Sustained safety and efficacy of ligelizumab in patients with chronic spontaneous urticaria: A one‐year extension study

Background: Ligelizumab, a next-generation, humanized anti-immunoglobulin E (IgE) monoclonal antibody is in development as a treatment for patients with chronic spontaneous urticaria, whose symptoms are inadequately controlled with standard-of-care therapy. Objective: To evaluate the long-term safety and re-treatment efficacy of ligelizumab 240 mg in patients who completed the core study and extension study. Methods: This open-label, single-arm, long-term Phase 2b extension study was designed to assess patients who were previously administered various doses of ligelizumab, omalizumab or placebo in the Phase 2b, dose-finding core study and who presented with active disease after Week 32. In the extension study, patients received ligelizumab 240 mg subcutaneously every 4 weeks, for 52 weeks and were monitored post-treatment for 48 weeks. Results: Overall, ligelizumab was well-tolerated with no newly identified safety signals. A total of 95.4% (226/237) screened patients received ligelizumab 240 mg in the extension study; 84.1% (190/226) of patients experienced at least one treatment-emergent adverse event. Most reported events were mild (41.6%) or moderate (35.8%) and mostly unrelated to the study treatment. At Week 12, 46.5% of patients had a complete response increasing to 53.1% after 52 weeks. Following 52 weeks of extension study treatment, 75.8% (95% confidence interval, 69.9, 81.3) of patients had cumulative complete responses. The median time to relapse in complete responders was 38 weeks. Conclusion: The long-term safety profile of ligelizumab 240 mg in patients with chronic spontaneous urticaria was consistent with the core study and re-treatment efficacy was shown. Trial registration: ClinicalTrials.gov Identifier: NCT02477332 and NCT02649218

Immunochemotherapy With Obinutuzumab or Rituximab for Previously Untreated Follicular Lymphoma in the GALLIUM Study: Influence of Chemotherapy on Efficacy and Safety

PurposeThe GALLIUM study (ClinicalTrials.gov identifier: NCT01332968) showed that obinutuzumab (GA101;G) significantly prolonged progression-free survival (PFS) in previously untreated patients with follicular lymphoma relative to rituximab (R) when combined with cyclophosphamide (C), doxorubicin, vincristine (V), and prednisone (P;CHOP);CVP;or bendamustine. This report focuses on the impact of chemotherapy backbone on efficacy and safety.Patients and Methods: A total of 1,202 patients with previously untreated follicular lymphoma (grades 1 to 3a), advanced disease (stage III or IV, or stage II with tumor diameter 7 cm), Eastern Cooperative Oncology Group performance status 0 to 2, and requiring treatment were randomly assigned 1:1 to G 1,000 mg on days 1, 8, and 15 of cycle 1 and day 1 of subsequent cycles or R 375 mg/m(2) on day 1 of each cycle, for six to eight cycles, depending on chemotherapy (allocated nonrandomly by center). Responding patients received G or R for 2 years or until disease progression.Results: Baseline Follicular Lymphoma International Prognostic Index risk, bulky disease, and comorbidities differed by chemotherapy. After 41.1 months median follow-up, PFS (primary end point) was superior for G plus chemotherapy (overall hazard ratio [HR], 0.68;95% CI, 0.54 to 0.87;P = .0016), with consistent results across chemotherapy backbones (bendamustine: HR, 0.63;95% CI, 0.46 to 0.88;CHOP: HR, 0.72;95% CI, 0.48 to 1.10;CVP: HR, 0.79;95% CI, 0.42 to 1.47). Grade 3 to 5 adverse events, notably cytopenias, were most frequent with CHOP. Grade 3 to 5 infections and second neoplasms were most frequent with bendamustine, which was associated with marked and prolonged reductions in T-cell counts. Fatal events were more frequent in patients treated with bendamustine, possibly reflecting differences in patient risk profiles.Conclusion: Improved PFS was observed for G plus chemotherapy for all three chemotherapy backbones. Safety profiles differed, although comparisons are confounded by nonrandom chemotherapy allocation

Development and Validation of Automated Magnetic Resonance Parkinsonism Index 2.0 to Distinguish Progressive Supranuclear Palsy-Parkinsonism From Parkinson's Disease

Background: Differentiating progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) is clinically challenging. Objective: This study aimed to develop an automated Magnetic Resonance Parkinsonism Index 2.0 (MRPI 2.0) algorithm to distinguish PSP-P from PD and to validate its diagnostic performance in two large independent cohorts. Methods: We enrolled 676 participants: a training cohort (n = 346; 43 PSP-P, 194 PD, and 109 control subjects) from our center and an independent testing cohort (n = 330; 62 PSP-P, 171 PD, and 97 control subjects) from an international research group. We developed a new in-house algorithm for MRPI 2.0 calculation and assessed its performance in distinguishing PSP-P from PD and control subjects in both cohorts using receiver operating characteristic curves. Results: The automated MRPI 2.0 showed excellent performance in differentiating patients with PSP-P from patients with PD and control subjects both in the training cohort (area under the receiver operating characteristic curve [AUC] = 0.93 [95% confidence interval, 0.89–0.98] and AUC = 0.97 [0.93–1.00], respectively) and in the international testing cohort (PSP-P versus PD, AUC = 0.92 [0.87–0.97]; PSP-P versus controls, AUC = 0.94 [0.90–0.98]), suggesting the generalizability of the results. The automated MRPI 2.0 also accurately distinguished between PSP-P and PD in the early stage of the diseases (AUC = 0.91 [0.84–0.97]). A strong correlation (r = 0.91, P < 0.001) was found between automated and manual MRPI 2.0 values. Conclusions: Our study provides an automated, validated, and generalizable magnetic resonance biomarker to distinguish PSP-P from PD. The use of the automated MRPI 2.0 algorithm rather than manual measurements could be important to standardize measures in patients with PSP-P across centers, with a positive impact on multicenter studies and clinical trials involving patients from different geographic regions. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Sustained safety and efficacy of ligelizumab in patients with chronic spontaneous urticaria: A one‐year extension study

Background Ligelizumab, a next-generation, humanized anti-immunoglobulin E (IgE) monoclonal antibody is in development as a treatment for patients with chronic spontaneous urticaria, whose symptoms are inadequately controlled with standard-of-care therapy. Objective To evaluate the long-term safety and re-treatment efficacy of ligelizumab 240 mg in patients who completed the core study and extension study. Methods This open-label, single-arm, long-term Phase 2b extension study was designed to assess patients who were previously administered various doses of ligelizumab, omalizumab or placebo in the Phase 2b, dose-finding core study and who presented with active disease after Week 32. In the extension study, patients received ligelizumab 240 mg subcutaneously every 4 weeks, for 52 weeks and were monitored post-treatment for 48 weeks. Results Overall, ligelizumab was well-tolerated with no newly identified safety signals. A total of 95.4% (226/237) screened patients received ligelizumab 240 mg in the extension study; 84.1% (190/226) of patients experienced at least one treatment-emergent adverse event. Most reported events were mild (41.6%) or moderate (35.8%) and mostly unrelated to the study treatment. At Week 12, 46.5% of patients had a complete response increasing to 53.1% after 52 weeks. Following 52 weeks of extension study treatment, 75.8% (95% confidence interval, 69.9, 81.3) of patients had cumulative complete responses. The median time to relapse in complete responders was 38 weeks. Conclusion The long-term safety profile of ligelizumab 240 mg in patients with chronic spontaneous urticaria was consistent with the core study and re-treatment efficacy was shown. Trial Registration: ClinicalTrials.gov Identifier: NCT02477332 and NCT02649218

Modelling the risk of Taenia solium exposure from pork produced in western Kenya

The tapeworm Taenia solium is the parasite responsible for neurocysticercosis, a neglected tropical disease of public health importance, thought to cause approximately 1/3 of epilepsy cases across endemic regions. The consumption of undercooked infected pork perpetuates the parasite’s life-cycle through the establishment of adult tapeworm infections in the community. Reducing the risk associated with pork consumption in the developing world is therefore a public health priority. The aim of this study was to estimate the risk of any one pork meal in western Kenya containing a potentially infective T. solium cysticercus at the point of consumption, an aspect of the parasite transmission that has not been estimated before. To estimate this, we used a quantitative food chain risk assessment model built in the @RISK add-on to Microsoft Excel. This model indicates that any one pork meal consumed in western Kenya has a 0.006 (99% Uncertainty Interval (U.I). 0.0002–0.0164) probability of containing at least one viable T. solium cysticercus at the point of consumption and therefore being potentially infectious to humans. This equates to 22,282 (99% U.I. 622–64,134) potentially infective pork meals consumed in the course of one year within Busia District alone. This model indicates a high risk of T. solium infection associated with pork consumption in western Kenya and the work presented here can be built upon to investigate the efficacy of various mitigation strategies for this locality

Nuclear SUN1 stabilizes endothelial cell junctions via microtubules to regulate blood vessel formation

Endothelial cells line all blood vessels, where they coordinate blood vessel formation and the blood-tissue barrier via regulation of cell-cell junctions. The nucleus also regulates endothelial cell behaviors, but it is unclear how the nucleus contributes to endothelial cell activities at the cell periphery. Here, we show that the nuclear-localized linker of the nucleoskeleton and cyto-skeleton (LINC) complex protein SUN1 regulates vascular sprouting and endothelial cell-cell junction morphology and function. Loss of murine endothelial Sun1 impaired blood vessel formation and destabilized junctions, angiogenic sprouts formed but retracted in SUN1-depleted sprouts, and zebrafish vessels lacking Sun1b had aberrant junctions and defective cell-cell connections. At the cellular level, SUN1 stabilized endothelial cell-cell junctions, promoted junction function, and regulated contractility. Mechanistically, SUN1 depletion altered cell behaviors via the cytoskeleton without changing transcriptional profiles. Reduced peripheral microtubule density, fewer junction contacts, and increased catastrophes accompanied SUN1 loss, and microtubule depolymerization phenocopied effects on junctions. Depletion of GEF-H1, a microtubule-regulated Rho activator, or the LINC complex protein nesprin-1 rescued defective junctions of SUN1-depleted endothelial cells. Thus, endothelial SUN1 regulates peripheral cell-cell junctions from the nucleus via LINC complex-based microtubule interactions that affect peripheral microtubule dynamics and Rho-regulated contractility, and this long-range regulation is important for proper blood vessel sprouting and junction integrity

A framework to move forward on the path to eco-innovation in the construction industry: implications to improve firms´ sustainable orientation

This paper examines key aspects in the innovative behavior of the construction firms that determine their environmental orientation while innovating. Structural equation modeling was used and data of 222 firms retrieved from the Spanish Technological Innovation Panel (PITEC) for 2010 to analyse the drivers of environmental orientation of the construction firms during the innovation process. The results show that the environmental orientation is positively affected by the product and process orientation of construction firms during the innovation process. Furthermore, the positive relation between the importance of market information sources and environmental orientation, mediated by process and product orientation, is discussed. Finally, a model that explains these relations is proposed and validated. Results have important managerial implications for those companies worried about their eco-innovative focus as the types of actions and relations within firms most suitable for improving their eco-innovative orientation are highlighted.The authors would like to thank the Spanish Economy and Competitiveness Ministry for its support through the research project (EC02011-27369) and also the Universitat Politecnica de Valencia (SP20140647).Segarra Oña, MDV.; Peiró Signes, A.; Cervelló Royo, RE. (2015). A framework to move forward on the path to eco-innovation in the construction industry: implications to improve firms´ sustainable orientation. Science and Engineering Ethics. 21(6):1469-1484. https://doi.org/10.1007/s11948-014-9620-2S14691484216Amara, N., & Landry, R. (2005). Sources of information as determinants of novelty of innovation in manufacturing firms: evidence from the 1999 statistics Canada innovation survey. Technovation, 25(3), 245–259.Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two- step approach. Psychological Bulletin, 103(3), 411–423.Ang, G. K. I. (2004). Competing revaluing construction paradigms in practice. Rotterdam: CIB.Audet, R., & Guyonnaud, M. F. (2013). Transition in practice and action in research. A French case study in piloting eco-innovations. Innovation: The European Journal of Social Science Research, 26(4), 398–415.Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 18(1), 74–94.Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least square (PLS) approach to causal modelling: Personal computer adoption and use as an illustration. Technology Studies, Special Issue on Research Methodology, 2(2), 285–309.Barrett, P. (2007). Revaluing construction: A holistic model. Building Research and Information, 35(3), 268–286.Barrett, P., & Lee, A. (2005). Revaluing construction: A CIB priority theme, Salford Centre for Research and Innovation. Salford/CIB: University of Salford, Rotterdam.Beamon, B. M. (2005). Environmental and sustainability ethics in supply chain management. Science and Engineering Ethics, 11(2), 221–234.Burciu, A., Bostan, I., Condrea, P., & Grosu, V. (2010). Financing the environmental policies in the communitarian space. Environmental Engineering and Management Journal, 9(9), 1179–1185.Carrascosa-López, C., Peiró-Signes, Á., & Segura-García-del-Río, B. (2012). Does it pay to be greener than legislation? An empirical study of spanish tile industry. Journal of Sustainable Development, 5(5), 17–26.Carter, T., & Fowler, L. (2008). Establishing green roof infrastructure through environmental policy instruments. Environmental Management, 42(1), 151–164.Cervelló-Royo, R., Garrido-Yserte, R., & Segura-García del Río, B. (2012). An urban regeneration model in heritage areas in search of sustainable urban development and internal cohesion. Journal of Cultural Heritage Management and Sustainable Development, 2(1), 44–61.Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–358). New Jersey: Lawrence Erlbaum Associates.Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modelling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic mail emotion/adoption study. Information Systems Research, 14(2), 189–217.Commission, European. (2004). Facing the challenge: The Lisbon strategy for growth and employment Brussels. Brussels: European Comission.Commission of the European Communities (2006). Action Plan for Energy Efficiency: Realising the Potential, Brussels. http://ec.europa.eu/energy/action_plan_energy_efficiency/doc/com_2006_0545_en.pdf . (Accessed 31/01/2014).Courtney, R., & Winch, G. (2002). CIB strategy for re-engineering construction. Rotterdam: CIB.Courtney, R., & Winch, G. M. (2003). Re-engineering construction: The role of research and implementation. Building Research and Information, 31(2), 172–178.Davis, M. (2001). The professional approach to engineering ethics: Five research questions. Science and Engineering Ethics, 7, 379–390.Ding, G. K. C. (2008). Sustainable construction. The role of environmental assessment tools. Journal of Environmental Management, 86(3), 451–464.Du Plessis, C., & Cole, R. J. (2011). Motivating change: Shifting the paradigm. Building Research and Information, 39(5), 436–449.Esty, D. C., & Winston, A. S. (2006). Green to gold, how smart companies use environmental strategy to innovate, create value, and build competitive advantage. Hoboken: Wiley.European Commission (2010) Europe 2020: A strategy for smart, sustainable and inclusive growth, Brussels.Falk, R., & Miller, N. (1992). A primer on soft modelling. Akron: The University of Akron Press.Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 328–388.Freeman, R. E. (1994). The politics of stakeholder theory: Some future directions. Business Ethics Quarterly, 4(4), 409–422.Gázquez-Abad, J. C., Huertas-García, R., Vázquez-Gómez, M. D., & Romeo, A. C. (2014). Drivers of sustainability strategies in Spain’s wine tourism industry. Cornell Hospitality Quarterly, 1938965514549657.Gebauer, H., Gustafsson, A., & Witell, L. (2011). Competitive advantage through service differentiation by manufacturing companies. Journal of Business Research, 64(12), 1270–1280.Geisser, S. (1975). A predictive approach to the random effect model. Biometrika, 61(1), 101–107.González-Benito, O., & González-Benito, J. (2008). Implications of market orientation on the environmental transformation of industrial firms. Ecological Economics, 64(4), 752–762.Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least square path modelling in international marketing. In I. Rudolf, R. Sinkovics & N. Pervez (Eds.), Advance in international marketing (Vol. 20, pp. 277–319).Hill, S., & Lorenz, D. (2011). Rethinking professionalism: Guardianship of land and resources. Building Research and Information, 39(3), 314–319.Huedo, P., & Lopez-Mesa, B. (2013). Review of tools to assist in the selection of sustainable building assemblies. Informes de la Construcción, 65(529), 77–88.IPCC. (2007a). Climate change 2007: The physical science basis. summary for policymakers: Contribution of working group i to the fourth assessment report of the intergovernmental panel on climate change. Geneva: IPCC.IPCC. (2007b). Mitigation. contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Geneva: IPCC.Jensen, J. S., Gottlieb, S. C., & Thuese, C. L. (2011). Construction sector development: Frames and governance responses. Building Research and Information, 39(6), 665–667.Kibert, Ch J. (2007). The next generation of sustainable construction. Building Research & Information, 35(6), 595–601.Kim, Y., Brodhag, C., & Mebratu, D. (2014). Corporate social responsibility driven innovation. Innovation: The European Journal of Social Science Research, 27(2), 175–196.Kuhn, S. (2001). Commentary on: The greening of engineers: A cross-cultural experience. Science and Engineering Ethics, 7(1), 123–124.Lam, P. T., Chan, E. H., Chau, C. K., Poon, C. S., & Chun, K. P. (2011). Environmental management system vs green specifications: How do they complement each other in the construction industry? Journal of Environmental Management, 92(3), 788–795.Leimeister, S., Leimeister, J. M., & Knebel, U. (2009). A cross-national comparison of perceived strategic importance of RFID for CIOs in Germany and Italy. International Journal of Information Management, 29(1), 37–47.Leman, A., & Bordass, B. (2007). Are users more tolerant of green buildings? Building Research and Information, 35(6), 662–673.Liefferink, D., & Andersen, M. S. (1998). Strategies of the green member states in EU environmental policy-making. Journal of European Public Policy, 5(2), 254–270.Losada, B. (2013). Smart cities through the smart grid: The sustainable smart city and its energy dependence. DYNA, 88(2), 154–155.Luetzkendorf, T. (2010). Sustainable properties-dream or trend? Informes de la Construcción, 61(517), 5–15.Lützkendorf, T., & Lorenz, D. (2007). Integrating sustainability into property risk assessments for market transformation. Building Research and Information, 35(6), 644–671.Matthyssensa, P., & Vandenbempt, K. (2008). Moving from basic offerings to value-added solutions: Strategies, barriers and alignment. Industrial Marketing Management, 37(3), 316–328.McKeiver, C., & Gadenne, D. (2005). Environmental management systems in small and medium business. Small Business Journal, 23(5), 513–537.Nunnally, J. C., & Bernstein, I. H. (1995). Teoría psicométrica. México: McGraw-Hill.Parsa, H. G., Segarra-Oña, M., Jang, S. S., Chen, R., & Singh, A. J. (2014). Special issue on sustainable and eco-innovative practices in hospitality and tourism. Cornell Hospitality Quarterly, 55(1), 5–5.Pearce, D. (2006). Is the construction sector sustainable? Building Research and Information, 34(3), 201–207.Peiró-Signes, A., Miret-Pastor, L. L., Segarra-Oña, M. V., & De Miguel Molina, B. (2013). Analysing the determinants of better performance through eco management tools at the food industry: An empirical study. In P. Golinska (Ed.), Eco Production and logistics (pp. 73–90). Heidelberg: Springer.Peiró-Signes, A., Verma, R., Mondéjar-Jiménez, J., & Vargas-Vargas, M. (2014). The impact of environmental certification on hotel guest ratings. Cornell Hospitality Quarterly, 55(1), 40–51.Petruzzelli, A. M., Dangelico, R. M., Rotolo, D., & Albino, V. (2011). Organizational factors and technological features in the development of green innovations: Evidence from patent analysis. Innovation: Management, Policy and Practice, 13(3), 291–310.Porter, M. E., & Kramer, M. R. (2006). Strategy and society: The link between competitive advantage and corporate social responsibility. Harvard Business Review, 84(12), 78–92.Porter, M. E., & Van der Linde, C. (1995). Toward a new conception of the environment competitiveness relationship. Journal of Economic Perspectives, 9(4), 97–118.Rennings, K. (2002). Redefining innovation—Eco-innovation research and the contribution from ecological economics. Ecological Economics, 32(2), 319–332.Rennings, K., Ziegler, A., Ankele, K., & Hoffman, E. (2006). The influence of different characteristics of the eu environmental management and auditing scheme on technical environmental innovations and economic performance. Ecological Economics, 57(1), 45–59.Ringle, C. M., Wende, S., & Will, A. (2005). SmartPLS 2.0 M3. http:// www.smartpls.de .Sánchez-Ollero, J. L., García-Pozo, A., & Marchante-Mera, A. (2013). How does respect for the environment affect final prices in the hospitality sector? A hedonic pricing approach. Cornell Hospitality Quarterly, 55, 31–39.Schmidt, V. A., & Radaelli, C. M. (2004). Policy change and discourse in Europe: Conceptual and methodological issues. West European Politics, 27(2), 183–210.Segarra-Oña, M.D.V., M.Peiró-Signes, Á., Verma, R., & Miret-Pastor, L. (2012). Does environmental certification help the economic performance of hotels? Evidence from the spanish hotel industry. Cornell Hospitality Quarterly, 1938965512446417.Segarra-Oña, M. V., Peiró-Signes, A., Albors-Garrigós, J., & Miret-Pastor, P. (2011). Impact of innovative practices in environmentally focused firms: Moderating factors. International Journal of Environmental Research, 5(2), 425–434.Segarra-Oña, M. D. V., Peiró-Signes, A., & Mondéjar-Jiménez, J. (2013). Identifying variables affecting the proactive environmental orientation of firms: An empirical study. Polish Journal of Environmental Studies, 22(3), 873–880.Sharma, A., Thomas, D., & Konsynski, B. (2008). Strategic and institutional perspectives in the evaluation, adoption and early integration of radio frequency identification (RFID): An empirical investigation of current and potential adopters. Proceedings of the 41st Hawaii international conference on system science, Waikoloa, Big Island, Hawaii, USA (pp 407–420).Sigala, M. (2014). Customer involvement in sustainable supply chain management a research framework and implications in tourism. Cornell Hospitality Quarterly, 55(1), 76–88.Song, M., Peng, J., Liu, W., & An, Q. (2014). A PSBM model for environmental efficiency evaluation and its application. Polish Journal of Environmental Studies, 23(3), 893–900.Stern, N. (2006). The economics of climate change: The stern review. Cambridge: Cambridge University Press.Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36, 111–147.Stone, G. W., & Wakefield, K. L. (2000). Eco-orientation: An extension of market orientation in an environmental context. Journal of Marketing Theory and Practice, 8(3), 21–31.Tenenhaus, M., Vinzi, V., Chatelin, J., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159–205.Tse, R. Y. (2001). The implementation of EMS in construction firms: Case study in Hong Kong. Journal of Environmental Assessment Policy and Management, 3(2), 177–194.Turner, R. K. (2006). Sustainability auditing and assessment challenges. Building Research and Information, 34(3), 197–200.Van Bueren, E., & De Jong, J. J. (2007). Establishing sustainability: Policy successes and failures. Building Research and Information, 35(5), 543–556.Vanasupa, L., Chen, K. C., & Slivovsky, L. (2006). Global challenges as inspiration: A classroom strategy to foster social responsibility. Science and Engineering Ethics, 12(2), 373–380.Vastag, G., Kerekes, S., & Rondinelli, D. A. (1996). Evaluation of corporate environmental management approaches: A framework and application. International Journal of Production Economics, 43(2–3), 193–211