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  • PANGAEA  (7)
  • American Society of Hematology  (3)
  • Molecular Diversity Preservation International  (2)
  • The Oceanography Society  (2)
  • 157, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U. S. Department of Energy  (1)
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  • 1
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    Synergistic Control of Acute GvHD: Effectively Down-Regulating T Cell Proliferation and Cytotoxicity with Combined mTOR Inhibition and CD28:CD80/86 Costimulation Blockade. (2012)
    American Society of Hematology
    Details
    Publication Date: 2012-11-16
    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.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
    Published by American Society of Hematology
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  • 2
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    Sirolimus Inhibits Proliferation but Enhances Suppressive Activity of Rhesus Macaque Natural CD4 Regulatory T Cells (2011)
    American Society of Hematology
    Details
    Publication Date: 2011-11-18
    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
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
    Published by American Society of Hematology
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  • 3
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    Defining the Primate GvHD Transcriptome: Network Analysis Identifies the Key Pathways Responsible for GvHD Pathogenesis and the Mechanisms of Partial GvHD Control with Sirolimus (2012)
    American Society of Hematology
    Details
    Publication Date: 2012-11-16
    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
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
    Published by American Society of Hematology
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  • 4
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    Data Management Strategy to Improve Global Use of Ocean Acidification Data and Information (2015)
    The Oceanography Society
    Details
    Publication Date: 2015-06-01
    Print ISSN: 1042-8275
    Electronic ISSN: 2377-617X
    Topics: Geosciences
    Published by The Oceanography Society
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  • 5
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    Granulibacter bethesdensis, a Pathogen from Patients with Chronic Granulomatous Disease, Produces a Penta-Acylated Hypostimulatory Glycero-D-talo-oct-2-ulosonic Acid–Lipid A Glycolipid (Ko-Lipid A) (2021)
    Molecular Diversity Preservation International
    Details
    Publication Date: 2021-03-24
    Description: Granulibacter bethesdensis can infect patients with chronic granulomatous disease, an immunodeficiency caused by reduced phagocyte NADPH oxidase function. Intact G. bethesdensis (Gb) is hypostimulatory compared to Escherichia coli, i.e., cytokine production in human blood requires 10–100 times more G. bethesdensis CFU/mL than E. coli. To better understand the pathogenicity of G. bethesdensis, we isolated its lipopolysaccharide (GbLPS) and characterized its lipid A. Unlike with typical Enterobacteriaceae, the release of presumptive Gb lipid A from its LPS required a strong acid. NMR and mass spectrometry demonstrated that the carbohydrate portion of the isolated glycolipid consists of α-Manp-(1→4)-β-GlcpN3N-(1→6)-α-GlcpN-(1⇿1)-α-GlcpA tetra-saccharide substituted with five acyl chains: the amide-linked N-3′ 14:0(3-OH), N-2′ 16:0(3-O16:0), and N-2 18:0(3-OH) and the ester-linked O-3 14:0(3-OH) and 16:0. The identification of glycero-d-talo-oct-2-ulosonic acid (Ko) as the first constituent of the core region of the LPS that is covalently attached to GlcpN3N of the lipid backbone may account for the acid resistance of GbLPS. In addition, the presence of Ko and only five acyl chains may explain the 〉10-fold lower proinflammatory potency of GbKo–lipidA compared to E. coli lipid A, as measured by cytokine induction in human blood. These unusual structural properties of the G.bethesdensis Ko–lipid A glycolipid likely contribute to immune evasion during pathogenesis and resistance to antimicrobial peptides.
    Print ISSN: 1661-6596
    Electronic ISSN: 1422-0067
    Topics: Chemistry and Pharmacology
    Published by Molecular Diversity Preservation International
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  • 6
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    The Role of Flavonoids in Invasion Strategy of Solidago canadensis L. (2021)
    Molecular Diversity Preservation International
    Details
    Publication Date: 2021-08-23
    Description: This study provides data on the problem of potential complexation of phenolic compounds synthesized by the plants Solidago canadensis L. and Solidago gigantea Ait. with ammonium forms of nitrogen, partly immobilized in the soil. A comparative analysis of secondary metabolites of the studied plants was performed by HPLC. The leaves of invasively active Solidago canadensis contain nine times more rutin than the plants of Solidago gigantea. Adding to the leaf extracts (v/v1/20) aqueous ammonia solution to pH 8.0 on the chromatograms decreases the intensity or completely causes peaks of flavonoids to disappear; instead, there are peaks of new polar substances (tR 1.5 and 2.0 min). The selective effect of the phenol-ammonium complex on various plant species was revealed. At a concentration of 20 μg/mL, these substances stimulated the formation of lateral roots in soybean seedlings and chrysanthemum cuttings. The suppression of root growth in radish seedlings occurred at a concentration of flavonoids in the extract of 25 μg/mL. In addition, a positive chemotaxis of the Pseudomonas putida (PGPR) was detected in the nitrogen-containing complex based on rutin (5 μg/mL). The identified feature allows PGPR colonization of the root system of Solidago canadensis with corresponding changes in the structure of the microbial community. The ability of the obtained nitrogen-containing polar complexes to regulate the growth processes of plants at extremely low concentration points to promising research in this direction.
    Electronic ISSN: 2223-7747
    Topics: Biology
    Published by Molecular Diversity Preservation International
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  • 7
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    CARINA Data Synthesis Project (2009)
    157, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U. S. Department of Energy
    In:  ORNL/CDIAC . 157, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U. S. Department of Energy, Oak Ridge, TN, USA, VII, 11 pp.
    Details
    Publication Date: 2019-10-10
    Type: Report , NonPeerReviewed
    Format: text
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  • 8
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    Surface Ocean CO2 Atlas (SOCAT) V4 (2016)
    PANGAEA
    Details
    Publication Date: 2024-05-02
    Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis activity by the international marine carbon research community (〉100 contributors). SOCAT version 4 has 18.5 million quality-controlled, surface ocean fCO2 (fugacity of carbon dioxide) observations with an accuracy of better than 5 µatm from 1957 to 2015 for the global oceans and coastal seas. Automation of data upload and initial data checks speeds up data submission and allows annual releases of SOCAT from version 4 onwards. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in research coordination, data access, biogeochemical and climate research and in informing policy.
    Keywords: SOCAT; Surface Ocean CO2 Atlas Project
    Type: Dataset
    Format: application/zip, 1265 datasets
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  • 9
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    Surface Ocean CO2 Atlas (SOCAT) v2019. New and updated individual cruise datasets (2019)
    PANGAEA
    Details
    Publication Date: 2024-05-02
    Description: The Surface Ocean CO2 Atlas (SOCAT) is a synthesis activity by the international marine carbon research community (〉100 contributors). SOCATv2019 has 25.7 million quality-controlled, surface ocean fCO2 (fugacity of carbon dioxide) observations from 1957 to 2019 for the global oceans and coastal seas. Calibrated sensor data are also available. Automation allows annual, public releases. SOCAT data is discoverable, accessible and citable. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in biogeochemical and climate research and in informing policy. This publication contains the individual cruise files that are new or updated from SOCATv6, with cruise QC flags A-E and all fCO2 WOCE flags. The synthesis file hosted in NOAA NCEI (see other version) contains A-D cruises and WOCE flag 2 (good) data. To download the SOCATv2019 data product in other formats or subsets, please go to www.socat.info.
    Keywords: SOCAT; SOCATv2019; Surface Ocean CO2 Atlas Project
    Type: Dataset
    Format: application/zip, 531 datasets
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  • 10
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    Surface Ocean CO2 Atlas (SOCAT) V1.4 (2013)
    PANGAEA
    In:  Supplement to: Pfeil, Benjamin; Olsen, Are; Bakker, Dorothee C E; Hankin, Steven; Koyuk, Heather; Kozyr, Alexander; Malczyk, Jeremy; Manke, Ansley; Metzl, Nicolas; Sabine, Christopher L; Akl, John; Alin, Simone R; Bellerby, Richard G J; Borges, Alberto Vieira; Boutin, Jacqueline; Brown, Peter J; Cai, Wei-Jun; Chavez, Francisco P; Chen, Arthur; Cosca, Catherine E; Fassbender, Andrea J; Feely, Richard A; González-Dávila, Melchor; Goyet, Catherine; Hardman-Mountford, Nicolas J; Heinze, Christoph; Hood, E Maria; Hoppema, Mario; Hunt, Christopher W; Hydes, David; Ishii, Masao; Johannessen, Truls; Jones, Steve D; Key, Robert M; Körtzinger, Arne; Landschützer, Peter; Lauvset, Siv K; Lefèvre, Nathalie; Lenton, Andrew; Lourantou, Anna; Merlivat, Liliane; Midorikawa, Takashi; Mintrop, Ludger J; Miyazaki, Chihiro; Murata, Akihiko; Nakadate, Akira; Nakano, Yoshiyuki; Nakaoka, Shin-Ichiro; Nojiri, Yukihiro; Omar, Abdirahman M; Padín, Xose Antonio; Park, Geun-Ha; Paterson, Kristina; Pérez, Fiz F; Pierrot, Denis; Poisson, Alain; Ríos, Aida F; Santana-Casiano, Juana Magdalena; Salisbury, Joe; Sarma, Vedula V S S; Schlitzer, Reiner; Schneider, Bernd; Schuster, Ute; Sieger, Rainer; Skjelvan, Ingunn; Steinhoff, Tobias; Suzuki, Toru; Takahashi, Taro; Tedesco, Kathy; Telszewski, Maciej; Thomas, Helmuth; Tilbrook, Bronte; Tjiputra, Jerry; Vandemark, Doug; Veness, Tony; Wanninkhof, Rik; Watson, Andrew J; Weiss, Ray F; Wong, Chi Shing; Yoshikawa-Inoue, Hisayuki (2013): A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT). Earth System Science Data, 5(1), 125-143, https://doi.org/10.5194/essd-5-125-2013
    Details
    Publication Date: 2024-05-02
    Description: A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968-2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.
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18QA19760111-track; 18QA19760619-track; 18QA19760911-track; 18QA19761204-track; 18VC19740105-track; 18VC19740216-track; 18VC19741113-track; 18VC19750622-track; 18VC19750913-track; 1995-10-BS; 1996-02-BS; 1997-05-BS; 1999-07-BS; 1999-11-BS; 1999-12-BS; 2000-01-BS; 2000-02-BS; 2000-03-BS; 2001-05-BS; 2001-06-BS; 2001-07-BS; 2001-08-BS; 2003-06-BS; 2003-07-BS; 2003-08-BS; 2003-09-BS; 2003-10-BS; 2004-02-BS; 2004-03-BS; 2004-04-BS; 2004-05-BS; 2004-06-BS; 2004-07-BS; 2004-08-BS; 2004-09-BS; 2004-10-BS; 2005-01-BS; 2005-02-BS; 2005-03-BS; 2005-04-BS; 2005-05-BS; 2005-06-BS; 2005-07-BS; 2005-08-BS; 2005-09-BS; 2005-10-BS; 2005-11-BS; 2005-12-BS; 2006-03-BS; 2006-04-BS; 2006-05-BS; 2006-06-BS; 2006-07-BS; 2006-08-BS; 2006-09-BS; 20070110_TC2; 20070117_TC2; 20070123_TC2; 20070130_TC2; 20070207_TC2; 20070219_TC2; 20070227_TC2; 20070305_TC2; 20070320_TC2; 20070327_TC2; 20070402_TC2; 20070409_TC2; 20070416_TC2; 20070423_TC2; 20070430_TC2; 20070508_TC2; 20070515_TC2; 20070521_TC2; 20070529_TC2; 20070604_TC2; 20070613_TC2; 20070620_TC2; 20070627_TC2; 20070703_TC2; 20070709_TC2; 20070716_TC2; 20070723_TC2; 20070730_TC2; 2007-07-BS; 20070806_TC2; 20070815_TC2; 20070820_TC2; 20070827_TC2; 2007-08-BS; 20070903_TC2; 20070910_TC2; 20070917_TC2; 20071001_TC2; 20071008_TC2; 20071010_TC2; 20071015_TC2; 20071023_TC2; 20071105_TC2; 20071115_TC2; 20071120_TC2; 20071128_TC2; 20071204_TC2; 20071211_TC2; 20071218_TC2; 20071225_TC2; 24N98L1; 24N98L2; 26GC20010421-track; 26GC20010831-track; 26NA20050107; 26NA20050107-track; 26NA20050115; 26NA20050115-track; 26NA20050130; 26NA20050130-track; 26NA20050207; 26NA20050207-track; 26NA20050317; 26NA20050317-track; 26NA20050321; 26NA20050321-track; 26NA20050402; 26NA20050402-track; 26NA20050420; 26NA20050420-track; 26NA20050502; 26NA20050502-track; 26NA20050511; 26NA20050511-track; 26NA20050523; 26NA20050523-track; 26NA20050531; 26NA20050531-track; 26NA20050614; 26NA20050614-track; 26NA20050624; 26NA20050624-track; 26NA20050714; 26NA20050714-track; 26NA20050720; 26NA20050720-track; 26NA20050730; 26NA20050730-track; 26NA20050805; 26NA20050805-track; 26NA20050815; 26NA20050815-track; 26NA20050824; 26NA20050824-track; 26NA20050914; 26NA20050914-track; 26NA20050927; 26NA20050927-track; 26NA20051005; 26NA20051005-track; 26NA20051018; 26NA20051018-track; 26NA20051026; 26NA20051026-track; 26NA20051110; 26NA20051110-track; 26NA20051117; 26NA20051117-track; 26NA20051130; 26NA20051130-track; 26NA20060518; 26NA20060518-track; 26NA20060527; 26NA20060527-track; 26NA20060607; 26NA20060607-track; 26NA20060617; 26NA20060617-track; 26NA20060628; 26NA20060628-track; 26NA20060708; 26NA20060708-track; 26NA20060719; 26NA20060719-track; 26NA20060728; 26NA20060728-track; 26NA20060809; 26NA20060809-track; 26NA20060818; 26NA20060818-track; 26NA20060830; 26NA20060830-track; 26NA20060908; 26NA20060908-track; 26NA20060920; 26NA20060920-track; 26NA20061011; 26NA20061011-track; 26NA20061021; 26NA20061021-track; 26NA20061128; 26NA20061128-track; 26NA20061202; 26NA20061202-track; 26NA20061214; 26NA20061214-track; 26NA20061225; 26NA20061225-track; 26NA20070103; 26NA20070103-track; 26NA20070112; 26NA20070112-track; 26NA20070125; 26NA20070125-track; 26NA20070205; 26NA20070205-track; 26NA20070216; 26NA20070216-track; 26NA20070323; 26NA20070323-track; 26NA20070329; 26NA20070329-track; 26NA20070410; 26NA20070410-track; 26NA20070418; 26NA20070418-track; 26NA20070427; 26NA20070427-track; 26NA20070509; 26NA20070509-track; 26NA20070518; 26NA20070518-track; 26NA20070530; 26NA20070530-track; 26NA20070610; 26NA20070610-track; 26NA20070622; 26NA20070622-track; 26NA20070701; 26NA20070701-track; 26NA20070712; 26NA20070712-track; 26NA20070721; 26NA20070721-track; 26NA20070802; 26NA20070802-track; 26NA20070811; 26NA20070811-track; 26NA20070901; 26NA20070901-track; 26NA20070912; 26NA20070912-track; 26NA20070923; 26NA20070923-track; 26NA20071003; 26NA20071003-track; 26NA20071014; 26NA20071014-track; 26NA20071024; 26NA20071024-track; 26NA20071103; 26NA20071103-track; 26NA20071114; 26NA20071114-track; 26NA20071124; 26NA20071124-track; 29HE050; 29HE19980729-track; 29HE20001028; 29HE20001028-track; 29HE20010306; 29HE20010306-track; 29HE20011027; 29HE20011027-track; 29HE20020305; 29HE20020305-track; 29HE20021028; 29HE20021028-track; 29HE20030409; 29HE20030409-track; 29HE20041021; 29HE20041021-track; 316N0154; 316N19810401-track; 316N19810416-track; 316N19810516-track; 316N19810619-track; 316N19810721-track; 316N19810821-track; 316N19810923-track; 316N19821202-track; 316N19821230-track; 316N19830130-track; 316N19831007-track; 316N19840111-track; 316N19871030-track; 316N19871123-track; 316N19871218-track; 316N19880128-track; 316N19940404-track; 316N19941201-track; 316N19950124-track; 316N19950310-track; 316N19950423-track; 316N19950611-track; 316N19950715-track; 316N19950829-track; 316N19951111-track; 316N19951205-track; 316N19961102-track; 316N19971005-track; 318M19780921-track; 318M19780928-track; 318M19790210-track; 318M19790308-track;
    Type: Dataset
    Format: application/zip, 1851 datasets
    Location Call Number Expected Availability
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    DATA PANGAEA
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