A comparative study of protoheme and heme d catalases : role of the heme and the heme pocket in catalysis and ligand binding

Catalase dismutes H20 2 to O2 and H20. In successive twoelectron reactions H20 2 induces both oxidation and reduction at the heme group. In the first step the protoheme prosthetic group of beef liver catalase forms compound I, in which the heme has been oxidized from Fe3+ to Fe4+=0 and a porphyrin radical has been created. Compound II is formed by the oneelectron reduction of comp I. It retains Fe4+=0 but lacks the porphyrin radical and is catalytically inert. Molecular structures are available for Escherichia coli Hydroperoxidase II, Micrococcus Iysodeiktus, Penicillium vitale and beef liver enzymes, which contain different hemes and heme pockets. In the present work, the pockets and substrate access channels of protoheme (beef liver & Micrococcus) and heme d (HPII of E. coli and Penicillium) catalases have been analysed using Quanta™ and CharmMTM molecular modeling packages on the Silicon Graphics Iris Indigo 2 computer. Experimental studies have been carried out with two catalases, HPII (and its mutants) and beef liver. Fluoride and formate' are inhibitors of both enzymes, and their binding is modulated by the heme and by distal residues N201 & H128. Both HPII and beef liver enzymes form compound I with H202 or peracetate. The reduction of beef liver enzyme compound I to II and the decay of compound II are accelerated by fluoride. The decay of compound II is also accelerated by formate, and this reagent acts as a 2-electron donor towards compound I of both enzymes. It is concluded that heme d enzymes (Penicillium and HPII of E. coli) are formed by autocatalytic transformation of protoheme in a modified pocket which contains a characteristic serine residue as well as a partially occluded heme channel. They are less active than protoheme enzymes but also do not form the inactive compound II species. Binding of peroxide as well as fluoride and formate is prevented by mutation of H128 and modulated by mutation of N201.

Social comparison and body image in non or infrequent exercisers and exercisers

Body image refers to an individual's internal representation ofhis/her outer self (Cash, 1994; Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999). It is a multidimensional construct which includes an individual's attitudes towards hislher own physical characteristics (Bane & McAuley, 1998; Cash, 1994; Cash, 2004; Davison & McCabe, 2005; Muth & Cash, 1997; Sabiston, Crocker, & Munroe-Chandler, 2005). Social comparison is the process of thinking about the self in relation to others in order to determine if one's opinions and abilities are adequate and to assess one's social status (Festinger, 1954; Wood, 1996). Research investigating the role of social comparisons on body image has provided some information on the types and nature of the comparisons that are made. The act of making social comparisons may have a negative impact on body image (van den Berg et ai., 2007). Although exercise may improve body image, the impact of social comparisons in exercise settings may be less positive, and there may be differences in the social comparison tendencies between non or infrequent exercisers and exercisers. The present study examined the nature of social comparisons that female collegeaged non or infrequent exercisers and exercisers made with respect to their bodies, and the relationship of these social comparisons to body image attitudes. Specifically, the frequency and direction of comparisons on specific tal-gets and body dimensions were examined in both non or infrequent exercisers and exercisers. Finally, the relationship between body-image attitudes and the frequency and direction with which body-related social comparisons were made for non or infrequent exercisers and exercisers were examined. One hundred and fifty-two participants completed the study (n = 70 non or ill infrequent exercisers; n = 82 exercisers). Participants completed measures of social physique anxiety (SPA), body dissatisfaction, body esteem, body image cognitions, leisure time physical activity, and social comparisons. Results suggested that both groups (non or infrequent exercisers and exercisers) generally made social comparisons and most frequently made comparisons with same-sex friends, and least frequently with same-sex parents. Also, both groups made more appearance-related comparisons than non-appearance-related comparisons. Further, both groups made more negative comparisons with almost all targets. However, non or infrequent exercisers generally made more negative comparisons on all body dimensions, while exercisers made negative comparisons only on weight and body shape dimensions. MANOV As were conducted to examine if any differences on social comparisons between the two groups existed. Results of the MANOVAs indicated that frequency of comparisons with targets, the frequency of comparisons on body dimensions, and direction of comparisons with targets did not differ based on exercise status. However, the direction of comparison of specific body dimensions revealed a significant (F (7, 144) = 3.26,p < .05; 1]2 = .132) difference based on exercise status. Follow-up ANOVAs showed significant differences on five variables: physical attractiveness (F (1, 150) = 6.33,p < .05; 1]2 = .041); fitness (F(l, 150) = 11.89,p < .05; 1]2 = .073); co-ordination (F(I, 150) = 5.61,p < .05; 1]2 = .036); strength (F(I, dO) = 12.83,p < .05; 1]2 = .079); muscle mass or tone (F(l, 150) = 17.34,p < .05; 1]2 = 1.04), with exercisers making more positive comparisons than non or infrequent exercisers. The results from the regression analyses for non or infrequent exercisers showed appearance orientation was a significant predictor of the frequency of social comparisons N (B = .429, SEB = .154, /3 = .312,p < .01). Also, trait body image measures accounted for significant variance in the direction of social comparisons (F(9, 57) = 13.43,p < .001, R2adj = .68). Specifically, SPA (B = -.583, SEB = .186, /3 = -.446,p < .01) and body esteem-weight concerns (B = .522, SEB = .207, /3 = .432,p < .01) were significant predictors of the direction of comparisons. For exercisers, regressions revealed that specific trait measures of body image significantly predicted the frequency of comparisons (F(9, 71) = 8.67,p < .001, R2adj = .463). Specifically, SPA (B = .508, SEB = .147, /3 = .497,p < .01) and appearance orientation (B = .457, SEB = .134, /3 = .335,p < .01) were significant predictors of the frequency of social comparisons. Lastly, for exercisers, the results for the regression of body image measures on the direction of social comparisons were also significant (F(9, 70) = 14.65,p < .001, R2adj = .609) with body dissatisfaction (B = .368, SEB = .143, /3 = .362,p < .05), appearan.ce orientation (B = .256, SEB = .123, /3 = .175,p < .05), and fitness orientation (B = .423, SEB = .194, /3 = .266,p < .05) significant predictors of the direction of social comparison. The results indicated that young women made frequent social comparisons regardless of exercise status. However, exercisers m,a de more positive comparisons on all the body dimensions than non or infrequent exercisers. Also, certain trait body image measures may be good predictors of one's body comp~son tendencies. However, the measures which predict comparison tendencies may be different for non or infrequent exercisers and exercisers. Future research should examine the effects of social comparisons in different populations (i.e., males, the obese, older adults, etc.). Implications for practice and research were discussed.

Infrared thermography: A non-invasive window into thermal physiology

Infrared thermography is a non-invasive technique that measures mid to long-wave infrared radiation emanating from all objects and converts this to temperature. As an imaging technique, the value of modern infrared thermography is its ability to produce a digitized image or high speed video rendering a thermal map of the scene in false colour. Since temperature is an important environmental parameter influencing animal physiology and metabolic heat production an energetically expensive process, measuring temperature and energy exchange in animals is critical to understanding physiology, especially under field conditions. As a non-contact approach, infrared thermography provides a non-invasive complement to physiological data gathering. One caveat, however, is that only surface temperatures are measured, which guides much research to those thermal events occurring at the skin and insulating regions of the body. As an imaging technique, infrared thermal imaging is also subject to certain uncertainties that require physical modeling, which is typically done via built-in software approaches. Infrared thermal imaging has enabled different insights into the comparative physiology of phenomena ranging from thermogenesis, peripheral blood flow adjustments, evaporative cooling, and to respiratory physiology. In this review, I provide background and guidelines for the use of thermal imaging, primarily aimed at field physiologists and biologists interested in thermal biology. I also discuss some of the better known approaches and discoveries revealed from using thermal imaging with the objective of encouraging more quantitative assessment.