Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional ...carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.
Plain Language Summary
A carbon budget for a particular site or region describes the inputs and outputs of carbon to that site or region as well as the processes that change carbon from one form to another. A carbon budget is needed to fully understand many important issues facing coastal waters. We constructed the carbon budget for coastal waters of eastern North America. We found that about 60% of the carbon entering the domain is from rivers and about 40% is from the atmosphere, while about 80% of the carbon leaving the domain goes to the open ocean and about 20% is buried. Transfers of carbon from wetlands to estuaries and from estuaries to the ocean were as important as transfers of carbon at the domain boundaries. Tidal wetlands and estuaries were found to be important to the carbon budget despite making up only 2.4 and 8.9% of the study domain area, respectively. This study shows that coastal carbon budgets should explicitly consider tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.
Key Points
Tidal wetlands, estuaries, and shelf waters each contribute substantially to the carbon budget of eastern North American coastal waters
Study region net ecosystem production, atmospheric uptake, and burial are 20.2 ± 4.4, 5.1 ± 2.4, and 2.5 ± 0.7 Tg C yr−1, respectively
Net lateral carbon fluxes between tidal wetlands, estuaries, and shelf waters are large terms in the carbon budget of eastern North American coastal waters
Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models ...could allow health systems and vector control programmes to respond more cost-effectively and efficiently.
The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007-2013. These data were split between the years 2007-2011 (historic period) and 2012-2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1-12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1-12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4-16 weeks.
An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Glioblastoma multiforme (GBM) is a primary brain tumor with a median survival of 14.6 months postdiagnosis. The infiltrative nature of GBM prevents complete resection and residual brain tumor cells ...give rise to recurrent GBM, a hallmark of this disease. Recurrent GBMs are known to harbor numerous mutations/gene rearrangements when compared to the primary tumor, which leads to the potential expression of novel proteins that could serve as tumor neoantigens. We have developed a combined immune-based gene therapeutic approach for GBM using adenoviral (Ads) mediated gene delivery of Herpes Simplex Virus Type 1-thymidine kinase (TK) into the tumor mass to induce tumor cells' death combined with an adenovirus expressing fms-like tyrosine kinase 3 ligand (Flt3L) to recruit dendritic cells (DCs) into the tumor microenvironment. This leads to the induction of specific anti-brain tumor immunity and immunological memory. In a model of GBM recurrence, we demonstrate that Flt3L/TK mediated immunological memory is capable of recognizing brain tumor neoantigens absent from the original treated tumor. These data demonstrate that the Flt3L/TK gene therapeutic approach can induce systemic immunological memory capable of recognizing a brain tumor neoantigen in a model of recurrent GBM.
Astrocytes usually respond to trauma, stroke, or neurodegeneration by undergoing cellular hypertrophy, yet, their response to a specific immune attack by T cells is poorly understood. Effector T ...cells establish specific contacts with target cells, known as immunological synapses, during clearance of virally infected cells from the brain. Immunological synapses mediate intercellular communication between T cells and target cells, both in vitro and in vivo. How target virally infected astrocytes respond to the formation of immunological synapses established by effector T cells is unknown.
Herein we demonstrate that, as a consequence of T cell attack, infected astrocytes undergo dramatic morphological changes. From normally multipolar cells, they become unipolar, extending a major protrusion towards the immunological synapse formed by the effector T cells, and withdrawing most of their finer processes. Thus, target astrocytes become polarized towards the contacting T cells. The MTOC, the organizer of cell polarity, is localized to the base of the protrusion, and Golgi stacks are distributed throughout the protrusion, reaching distally towards the immunological synapse. Thus, rather than causing astrocyte hypertrophy, antiviral T cells cause a major structural reorganization of target virally infected astrocytes.
Astrocyte polarization, as opposed to hypertrophy, in response to T cell attack may be due to T cells providing a very focused attack, and thus, astrocytes responding in a polarized manner. A similar polarization of Golgi stacks towards contacting T cells was also detected using an in vitro allogeneic model. Thus, different T cells are able to induce polarization of target astrocytes. Polarization of target astrocytes in response to immunological synapses may play an important role in regulating the outcome of the response of astrocytes to attacking effector T cells, whether during antiviral (e.g. infected during HIV, HTLV-1, HSV-1 or LCMV infection), anti-transplant, autoimmune, or anti-tumor immune responses in vivo and in vitro.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Soluble antigens diffuse out of the brain and can thus stimulate a systemic immune response, whereas particulate antigens (from infectious agents or tumor cells) remain within brain tissue, thus ...failing to stimulate a systemic immune response. Immune privilege describes how the immune system responds to particulate antigens localized selectively within the brain parenchyma. We believe this immune privilege is caused by the absence of antigen presenting dendritic cells from the brain. We tested the prediction that expression of fms-like tyrosine kinase ligand 3 (Flt3L) in the brain will recruit dendritic cells and induce a systemic immune response against exogenous influenza hemagglutinin in BALB/c mice. Coexpression of Flt3L with HA in the brain parenchyma induced a robust systemic anti-HA immune response, and a small response against myelin basic protein and proteolipid protein epitopes. Depletion of CD4 + CD25+ regulatory T cells (Tregs) enhanced both responses. To investigate the autoimmune impact of these immune responses, we characterized the neuropathological and behavioral consequences of intraparenchymal injections of Flt3L and HA in BALB/c and C57BL/6 mice. T cell infiltration in the forebrain was time and strain dependent, and increased in animals treated with Flt3L and depleted of Tregs; however, we failed to detect widespread defects in myelination throughout the forebrain or spinal cord. Results of behavioral tests were all normal. These results demonstrate that Flt3L overcomes the brain's immune privilege, and supports the clinical development of Flt3L as an adjuvant to stimulate clinically effective immune responses against brain neo-antigens, for example, those associated with brain tumors.
CD8(+) T cells infiltrate the brain during an anti-viral immune response. Within the brain CD8(+) T cells recognize cells expressing target antigens, become activated, and secrete IFNγ. However, ...there are no methods to recognize individual cells that respond to IFNγ. Using a model that studies the effects of the systemic anti-adenoviral immune response upon brain cells infected with an adenoviral vector in mice, we describe a method that identifies individual cells that respond to IFNγ. To identify individual mouse brain cells that respond to IFNγ we constructed a series of adenoviral vectors that contain a transcriptional response element that is selectively activated by IFNγ signaling, the gamma-activated site (GAS) promoter element; the GAS element drives expression of a transgene, Cre recombinase (Ad-GAS-Cre). Upon binding of IFNγ to its receptor, the intracellular signaling cascade activates the GAS promoter, which drives expression of the transgene Cre recombinase. We demonstrate that upon activation of a systemic immune response against adenovirus, CD8(+) T cells infiltrate the brain, interact with target cells, and cause an increase in the number of cells expressing Cre recombinase. This method can be used to identify, study, and eventually determine the long term fate of infected brain cells that are specifically targeted by IFNγ. The significance of this method is that it will allow to characterize the networks in the brain that respond to the specific secretion of IFNγ by anti-viral CD8(+) T cells that infiltrate the brain. This will allow novel insights into the cellular and molecular responses underlying brain immune responses.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
BackgroundType 2 diabetes (T2D) is a major risk factor associated with cardiometabolic diseases, and a major contributor towards mortality and morbidity, given its rapidly rising prevalence ...worldwide. In experimental studies, trans-fatty acids (TFAs) exert harmful biologic effects that may affect T2D risk, but findings from observational studies remain inconclusive, especially for biomarkers which provide an objective advantage with less recall bias and estimation errors. By pooling multiple studies, we may also increase generalizability, statistical power, and address potential interactions by subgroups. Therefore, we assessed prospective associations between circulating biomarkers of individual TFAs and incident T2D in a large, diverse sample.MethodsWe pooled ten prospective cohort or nested-case-control studies from Australia, Germany, Iceland, UK, and the USA to perform an analysis using harmonized individual level data for TFA biomarkers and incident T2D. Fatty acids (FAs) were measured in plasma phospholipid, red blood cell membrane phospholipid, or total plasma collected between 1990–2008 from 22,711 participants aged ≥18 years without prevalent diabetes. Evaluated TFAs included trans-16:1n-9, sum of trans-18:1 isomers (trans-18:1n6 to trans-18:1n12), sum of trans-18:2 isomers (cis/trans-18:2, trans/cis-18:2, trans/trans-18:2), and individual trans-18:2 isomers. The multivariable-adjusted relative risk or odds ratio was estimated for each cohort by lipid compartments using a pre-specified protocol for definitions of exposures, covariates, and outcomes for statistical analysis. Association estimates were pooled using fixed-effects inverse-variance weighted meta-analysis.ResultsDuring an average maximum of 14 years of follow-up, 2,244 cases of incident T2D were identified. Median levels of TFAs across cohorts were 0.05–0.18% total FAs for trans-16:1n-9, 0.09–2.05% for total trans-18:1, 0.10–0.73% for total trans-18:2, and 0.01–0.36% for individual trans-18:2 isomers. In overall pooled analysis, TFAs evaluated per inter-quintile range were not significantly associated with risk of T2D. Relative risks for individual TFAs were 1.02 (0.78–1.32) for trans-16:1n-9, 0.92 (0.79–1.08) for total trans-18:1, 1.16 (0.98–1.37) for trans/trans-18:2, 0.98 (0.79–1.21) for cis/trans-18:2, 0.93 (0.76–1.14) for trans/cis-18:2, and 0.90 (0.78–1.04) for total trans-18:2. Findings were consistent when TFAs were assessed categorically by study-specific quintiles, and when associations were pooled within lipid compartment (phospholipids or total plasma).ConclusionWe found that biomarker levels of TFAs were not significantly associated with risk of incident T2D in this international pooling project. Findings may reflect no effect of circulating TFA on T2D or be influenced by mixed TFA sources (industrial or ruminant), or to a general decline in TFA exposure during this period. Associations with T2D for higher levels of TFA biomarkers should be investigated.
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Background: The interaction between donor killer immunoglobulin-like receptor (KIR) and recipient HLA has been postulated to enhance the graft-versus-leukemia effect in allogeneic hematopoietic ...cell transplantation (HCT) for acute myeloid leukemia (AML). Historically, analyses of individual interactions between single KIR and their respective HLA ligands have yielded conflicting findings, and the clinical importance of these interactions in the matched unrelated donor (MUD) setting remains controversial. Here, we applied a systematic approach, studying both a wide range of KIR and class I HLA interactions at the single-receptor level as well as the most prevalent KIR genotypes in a large cohort of AML patients undergoing MUD transplantation.
Methods: We included adult AML patients in complete remission transplanted from an 8/8-HLA MUD between 2010 and 2016 and reported to the Center for International Blood and Marrow Transplant Research (CIBMTR). Donor-KIR and respective recipient-HLA ligand interactions were assessed in multivariable Cox proportional hazard models for standard transplantation outcomes. To account for the compound effect of simultaneous KIR/HLA interactions, we applied a combinatorial approach to identify aggregate KIR genotypes based on combinations of individual KIR genes. The most frequently observed donor-KIR genotypes, in combination with recipient ligands, were evaluated for association with relapse using multivariable regression. Those associated (p < 0.01) with relapse risk were evaluated for differential relapse in a DRST (German stem-cell registry)/Collaborative Biobank cohort of donors/patients with similar inclusion criteria.
Results: A total of 2,036 transplantations from the CIBMTR were included. Most patients were treated in first complete remission (78%) and received myeloablative conditioning (59%). We first studied eight known interactions between donor KIR and their respective HLA ligands (Figure A). Only donor-KIR-2DL2+/recipient-HLA-C1+ was associated with reduced relapse (compared to donor-KIR-2DL2-/recipient-HLA-C1+, hazard ratio HR 0.80 95% confidence interval 0.67-0.94, p=0.008). However, no difference was found when comparing HLA-C group pairs among KIR-2DL2+ recipients, suggesting this finding is confounded by co-occurrence of other receptors.
There are hundreds of possible KIR gene combinations (i.e. genotypes), which are typically clustered into two primary haplotypes, A and B. To study the cumulative effect of donor KIR, we investigated nine prevalent KIR genotypes (Figure B) and identified three significantly associated with relapse risk. (1) Donor KIR genotype 5 in all recipients irrespective of their HLA (Figure C, n = 138/2,036) and (2) genotype 3 in HLA-Bw4/x recipients (Figure D, n = 51/1,198) had significantly decreased relapse risk (HR 0.53 0.37-0.78, p=0.002 and 0.34 0.15-0.75, p=0.008, respectively). (3) KIR genotype 2 was associated with greater relapse in HLA-C1-homozygous recipients (Figure E, n = 87/836, HR 1.62 1.14-2.30, p=0.007). These findings were not confirmed in the external European dataset (n = 796, Figure 1C-E); however, this cohort differed in ways that might affect the importance of KIRs, such as the higher frequency of reduced intensity conditioning (74% vs. 41%) and in-vivo T-cell depletion (79% vs. 37%).
Conclusion: Our systematic investigation in two large AML cohorts receiving MUD allogenic HCT did not validate any association between individual KIR-HLA interactions and clinical outcomes. A combinatorial approach identified combinations potentially protective against relapse, however these could not be confirmed in a second dataset. Overall, our findings do not support KIR-informed donor selection using the approaches outlined here.
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Shouval: Medexus: Consultancy. Kroeger: AOP Pharma: Honoraria; Gilead/Kite: Honoraria; Riemser: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Sanofi: Honoraria; Neovii: Honoraria, Research Funding; Novartis: Honoraria. Horowitz: Daiicho Sankyo: Research Funding; Allovir: Consultancy; Miltenyi Biotech: Research Funding; Medac: Research Funding; Kite/Gilead: Research Funding; Genentech: Research Funding; Jazz Pharmaceuticals: Research Funding; Janssen: Research Funding; Kiadis: Research Funding; CSL Behring: Research Funding; Gamida Cell: Research Funding; bluebird bio: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Research Funding; Astellas: Research Funding; Chimerix: Research Funding; GlaxoSmithKline: Research Funding; Novartis: Research Funding; Magenta: Consultancy, Research Funding; Actinium: Research Funding; Mesoblast: Research Funding; Omeros: Research Funding; Orca Biosystems: Research Funding; Pfizer, Inc: Research Funding; Pharmacyclics: Research Funding; Regeneron: Research Funding; Sanofi: Research Funding; Seattle Genetics: Research Funding; Shire: Research Funding; Sobi: Research Funding; Stemcyte: Research Funding; Takeda: Research Funding; Tscan: Research Funding; Vertex: Research Funding; Vor Biopharma: Research Funding; Xenikos: Research Funding. Malmberg: Merck: Research Funding; Vycellix: Consultancy; Fate Therapeutics: Consultancy, Research Funding. Miller: Sanofi: Membership on an entity's Board of Directors or advisory committees; Magenta: Membership on an entity's Board of Directors or advisory committees; ONK Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Vycellix: Consultancy; GT Biopharma: Consultancy, Patents & Royalties, Research Funding; Fate Therapeutics, Inc: Consultancy, Patents & Royalties, Research Funding; Wugen: Membership on an entity's Board of Directors or advisory committees. Mohty: Sanofi: Honoraria, Research Funding; Pfizer: Honoraria; Novartis: Honoraria; Takeda: Honoraria; Jazz: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Gilead: Honoraria; Celgene: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria; Astellas: Honoraria; Amgen: Honoraria; Adaptive Biotechnologies: Honoraria. Romee: Crispr Therapeutics: Research Funding; Glycostem: Membership on an entity's Board of Directors or advisory committees. Schetelig: Roche: Honoraria, Other: lecture fees; Novartis: Honoraria, Other: lecture fees; BMS: Honoraria, Other: lecture fees; Abbvie: Honoraria, Other: lecture fees; AstraZeneca: Honoraria, Other: lecture fees; Gilead: Honoraria, Other: lecture fees; Janssen: Honoraria, Other: lecture fees . Weisdorf: Fate Therapeutics: Research Funding; Incyte: Research Funding. Koreth: Biolojic Design: Other: Scientific Advisory Board; Mallinckrodt: Other: Scientific Advisory Board; Cugene: Other: Scientific Advisory Board; Moderna: Consultancy; Amgen: Consultancy; EMD Serono/Merck: Consultancy; Gentibio Inc.: Consultancy; Miltenyi Biotec: Research Funding; BMS: Research Funding; Clinigen Labs: Research Funding; Regeneron: Research Funding; Equillium: Research Funding.
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