Biomass burning fuel consumption rates: a field measurement database

Landscape fires show large variability in the amount of biomass or fuel consumed per unit area burned. Fuel consumption (FC) depends on the biomass available to burn and the fraction of the biomass that is actually combusted, and can be combined with estimates of area burned to assess emissions. While burned area can be detected from space and estimates are becoming more reliable due to improved algorithms and sensors, FC is usually modeled or taken selectively from the literature. We compiled the peerreviewed literature on FC for various biomes and fuel categories to understand FC and its variability better, and to provide a database that can be used to constrain biogeochemical models with fire modules. We compiled in total 77 studies covering 11 biomes including savanna (15 studies, average FC of 4.6 t DM (dry matter) ha 1 with a standard deviation of 2.2),tropical forest (n = 19, FC = 126 +/- 77),temperate forest (n = 12, FC = 58 +/- 72),boreal forest (n = 16, FC = 35 +/- 24),pasture (n = 4, FC = 28 +/- 9.3),shifting cultivation (n = 2, FC = 23, with a range of 4.0-43),crop residue (n = 4, FC = 6.5 +/- 9.0),chaparral (n = 3, FC = 27 +/- 19),tropical peatland (n = 4, FC = 314 +/- 196),boreal peatland (n = 2, FC = 42 [42-43]),and tundra (n = 1, FC = 40). Within biomes the regional variability in the number of measurements was sometimes large, with e. g. only three measurement locations in boreal Russia and 35 sites in North America. Substantial regional differences in FC were found within the defined biomes: for example, FC of temperate pine forests in the USA was 37% lower than Australian forests dominated by eucalypt trees. Besides showing the differences between biomes, FC estimates were also grouped into different fuel classes. Our results highlight the large variability in FC, not only between biomes but also within biomes and fuel classes. This implies that substantial uncertainties are associated with using biome-averaged values to represent FC for whole biomes. Comparing the compiled FC values with co-located Global Fire Emissions Database version 3 (GFED3) FC indicates that modeling studies that aim to represent variability in FC also within biomes, still require improvements as they have difficulty in representing the dynamics governing FC

PET imaging of T cells derived from umbilical cord blood

Progress in understanding tumor-specific immune responses, genetic engineering and ex vivo manufacturing, have led to improvements in the safety and feasibility of adoptive transfer of genetically modified T cells. However, rational design, application and evaluation of T-cell therapy requires monitoring methods that can detect, locate and serially quantify these cell-mediated immune responses. Currently, such monitoring methods are chiefly limited to invasive techniques to investigate recovered cell populations for in vitro measurements including histology, flow cytometry, Q-PCR or the detection of cytokines. These assays provide episodic glimpses of the bio distribution of T cells and are limited by the number and sites of sampling. In contrast, imaging provides a methodology for quantitative, non-invasive, longitudinal and spatial in vivo information about the dynamic processes of infused T cells

Adoptive T-cell therapy improves treatment of canine non–Hodgkin lymphoma post chemotherapy

Clinical observations reveal that an augmented pace of T-cell recovery after chemotherapy correlates with improved tumor-free survival, suggesting the add-back of T cells after chemotherapy may improve outcomes. To evaluate adoptive immunotherapy treatment for B-lineage non-Hodgkin lymphoma (NHL), we expanded T cells from client-owned canines diagnosed with NHL on artificial antigen presenting cells (aAPC) in the presence of human interleukin (IL)-2 and IL-21. Graded doses of autologous T cells were infused after CHOP chemotherapy and persisted for 49 days, homed to tumor, and significantly improved survival. Serum thymidine kinase changes predicted T-cell engraftment, while anti-tumor effects correlated with neutrophil-to-lymphocyte ratios and granzyme B expression in manufactured T cells. Therefore, chemotherapy can be used to modulate infused T-cell responses to enhance anti-tumor effects. The companion canine model has translational implications for human immunotherapy which can be readily exploited since clinical-grade canine and human T cells are propagated using identical approaches

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Non peer reviewe

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Lette

Tree biomass equations for tropical peat swamp forest ecosystems in Indonesia

To assist countries to reduce emissions from deforestation and forest degradation, the United Nations has introduced the REDD+ mechanism. This performance-based incentive mechanism requires accurate quantification of carbon stock and emissions. However, currently there are limited existing local or regional equations for estimating aboveground biomass in peat swamp forests. The main objective of this study was to define the most accurate models for aboveground biomass estimation in Indonesian peat swamp forests. We found that the pan-tropical equations performed better in estimating biomass of peat swamp forests than did existing local equations. We developed new equations, based on 148 trees from 24 families with diameter at breast height in the range of 2–167 cm collected from peat swamp forests in the western part of Indonesia. Statistical indicators showed that the best model form was the common linear one using log-transformed data. Estimated biomass values needs to be back-transformed applying correction factors. The ratio estimator correction factor which derives from the ratio between the average of measured biomass and the average of predicted biomass, was found to provide the lowest mean deviation. The existing pan-tropical equations performed similarly to our mixed species and dipterocarp models but they systematically under- or over-estimated the biomass of certain species groups, especially non-dipterocarp trees. We also found that grouping by family (dipterocarp vs. non-dipterocarp) and wood density class (hardwood vs. softwood) significantly improved the accuracy of biomass estimation. In the absence of wood density values, wood density-class specific equations, instead of mixed-species equations improved the accuracy of biomass estimates