Assessing freshwater use impacts in LCA,part 2: case study of broccoli production in the UK and Spain

Background, aim and scope  

Milà i Canals et al. (Int J Life Cycle Ass 14(1):28-42, 2009) referred to as ‘Part 1’ in this paper) showed that impacts associated with use of freshwater must be treated more rigorously than is usual in life cycle assessment (LCA), going beyond the conventional consideration only of ‘blue’ water (i.e. irrigation and other abstractions), and suggested an operational method to include the impacts on freshwater ecosystems (freshwater ecosystem impact) and abiotic resource depletion (freshwater depletion). The inclusion of water-related impacts in LCA is of paramount importance, particularly for agricultural systems due to their large water consumption worldwide. A case study of UK consumption of broccoli grown in the UK and Spain is presented here to illustrate the method suggested in Part 1.     

Approaches for Addressing Life Cycle Assessment Data Gaps for Bio‐based Products

There is an increasing need for life cycle data for bio‐based products, which becomes particularly evident with the recent drive for greenhouse gas reporting and carbon footprinting studies. Meeting this need is challenging given that many bio‐products have not yet been studied by life cycle assessment (LCA), and those that have are specific and limited to certain geographic regions. In an attempt to bridge data gaps for bio‐based products, LCA practitioners can use either proxy data sets (e.g., use existing environmental data for apples to represent pears) or extrapolated data (e.g., derive new data for pears by modifying data for apples considering pear‐specific production characteristics). This article explores the challenges and consequences of using these two approaches. Several case studies are used to illustrate the trade‐offs between uncertainty and the ease of application, with carbon footprinting as an example. As shown, the use of proxy data sets is the quickest and easiest solution for bridging data gaps but also has the highest uncertainty. In contrast, data extrapolation methods may require extensive expert knowledge and are thus harder to use but give more robust results in bridging data gaps. They can also provide a sound basis for understanding variability in bio‐based product data. If resources (time, budget, and expertise) are limited, the use of averaged proxy data may be an acceptable compromise for initial or screening assessments. Overall, the article highlights the need for further research on the development and validation of different approaches to bridging data gaps for bio‐based products.     

Analysis of apoptosis regulatory genes altered by histone deacetylase inhibitors in chronic lymphocytic leukemia cells

Histone deacetylases (HDACs) play a key role in the regulation of acetylation status not only of histones but also of many other non-histone proteins involved in cell cycle regulation, differentiation or apoptosis. Therefore, histone deacetylase inhibitors (HDACi) have emerged as promising anticancer agents. Herein, we report the characterization of apoptosis in B-cell chronic lymphocytic leukemia (CLL) induced by two HDACi, Kendine 92 and SAHA. Both inhibitors induce dose-, time- and caspase-dependent apoptosis through the mitochondrial pathway. Interestingly, Kendine 92 and SAHA show a selective cytotoxicity for B lymphocytes and induce apoptosis in CLL cells with mutated or deleted TP53 as effectively as in tumor cells harboring wild-type TP53. The pattern of apoptosis-related gene and protein expression profile has been characterized. It has shown to be irrespective of TP53 status and highly similar between SAHA and Kendine 92 exposure. The balance between the increased BAD, BNIP3L, BNIP3, BIM, PUMA and AIF mRNA expression levels, and decreased expression of BCL-W, BCL-2, BFL-1, XIAP and FLIP indicates global changes in the apoptosis mRNA expression profile consistent with the apoptotic outcome. Protein expression analysis shows increased levels of NOXA, BIM and PUMA proteins upon Kendine 92 and SAHA treatment. Our results highlight the capability of these molecules to induce apoptosis not only in a selective manner but also in those cells frequently resistant to standard treatments. Thus, Kendine 92 is a novel HDACi with anticancer efficacy for non-proliferating CLL cells.     

Activation of p53 by nutlin-3a induces apoptosis and cellular senescence in human glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in adults. Despite concerted efforts to improve current therapies and develop novel clinical approaches, patient survival remains poor. As such, increasing attention has focused on developing new therapeutic strategies that specifically target the apoptotic pathway in order to improve treatment responses. Recently, nutlins, small-molecule antagonists of MDM2, have been developed to inhibit p53-MDM2 interaction and activate p53 signaling in cancer cells. Glioma cell lines and primary cultured glioblastoma cells were treated with nutlin-3a. Nutlin-3a induced p53-dependent G1- and G2-M cell cycle arrest and apoptosis in glioma cell lines with normal TP53 status. In addition, nutlin-arrested glioma cells show morphological features of senescence and persistent induction of p21 protein. Furthermore, senescence induced by nutlin-3a might be depending on mTOR pathway activity. In wild-type TP53 primary cultured cells, exposure to nutlin-3a resulted in variable degrees of apoptosis as well as cellular features of senescence. Nutlin-3a-induced apoptosis and senescence were firmly dependent on the presence of functional p53, as revealed by the fact that glioblastoma cells with knockdown p53 with specific siRNA, or cells with mutated or functionally impaired p53 pathway, were completely insensitive to the drug. Finally, we also found that nutlin-3a increased response of glioma cells to radiation therapy. The results provide a basis for the rational use of MDM2 antagonists as a novel treatment option for glioblastoma patients.     

Two Functional Variants of IRF5 Influence the Development of Macular Edema in Patients with Non-Anterior Uveitis

Objective

Interferon (IFN) signaling plays a crucial role in autoimmunity. Genetic variation in interferon regulatory factor 5 (IRF5), a major regulator of the type I interferon induction, has been associated with risk of developing several autoimmune diseases. In the current study we aimed to evaluate whether three sets of correlated IRF5 genetic variants, independently associated with SLE and with different functional roles, are involved in uveitis susceptibility and its clinical subphenotypes.

Methods

Three IRF5 polymorphisms, rs2004640, rs2070197 and rs10954213, representative of each group, were genotyped using TaqMan® allelic discrimination assays in a total of 263 non-anterior uveitis patients and 724 healthy controls of Spanish origin.

Results

A clear association between two of the three analyzed genetic variants, rs2004640 and rs10954213, and the absence of macular edema was observed in the case/control analysis (P _FDR=5.07E-03, OR=1.48, CI 95%=1.14-1.92 and P _FDR=3.37E-03, OR=1.54, CI 95%=1.19-2.01, respectively). Consistently, the subphenotype analysis accordingly with the presence/absence of this clinical condition also reached statistical significance (rs2004640: P=0.037, OR=0.69, CI 95%=0.48-0.98; rs10954213: P=0.030, OR=0.67, CI 95%=0.47-0.96), thus suggesting that both IRF5 genetic variants are specifically associated with the lack of macular edema in uveitis patients.

Conclusion

Our results clearly showed for the first time that two functional genetic variants of IRF5 may play a role in the development of macular edema in non-anterior uveitis patients. Identifying genetic markers for macular edema could lead to the possibility of developing novel treatments or preventive therapies.     

Principles for life cycle inventories of land use on a global scale

Purpose

To assess the diverse environmental impacts of land use, a standardization of quantifying land use elementary flows is needed in life cycle assessment (LCA). The purpose of this paper is to propose how to standardize the land use classification and how to regionalize land use elementary flows.

Materials and methods

In life cycle inventories, land occupation and transformation are elementary flows providing relevant information on the type and location of land use for land use impact assessment. To find a suitable land use classification system for LCA, existing global land cover classification systems and global approaches to define biogeographical regions are reviewed.

Results and discussion

A new multi-level classification of land use is presented. It consists of four levels of detail ranging from very general global land cover classes to more refined categories and very specific categories indicating land use intensities. Regionalization is built on five levels, first distinguishing between terrestrial, freshwater, and marine biomes and further specifying climatic regions, specific biomes, ecoregions and finally indicating the exact geo-referenced information of land use. Current land use inventories and impact assessment methods do not always match and hinder a comprehensive assessment of land use impact. A standardized definition of land use types and geographic location helps to overcome this gap and provides the opportunity to test the optimal resolution of land cover types and regionalization for each impact pathway.

Conclusions and recommendation

The presented approach provides the necessary flexibility to providers of inventories and developers of impact assessment methods. To simplify inventories and impact assessment methods of land use, we need to find archetypical situations across impact pathways, land use types and regions, and aggregate inventory entries and methods accordingly.

     

Consider a Spherical Man

Emissions derived from human digestion of food and subsequent excretion are very relevant from a life cycle perspective, and yet they are often omitted from food life cycle assessment (LCA) studies. This article offers a simple model to allocate and include these emissions in LCAs of specific foodstuffs. The model requires basic food composition values and calculates the mass and energy balance for carbon, water, nutrients (mainly nitrogen [N] and phosphorus [P]), and other inorganic substances through different excretion paths: breathing, feces, and urine. In addition to direct excretion, the model also allocates some auxiliary materials and energy related to toilet use, such as flushing and washing and drying hands. Wastewater composition is also an output of the model, enabling water treatment to be modeled in LCA studies. The sensitivity of the model to food composition is illustrated with different food products, and the relative importance of excretion in a product's life cycle is shown with an example of broccoli. The results show that this model is sensitive to food composition and thus useful for assessing the environmental consequences of shifts in diet. From a life cycle perspective, the results show that postconsumption nutrient emissions may dominate the impacts on eutrophication potential, and they illustrate how the carbon cycle is closed with the human emissions after food preparation and consumption.