Liver glucose-6-phosphatase proteins in suckling and weaned grey seal pups: structural similarities to other mammals and relationship to nutrition, insulin signalling and metabolite levels

Phocid seals have been proposed as models for diabetes because they exhibit limited insulin response to glucose, high blood glucose and increasing insulin resistance when fasting. Liver glucose-6-phosphatase (G6Pase) catalyses the final step in glucose production and is central to glucose regulation in other animals. G6Pase comprises a translocase (SLC37A4) and a catalytic subunit (G6PC). G6PC and SLC37A4 expression and activity are normally regulated by nutritional state and glucostatic hormones, particularly insulin, and are elevated in diabetes. We tested the hypotheses that (1) grey seal G6PC and SLC37A4 cDNA and predicted protein sequences differ from other species’ at functional sites, (2) relative G6Pase protein abundances are lower during feeding than fasting and (3) relative G6Pase protein abundances are related to insulin, insulin receptor phosphorylation and key metabolite levels. We show that G6PC and partial SLC37A4 cDNA sequences encode proteins sharing 82–95 % identity with other mammals. Seal G6PC contained no differences in sites responsible for activity, stability or subcellular location. Several substitutions in seal SLC37A4 were predicted to be tolerated with low probability, which could affect glucose production. Suckling pups had higher relative abundance of both subunits than healthy, postweaned fasting pups. Furthermore, relative G6PC abundance was negatively related to glucose levels. These findings contrast markedly with the response of relative hepatic G6Pase abundance to feeding, fasting, insulin, insulin sensitivity and key metabolites in other animals, and highlight the need to understand the regulation of enzymes involved in glucose control in phocids if these animals are to be informative models of diabetes.

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

HSP70 abundance and antioxidant capacity in feeding and fasting gray seal pups: suckling is associated with higher levels of key cellular defenses

Heat shock proteins (HSPs) and antioxidants are key cellular defenses against stress. Seals routinely undergo protracted fasting, which is normally associated with physiological stress in other animals. We tested the hypotheses that (1) relative HSP70 protein abundance is higher in liver and blubber of fasting relative to suckling wild gray seal pups; (2) differences in HSP70 are mirrored in tissue superoxide dismutase (SOD) and catalase activity, as well as glutathione levels; (3) extracellular HSP70 correlates with hepatic and blubber HSP70 abundance; and (4) protein carbonylation, an index of oxidative damage, is lower in tissues with higher levels of these cellular stress markers. In contrast to our expectation, suckling pups had higher relative HSP70 abundance and glutathione levels in liver and blubber and higher hepatic catalase activity. Plasma HSP70 did not correlate with liver or blubber abundance of the protein. Suckling pups did not experience greater protein carbonylation, suggesting that cellular protective mechanisms prevent protein damage despite an apparent increase in cellular stress. SOD activity was not affected by nutritional state, but in blubber tissue, it was positively correlated with blubber thickness. Greater requirements for antioxidants and HSPs in suckling pups or in animals with thicker blubber could arise from rapid protein synthesis, high metabolic fuel availability, and/or exposure to lipophilic toxins. Developmental and nutritional changes in cellular defenses have important implications for gray seals’ susceptibility to additional stress exposure.

Phocid seal leptin: tertiary structure and hydrophobic receptor binding site preservation during distinct leptin gene evolution

The cytokine hormone leptin is a key signalling molecule in many pathways that control physiological functions. Although leptin demonstrates structural conservation in mammals, there is evidence of positive selection in primates, lagomorphs and chiropterans. We previously reported that the leptin genes of the grey and harbour seals (phocids) have significantly diverged from other mammals. Therefore we further investigated the diversification of leptin in phocids, other marine mammals and terrestrial taxa by sequencing the leptin genes of representative species. Phylogenetic reconstruction revealed that leptin diversification was pronounced within the phocid seals with a high dN/dS ratio of 2.8, indicating positive selection. We found significant evidence of positive selection along the branch leading to the phocids, within the phocid clade, but not over the dataset as a whole. Structural predictions indicate that the individual residues under selection are away from the leptin receptor (LEPR) binding site. Predictions of the surface electrostatic potential indicate that phocid seal leptin is notably different to other mammalian leptins, including the otariids. Cloning the grey seal leptin binding domain of LEPR confirmed that this was structurally conserved. These data, viewed in toto, support a hypothesis that phocid leptin divergence is unlikely to have arisen by random mutation. Based upon these phylogenetic and structural assessments, and considering the comparative physiology and varying life histories among species, we postulate that the unique phocid diving behaviour has produced this selection pressure. The Phocidae includes some of the deepest diving species, yet have the least modified lung structure to cope with pressure and volume changes experienced at depth. Therefore, greater surfactant production is required to facilitate rapid lung re-inflation upon surfacing, while maintaining patent airways. We suggest that this additional surfactant requirement is met by the leptin pulmonary surfactant production pathway which normally appears only to function in the mammalian foetus.