How Can the Eco‐efficiency of a Region be Measured and Monitored?

The concept of eco-efficiency is commonly referred to as a business link to sustainable development. In this article, ecoefficiency is examined at a regional level as an approach to promoting the competitiveness of economic activities in the Finnish Kymenlaakso region and mitigating their harmful impacts on the environment. The aim is to develop appropriate indicators for monitoring changes in the eco-efficiency of the region. A starting point is to produce indicators for the environmental and economic dimensions of regional development and use them for measuring regional eco-efficiency. The environmental impact indicators are based on a life-cycle assessment method, producing different types of environmental impact indicators: pressure indicators (e.g., emissions of CO₂), impact category indicators (e.g., CO₂ equivalents in the case of climate change), and a total impact indicator (aggregating different impact category indicator results into a single value). Environmental impact indicators based on direct material input, total material input, and total material requirement of the Kymenlaakso region are also assessed. The economic indicators used are the gross domestic product, the value added, and the output of the main economic sectors of Kymenlaakso. In the eco-efficiency assessment, the economic and environmental impact indicators are monitored in the same graph. In a few cases eco-efficiency ratios can also be calculated (the economic indicators are divided by the environmental indicators). Output (= value added + intermediate consumption) is used as an economic indicator related to the environmental impact indicators, which also cover the upstream processes of the region's activities. In the article, we also discuss the strengths and weaknesses of using the different environmental impact indicators.     

Debating the greening vs. browning of the North American boreal forest: differences between satellite datasets

A number of remote sensing studies have evaluated the temporal trends of the normalized difference vegetation index (NDVI or vegetation greenness) in the North American boreal forest during the last two decades, often getting quite different results. To examine the effect that the use of different datasets might be having on the estimated trends, we compared the temporal trends of recently burned and unburned sites of boreal forest in central Canada calculated from two datasets: the Global Inventory, Monitoring, and Modeling Studies (GIMMS), which is the most commonly used 8 km dataset, and a new 1 km dataset developed by the Canadian Centre for Remote Sensing (CCRS). We compared the NDVI trends of both datasets along a fire severity gradient in order to evaluate the variance in regeneration rates. Temporal trends were calculated using the seasonal Mann–Kendall trend test, a rank‐based, nonparametric test, which is robust against seasonality, nonnormality, heteroscedasticity, missing values, and serial dependence. The results showed contrasting NDVI trends between the CCRS and the GIMMS datasets. The CCRS dataset showed NDVI increases in all recently burned sites and in 50% of the unburned sites. Surprisingly, the GIMMS dataset did not capture the NDVI recovery in most burned sites and even showed NDVI declines in some burned sites one decade after fire. Between 50% and 75% of GIMMS pixels showed NDVI decreases in the unburned forest compared with <1% of CCRS pixels. Being the most broadly used dataset for monitoring ecosystem and carbon balance changes, the bias towards negative trends in the GIMMS dataset in the North American boreal forest has broad implications for the evaluation of vegetation and carbon dynamics in this region and globally.     

Comparison of Fat–Water MRI and Single‐voxel MRS in the Assessment of Hepatic and Pancreatic Fat Fractions in Humans

The ability to accurately and noninvasively quantify fatty infiltration in organs such as the liver and the pancreas remains a critical component in understanding the link between obesity and its comorbidities such as type 2 diabetes and fatty liver disease. Single‐voxel (¹H) proton magnetic resonance spectroscopy (MRS) has long been regarded as the gold‐standard noninvasive technique for such measurements. Recent advances in three‐dimensional fat–water magnetic resonance imaging (MRI) methods have led to the development of rapid, robust, and quantitative approaches that can accurately characterize the proportion of fat and water content in underlying tissues across the full imaging volume, and hence entire organs of interest. One such technique is called IDEAL (Iterative Decomposition with Echo Asymmetry and Least squares estimation). This article prospectively compares three‐dimensional (3D) IDEAL‐MRI and single‐voxel MRS in the assessment of hepatic (HFF) and pancreatic fat fraction (PFF) in 16 healthy subjects. MRS acquisitions took 3–4 min to complete whereas IDEAL acquisitions were completed in 20‐s breath‐holds. In the liver, there was a strong correlation (slope = 0.90, r² = 0.95, P < 0.001) between IDEAL and MRS‐based fat fractions. In the pancreas, a poorer agreement between IDEAL and MRS was observed (slope = 0.32, r² = 0.51, P < 0.02). The discrepancy of PFF is likely explained by MRS signal contamination from surrounding visceral fat, presumably during respiratory motion. We conclude that IDEAL is equally accurate in characterizing hepatic fat content as MRS, and is potentially better suited for fat quantification in smaller organs such as the pancreas.     

NMR study of isoleucine transfer RNA from Thermus thermophilus

An NMR and nuclear Overhauser effect (NOE) analysis of Thermus thermophilus tRNAIle1a is presented. This species contains modifications including s2T54 and s4U8 [Horie, N., Hara-Yokoyama, M., Yokoyama, S., Watanabe, K., Kuchino, Y., Nishimura, S., & Miyazawa, T. (1985) Biochemistry 24, 5711-5715]. All the expected secondary and reverse Hoogsteen AU pairs were identified, with one possible exception. The general geometry of the T psi C loop is the same as the Escherichia coli species, and there is NOE evidence for an A9-UA12 triple. Preliminary measurements of solvent exchange rates of internally hydrogen-bonded bases suggest that this tRNA is more stable than previously studied E. coli and yeast tRNAs.     

Proliferation of myofibroblasts in the stroma of renal oncocytoma

Objectives: Myofibroblasts are a vital component of stroma of many malignant neoplasms, but it is not yet established whether stromal myofibroblasts also exist in benign tumours such as oncocytoma of the kidney. Materials and methods: Histomorphological and immunohistochemical analysis of 16 renal oncocytomas diagnosed at Chang Gung Memorial Hospital, Taiwan, has been performed. Results: Renal oncocytomas were composed of oncocytes, large cells with granular eosinophilic cytoplasm, arranged mostly in sheets, in tubulocystic or combined pattern. Few oncocytes appeared to be undergoing proliferation or apoptosis. MIB‐1 and active caspase 3 indices were low, but higher in tumour than in surrounding non‐tumour parenchyma (MIB‐1: 0.93 ± 0.09 versus 0.46 ± 0.07, P < 0.001 and active caspase 3: 0.76 ± 0.08 versus 0.41 ± 0.09, P < 0.001). Wnt/β‐catenin signalling was not implicated in this neoplasm, as there was no loss of E‐cadherin membranous localization or expression of intranuclear β‐catenin in the cells. Clumps of oncocytes were stained with periodic acid Schiff and had collagen I‐, collagen III‐ and fibronectin‐positive, but desmin‐ and human caldesmon‐negative stromas. Importantly, α‐smooth muscle actin (SMA)‐immunostaining established the myofibroblastic nature of many of the stromal cells. Some of the myofibroblasts were also positive for MIB‐1, indicating a proliferative role for them in the stroma. Conclusions: Renal oncocytomas were composed of two independent compartments: benign oncocytes and pronounced fibrotic stroma, which consisted of proliferating myofibroblasts (SMA‐ and MIB‐1‐positive) which were associated with excessive deposition of extracellular matrix (periodic acid Schiff‐component, collagen I‐, collagen III‐ and fibronectin‐positive, and desmin‐ and human caldesmon‐negative).     

A fast dynamic mode of the EF‐G‐bound ribosome

A key intermediate in translocation is an ‘unlocked state’ of the pre‐translocation ribosome in which the P‐site tRNA adopts the P/E hybrid state, the L1 stalk domain closes and ribosomal subunits adopt a ratcheted configuration. Here, through two‐ and three‐colour smFRET imaging from multiple structural perspectives, EF‐G is shown to accelerate structural and kinetic pathways in the ribosome, leading to this transition. The EF‐G‐bound ribosome remains highly dynamic in nature, wherein, the unlocked state is transiently and reversibly formed. The P/E hybrid state is energetically favoured, but exchange with the classical P/P configuration persists; the L1 stalk adopts a fast dynamic mode characterized by rapid cycles of closure and opening. These data support a model in which P/E hybrid state formation, L1 stalk closure and subunit ratcheting are loosely coupled, independent processes that must converge to achieve the unlocked state. The highly dynamic nature of these motions, and their sensitivity to conformational and compositional changes in the ribosome, suggests that regulating the formation of this intermediate may present an effective avenue for translational control.     

Variation in Volatile Leaf Oils of Eleven Eucalyptus Species Harvested from Korbous Arboreta (Tunisia)

Hydrodistillation of the dried leaves of eleven species of the genus Eucalyptus L 'Hér ., i.e., E. astringens Maiden , E. camaldulensis Dehnh ., E. diversifolia Bonpl ., E. falcata Turcz ., E. ficifolia F. Muell ., E. gomphocephala DC., E. lehmannii (Schauer ) Benth ., E. maculata Hook ., E. platypus Hook ., E. polyanthemos Schauer, and E. rudis Endl ., harvested from Korbous arboreta (region of Nabeul, northeast of Tunisia) in April 2006, afforded essential oils in yields varying from 0.1±0.1 to 3.8±0.1%, dependent on the species. E. astringens and E. ficifolia showed the highest and the lowest mean percentage of essential oil amongst all the species examined, respectively. Analysis by GC (RI) and GC/MS allowed the identification of 138 components, representing 74.0 to 99.1% of the total oil. The contents of the different samples varied according to the species. The main components were 1,8‐cineole, followed by trans‐pinocarveol ( 1 ), spathulenol ( 2 ), α‐pinene, p‐cymene, (E,E)‐farnesol, cryptone, globulol ( 3 ), β‐phellandrene, α‐terpineol, viridiflorol, and α‐eudesmol. The principal‐component and the hierarchical‐cluster analyses separated the eleven Eucalyptus leaf essential oils into seven groups, each constituting a chemotype.