Generalization of the complete data fusion to multi-target retrieval of atmospheric parameters and application to FORUM and IASI-NG simulated measurements

Abstract In the context of a growing need for innovatory techniques to take advantage of the largest amount of information from the great number of available remote sensing data, the Complete Data Fusion (CDF) algorithm was presented as a new method to combine independent measurements of the same vertical profile of an atmospheric parameter into a single estimate for a concise and complete characterization of the atmospheric state. The majority of the atmospheric composition measurements determine the altitude distribution of a great number of quantities: multi-target retrievals (MTRs) are increasingly applied to remote sensing observations to determine simultaneously atmospheric constituents with the purpose to reduce the systematic error caused by interfering species. In this work, we optimised the CDF for the application to MTR products. We applied the method to simulated retrievals in the thermal infrared and in the far infrared spectral ranges, considering the instrumental specifications and performances of IASI-NG (Infrared Atmospheric Sounding Interferometer New Generation) and FORUM (Far-Infrared Outgoing Radiation Understanding and Monitoring) instruments, respectively. The obtained results show that the CDF algorithm can cope with state vectors from MTRs, that must share at least one retrieved variable. In particular, the results show that the fused profile has the greatest number of degrees of freedom and the smallest error for all considered cases. The comparison between the CDF products and the synergistic retrieval ones shows the equivalence of the two methods when the linear approximation is adopted to simplify the treatment of the retrieval problem

A Distributed Modular Data Processing Chain Applied to Simulated Satellite Ozone Observations

Remote sensing of the atmospheric composition from current and future satellites, such as the Sentinel missions of the Copernicus programme, yields an unprecedented amount of data to monitor air quality, ozone, UV radiation and other climate variables. Hence, full exploitation of the growing wealth of information delivered by spaceborne observing systems requires addressing the technological challenges for developing new strategies and tools that are capable to deal with these huge data volumes. The H2020 AURORA (Advanced Ultraviolet Radiation and Ozone Retrieval for Applications) project investigated a novel approach for synergistic use of ozone profile measurements acquired at different frequencies (ultraviolet, visible, thermal infrared) by sensors onboard Geostationary Equatorial Orbit (GEO) and Low Earth Orbit (LEO) satellites in the framework of the Copernicus Sentinel-4 and Sentinel-5 missions. This paper outlines the main features of the technological infrastructure, designed and developed to support the AURORA data processing chain as a distributed data processing and describes in detail the key components of the infrastructure and the software prototype. The latter demonstrates the technical feasibility of the automatic execution of the full processing chain with simulated data. The Data Processing Chain (DPC) presented in this work thus replicates a processing system that, starting from the operational satellite retrievals, carries out their fusion and results in the assimilation of the fused products. These consist in ozone vertical profiles from which further modules of the chain deliver tropospheric ozone and UV radiation at the Earth's surface. The conclusions highlight the relevance of this novel approach to the synergistic use of operational satellite data and underline that the infrastructure uses general-purpose technologies and is open for applications in different contexts

Cabozantinib After a Previous Immune Checkpoint Inhibitor in Metastatic Renal Cell Carcinoma: A Retrospective Multi-Institutional Analysis

Background: Angiogenesis has been recognized as the most important factor for tumor invasion, proliferation, and progression in metastatic renal cell carcinoma (mRCC). However, few clinical data are available regarding the efficacy of cabozantinib following immunotherapy. Objective: To describe the outcome of cabozantinib in patients previously treated with immunotherapy. Patients and methods: Patients with mRCC who received cabozantinib immediately after nivolumab were included. The primary endpoint was to assess the outcome in terms of efficacy and activity. Results: Eighty-four mRCC patients met the criteria to be included in the final analysis. After a median follow-up of 9.4 months, median overall survival was 17.3 months. According to the IMDC criteria, the rates of patients alive at 12 months in the good, intermediate, and poor prognostic groups were 100%, 74%, and 33%, respectively (p < 0.001). The median progression-free survival (PFS) was 11.5 months (95% CI 8.3-14.7); no difference was found based on duration of previous first-line therapy or nivolumab PFS. The overall response rate was 52%, stable disease was found as the best response in 25.3% and progressive disease in 22.7% of patients. Among the 35 patients with progressive disease on nivolumab, 26 (74.3%) patients showed complete/partial response or stable disease with cabozantinib as best response after nivolumab. The major limitations of this study are the retrospective nature and the short follow-up. Conclusions: Cabozantinib was shown to be effective and active in patients previously receiving immune checkpoint inhibitors. Therefore, cabozantinib can be considered a valid therapeutic option for previously treated mRCC patients, irrespective of the type and duration of prior therapies

Adjuvant capecitabine in triple negative breast cancer patients with residual disease after neoadjuvant treatment: real-world evidence from CaRe, a multicentric, observational study

Background: In triple negative breast cancer patients treated with neoadjuvant chemotherapy, residual disease at surgery is the most relevant unfavorable prognostic factor. Current guidelines consider the use of adjuvant capecitabine, based on the results of the randomized CREATE-X study, carried out in Asian patients and including a small subset of triple negative tumors. Thus far, evidence on Caucasian patients is limited, and no real-world data are available. Methods: We carried out a multicenter, observational study, involving 44 oncologic centres. Triple negative breast cancer patients with residual disease, treated with adjuvant capecitabine from January 2017 through June 2021, were recruited. We primarily focused on treatment tolerability, with toxicity being reported as potential cause of treatment discontinuation. Secondarily, we assessed effectiveness in the overall study population and in a subset having a minimum follow-up of 2 years. Results: Overall, 270 patients were retrospectively identified. The 50.4% of the patients had residual node positive disease, 7.8% and 81.9% had large or G3 residual tumor, respectively, and 80.4% a Ki-67 >20%. Toxicity-related treatment discontinuation was observed only in 10.4% of the patients. In the whole population, at a median follow-up of 15 months, 2-year disease-free survival was 62%, 2 and 3-year overall survival 84.0% and 76.2%, respectively. In 129 patients with a median follow-up of 25 months, 2-year disease-free survival was 43.4%, 2 and 3-year overall survival 78.0% and 70.8%, respectively. Six or more cycles of capecitabine were associated with more favourable outcomes compared with less than six cycles. Conclusion: The CaRe study shows an unexpectedly good tolerance of adjuvant capecitabine in a real-world setting, although effectiveness appears to be lower than that observed in the CREATE-X study. Methodological differences between the two studies impose significant limits to comparability concerning effectiveness, and strongly invite further research

How Certain are We of the Uncertainties in Recent Ozone Profile Trend Assessments of Merged Limbo Ccultation Records? Challenges and Possible Ways Forward

Most recent assessments of long-term changes in the vertical distribution of ozone (by e.g. WMO and SI2N) rely on data sets that integrate observations by multiple instruments. Several merged satellite ozone profile records have been developed over the past few years; each considers a particular set of instruments and adopts a particular merging strategy. Their intercomparison by Tummon et al. revealed that the current merging schemes are not sufficiently refined to correct for all major differences between the limb/occultation records. This shortcoming introduces uncertainties that need to be known to obtain a sound interpretation of the different satellite-based trend studies. In practice however, producing realistic uncertainty estimates is an intricate task which depends on a sufficiently detailed understanding of the characteristics of each contributing data record and on the subsequent interplay and propagation of these through the merging scheme. Our presentation discusses these challenges in the context of limb/occultation ozone profile records, but they are equally relevant for other instruments and atmospheric measurements. We start by showing how the NDACC and GAW-affiliated ground-based networks of ozonesonde and lidar instruments allowed us to characterize fourteen limb/occultation ozone profile records, together providing a global view over the last three decades. Our prime focus will be on techniques to estimate long-term drift since our results suggest this is the main driver of the major trend differences between the merged data sets. The single-instrument drift estimates are then used for a tentative estimate of the systematic uncertainty in the profile trends from merged data records. We conclude by reflecting on possible further steps needed to improve the merging algorithms and to obtain a better characterization of the uncertainties involved