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Association between long-term exposure to air pollution on the risk of infection by SARS-CoV-2 virus and COVID-19 disease in the French CONSTANCES cohort
No full textInternational audienceLong-term air pollution exposure has been associated with increased risk of SARS-CoV-2 infection. However, few studies have used individual-level data, and even fewer serology data.We aimed to investigate the association between long-term exposure to air pollution and 1) SARS-CoV-2 infection and 2) COVID-19 disease, among adults from the French CONSTANCES population-based cohort.SARS-CoV-2 infection was assessed in May–November 2020 using ELISA test serology; COVID-19 disease was self-reported as medical diagnosis of SARS-CoV-2 infection and associated symptoms. Annual 2019 exposures to particulate matter with an aerodynamic diameter of ≤2.5 (PM2.5), black carbon (BC) and nitrogen dioxide (NO2) were estimated using hybrid land-use regression models and assigned at pre-pandemic residential address.We estimated log-binomial risk ratios (RRs for an interquartile range increase), adjusting for individual and area-level covariates.The population included 33,974 participants, among which 1695 (4.99 %) had a SARS-CoV-2 infection, and 802 (2.8 %) reported COVID-19 disease. Exposure to PM2.5 and NO2 were associated with a higher probability of SARS-CoV-2 infection (Adjusted RRs (aRR[95 %CI]): 1.28[1.10: 1.50] for PM2.5, 1.21[1.07: 1.37] for NO2) and COVID-19 disease (1.41[1.11: 1.79] for PM2.5, 1.40[1.18: 1.66] for NO2). Exposure to BC was associated with a higher probability of COVID-19 disease (1.20[1.03: 1.39]) but not SARS-CoV-2 infection (1.07[0.97–1.19]). Stratified analyses showed higher risks for men, age >60, or having pre-existent chronic disease.Using individual data, long-term exposure to air pollution was associated with increased risks of SARS-CoV-2 infection and COVID-19 disease. These results could help to better understand or prevent respiratory infections
IPSL-Perm-LandN: improving the IPSL Earth System Model to represent permafrost carbon-nitrogen interactions
No full textInternational audienceAbstract. Permafrost soils have the potential to release large amounts of soil carbon to the atmosphere under climate change. However, in the Sixth Coupled Model Intercomparison Project (CMIP6), only two Earth System Models (ESM) represented permafrost carbon, both sharing the same land surface model. This makes future permafrost carbon dynamics highly uncertain and underscores the urgent need to include permafrost carbon in ESMs to enable more reliable future projections of climate change and remaining carbon budget estimates. Here, we present IPSL-Perm-LandN, an improved version of the Institut Pierre-Simon Laplace (IPSL) ESM (used for CMIP6) aiming at better representing high-latitude land ecosystems. The main developments are the inclusion of an explicit nitrogen cycle and of key permafrost physical and biogeochemical processes. The latent heat associated with soil water freeze/thaw is taken into account in the energy budget, as well as soil thermal insulation by soil organic matter and a surface organic layer (e.g. litter or moss). Soil organic carbon and nitrogen are vertically resolved with depth-dependent decomposition dynamics, a key feature for representing the effect of gradual permafrost thaw on soil biogeochemistry. Cryoturbation is represented as a diffusion process that buries organic matter in the deeper soil layers. Compared to the previous version of the model used for CMIP6, we show that the extent of the permafrost region has improved significantly and that the simulated active layer thickness in the Arctic is in better agreement with observations. Permafrost soil carbon stocks have increased 20-fold to reach 1006 PgC in the top 3 m of soil, which is consistent with observation-based estimates. We simulate that the permafrost region has been a net carbon sink over the past 150 years (+0.32 ± 0.04 PgC yr−1 on average between 2005 and 2014), primarily due to carbon uptake from boreal forests. This is comparable with recent pan-Arctic carbon balance estimates, when accounting for unrepresented processes in our model (fire and riverine carbon losses). Overall, the inclusion of permafrost processes has improved the response of the model to anthropogenic perturbations in high latitudes over the past century, marking a step forward in the representation of Arctic ecosystems
Building a Standardised Statistical Reporting Toolbox in an Academic Oncology Clinical Trials Unit: The grstat R Package
No full textAcademic Clinical Trial Units frequently face fragmented statistical workflows, leading to duplicated effort, limited collaboration, and inconsistent analytical practices. To address these challenges within an oncology Clinical Trial Unit, we developed grstat, an R package providing a standardised set of tools for routine statistical analyses.Beyond the software itself, the development of grstat is embedded in a structured organisational framework combining formal request tracking, peer-reviewed development, automated testing, and staged validation of new functionalities. The package is intentionally opinionated, reflecting shared practices agreed upon within the unit, and evolves through iterative use in real-world projects. Its development as an open-source project on GitHub supports transparent workflows, collective code ownership, and traceable decision-making.While primarily designed for internal use, this work illustrates a transferable approach to organising, validating, and maintaining a shared analytical toolbox in an academic setting. By coupling technical implementation with governance and validation principles, grstat supports efficiency, reproducibility, and long-term maintainability of biostatistical workflows, and may serve as a source of inspiration for other Clinical Trial Units facing similar organisational challenges.</p
Identification of transdiagnostic phenomena among patients, the general population, relatives, and mental health professionals using topic modeling techniques
No full textInternational audienceIntroduction Recent research has highlighted the limitations of the categorical approach to mental disorders and has increasingly supported the development of a transdiagnostic perspective. This emerging approach focuses on common distal factors (circumstantial, biological, and social) and psychological processes that contribute to psychological suffering across a range of disorders, as well as on the resulting psychological symptoms. The present study aims to identify transdiagnostic distal factors, psychological processes, and symptoms by analyzing narratives through topic modeling—an unsupervised machine learning technique, specifically within Natural Language Processing (NLP). Topic modeling enables the automatic extraction of latent themes from unstructured text, making it possible to identify psychological patterns grounded in patients’ lived experiences. Methods We recruited four groups of participants: Patients diagnosed with a psychiatric disorder ( N = 445), Individuals from the general population ( N = 570), Relatives of patients with psychiatric disorders ( N = 354), and Mental health professionals ( N = 131). Participants answered open-ended questions exploring the causes of psychological suffering, their wishes for change, and their previous experiences with psychotherapy. Results We identified 258 topics, which were organized into 12 overarching themes. The most prominent topics concerned Emotional and Psychological Difficulties , Family and Social Relationships , and Therapeutic Processes . Each theme showed a comparable prevalence across the different diagnostic categories, supporting the transdiagnostic nature of these phenomena. Conclusion Topic modeling can be used effectively to identify transdiagnostic distal factors, psychological processes, and symptoms from diverse narratives. This approach tends to provide a novel means of supporting the relevance and validity of the transdiagnostic perspective
PM2.5, Black Carbon and NO2 associations with rhinitis and asthma multimorbidity in adults: The Constances Cohort
No full textInternational audienceBackground: Rhinitis and asthma often co-occur; however, studies on their associations with air pollution have always considered them separately.Objective: We investigated the association between long-term air pollution exposure and rhinitis and asthma multimorbidity in adults.Methods: Data at inclusion from Constances, a large French population-based adult cohort were used. Current Rhinitis (CR) and Current Asthma (CA) were defined by questionnaire. Annual exposure to nitrogen dioxide (NO2), particulate matter ≤2.5 μm (PM2.5) and black carbon (BC) were estimated by linking participants' residential address to land-use regression models. Cross-sectional multinomial logistic regressions were performed between each air pollutant and CR alone, CA alone, and CR+CA (no-CR/no-CA being the reference) adjusted for age, sex, smoking, education level and French deprivation index.Results: Among the 177,968 participants included in the analyses (mean age: 47 yrs., 54% females), 111,108 (62%) were classified as no-CR/no-CA, 49,971 (28%) CR alone, 6,435 (4%) CA alone, and 10,454 (6%) CR+CA. One interquartile range (IQR) increase of BC and NO2 was significantly associated with the three phenotypes, with adjusted ORs from 1.04 to 1.13 for BC (IQR: 0.55 10-5.m-1), and from 1.06 to 1.14 for NO2 (IQR: 13.7 μg.m-3). For PM2.5, one IQR increase (4.09 μg.m-3) was significantly associated with CR alone and CR+CA. In all our analysis, the highest associations were observed for CR alone.Conclusion: Our results show that long-term air pollution is more associated with rhinitis alone or with asthma multimorbidity than with asthma alone
Why methane surged in the atmosphere during the early 2020s
No full textInternational audienceThe atmospheric methane (CH 4 ) growth rate surged after 2019, peaking at 16.2 parts per billion per year (ppb year −1 ) in 2020 before declining to 8.6 ppb year −1 in 2023. Using multiple atmospheric inversions constrained by observation- and model-based prescribed hydroxyl radical (OH) fields and CH 4 atmospheric data, we show that a drop of OH radicals in 2020–2021, followed by recovery in 2022–2023, accounted for 83% of year-on-year variations in the CH 4 growth rate, the rest being explained by wetland and inland water emissions, which increased between 2019 and 2020–2022 [+8.6 ± 2.6 teragrams of CH 4 per year (TgCH 4 year −1 )] and then decreased between 2022 and 2023 (−9.9 ± 3.3 TgCH 4 year −1 ). Most emission changes from 2019 to 2023 occurred in northern tropical wetlands in Africa and Asia, whereas South American wetlands emissions declined and Arctic emissions increased after 2019
Data for "Atmospheric Methane Removal as a Third Climate Intervention: Termination Risks and Air Pollutant Effects"
No full textInternational audienceThis dataset contains codes, data, tables, and figures related to the following publication: Tanaka, K., W. Xiong, D. A. Hauglustaine, D. J. A. Johansson, N. Bauer, P. Bousquet, P. Ciais, R. de Richter, M. T. Lund, R. Skeie, E. Zusman (2026) Atmospheric Methane Removal as a Third Climate Intervention: Termination Risks and Air Pollutant Effects. Arxiv (preprint). 24 January 2026. https://doi.org/10.48550/arXiv.2601.1746
Spatiotemporal changes and drivers of net greenhouse gas emissions from major cropping systems in China during 1984–2018
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Identifying high-risk relapse in early-stage I to II ovarian cancer using the CA125 ELIMination rate constant K (KELIM) score: a Gynecologic Cancer InterGroup individual patient-data meta-analysis.
No full textInternational audienceObjective: Despite curative surgery and adjuvant chemotherapy, a significant number of early stage I to II ovarian cancers relapse. The CA125 ELIMination rate constant K (KELIM) is a pragmatic indicator of tumor intrinsic chemosensitivity in advanced epithelial ovarian cancer. We assessed the prognostic value of KELIM in patients with early-stage ovarian cancer, with respect to 5-year recurrence-free survival and overall survival, using the Meta-Analysis in Ovarian Cancer, which is the Gynecologic Cancer InterGroup individual patient-data meta-analysis of randomized trials evaluating different adjuvant chemotherapy regimens.Methods: Individual patient KELIM values were previously estimated in 5884 patients from the Meta-Analysis in Ovarian Cancer. The prognostic value of KELIM was assessed using univariable & multivariable analyses in patients with resected International Federation of Gynecology and Obstetrics stage I and II disease.Results: Overall, 1143 patients were identified, including clear cell (46.7%); serous (23.7%); endometrioid (12.4%); and mucinous carcinomas (3.9%). In multivariable analyses, a favorable KELIM score (≥1.0) was associated with higher 5-year recurrence-free survival (68.3% vs 55.9%; HR 0.61, 95% CI 0.48 to 0.77) and 5-year overall survival (80.7% vs 72.8%; HR 0.50, 95% CI 0.36 to 0.68), as was the histological sub-type. In exploratory analyses, KELIM score was a prognostic factor regarding 5-year recurrence-free survival and overall survival across all sub-types (especially clear cell carcinoma and serous, with HR ranging from 0.45 to 0.63) with baseline CA125 ≥15 IU/L, except for mucinous histology.Conclusions: The pragmatic KELIM score is an independent prognostic factor in patients with a non-mucinous stage I to II ovarian cancer optimally resected and treated with adjuvant chemotherapy. KELIM may help identify the patients at higher risk of relapse and death requiring closer follow-up or treatment intensification
Long-duration in situ monitoring of H2O and CH4 in the equatorial tropopause with the Pico-STRAT Bi Gaz balloon borne laser diode spectrometer during the Strateole 2 campaign
No full textInternational audienceThe Pico-STRAT Bi Gaz spectrometer provides in situ mixing ratio measurements of H2O and CH4 (or CO2 ) under balloon. The instrument was flown in the tropical upper troposphere and lower stratosphere in 2019/2020 and 2021/2022 during the Strateole 2 campaigns for a total of five flights of 20 to 80 days between 18 and 20 km altitude. In this frame, in situ measurements of water vapor and methane were performed every 4 to 12 minutes in the equatorial tropopause layer. On several occasions, water vapor measurements of Pico-STRAT Bi Gaz have been compared with localized measurements from the FLASH-B Lyman-α hygrometer and vertical profiles of the NOAA Global Monitoring Laboratory (GML) frost point hygrometer over Hilo, Hawaii. Pico-STRAT Bi Gaz measurements agreed with the FLASH-B hygrometer to within 2.2 ± 5.3 % between 18.2 and 18.7 km in 2021 and to within 1.3 ± 5.3 % near 19 km in December 2019. Pico-STRAT Bi Gaz agreed with NOAA’s FPH hygrometer to within 1.2 ± 4.1% between 18 and 19 km on four occasions during the two campaigns. These are within both instruments’ uncertainties. Methane measurements from Pico-STRAT Bi Gaz have been compared with in situ measurements from the Whole Air Sampler instrument (WAS), flown aboard the NASA WB-57 aircraft during the ACCLIP 2022 campaign over South Korea, eight months after the Pico-STRAT Bi Gaz overpass. The relative difference between both instruments is found to be of (−0.1 ± 0.9) % within the altitude range from 17 to 19 km and within the Pico-STRAT measurement uncertainty