behaviour Research (IATBR), Toronto, July (2012)Marchal, F., Nagel, K.: Allowed cooperative agents in a microsimulation to share information with each other about activity locations and about other agents, in order to optimize trip chains (2006)Molin, E.J.E., Arentze, T.A., Timmermans, H.J.P.: Social activities and travel demands : a model-based analysis of social-network data. Transp. Res. Rec. 2082, 168–175 (2007)Moore, J., Carrasco, J.A., Tudela, A.: Exploring the links between personal networks, time use, and the spatial distribution of social contacts. Transportation 40(4), 773–788 (2013)Onnela, J.-P., Saramaki, J., Hyvonen, J., Szabo, G., Lazer, D., et al.: Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. U.S.A. 104, 7332–7336 (2007)Páez, A., Scott, D.M.: Social influence on travel behavior: a simulation example of the decision to telecommute. Environ. Plan. A 39(3), 647–665 (2007)Phithakkitnukoon, S., Calabrese, F., Smoreda, Z., Ratti, C.: Out of sight out of mind: how our mobile social network changes during migration. Proceedings of the IEEE International Conference on Social Computing, pp. 515–520. Cambridge University Press, Cambridge (2011)Phithakkitnukoon, S., Smoreda, Z., Olivier, P.: Socio-geography of human mobility: a study using longitudinal mobile phone data. PLoS One 7(6), e39253 (2012). doi: 10.1371/journal.pone.0039253Ronald, N.A., Arentze, T.A., Timmermans, H.J.P.: Modeling social interactions between individuals for joint activity scheduling. Transp. Res. Part B 46, 276–290 (2012a)Ronald, N.A., Dignum, V., Jonker, C., Arentze, T.A., Timmermans, H.J.P.: On the engineering of agent-based simulations of social activities with social networks. Inf. Softw. Technol. 54(6), 625–638 (2012b)Rose, G.: Mobile phones as traffic probes: practices, prospects and issues. Transp. Rev. 26(3), 275–291 (2006)Sharmeen, F., Arentze, T., Timmermans, H.: A multilevel path analysis of social network dynamics and the mutual interdependencies between face-to-face and ICT modes of social interaction in the context of life-cycle events. In: Roorda, M.J., Miller, E.J. (eds.) Travel Behaviour Research: Current Foundations, Future Prospects, pp. 411–432. Lulu Press, Toronto (2013)Sharmeen, F., Arentze, T.A., Timmermans, H.J.P.: Dynamics of face-to-face social interaction frequency: role of accessibility, urbanization, changes in geographical distance and path dependence. J. Transp. Geogr. 34, 211–220 (2014)Silm, S., Ahas, R.: The seasonal variability of population in estonian municipalities. Environ. Plan. A 42, 2527–2546 (2010)Silvis, J., Niemeier, D., D’Souza, R.: Social networks and travel behavior: report from an integrated travel diary. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Sobolevsky, S., Szell, M., Campari, R., Couronné, T., Smoreda, Z., et al.: Delineating geographical regions with networks of human interactions in an extensive set of countries. PLoS One 8(12), e81707 (2013)Sohn, K., Kim, D.: Dynamic origin–destination flow estimation using cellular communication system. IEEE Trans. Veh. Technol. 57(5), 2703–2713 (2008)Song, C., Koren, T., Wang, P., Barabási, A.-L.: Modelling the scaling properties of human mobility. Nat. Phys. 6(2010), 818–823 (2010a)Song, C., Qu, Z., Blumm, N., Barabási, L.-L.: Limits of predictability in human mobility. Science 327(5968), 1018–1021 (2010b)Steenbruggen, J., Borzacchiello, M.T., Nijkamp, P., Scholten, H.: Mobile phone data from gsm networks for traffic parameter and urban spatial pattern assessment: A review of applications and opportunities. GeoJournal 78, 223–243 (2011). doi: 10.1007/s10708-011-9413-yVan den Berg, P., Arentze, T., Timmermans, H.J.P.: A path analysis of social networks, telecommunication and social activity–travel patterns. Transp. Res. Part C 26(2013), 256–268 (2013)Wang, H., Calabrese, F., Lorenzo, G. D., Ratti, C.: Transportation mode inference from anonymized and aggregated mobile phone call detail records. In: 13th international IEEE annual conference on intelligent transportation systems, 318–323 (2010)White, J. and Wells, I.: Extracting origin destination information from mobile phone data. Road transport information and Control, 19–21 Mar (2002)Yim, Y.: The state of cellular probes. California PATH Working Paper, UCB-ITS-PRR-2003-25 (2003)Ythier, J., Walker, J.L., Bierlaire, M.: The influence of social contacts and communication use on travel behavior: a smartphone-based study. In: Transportation Research Board annual meeting (2013

Cost-effectiveness of oral alitretinoin in patients with severe chronic hand eczema - a long-term analysis from a Swiss perspective

BACKGROUND: The impact on patients suffering from chronic hand eczema (CHE) is enormous, as no licensed systemic treatment option with proven efficacy for CHE is available. Alitretinoin is a novel agent which showed high clinical efficacy in patients with severe, refractory CHE. We assessed the cost-effectiveness of alitretinoin for CHE patient treatment from a Swiss third party payer perspective. A further objective of this study was to determine the burden of disease in Switzerland. METHODS: A long-term Markov cohort simulation model was used to estimate direct medical costs (euro) and clinical effectiveness (quality adjusted life years, QALYs) of treating severe CHE patients with alitretinoin. Comparison was against the standard treatment of supportive care (optimised emollient therapy). Information on response rates were derived from a randomized controlled clinical trial. Costs were considered from the perspective of the Swiss health system. Swiss epidemiological data was derived from official Swiss Statistic institutions. RESULTS: Annual costs of alitretinoin treatment accounted for 2'212 euro. After a time horizon of 22.4 years, average remaining long-term costs accounted for 42'208 euro or 38'795 euro in the alitretinoin and the standard treatment arm, respectively. Compared with the standard therapy, the addition of alitretinoin yielded an average gain of 0.230 QALYs at the end of the simulation. Accordingly, the incremental cost-effectiveness ratio resulted in 14'816 euro/QALY gained. These results were robust to changes in key model assumptions. CONCLUSION: The therapy for CHE patients is currently insufficient. In our long-term model we identified the treatment with alitretinoin as a cost-effective alternative for the therapy of CHE patients in Switzerland

The HOG Pathway Dictates the Short-Term Translational Response after Hyperosmotic Shock

In the global osmoshock translational response in yeast, some gene products were translationally mobilized without transcriptional up-regulation. Conversely, other transcriptionally up-regulated mRNAs were translationally inhibited. Analogous changes occurred on the protein level. These translational responses were strongly dependent on Hog1 and Rck2