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International audience Road cycling ranks among the most intense endurance exercises. Previous studies and mathematical models describing road cycling have not analysed performances per se. We describe the evolution of road cycling performance over the past 116 years. We studied the top ten cyclists' mean speeds in eight famous classic races and three European Grand Tours, using a previously published multi-exponential model that highlights the different progression periods of an event during the century. In addition, we measured an indicator of difficulty for the Tour de France by calculating the climbing index (i.e. the total altitude climbed over total distance). The eleven races' mean speed increased progressively from 23.13 km · h-1 in 1892 to 41.19+2.03 km • h-1 in 2008. Road cycling development, like other quantifiable disciplines, fits a piecewise progression pattern that follows three periods: before, between, and after the two World Wars. However, a fourth period begins after 1993, providing a speed progression of 6.38% from the third one. The Tour de France's climbing index also provided insight into a recent paradoxical relationship with speeds: when the climbing index increased, the winner's speed also increased. Our results show a major improvement (6.38%) in road cycling performance in the last 20 years and question the role of extra-physiological parameters in this recent progression.

International audience ; Sex is a major factor influencing best performances and world records. Here the evolution of the difference between men and women's best performances is characterized through the analysis of 82 quantifiable events since the beginning of the Olympic era. For each event in swimming, athletics, track cycling, weightlifting and speed skating the gender gap is fitted to compare male and female records. It is also studied through the best performance of the top 10 performers in each gender for swimming and athletics. A stabilization of the gender gap in world records is observed after 1983, at a mean difference of 10.0% ± 2.94 between men and women for all events. The gender gap ranges from 5.5% (800-m freestyle, swimming) to 18.8% (long jump). The mean gap is 10.7% for running performances, 17.5% for jumps, 8.9% for swimming races, 7.0% for speed skating and 8.7% in cycling. The top ten performers' analysis reveals a similar gender gap trend with a stabilization in 1982 at 11.7%, despite the large growth in participation of women from eastern and western countries, that coincided with later-published evidence of state-institutionalized or individual doping. These results suggest that women will not run, jump, swim or ride as fast as men.

International audience ; Sex is a major factor influencing best performances and world records. Here the evolution of the difference between men and women's best performances is characterized through the analysis of 82 quantifiable events since the beginning of the Olympic era. For each event in swimming, athletics, track cycling, weightlifting and speed skating the gender gap is fitted to compare male and female records. It is also studied through the best performance of the top 10 performers in each gender for swimming and athletics. A stabilization of the gender gap in world records is observed after 1983, at a mean difference of 10.0% ± 2.94 between men and women for all events. The gender gap ranges from 5.5% (800-m freestyle, swimming) to 18.8% (long jump). The mean gap is 10.7% for running performances, 17.5% for jumps, 8.9% for swimming races, 7.0% for speed skating and 8.7% in cycling. The top ten performers' analysis reveals a similar gender gap trend with a stabilization in 1982 at 11.7%, despite the large growth in participation of women from eastern and western countries, that coincided with later-published evidence of state-institutionalized or individual doping. These results suggest that women will not run, jump, swim or ride as fast as men.

International audience ; Sex is a major factor influencing best performances and world records. Here the evolution of the difference between men and women's best performances is characterized through the analysis of 82 quantifiable events since the beginning of the Olympic era. For each event in swimming, athletics, track cycling, weightlifting and speed skating the gender gap is fitted to compare male and female records. It is also studied through the best performance of the top 10 performers in each gender for swimming and athletics. A stabilization of the gender gap in world records is observed after 1983, at a mean difference of 10.0% ± 2.94 between men and women for all events. The gender gap ranges from 5.5% (800-m freestyle, swimming) to 18.8% (long jump). The mean gap is 10.7% for running performances, 17.5% for jumps, 8.9% for swimming races, 7.0% for speed skating and 8.7% in cycling. The top ten performers' analysis reveals a similar gender gap trend with a stabilization in 1982 at 11.7%, despite the large growth in participation of women from eastern and western countries, that coincided with later-published evidence of state-institutionalized or individual doping. These results suggest that women will not run, jump, swim or ride as fast as men.

International audience ; A previous analysis of World Records (WR) has revealed the potential limits of human physiology through athletes' personal commitment. The impact of political factors on sports has only been studied through Olympic medals and results. Here we studied 2876 WR from 63 nations in four summer disciplines. We propose three new indicators and show the impact of historical, geographical and economical factors on the regional WR evolution. The south-eastward path of weighted annual barycenter (i.e. the average of country coordinates weighting by the WR number) shows the emergence of East Africa and China in WR archives. Home WR ratio decreased from 79.9% before the second World War to 23.3% in 2008, underlining sports globalization. Annual Cumulative Proportions (ACP, i.e. the cumulative sum of the WR annual rate) highlight the regional rates of progression. For all regions, the mean slope of ACP during the Olympic era is 0.0101, with a maximum between 1950 and 1989 (0.0156). For European countries, this indicator reflects major historical events (slowdown for western countries after 1945, slowdown for eastern countries after 1990). Mean North-American ACP slope is 0.0029 over the century with an acceleration between 1950 and 1989 at 0.0046. Russia takes off in 1935 and slows down in 1988 (0.0038). For Eastern Europe, maximal progression is seen between 1970 and 1989 (0.0045). China starts in 1979 with a maximum between 1990 and 2008 (0.0021), while other regions have largely declined (mean ACP slope for all other countries = 0.0011). A similar trend is observed for the evolution of the 10 best performers. The national analysis of WR reveals a precise and quantifiable link between the sport performances of a country, its historical or geopolitical context, and its steps of development.

International audience A previous analysis of World Records (WR) has revealed the potential limits of human physiology through athletes' personal commitment. The impact of political factors on sports has only been studied through Olympic medals and results. Here we studied 2876 WR from 63 nations in four summer disciplines. We propose three new indicators and show the impact of historical, geographical and economical factors on the regional WR evolution. The south-eastward path of weighted annual barycenter (i.e. the average of country coordinates weighting by the WR number) shows the emergence of East Africa and China in WR archives. Home WR ratio decreased from 79.9% before the second World War to 23.3% in 2008, underlining sports globalization. Annual Cumulative Proportions (ACP, i.e. the cumulative sum of the WR annual rate) highlight the regional rates of progression. For all regions, the mean slope of ACP during the Olympic era is 0.0101, with a maximum between 1950 and 1989 (0.0156). For European countries, this indicator reflects major historical events (slowdown for western countries after 1945, slowdown for eastern countries after 1990). Mean North-American ACP slope is 0.0029 over the century with an acceleration between 1950 and 1989 at 0.0046. Russia takes off in 1935 and slows down in 1988 (0.0038). For Eastern Europe, maximal progression is seen between 1970 and 1989 (0.0045). China starts in 1979 with a maximum between 1990 and 2008 (0.0021), while other regions have largely declined (mean ACP slope for all other countries = 0.0011). A similar trend is observed for the evolution of the 10 best performers. The national analysis of WR reveals a precise and quantifiable link between the sport performances of a country, its historical or geopolitical context, and its steps of development.

International audience ; A previous analysis of World Records (WR) has revealed the potential limits of human physiology through athletes' personal commitment. The impact of political factors on sports has only been studied through Olympic medals and results. Here we studied 2876 WR from 63 nations in four summer disciplines. We propose three new indicators and show the impact of historical, geographical and economical factors on the regional WR evolution. The south-eastward path of weighted annual barycenter (i.e. the average of country coordinates weighting by the WR number) shows the emergence of East Africa and China in WR archives. Home WR ratio decreased from 79.9% before the second World War to 23.3% in 2008, underlining sports globalization. Annual Cumulative Proportions (ACP, i.e. the cumulative sum of the WR annual rate) highlight the regional rates of progression. For all regions, the mean slope of ACP during the Olympic era is 0.0101, with a maximum between 1950 and 1989 (0.0156). For European countries, this indicator reflects major historical events (slowdown for western countries after 1945, slowdown for eastern countries after 1990). Mean North-American ACP slope is 0.0029 over the century with an acceleration between 1950 and 1989 at 0.0046. Russia takes off in 1935 and slows down in 1988 (0.0038). For Eastern Europe, maximal progression is seen between 1970 and 1989 (0.0045). China starts in 1979 with a maximum between 1990 and 2008 (0.0021), while other regions have largely declined (mean ACP slope for all other countries = 0.0011). A similar trend is observed for the evolution of the 10 best performers. The national analysis of WR reveals a precise and quantifiable link between the sport performances of a country, its historical or geopolitical context, and its steps of development.

International audience ; A previous analysis of World Records (WR) has revealed the potential limits of human physiology through athletes' personal commitment. The impact of political factors on sports has only been studied through Olympic medals and results. Here we studied 2876 WR from 63 nations in four summer disciplines. We propose three new indicators and show the impact of historical, geographical and economical factors on the regional WR evolution. The south-eastward path of weighted annual barycenter (i.e. the average of country coordinates weighting by the WR number) shows the emergence of East Africa and China in WR archives. Home WR ratio decreased from 79.9% before the second World War to 23.3% in 2008, underlining sports globalization. Annual Cumulative Proportions (ACP, i.e. the cumulative sum of the WR annual rate) highlight the regional rates of progression. For all regions, the mean slope of ACP during the Olympic era is 0.0101, with a maximum between 1950 and 1989 (0.0156). For European countries, this indicator reflects major historical events (slowdown for western countries after 1945, slowdown for eastern countries after 1990). Mean North-American ACP slope is 0.0029 over the century with an acceleration between 1950 and 1989 at 0.0046. Russia takes off in 1935 and slows down in 1988 (0.0038). For Eastern Europe, maximal progression is seen between 1970 and 1989 (0.0045). China starts in 1979 with a maximum between 1990 and 2008 (0.0021), while other regions have largely declined (mean ACP slope for all other countries = 0.0011). A similar trend is observed for the evolution of the 10 best performers. The national analysis of WR reveals a precise and quantifiable link between the sport performances of a country, its historical or geopolitical context, and its steps of development.

Background: Advanced systemic mastocytosis (advSM) is characterized by presence of the KIT D816V mutation and pathologic accumulation of neoplastic mast cells (MCs) in various tissues, leading to severe symptoms and organ damage (eg, cytopenias, liver dysfunction, portal hypertension, malabsorption, and weight loss). Treatment with midostaurin, an orally active multikinase/KIT inhibitor now approved for advSM in the United States and the European Union, resulted in a high rate of response accompanied by reduced MC infiltration of the bone marrow and lowered serum tryptase level. Objective: We aimed to determine whether midostaurin improves health-related quality of life (QOL) and MC mediator related symptoms in patients with advSM. Methods: In 116 patients with systemic mastocytosis (89 patients with advSM fulfilling the strict inclusion criteria of the D2201 study [ClinicalTrials.gov identifier NCT00782067]), QOL and symptom burden were assessed during treatment with midostaurin by using the 12-Item Short-Form Health Survey (SF-12) and the Memorial Symptom Assessment Scale patient reported questionnaires, respectively. MC mediator related symptoms were evaluated by using a specific physician-reported questionnaire Results: Over the first 6 cycles of treatment with midostaurin (ie, 6 months), patients experienced significant improvements in total SF-12 and Memorial Symptom Assessment Scale scores, as well as in subscores of each instrument. These improvements were durable during 36 months of follow-up. Similarly, we found substantial improvements (67%-100%) in all MC mediator related symptoms. Conclusion: QOL and MC mediator related symptoms significantly improve with midostaurin treatment in patients with advSM (ClinicalTrials.gov identifier, NCT00782067).

Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-α and/or IFN-ω are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or IFN-ω (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or IFN-ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases. ; The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Awards (CTSA) program (UL1 TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at George Mason University, the Yale Center for Mendelian Genomics and the GSP Coordinating Center funded by the National Human Genome Research Institute (NHGRI) (UM1HG006504 and U24HG008956), the Yale High Performance Computing Center (S10OD018521), the Fisher Center for Alzheimer's Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the "Investments for the Future" program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the FRM and ANR GENCOVID project (ANR-20-COVI-0003), ANRS Nord-Sud (ANRS-COV05), ANR GENVIR (ANR-20-CE93-003) and ANR AABIFNCOV (ANR-20-CO11-0001) projects, the European Union's Horizon 2020 research and innovation programme under grant agreement no. 824110 (EASI-Genomics), the Square Foundation, Grandir–Fonds de solidarité pour l'Enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM; and the University of Paris. P.B. was supported by the FRM (EA20170638020). P.B., J.R., and T.L.V. were supported by the MD-PhD program of the Imagine Institute (with the support of the Fondation Bettencourt Schueller). Work in the Laboratory of Virology and Infectious Disease was supported by the NIH (P01AI138398-S1, 2U19AI111825, and R01AI091707-10S1), a George Mason University Fast Grant, and the G. Harold and Leila Y. Mathers Charitable Foundation. The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (RECOVER WP 6). This work was also partly supported by the Intramural Research Program of the NIAID and NIDCR, NIH (grants ZIA AI001270 to L.D.N. and 1ZIAAI001265 to H.C.S.). This program is supported by the Agence Nationale de la Recherche (reference ANR-10-LABX-69-01). K.K.'s group was supported by the Estonian Research Council grants PRG117 and PRG377. R.H. was supported by an Al Jalila Foundation Seed Grant (AJF202019), Dubai, UAE, and a COVID-19 research grant (CoV19-0307) from the University of Sharjah, UAE. S.G.T. is supported by Investigator and Program Grants awarded by the National Health and Medical Research Council of Australia and a UNSW Sydney COVID Rapid Response Initiative Grant. L.I. reported funding from Regione Lombardia, Italy (project "Risposta immune in pazienti con COVID-19 e co-morbidità"). L.I. and G. L. Marseglia reported funding from Regione Lombardia, Italy (project Risposta immune in pazienti con COVID-19 e co-morbidità). This research was partially supported by the Instituto de Salud Carlos III (COV20/0968). J.R.H. reported funding from Biomedical Advanced Research and Development Authority HHSO10201600031C. S.O. reports funding Research Program on Emerging and Re-emerging Infectious Diseases from Japan Agency for Medical Research and Development, AMED (grant number JP20fk0108531). G.G. was supported by ANR Flash COVID-19 program and SARS-CoV-2 Program of the Faculty of Medicine from Sorbonne University iCOVID programs. The Three-City (3C) Study was conducted under a partnership agreement among the INSERM, the Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also supported by the Caisse Nationale d'Assurance Maladie des Travailleurs Salariés, Direction générale de la Santé, Mutuelle Générale de l'Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme "Cohortes et collections de données biologiques". S. Debette was supported by the University of Bordeaux Initiative of Excellence. P.K.G. reports funding from the National Cancer Institute, NIH, under contract no. 75N91019D00024, task order no. 75N91021F00001. J.W. is supported by an FWO Fundamental Clinical Mandate (1833317N). Sample processing at IrsiCaixa was possible thanks to the crowdfunding initiative YoMeCorono. Work at Vall d'Hebron was also partly supported by research funding from Instituto de Salud Carlos III grant PI17/00660 cofinanced by the European Regional Development Fund (ERDF). C.R.-G. and colleagues of the Canarian Health System Sequencing Hub were supported by the Instituto de Salud Carlos III (COV20_01333 and COV20_01334, Spanish Ministry for Science and Innovation RTC-2017-6471-1; AEI/FEDER, UE), Fundación DISA (OA18/017 and OA20/024), and Cabildo Insular de Tenerife (CGIEU0000219140 and "Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19"). C.M.B. is supported by a MSFHR Health Professional-Investigator Award. P.Q.H. and L.H. were funded by the European Union's Horizon 2020 research and innovation program (ATAC, 101003650). Work at Y.-L.L.'s laboratory in the University of Hong Kong (HKU) was supported by the Society for the Relief of Disabled Children. MBBS/PhD study of D.L. in HKU was supported by the Croucher Foundation. J.L.F. was supported in part by the Coopération Scientifique France-Colciencias (ECOS-Nord/COLCIENCIAS/MEN/ICETEX (806-2018) and Colciencias contract 713-2016 (code 111574455633)]. A.K. was in part supported by grants NU20-05-00282 and NV18-05-00162 issued by the Czech Health Research Council and Ministry of Health, Czech Republic. L.P. was funded by Program Project COVID-19 OSR-UniSR and Ministero della Salute (COVID-2020-12371617). I.M. is a Senior Clinical Investigator at the Research Foundation–Flanders and is supported by the CSL Behring Chair of Primary Immunodeficiencies; by the KU Leuven C1 grant C16/18/007; by a VIB-GC PID grant; by the FWO frants G0C8517N, G0B5120N, and G0E8420N; and by the Jeffrey Modell Foundation. I.M. has received funding under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 948959). E.A. received funding from the Hellenic Foundation for Research and Innovation (INTERFLU, no. 1574). M.Vi received funding from the São Paulo Research Foundation (FAPESP) (grant number 2020/09702-1) and JBS SA (grant number 69004). The NH-COVAIR study group consortium was supported by a grant from the Meath Foundation ; Peer reviewed