ICM Articles

Displaying 1 - 5 of 79 records

Convexity and Monotonicity in Language Coordination: Simulating the Emergence of Semantic Universals in Populations of Cognitive Agents
(Springer Nature, 2023) Gierasimczuk, Nina; Kalociński, Dariusz; Rakowski, Franciszek; Uszyński, Jakub; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark; Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; National Information Processing Institute, Warsaw, Poland
Natural languages vary in their quantity expressions, but the variation seems to be constrained by general properties, so-called universals. Their explanations have been sought among constraints of human cognition, communication, complexity, and pragmatics. In this article, we apply a state-of-the-art language coordination model to the semantic domain of quantities to examine whether two quantity universals—monotonicity and convexity—arise as a result of coordination. Assuming precise number perception by the agents, we evolve communicatively usable quantity terminologies in two separate conditions: a numeric-based condition in which agents communicate about a number of objects and a quotient-based condition in which agents communicate about the proportions. We find out that both universals take off in all conditions but only convexity almost entirely dominates the emergent languages. Additionally, we examine whether the perceptual constraints of the agents can contribute to the further development of universals. We compare the degrees of convexity and monotonicity of languages evolving in populations of agents with precise and approximate number sense. The results suggest that approximate number sense significantly reinforces monotonicity and leads to further enhancement of convexity. Last but not least, we show that the properties of the evolved quantifiers match certain invariance properties from generalized quantifier theory.
SIR-Model for Households
(2023-01-11) Donges, Philipp; Gotz, Thomas; Kruger, Tyll; Niedzielewski, Karol; Priesemann, Viola; Schafer, Moritz; Max Planck Institute for dynamics and self–organization, Gottingen, Germany; Mathematical Institute, University Koblenz, Germany; Polytechnic University Wroclaw, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw
Households play an important role in disease dynamics. Many infections happening there due to the close contact, while mitigation measures mainly target the transmission between households. Therefore, one can see households as boosting the transmission depending on household size. To study the effect of household size and size distribution, we differentiated the within and between household reproduction rate. There are basically no preventive measures, and thus the close contacts can boost the spread. We explicitly incorporated that typically only a fraction of all household members are infected. Thus, viewing the infection of a household of a given size as a splitting process generating a new, small fully infected sub–household and a remaining still susceptible sub–household we derive a compartmental ODE model for the dynamics of the sub–households. In this setting, the basic reproduction number as well as prevalence and the peak of an infection wave in a population with given households size distribution can be computed analytically. We compare numerical simulation results of this novel household–ODE model with results from an agent–based model using data for realistic household size distributions of different countries. We find good agreement of both models showing the catalytic effect of large households on the overall disease dynamics.
Allogenic Adipose-Derived Stem Cells in Diabetic Foot Ulcer Treatment: Clinical Effectiveness, Safety, Survival in the Wound Site, and Proteomic Impact
(MDPI, 2023-01-12) Mrozikiewicz-Rakowska, Beata; Szabłowska-Gadomska, Ilona; Cysewski, Dominik; Rudziński, Stefan; Płoski, Rafał; Gasperowicz, Piotr; Konarzewska, Magdalena; Zieliński, Jakub; Mieczkowski, Mateusz; Sieńko, Damian; Grzela, Tomasz; Noszczyk, Maria; Paleska, Barbara; Czupryniak, Leszek; Lewandowska-Szumiel, Malgorzata; Department of Endocrinology, Centre of Postgraduate Medical Education, Warsaw, Poland; Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland; Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland; Department of Medical Genetics, Warsaw Medical University, Warsaw, Poland; Department of Forensic Medicine, Warsaw Medical University, Warsaw, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; Department of Diabetology and Internal Diseases, Medical University of Warsaw, Warsaw, Poland; Laboratory for Cell Research and Application, Medical University of Warsaw, Warsaw, Poland; Doctoral School, Medical University of Warsaw, Warsaw, Poland; Department of Histology and Embryology, Medical University of Warsaw, Warsaw, Poland; Melitus Aesthetic Medicine and Anti-Aging Clinic, Warsaw, Poland
Although encouraging results of adipose-derived stem cell (ADSC) use in wound healing are available, the mechanism of action has been studied mainly in vitro and in animals. This work aimed to examine the safety and efficacy of allogenic ADSCs in human diabetic foot ulcer treatment, in combination with the analyses of the wound. Equal groups of 23 participants each received fibrin gel with ADSCs or fibrin gel alone. The clinical effects were assessed at four time points: days 7, 14, 21 and 49. Material collected during debridement from a subset of each group was analyzed for the presence of ADSC donor DNA and proteomic changes. The reduction in wound size was greater at all subsequent visits, significantly on day 21 and 49, and the time to 50% reduction in the wound size was significantly shorter in patients who received ADSCs. Complete healing was achieved at the end of the study in seven patients treated with ADSCs vs. one treated without ADSCs. One week after ADSC application, 34 proteins significantly differentiated the material from both groups, seven of which, i.e., GAPDH, CAT, ACTN1, KRT1, KRT9, SCL4A1, and TPI, positively correlated with the healing rate. We detected ADSC donor DNA up to 21 days after administration. We confirmed ADSC-related improvement in wound healing that correlated with the molecular background, which provides insights into the role of ADSCs in wound healing—a step toward the development of cell-based therapies.
COVID-19 mRNA BNT162b2 vaccine immunogenicity among children with a history of paediatric multisystem inflammatory syndrome temporally associated with COVID-19 (PIMS-TS)
(Elsevier Ltd., 2023-05-05) Ludwikowska, Kamila M.; Popiel, Aneta; Matkowska-Kocjan, Agnieszka; Biela, Mateusz; Wójcik, Marta; Szenborn, Filip; Wielgos, Katarzyna; Pielka-Markiewicz, Ewa; Zaryczański, Janusz; Kursa, Miron B.; Szenborn, Leszek; Department of Pediatric Infectious Diseases, Wroclaw Medical University, Wrocław, Poland; Department of Histology and Embryology, Department of Human Morphology and Embryology, Wroclaw Medical University, Wrocław, Poland; Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland; Department of Paediatrics, J. Gromkowski Regional Specialist Hospital in Wroclaw, Wroclaw, Poland; University Clinical Hospital in Opole Pediatric Ward, Opole, Poland; Department of Paediatrics, Institute of Medical Sciences, University of Opole, Opole, Poland; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw
We conducted a prospective cohort study of 20 patients with a history of paediatric multisystem inflam- matory syndrome temporally associated with COVID-19 (PIMS group, median age seven years, 70% male) and 34 healthy controls without such a history (CONTROL group, median age eight years, 38% male) aged 5–12 years, to assess the immunogenicity of Pfizer-BioNTech COVID-19 mRNA BNT162b2 vaccine (ComirnatyÒ). Patients received two doses of COVID-19 mRNA BNT162b2 vaccine (10 ug/dose) 21 days apart. Pre-vaccine anti-S SARS-CoV-2 IgG antibodies were measured on the day of the first dose and at the median of 23 days after the second dose. The study was conducted during the COVID-19 wave dominated by the Omicron variant of the virus. Anti-NCP SARS-CoV-2 IgG antibodies were measured twice to evaluate incidents of infection during the study period. Pre-vaccine quantification of both types of antibodies allowed us to differentiate patients into COVID-19 naive and previously infected in order to compare hybrid immunity with vaccine-induced immunity. Before vaccination, anti-S IgG serum geometric mean concentration (GMC) was 61.17 BAU/ml in the PIMS group and 24.97 in the CONTROL group, while post-vaccination GMC was 3879.14 BAU/ml and 3704.87 BAU/ml, respectively, and did not significantly differ between the groups. Hybrid immunity (regardless of PIMS history) resulted in a higher concentration of SARS-CoV-2 anti-S antibodies after vaccination. Four (20%) of the children in the PIMS group and 11 (32%) in the CONTROL group got infected with SARS-CoV-2 during the study period, yet all of them asymptomatically, and this event has not significantly altered post-vaccination anti-S titers. In conclusion, COVID-19 vaccination was highly immunogenic in children, including those with a history of PIMS-TS; hybrid immunity overperforms vaccine-induced immunity in terms of serological response in children. However, vaccination effectiveness in preventing SARS-CoV-2 infections in children should be further evaluated.
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
(eLife Sciences Publications Ltd., 2023-06-02) Sherratt, Katharine; Gruson, Hugo; Grah, Rok; Johnson, Helen; Niehus, Rene; Prasse, Bastian; Sandmann, Frank; Deuschel, Jannik; Wolffram, Daniel; Abbott, Sam; Ullrich, Alexander; Gibson, Graham; Ray, Evan L; Reich, Nicholas G; Sheldon, Daniel; Wang, Yijin; Wattanachit, Nutcha; Wang, Lijing; Trnka, Jan; Obozinski, Guillaume; Sun, Tao; Thanou, Dorina; Pottier, Loic; Krymova, Ekaterina; Meinke, Jan H; Barbarossa, Maria Vittoria; Leithauser, Neele; Mohring, Jan; Schneider, Johanna; Wlazlo, Jaroslaw; Fuhrmann, Jan; Lange, Berit; Rodiah, Isti; Baccam, Prasith; Gurung, Heidi; Stage, Steven; Suchoski, Bradley; Budzinski, Jozef; Walraven, Robert; Villanueva, Inmaculada; Tucek, Vit; Smid, Martin; Zajicek, Milan; Perez Alvarez, Cesar; Reina, Borja; Bosse, Nikos I; Meakin, Sophie R; Castro, Lauren; Fairchild, Geoffrey; Michaud, Isaac; Osthus, Dave; Alaimo Di Loro, Pierfrancesco; Maruotti, Antonello; Eclerova, Veronika; Kraus, Andrea; Kraus, David; Pribylova, Lenka; Dimitris, Bertsimas; Li, Michael Lingzhi; Saksham, Soni; Dehning, Jonas; Mohr, Sebastian; Priesemann, Viola; Redlarski, Grzegorz; Bejar, Benjamin; Ardenghi, Giovanni; Parolini, Nicola; Ziarelli, Giovanni; Bock, Wolfgang; Heyder, Stefan; Hotz, Thomas; Singh, David E; Guzman- Merino, Miguel; Aznarte, Jose L; Morina, David; Alonso, Sergio; Alvarez, Enric; Lopez, Daniel; Prats, Clara; Burgard, Jan Pablo; Rodloff, Arne; Zimmermann, Tom; Kuhlmann, Alexander; Zibert, Janez; Pennoni, Fulvia; Divino, Fabio; Catala, Marti; Lovison, Gianfranco; Giudici, Paolo; Tarantino, Barbara; Bartolucci, Francesco; Lasinio, Giovanna Jona; Mingione, Marco; Farcomeni, Alessio; Srivastava, Ajitesh; Montero-Manso, Pablo; Adiga, Aniruddha; Hurt, Benjamin; Lewis, Bryan; Marathe, Madhav; Porebski, Przemyslaw; Venkatramanan, Srinivasan; Bartczuk, Rafal P; Dreger, Filip; Gambin, Anna; Gogolewski, Krzysztof; Gruziel-Slomka, Magdalena; Krupa, Bartosz; Moszyński, Antoni; Niedzielewski, Karol; Nowosielski, Jedrzej; Radwan, Maciej; Rakowski, Franciszek; Semeniuk, Marcin; Szczurek, Ewa; Zielinski, Jakub; Kisielewski, Jan; Pabjan, Barbara; Holger, Kirsten; Kheifetz, Yuri; Scholz, Markus; Biecek, Przemyslaw; Bodych, Marcin; Filinski, Maciej; Idzikowski, Radoslaw; Krueger, Tyll; Ozanski, Tomasz; Bracher, Johannes; Funk, Sebastian; London School of Hygiene & Tropical Medicine, London, United Kingdom; European Centre for Disease Prevention and Control (ECDC), Stockholm, Sweden; Karlsruhe Institute of Technology, Karlsruhe, Germany; Robert Koch Institute, Berlin, Germany; University of Massachusetts Amherst, Amherst, United States; Boston Children’s Hospital and Harvard Medical School, Boston, United States; Third Faculty of Medicine, Charles University, Prague, Czech Republic; Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland; Éducation nationale, Valbonne, France; Eidgenossische Technische Hochschule, Zurich, Switzerland; Forschungszentrum Jülich GmbH, Jülich, Germany; Frankfurt Institute for Advanced Studies, Frankfurt, Germany; raunhofer Institute for Industrial Mathematics, Kaiserslautern, Germany; Heidelberg University, Heidelberg, Germany; Helmholtz Centre for Infection Research, Braunschweig, Germany; IEM, Inc, Bel Air, United States; IEM, Inc, Baton Rouge, United States;; Institut d’Investigacions Biomèdiques August Pi i Sunyer, Universitat Pompeu Fabra, Barcelona, Spain; Institute of Computer Science of the CAS, Prague, Czech Republic; Institute of Information Theory and Automation of the CAS, Prague, Czech Republic; Inverence, Madrid, Spain; Los Alamos National Laboratory, Los Alamos, United States; LUMSA University, Rome, Italy; Masaryk University, Brno, Czech Republic; Massachusetts Institute of Technology, Cambridge, United States; Max-Planck-Institut für Dynamik und Selbstorganisation, Göttingen, Germany; Medical University of Gdansk, Gdańsk, Poland; Paul Scherrer Institute, Villigen, Switzerland; Politecnico di Milano, Milan, Italy; Technical University of Kaiserlautern, Kaiserslautern, Germany; Technische Universität Ilmenau, Ilmenau, Germany; Universidad Carlos III de Madrid, Leganes, Spain; Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain; Universitat de Barcelona, Barcelona, Spain; Universitat Politècnica de Catalunya, Barcelona, Spain; Universitat Trier, Trier, Germany; University of Cologne, Cologne, Germany; University of Halle, Halle, Germany; University of Ljubljana, Ljubljana, Slovenia; University of Milano-Bicocca, Milano, Italy; University of Molise, Pesche, Italy; University of Oxford, Oxford, United Kingdom; University of Palermo, Palermo, Italy; University of Pavia, Pavia, Italy; University of Perugia, Perugia, Italy; University of Rome "La Sapienza", Rome, Italy; University of Rome "Tor Vergata", Rome, Italy; University of Southern California, Los Angeles, United States; University of Sydney, Sydney, Australia; University of Virginia, Charlottesville, United States; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw; University of Bialystok, Poland; University of Wroclaw, Wroclaw, Poland; Universtät Leipzig, Leipzig, Germany; Warsaw University of Technology, Warsaw, Poland; Wroclaw University of Science and Technology, Wroclaw, Poland
Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.

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