ALBERT

Description: Anthropogenic emissions of CO2 to the atmosphere have modified the carbon cycle for more than 2 centuries. As the ocean stores most of the carbon on our planet, there is an important task in unraveling the natural and anthropogenic processes that drive the carbon cycle at different spatial and temporal scales. We contribute to this by designing a global monthly climatology of total dissolved inorganic carbon (TCO2), which offers a robust basis in carbon cycle modeling but also for other studies related to this cycle. A feedforward neural network (dubbed NNGv2LDEO) was configured to extract from the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2.2019) and the Lamont–Doherty Earth Observatory (LDEO) datasets the relations between TCO2 and a set of variables related to the former's variability. The global root mean square error (RMSE) of mapping TCO2 is relatively low for the two datasets (GLODAPv2.2019: 7.2 µmol kg−1; LDEO: 11.4 µmol kg−1) and also for independent data, suggesting that the network does not overfit possible errors in data. The ability of NNGv2LDEO to capture the monthly variability of TCO2 was testified through the good reproduction of the seasonal cycle in 10 time series stations spread over different regions of the ocean (RMSE: 3.6 to 13.2 µmol kg−1). The climatology was obtained by passing through NNGv2LDEO the monthly climatological fields of temperature, salinity, and oxygen from the World Ocean Atlas 2013 and phosphate, nitrate, and silicate computed from a neural network fed with the previous fields. The resolution is 1∘×1∘ in the horizontal, 102 depth levels (0–5500 m), and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution, and it is centered around the year 1995. The uncertainty of the climatology is low when compared with climatological values derived from measured TCO2 in the largest time series stations. Furthermore, a computed climatology of partial pressure of CO2 (pCO2) from a previous climatology of total alkalinity and the present one of TCO2 supports the robustness of this product through the good correlation with a widely used pCO2 climatology (Landschützer et al., 2017). Our TCO2 climatology is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/10551, Broullón et al., 2020).

Description: Abstract 2998 Introduction: GvHD remains the most deadly complication of HSCT despite current prevention strategies. To address the unmet need for better GvHD control, we have created a non-human primate (NHP) model with which to rigorously test mechanism and efficacy of novel therapeutics. In this study, we determined whether a novel combination of mTOR inhibition (with sirolimus) and CD28:CD80/86 costimulation blockade (with belatacept) could control GvHD. Here we show for the first time that these two agents combine synergistically to prevent both the clinical and immunologic manifestations of primate aGvHD. Methods: Rhesus macaque recipients were irradiated (9.6 Gy in 2 fractions at 7cGy/min), and then transplanted with G-CSF-mobilized PBSC from a haplo-identical donor (1–5×108 TNC/kg). Recipients were treated with either sirolimus alone (n = 4, troughs targeted at 5–10 ng/mL), belatacept alone (receiving weekly doses of 20 mg/kg), or combination therapy. Clinical GvHD was monitored using our previously described NHP grading scale (Miller et al., Blood 2010), and multiparameter flow cytometric analysis was performed. Results: Untreated controls (n = 5) developed rapid, severe histopathologically-proven aGvHD and succumbed rapidly (MST = 7 days). Recipients treated with either sirolimus or belatacept alone were partially protected from the clinical manifestations of GvHD. Sirolimus-treated recipients (n = 6) developed predominantly GI disease (with diarrhea but no elevation of bilirubin) and had an MST of 14 days (Figure 1). Recipients treated with belatacept alone (n = 3) developed primarily liver aGvHD (bilirubin rapidly rising to 6–30 × normal with histologically-confirmed lymphocytic infiltration) and an MST of 11 days. In striking contrast, recipients treated with combined sirolimus + belatacept (n = 5) demonstrated neither uncontrolled diarrhea nor hyperbilirubinemia at the timed terminal analysis (1 month post-transplant). We employed multiparameter flow cytometry to determine the immunologic consequences of sirolimus and belatacept on T cell proliferation (using Ki-67 expression) and cytotoxity (using granzyme B expression). We found that the clinical synergy observed with combined therapy was recapitulated immunologically. Thus, while untreated aGvHD was associated with rampant CD8+ proliferation (with 83 +/− 14% Ki-67+ CD8+ vs 4.7 +/− 0.6% pre-transplant), sirolimus or belatacept as monotherapy both partially controlled proliferation (35 +/− 3% and 65 +/− 23% Ki-67+ CD8+ with sirolimus or belatacept, respectively). Combined sirolimus + belatacept dramatically reduced proliferation (to 8 +/− 3%, favorably comparing with 13% Ki-67+ CD8+ T cells using standard Calcineurin Inhibitor/Methotrexate (CNI/MTX) prophylaxis). Sirolimus and belatacept both also partially controlled GvHD-related T cell cytotoxicity. Thus, while untreated aGvHD was associated with excessive granzyme B expression in CD8+ T cells (82 +/− 2% granzyme Bvery high CD8+ cells vs 0.3 +/− 0.2% pre-transplant) sirolimus or belatacept monotherapy also partially controlled cytotoxicity (8 +/− 1% and 35 +/− 1% granzyme Bvery high with sirolimus or belatacept, respectively). Combination therapy dramatically reduced the proportion of these cells, to 1.5 +/− 0.8 % granzyme Bvery high, favorably comparing with 4% granzyme Bvery high using CNI/MTX. The ability of sirolimus, belatacept, or the combination to control Ki-67 and Granzyme B expression closely correlated with survival (Figure 2A, B) supporting a pathogenic role for these highly proliferative and cytotoxic cells in aGvHD pathology. Moreover, significant co-expression of granzyme B in the Ki-67+ cells was observed (Figure 2C) suggesting that dual-positive Ki-67/Granzyme B cells may mark a pathogenic population, amenable to tracking in the peripheral blood. Implications: These results reveal a previously undiscovered synergy between sirolimus and belatacept in the control of primate aGvHD, and provide support for future clinical investigation of this novel prevention strategy. They also identify CD8+/Ki-67+/Granzyme Bvery high dual-positive T cells as a potentially sensitive biomarker of GvHD pathogenesis, amenable to monitoring in either the blood or in GvHD target organs. Disclosures: No relevant conflicts of interest to declare.

Description: Abstract 1008 Regulatory T cells (Tregs) have been shown to be potent inhibitors of autoimmunity, and to be capable of suppressing alloimmune responses that occur during both allograft rejection and graft-versus host disease. However, they have yet to gain widespread use clinically, due in part to the fact that it remains extremely costly and difficult to produce them in sufficient numbers and with sufficient suppressive capacity to significantly impact the alloimmune response. Here we have used our established non-human primate model to demonstrate that significant Treg expansion (up to 600-fold in 21 days) can be maintained, and suppressive capacity enhanced by exposing Treg cultures to a short burst of sirolimus at the end of the culture period. Using a highly sensitive and specific in vitro CFSE-MLR assay we show that Tregs significantly inhibit allo-proliferation of multiple T cell subpopulations including both CD4+ and CD8+ T cells (3.2 and 2.7-fold inhibition of proliferation, respectively), as well as their CD28+CD95+ and CD28-CD95+ subpopulations (2.2 and 2.1 and 1.9 and 2.7-fold inhibition of CD4+ and CD8+ subpopulation proliferation, respectively). Tregs were able to combine in vitro with the newly FDA-approved CTLA4-Ig analog belatacept to enhance the inhibition of alloproliferation that occurred with either agent alone (4.8-fold inhibition of CD8 T cell proliferation with Tregs + belatacept, compared to 3.0-fold or 1.9-fold inhibition of CD8 T cell proliferation with Tregs or belatacept alone, respectively). Importantly, we have found that the suppressive activity of ex-vivo expanded Tregs could be further enhanced by pulsing with sirolimus. Thus, while long-term culture of Tregs in the presence of sirolimus (1–1000 nM) profoundly inhibited Treg expansion (50–800 fold inhibition of expansion when cultured in the presence of 1–1000 nM sirolimus), a 48 hour pulse of sirolimus (100 nM) on days 20–21 of culture completely preserved Treg yields while doubling their suppressive function against CD8 proliferation when compared to unpulsed Tregs, p

Description: Abstract 1888 Introduction: There is a critical unmet need to devise effective strategies to prevent GvHD. However, the best combinatorial therapies remain undetermined, and the identification of new targeted approaches to GvHD prevention remains a challenge. To address this, we have developed a genome-wide approach to studying GvHD, using whole-transcriptome analysis of pathogenic T cells in a clinically-relevant non-human primate (NHP) model. Using computational approaches, we have identified, for the first time, the transcriptional networks that drive primate GvHD, and that lead to its partial control with sirolimus. Methods: CD3+/CD20- T cells were purified flow cytometrically from 4 cohorts: (1) Healthy Controls (“HC” n = 15); (2) Recipients of an autologous HSCT (“Auto” n = 3); (3) Haplo-identical allogeneic HSCT recipients without GvHD prophylaxis, who developed histopathologically confirmed severe aGvHD (“GvHD” n = 4); and (4) Allo-HSCT recipients who received sirolimus alone, and were partially protected from aGvHD (“Sirolimus” n = 4). Purification of T cells after allo-HSCT occurred 1–2 weeks post-transplant. RNA was purified (Qiagen), and rhesus macaque-specific Affymetrix Gene Arrays were performed. Computation: Gene array signals were processed and normalized using the Robust Multichip Averaging Method and ComBat. Principal Component Analysis (PCA) was applied to summarize modes of gene array variance. Importantly, PCA revealed that variation was primarily determined by the experimental cohort (Figure 1). This result was critical, and confirmed that transcriptomics could be applied to identify genes and pathways controlling GvHD. Differentially expressed genes (“DE”, fold change 〉 2) were defined between cohorts, yielding unique and overlapping gene signatures. We found that 775 annotated genes were DE between GvHD and HC and 286 were DE between Sirolimus and HC (Figure 2A, B). Importantly, a subset of the GvHD and Sirolimus DE gene sets were overlapping, indicating incomplete control of T cell activation with sirolimus (Figure 2B), and identifying pathways that could be targeted in combination with sirolimus for improved GvHD control. To further define genes by their individual expression profiles using an unbiased approach, we applied Class Neighbor Analysis (GenePattern, Figure 3A). Finally, using Ingenuity Pathway Analysis (IPA) we characterized gene signatures according to molecular pathways (using right-tailed Fisher's Exact test and FDR correction, Figure 3B). Results: T cells from animals with severe aGvHD demonstrated transcriptional signs of rampant proliferation and cytotoxicity as well as potentially counter-regulatory cell death pathways. IPA identified highly statistically significant upregulation of Cell Cycle and Cellular Movement networks (Figure 3B, p〈 0.001) as well as Cell Trafficking and Inflammatory Response Networks (Figure 3B, p 〈 0.001). These networks contained some expected genes and some surprises. Thus, as previously documented, GvHD was associated with upregulation of JAK and IFN signaling (p 〈 0.001). Unexpectedly, GvHD was also associated with upregulation of the Sonic Hedgehog and Aurora Kinase A Pathways (p 〈 0.01). Both of these represent targetable pathways for which novel therapeutics are currently available. Sirolimus resulted in significantly different gene expression patterns compared to uncontrolled GvHD. This included partial downregulation of the proliferation marker Ki-67 and the cytotoxicity gene, Granzyme B. However, there were many genes, pathways and networks that were shared between the Sirolimus and GvHD cohorts. These prominently included upregulation of the FOXM1 and IRF8 transcription factors, involved in cell cycle progression (p

Description: The Surface Ocean CO2 Atlas (SOCAT) is an effort by the international marine carbon research community. It aims to improve access to carbon dioxide measurements in the surface oceans by regular releases of quality controlled and fully documented synthesis and gridded fCO2 (fugacity of carbon dioxide) products. SOCAT version 2 presented here extends the data set for the global oceans and coastal seas by four years and has 10.1 million surface water fCO2 values from 2660 cruises between 1968 and 2011. The procedures for creating version 2 have been comparable to those for version 1. The SOCAT website (http://www.socat.info/) provides access to the individual cruise data files, as well as to the synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Scientific users can also retrieve the data as downloadable files or via Ocean Data View. Version 2 enables carbon specialists to expand their studies until 2011. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longer-term variation, as well as initialisation or validation of ocean carbon models and coupled-climate carbon models.

Description: This paper defines the best practices for documenting ocean acidification (OA) metadata and presents a framework for an OA metadata template. Metadata is structured information that describes and locates an information resource. It is the key to ensuring that a data set will survive and continue to be accessible into the future. With the rapid expansion of studies on biological responses of organisms to OA, the lack of a common metadata template to document the resulting data poses a significant hindrance to effective OA data management efforts. In this paper, we present a metadata template that can be applied to a broad spectrum of OA studies, including those studying the biological responses of organisms to OA. The "variable metadata section", which includes the variable name, observation type, whether the variable is a manipulation condition or response variable, and the biological subject on which the variable is studied, forms the core of this metadata template. Additional metadata elements, such as investigators, temporal and spatial coverage, platforms for the sampling, data citation, are essential components to complete the template. We also explain the structure of the template, and define many metadata elements that may be unfamiliar to researchers. Template availability. - Available at: http://ezid.cdlib.org/id/doi:10.7289/V5C24TCK. - DOI: doi:10.7289/V5C24TCK. - NOAA Institutional Repository Accession number: ocn881471371.

Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.5 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.4 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "Living Data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014).

Description: For version 2 of the Global Ocean Data Analysis Project (GLODAPv2) we collated data from 724 scientific cruises covering the global ocean: data assembled in the previous efforts GLODAPv1.1 (Global Ocean Data Analysis Project version 1.1) in 2004, CARINA (CARbon IN the Atlantic) in 2009/10, and PACIFICA (PACIFic ocean Interior CArbon) in 2013, and an additional 168 cruises. Twelve core parameters (salinity, oxygen, macronutrients, seawater CO2 chemistry parameters and halogenated transient tracers) have been subjected to extensive quality control including systematic evaluation of biases between cruises. The data are available in two formats: (i) as submitted but updated to WOCE exchange format whenever required, and (ii) as a merged and calibrated data product. In the latter, adjustments have been applied to remove significant biases, respecting occurrences of any known or likely time trends. Adjustments determined by previous efforts have been re-evaluated. Hence, GLODAPv2 is not a simple merge of previous collections and some new data, but represents a unique, internally consistent data product. The original data and their documentation and doi codes are available at the Carbon Dioxide Information Analysis Center (http://cdiac.ornl.gov/oceans/GLODAPv2/). This site also provides access to the calibrated data product, which is provided as a single global file or 4 regional ones: the Arctic, Atlantic, Indian, and Pacific Oceans, under the doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2. The product files also include significant ancillary and approximated data. The latter were obtained either by interpolation of, or by calculation from, measured data. This paper documents the GLODAPv2 history, methods, and products, including a broad overview of the secondary quality control results. The magnitude of and reasoning behind the adjustments are available on a per cruise and parameter basis in an online Adjustment Table.

Description: In an intensifying effort to track ocean change and distinguish between natural and anthropogenic drivers, sustained ocean time-series measurements are becoming increasingly important. Advancements in the ocean carbon observation network over the last decade, such as the development and deployment of Moored Autonomous pCO2 (MAPCO2) systems, have dramatically improved our ability to characterize ocean climate, sea–air gas exchange, and biogeochemical processes. The MAPCO2 system provides high-resolution data that can measure interannual, seasonal, and sub-seasonal dynamics and constrain the impact of short-term biogeochemical variability on carbon dioxide (CO2) flux. Overall uncertainty of the MAPCO2 using in situ calibrations with certified gas standards and post-deployment standard operating procedures is 〈 2 μatm for seawater partial pressure of CO2 (pCO2) and 〈 1 μatm for air pCO2. The MAPCO2 maintains this level of uncertainty for over 400 days of autonomous operation. MAPCO2 measurements are consistent with ship-board seawater pCO2 measurements and GLOBALVIEW-CO2 boundary layer atmospheric values. Here we provide an open ocean MAPCO2 data set including over 100 000 individual air and seawater pCO2 measurements on 14 surface buoys from 2004 through 2011 and a description of the methods and data quality control involved. The climate quality data provided by the MAPCO2 has allowed for the establishment of open ocean observatories to track surface ocean pCO2 changes around the globe. Data are available at doi:10.3334/CDIAC/OTG.TSM_NDP092 and cdiac.ornl.gov/oceans/Moorings/ndp092.

Description: In an intensifying effort to track ocean change and distinguish between natural and anthropogenic drivers, sustained ocean time series measurements are becoming increasingly important. Advancements in the ocean carbon observation network over the last decade, such as the development and deployment of Moored Autonomous pCO2 (MAPCO2) systems, have dramatically improved our ability to characterize ocean climate, sea–air gas exchange, and biogeochemical processes. The MAPCO2 system provides high-resolution data that can measure interannual, seasonal, and sub-seasonal dynamics and constrain the impact of short-term biogeochemical variability on carbon dioxide (CO2) flux. Overall uncertainty of the MAPCO2 using in situ calibrations with certified gas standards and post-deployment standard operating procedures is 〈 2 μatm for seawater partial pressure of CO2 (pCO2) and 〈 1 μatm for air pCO2. The MAPCO2 maintains this level of uncertainty for over 400 days of autonomous operation. MAPCO2 measurements are consistent with shipboard seawater pCO2 measurements and GLOBALVIEW-CO2 boundary layer atmospheric values. Here we provide an open-ocean MAPCO2 data set including over 100 000 individual atmospheric and seawater pCO2 measurements on 14 surface buoys from 2004 through 2011 and a description of the methods and data quality control involved. The climate-quality data provided by the MAPCO2 have allowed for the establishment of open-ocean observatories to track surface ocean pCO2 changes around the globe. Data are available at doi:10.3334/CDIAC/OTG.TSM_NDP092 and http://cdiac.ornl.gov/oceans/Moorings/ndp092.