Network-forming materials are ubiquitous and appear in industrial products such as tires, food andcosmetics as well as composing the cytoskeleton within the cells of living organisms. They arelightweight and display properties such as optical transparency and reversible deformability up to largestrains. However, microscopic mechanisms protecting a network against macroscopic fracture and theprocesses that control crack growth are still poorly understood. A deeper understanding is needed tofully exploit the potential of polymer networks in advanced and novel material design. To this end, weadapt photon correlation imaging [1] (PCI) to reveal the microscopic rearrangements within poly(ethylacrylate) networks [2] during deformation by extension and fracture (see figure 1).PCI creates a time-resolved macroscopic map (field of view of several mm) of the microscopicmovements (on the order of 1µm) induced by the applied strain preceding fracture. We find that, in ournearly transparent samples, surface scattering dominates the PCI signal, obscuring bulk rearrangements.To address this issue, we first minimise surface scattering by immersing the sample in a pool filled withrefractive index matching glycerol, where the geometry of the pool walls is carefully designed to avoidreflections. Furthermore, the pool design allows PCI to be performed at both high (176o) and low (4o)angles simultaneously to measure rearrangements of the polymer network on length scales of 200 nmand 5 µm, respectively. Second, we introduce melamine formaldehyde nanoparticles to the polymernetworks to increase the scattering from the bulk. Preliminary measurements reveal non-affinecontributions even at low strain, well within the linear regime. We will continue by investigating therole that network architecture, such as interpenetrated multiple networks [3,4], has in the dynamicresponse of the network and the resultant resistance to fracture. References[1] A. Duri, D. A. Sessoms, V. Trappe, and L. Cipelletti Phys. Rev. Lett., 2009 102(8), 085702.[2] P. Millereau, E. Ducrot, J. M. Clough, M. E. Wiseman, H. R. Brown, R. P. Sijbesma, and C.Creton, PNAS, 2018 115(37), 9110–9115.[3] J. P. Gong, Y. Katsuyama, T. Kurokawa, and Y. Osada Adv. Mater., 2003 15, 1155.[4] E. Ducrot, Y. Chen, M. Bulters, R. P. Sijbesma, and C. Creton Science, 2014 344, 186.

This research was carried out to examine the distribution of enzymatic activities of some tissues (liver, muscles and gills) of selected aquatic organisms (Nile tilapia, Mullet fish and Crab) collected from some crude oil polluted rivers (Abuloma Jetty and Woji Jetty) and Ojimba-ama a non-oil polluted area which served as control. The aquatic organisms were obtained from rivers which are used as jetty for transportation of petroleum products and other industrial activities like welding, dredging, refuse dump, etc. Enzyme activities of fish and crab tissues (liver, muscles and gills) were measured for some biomarker enzymes such as catalase, rhodanase and glutathione S-transferase. Results were shown in means of triplicate values which were subjected to statistical analysis using analysis of variance (ANOVA). Enzyme activity in Nile tilapia across the three locations ranged from 44.39±0.01 μ/mgprotein to 171.45±0.01 μ/mgprotein with GST in gills having the lowest value and rhodanase in the liver recording the highest value. Enzyme activity in Mullet across the three locations ranged from 18.58±0.10 μ/mgprotein to 120.37±0.02 μ/mgprotein with catalase in muscles having the lowest value and rhodanase in the liver recording the highest value. Enzyme activity in Crab across the three locations ranged from 40.79±0.03 μ/mgprotein to 130.72±0.01 μ/mgprotein with GST in gills having the lowest value and rhodanase in the liver recording the highest value. Rhodanase showed the highest level of enzyme activity in all the tissues. Liver recorded the highest enzyme activity across all samples from the three locations which may be as a result of the liver being the principal detoxification organ for xenobiotic substances. From this study, there was an increase in the enzyme activities of the biomarkers across all the tissues which indicate a contamination from pollutants capable of causing oxidative stress in the organisms.