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Source apportionment models were widely used to successfully assign highly time-resolved aerosol data to specific emissions and/or atmospheric chemical processes. These techniques are necessary for targeting the sources affecting air quality and for designing effective mitigation strategies. Moreover, evaluation of the toxicity of airborne particulate matter is important since the classically measured particulate matter (PM) concentrations appear insufficient for characterizing the impact on human health. Oxidative potential (OP) measurement has recently been developed to quantify the capability of PM to induce an oxidative imbalance in the lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using positive matrix factorization (PMF) from organic aerosol (OA) mass spectra measured at a 15 min time resolution using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and from 19 trace elements measured on an hourly basis using an online metal analyser (Xact 625i). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSMs and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM 1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM, and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. Overall, eight factors were identified, each of them corresponding to a more precise source than performing single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM 1 originated from distinct combustion sources, including emissions from traffic, shipping, industrial activities, cooking, and biomass burning. Simultaneously, PM 1 filters were collected during the experimental period on a 4 h sampling basis. On these filters, two acellular OP assays were performed (dithiothreitol; OP DTT and ascorbic acid; OP AA) and an inversion method was applied on factors issued from all PMFs to assess the contribution of the PM sources to the OP. This work highlights the sensitivity of OP AA to industrial and dust resuspension sources and those of OP DTT to secondary ammonium sulfate, shipping, and biomass burning. [ABSTRACT FROM AUTHOR]

Source apportionment models were widely used and/or atmospheric chemical processes. These technics are necessary to target the sources affecting air quality and to design effective mitigation strategies. More, the evaluation of the toxicity of airborne particulate matter gains interest as the PM concentrations classically measured appear insufficient to characterise the human health impact. Oxidative Potential (OP) measurement have recently been developed to quantify the PM capability to induce an oxidative imbalance in lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using Positive Matrix Factorization (PMF) from organic aerosol (OA) mass spectra measured at 15 min time resolution using a Time of Flight-Aerosol Chemical Speciation Monitor (ToF-ACSM) and from 19 trace elements measured on an hour basis using an online metals analyser (Xact). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSM and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. In overall, 8 factors were identified, each of them corresponding to a more precise source than performing the previous single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM1 were originated from combustion processes (traffic, shipping, industrial, cooking and biomass burning emissions). Simultaneously, PM1 filters were collected during the experimental period on a 4 hours sampling basis. On these filters, two acellular OP assays were measured (dithiothreitiol; OPDTT and ascorbic acid; OPAA) and an inversion method is applied on factors issued from all PMFs to assess contributions of the PM sources to the OP. This work highlights the sensitivity of OPAA toward industrial and dust resuspension sources and those of OPDTT toward secondary ammonium sulfate, shipping and biomass burning. [ABSTRACT FROM AUTHOR]

Simple Summary: While information about sociodemographic characteristics of Hodgkin lymphoma (HL) and their influence on outcomes remains elusive, the objective of this present study was to decipher the potential impact of social disparities on the disease features at diagnosis and to analyze how sociodemographic patient characteristics could impact HL outcomes. These findings suggest that some patient sociodemographic characteristics might impact access to medical care leading to a higher frequency of unfavorable presentations. Introduction: Whereas numerous studies on several cancers describe the link between social conditions and disease severity, little is known about the social and demographic characteristics of Hodgkin lymphoma (HL) patients. At diagnosis, 10–15% of the patients in the advanced stages have a well-known poor outcome owing to their chemoresistance, but the determinants of the more advanced stages remain elusive. The objective of the present study was to decipher the potential impact of social disparities on the disease features at diagnosis and analyze how the sociodemographic patient features could impact the HL outcome of patients with advanced-stage HL enrolled in the AHL2011 trial. Methods: This ancillary study was conducted on a cohort of patients from French centers that had recruited more than five patients in the phase III AHL2011 study (NCT0135874). Patients had to be alive at the time of the ancillary study and had to have given their consent to answer the questionnaire. Pre-treatment data (age, gender, stage, B symptoms, IPS), the treatment received, the responses to PET-CT, and the presence of serious adverse events (serious adverse events—SAEs) were all extracted from the AHL2011 trial database. Sociodemographic data—marital status, living area, level of education, socio-professional category, and professional situation—were extracted from the questionnaires. The population density at the point of diagnosis was determined based on ZIP Code, and the distance from the reference medical center was then calculated by the road network. Baseline PET acquisition was performed before any treatment. PET images at baseline were centrally reviewed. The total metabolic tumor volume (TMTV) at the baseline was calculated using a 41% SUVmax cutoff for each lesion. Progression-free survival was defined as the time from randomization to the first progression, relapse, or death from any cause or the last follow-up. The data cutoff for the analyses presented here was 31 October 2017. The progression-free survival was analyzed on an intention-to-treat basis. Results: Among the 823 patients enrolled in the AHL2011 study, the questionnaire was sent to 394 patients, of whom 232 (58.9%) responded. At the time of HL diagnosis, 61.9% (N = 143) of patients declared that they were not socially isolated, 38.1% (N = 88) that they were single, 163 (71.2%) had a professional activity, and 66 (28.8%) were inactive owing to unemployment, retirement, or sick leave. Of the patients, 31.1% (N = 71) lived in a rural region, compared to 68.9% (N = 157) that lived in an urban region. The residence ZIP Code at the time of HL diagnosis was available for 163 (70%). Sociodemographic characteristics did not influence the presence of usual prognostic factors (ECOG, B symptoms, bulky mass, IPS) except for professional activity, which was associated with more frequent low IPS (0–2) (79 (48.5%) active versus 20 (30.3%) inactive patients; p = 0.012). Likewise, no correlation was observed between TMTV and sociodemographic characteristics. However, the TMTV quartile distribution was different according to the living area, with the two upper quartiles being enriched with patients living in a rural area (p = 0.008). Moreover, a negative correlation between the average number of the living area's inhabitants and TMTV (R Pearson = −0.29, p = 0.0004) was observed. Conclusion: This study focused on sociodemographic parameters in advanced-stage HL patients and shows that professional activity is associated with more favorable disease features (low IPS), while patients living in rural or low-populated areas are more likely to have an unfavorable HL presentation with a high tumor burden (high TMTV). These data suggest that some patient sociodemographic characteristics might impact either access to medical care or environmental exposure, leading to a higher frequency of unfavorable presentations. Further prospective sociodemographic studies are necessary to confirm these preliminary results. [ABSTRACT FROM AUTHOR]

In order to gain understanding on the vertical structure of atmospheric water vapour above mountain lakes and to assess the respective influence of evaporation and advection processes, the L-WAIVE (Lacustrine-Water vApor Isotope inVentory Experiment) field campaign was conducted in the Annecy valley in the French Alps in June 2019. This campaign was based on a synergy between a suite of ground-based, boat-borne, and airborne measuring platforms implemented to characterise the thermodynamic and isotopic state above the lake environment using both in-situ and remote sensing instruments. Two ultra-light aircrafts (ULA), one equipped with a Rayleigh-Mie lidar, solar fluxmeters and an optical counter, and one equipped with a Cavity Ring-down Spectrometer (CRDS) and an in-cloud liquid water collector, were deployed to characterize the vertical distribution of the main stable water vapour isotopes (H216O, H218O and H2H16O), and their potential interactions with clouds and aerosols. ULA flight patterns were repeated several times per day to capture the diurnal evolution as well as variability associated with different weather events. ULA flights were anchored to continuous water vapour and wind profiling of the lower troposphere performed by two dedicated ground-based lidars. Additional flights have been conducted to map the spatial variability of the water vapour isotope composition regarding the lake and surrounding topography. Throughout the campaign, ship-borne lake temperature profiles as well as liquid water samples at the air-water interface and at 2 m depth were made, supplemented on one occasion by atmospheric water vapour isotope measurements from the ship. The campaign period included a variety of weather events leading to contrasting humidity and cloud conditions, slope wind regimes and aerosol contents in the valley. The water vapor mixing ratio values in the valley atmospheric boundary layer were found to range from 3–4 g kg−1 to more than 10 g kg−1 and to be strongly influenced by the subsidence of higher altitude air masses as well as slope winds. A significant variability of the isotopic composition was observed within the first 3 km above ground level. The influence of the lake evaporation was mainly detected in the first 500 m of the atmosphere. Well-mixed conditions prevailed in the lower free troposphere, mainly above the mean altitude of the mountain tops surrounding the lake. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article regarding the use of the Munc13-4- protein deficient CD81 T cells in the Epstein-Barr virus (EBV)-driven lymphoproliferation in the NOD scid gamma (NSG) mice.

The aim of this study was to evaluate the prognostic impact of the F-fluorodeoxyglucose positron emission tomography response at 1 month (M1) and 3 months (M3) after anti-CD19 chimeric antigen receptor (CAR) T-cell therapy in a multicenter cohort of 160 patients with relapsed/refractory large B-cell lymphomas (R/R LBCL). In total, 119 (75%) patients reached M1 evaluation; 64 (53%, 64/119) had a complete response (CR); 91% were Deauville Score (DS) 1-3. Progressionfree survival (PFS) and overall survival (OS) were significantly worse in patients with DS-5 at M1, than in patients with DS 1-3 (PFS hazard ratio [HR]=6.37, 95% confidence interval [CI]: 3.5-11.5 vs. OS HR=3.79, 95% CI: 1.7-8.5) and DS-4 (PFS HR=11.99, 95% CI: 5.0-28.9 vs. OS HR=12.49, 95% CI: 2.8-55.8). The 1-year PFS rates were 78.9% (95% CI: 58.9-89.9) for DS-4 at M1, similar to 67.3% (95% CI: 51.8-78.8) for patients with DS 1-3 at M1, very different to 8.6% (95% CI: 1.8-22.4) for DS-5, respectively. Only eight of 30 (26%) patients with DS-4 progressed. Response at M3 evaluated in 90 (57%) patients was prognostic for PFS with lower discrimination (HR=3.28, 95% CI: 1.5-7.0; P=0.003) but did not predict OS (HR=0.61, 95% CI: 0.2-2.3; P=0.45). Patients with a high baseline total metabolic tumor volume (TMTV) >80 mL had worse PFS (HR=2.05, 95% CI: 1.2-3.5; P=0.009) and OS (HR=4.52, 95% CI: 2.5-8.1; P<0.001) than patients with low TMTV. Multivariable analyses identified baseline elevated lactate dehydrogenase, DS-5, CAR T cells at M1 for PFS and baseline elevated lactate dehydrogenase, TMTV >80 mL, and DS-5 at M1 for OS. In conclusion, baseline TMTV and response at M1 strongly predicts outcomes of patients with R/R LBCL undergoing CAR T-cell therapy.