Matrix metalloproteinase activities and their relationship with collagen remodelling in tendon pathology

Our aim was to correlate the activity of matrix metalloproteinases (MMPs) with denaturation and the turnover of collagen in normal and pathological human tendons. MMPs were extracted from ruptured supraspinatus tendons (n=10), macroscopically normal (‘control’) supraspinatus tendons (n=29) and normal short head of biceps brachii tendons (n=24). Enzyme activity was measured using fluorogenic substrates selective for MMP-1, MMP-3 and enzymes with gelatinolytic activity (MMP-2, MMP-9 and MMP-13). Collagen denaturation was determined by a-chymotrypsin digestion. Protein turnover was determined by measuring the percentage of d-aspartic acid (% d-Asp). Zymography was conducted to identity specific gelatinases. MMP-1 activity was higher in ruptured supraspinatus compared to control supraspinatus and normal biceps brachii tendons (70.9, 26.4 and 11.5 fmol/mg tendon, respectively;

Image effects in transport at metal-molecule interfaces

We present a method for incorporating image-charge effects into the description of charge transport through molecular devices. A simple model allows us to calculate the adjustment of the transport levels, due to the polarization of the electrodes as charge is added to and removed from the molecule. For this, we use the charge distributions of the molecule between two metal electrodes in several charge states, rather than in gas phase, as obtained from a density-functional theory-based transport code. This enables us to efficiently model level shifts and gap renormalization caused by image-charge effects, which are essential for understanding molecular transport experiments. We apply the method to benzene di-amine molecules and compare our results with the standard approach based on gas phase charges. Finally, we give a detailed account of the application of our approach to porphyrin-derivative devices recently studied experimentally by Perrin et al. [Nat. Nanotechnol. 8, 282 (2013)], which demonstrates the importance of accounting for image-charge effects when modeling transport through molecular junctions

Automated interpretation of benthic stereo imagery

Autonomous benthic imaging, reduces human risk and increases the amount of collected data. However, manually interpreting these high volumes of data is onerous, time consuming and in many cases, infeasible. The objective of this thesis is to improve the scientific utility of the large image datasets. Fine-scale terrain complexity is typically quantified by rugosity and measured by divers using chains and tape measures. This thesis proposes a new technique for measuring terrain complexity from 3D stereo image reconstructions, which is non-contact and can be calculated at multiple scales over large spatial extents. Using robots, terrain complexity can be measured without endangering humans, beyond scuba depths. Results show that this approach is more robust, flexible and easily repeatable than traditional methods. These proposed terrain complexity features are combined with visual colour and texture descriptors and applied to classifying imagery. New multi-dataset feature selection methods are proposed for performing feature selection across multiple datasets, and are shown to improve the overall classification performance. The results show that the most informative predictors of benthic habitat types are the new terrain complexity measurements. This thesis presents a method that aims to reduce human labelling effort, while maximising classification performance by combining pre-clustering with active learning. The results support that utilising the structure of the unlabelled data in conjunction with uncertainty sampling can significantly reduce the number of labels required for a given level of accuracy. Typically 0.00001–0.00007% of image data is annotated and processed for science purposes (20–50 points in 1–2% of the images). This thesis proposes a framework that uses existing human-annotated point labels to train a superpixel-based automated classification system, which can extrapolate the classified results to every pixel across all the images of an entire survey

The System Nobody Sees: Irrigated Wetland Management and Alpaca Herding in the Peruvian Andes

Increasingly, attention in regional, national, and international water governance arenas has focused on high-altitude wetlands. However, existing local water management practices in these wetlands are often overlooked. This article looks at the irrigation activities of alpaca herders in the community of Ccarhuancho in the Central Andes of Peru. For more than two centuries, they have been constructing small-scale irrigation canals to maintain and expand the local wetlands, called bofedales. The seminomadic character of alpaca herders complicates irrigated wetland activities, such as operation and maintenance. Climate change and human and animal population pressure have increased not only the importance of these irrigation systems but also of local conflicts and communal decision making. Local irrigation activities in Ccarhuancho go unnoticed in broader water governance arenas because of its remoteness, limits to what popular new analytical tools can measure, a general undervaluation of wetlands, and a tendency of the canals to merge over time with the surrounding bofedales, making them less visible. Nevertheless, these man-made systems account for 40% of the wetlands in the study area and risk being seriously degraded or destroyed without local water management. With climatic changes affecting existing natural wetlands, the local herders were the first to recognize and respond to these changes and to defend the wetlands against degradation. Their efforts are, however, largely overlooked, even though such local water governance practices are crucial for the success of regional and national water governance in the Andes and other mountain areas. (Note: The title of this paper is an adaptation of Netting's [1974] paper “The system nobody knows” about small-scale irrigation in the Swiss Alps.