Around the globe, people fight for their honor, even if it means sacrificing their lives. This is puzzling from an evolutionary perspective, and little is known about the conditions under which honor cultures evolve. We implemented an agent-based model of honor, and our simulations showed that the reliability of institutions and toughness of the environment are crucial conditions for the evolution of honor cultures. Honor cultures survive when the effectiveness of the authorities is low, even in very tough environments. Moreover, the results show that honor cultures and aggressive cultures are mutually dependent in what resembles a predator-prey relationship described in the renowned Lotka-Volterra model. Both cultures are eliminated when institutions are reliable. These results have implications for understanding conflict throughout the world, where Western-based strategies are exported, often unsuccessfully, to contexts of weak institutional authority wherein honor-based strategies have been critical for survival.

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Age-associated decline in muscle function represents a significant public health burden. Vitamin D-deficiency is also prevalent in aging subjects, and has been linked to loss of muscle mass and strength (sarcopenia), but the precise role of specific vitamin D metabolites in determining muscle phenotype and function is still unclear. To address this we quantified serum concentrations of multiple vitamin D metabolites, and assessed the impact of these metabolites on body composition/muscle function parameters, and muscle biopsy gene expression in a retrospective study of a cohort of healthy volunteers. Active serum 1,25-dihydroxyvitamin D3 (1α,25(OH)2D3), but not inactive 25-hydroxyvitamin D3 (25OHD3), correlated positively with measures of lower limb strength including power (rho = 0.42, p = 0.02), velocity (Vmax, rho = 0.40, p = 0.02) and jump height (rho = 0.36, p = 0.04). Lean mass correlated positively with 1α,25(OH)2D3 (rho = 0.47, p = 0.02), in women. Serum 25OHD3 and inactive 24,25-dihydroxyvitamin D3 (24,25(OH)2D3) had an inverse relationship with body fat (rho = -0.30, p = 0.02 and rho = -0.33, p = 0.01, respectively). Serum 25OHD3 and 24,25(OH)2D3 were also correlated with urinary steroid metabolites, suggesting a link with glucocorticoid metabolism. PCR array analysis of 92 muscle genes identified vitamin D receptor (VDR) mRNA in all muscle biopsies, with this expression being negatively correlated with serum 25OHD3, and Vmax, and positively correlated with fat mass. Of the other 91 muscle genes analysed by PCR array, 24 were positively correlated with 25OHD3, but only 4 were correlated with active 1α,25(OH)2D3. These data show that although 25OHD3 has potent actions on muscle gene expression, the circulating concentrations of this metabolite are more closely linked to body fat mass, suggesting that 25OHD3 can influence muscle function via indirect effects on adipose tissue. By contrast, serum 1α,25(OH)2D3 has limited effects on muscle gene expression, but is associated with increased muscle strength and lean mass in women. These pleiotropic effects of the vitamin D ‘metabolome’ on muscle function indicate that future supplementation studies should not be restricted to conventional analysis of the major circulating form of vitamin D, 25OHD3.

We propose the use of Twitter analysis as an alternative source of data to document weekly trends in emotion and stress, and attempt to use the method to estimate the work recovery effect of weekends. On the basis of 2,102,176,189 Tweets, we apply Pennebakers linguistic inquiry word count (LIWC) approach to measure daily Tweet content across 18 months, aggregated to the US national level of analysis. We derived a word count dictionary to assess work stress and applied p-technique factor analysis to the daily word count data from 19 substantively different content areas covered by the LIWC dictionaries. Dynamic factor analysis revealed two latent factors in day-level variation of Tweet content. These two factors are: (a) a negative emotion/stress/somatic factor, and (b) a positive emotion/food/friends/home/family/leisure factor, onto which elements of work, money, achievement, and health issues have strong negative loadings. The weekly trend analysis revealed a clear "Friday dip" for work stress and negative emotion expressed on Twitter. In contrast, positive emotion Tweets showed a "mid-week dip" for Tuesday-Wednesday-Thursday and "weekend peak" for Friday through Sunday, whereas work/money/achievement/health problem Tweets showed a small "weekend dip" on Fridays through Sundays. Results partially support the Effort-Recovery theory. Implications and limitations of the method are discussed.

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