Dominance-related contributions to collective territory defence are adjusted according to the threat

Across diverse societies, group members benefit from the cooperative maintenance of a shared territory (a public good). How such public goods are maintained has received extensive interest, yet individual contributions to cooperative territory defence remain poorly understood. Recent theory predicts that, in groups with social hierarchies, privileged individuals will contribute most to competition with rival groups as they benefit most from defence of the territory. Here, we investigate whether dominant individuals contribute more to territory defence in a group-territorial bird in which dominants monopolise within-group reproduction; the white-browed sparrow weaver (Plocepasser mahali). Using simulated territorial intrusions, we demonstrate that dominants contribute significantly more than subordinates to territory defence. We also demonstrate that individual contributions are adjusted according to threat: males of both social classes significantly and similarly increased their contributions to defence in response to a high threat (playback of an unfamiliar pair’s duet, rather than that of a neighbouring pair), which was associated with a stronger collective response by the group. Thus, while dominants contribute most as predicted by the asymmetry in benefits, subordinates do increase contributions when they are needed most (in small groups and under greater threat). Contributions by subordinates when needed most also highlights that dominants could still benefit substantially from tolerating the presence of subordinates despite their overall lower contributions. Our results show that public goods can be maintained despite unequal contributions, and highlight the potential importance of context-dependent behavioural flexibility in mitigating collective action problems

Use of fat mass and fat free mass standard deviation scores obtained using simple measurement methods in healthy children and patients: comparison with the reference 4-component model

Background Clinical application of body composition (BC) measurements for individual children has been limited by lack of appropriate reference data. Objectives (1) To compare fat mass (FM) and fat free mass (FFM) standard deviation scores (SDS) generated using new body composition reference data and obtained using simple measurement methods in healthy children and patients with those obtained using the reference 4-component (4-C) model; (2) To determine the extent to which scores from simple methods agree with those from the 4-C model in identification of abnormal body composition. Design FM SDS were calculated for 4-C model, dual-energy X-ray absorptiometry (DXA; GE Lunar Prodigy), BMI and skinfold thicknesses (SFT); and FFM SDS for 4CM, DXA and bioelectrical impedance analysis (BIA; height2/Z)) in 927 subjects aged 3.8–22.0 y (211 healthy, 716 patients). Results DXA was the most accurate method for both FM and FFM SDS in healthy subjects and patients (mean bias (limits of agreement) FM SDS 0.03 (±0.62); FFM SDS −0.04 (±0.72)), and provided best agreement with the 4-C model in identifying abnormal BC (SDS ≤−2 or ≥2). BMI and SFTs were reasonable predictors of abnormal FM SDS, but poor in providing an absolute value. BIA was comparable to DXA for FFM SDS and in identifying abnormal subjects

The "drive to eat" hypothesis: energy expenditure and fat-free mass but not adiposity are associated with milk intake and energy intake in 12 week infants

BACKGROUND: Recent work has challenged the long-held assumption that appetite functions to maintain stable body mass and fat mass (FM), suggesting instead that appetite matches food intake to energy expenditure and its correlate, fat-free mass (FFM). Whether this scenario applies to young infants, in chronic positive energy balance, remains unknown. OBJECTIVES: To test associations of components of energy expenditure and body composition with milk intake (MI) and energy intake (EI) in 12-week infants, by reanalyzing published cross-sectional data. METHODS: Data were available for 48 infants. In addition to anthropometric measurements, we assessed MI and EI by test-weighing, sleeping metabolic rate (SMR) by indirect calorimetry, and FFM, FM, and total energy expenditure (TEE) by doubly labeled water. Mean parental height was calculated as a marker of infant growth drive. Correlation and multiple regression analyses were applied. RESULTS: MI and EI correlated with FFM (r = 0.47 and 0.57, respectively; P  0.6). MI and EI correlated with SMR (r = 0.42 and 0.53, respectively; P  0.2). In a multiple regression analysis, MI was independently associated with TEE (partial r = 0.39) and FFM (partial r = 0.35). EI showed similar associations. Mean parental height was correlated with weight gain, MI, and EI. CONCLUSIONS: As in adults, MI and EI in young infants were strongly associated with FFM and with total and sleeping components of energy expenditure, but not with fatness. The infant's growth drive contributed to these associations. This suggests that appetite is regulated by the rate of energy expenditure, the size of energy-using tissues, and tissue deposition rate, and that the high levels of body fat characteristic of infants may not constrain weight gain

Resting Energy Expenditure of Children With End-stage Chronic Liver Disease Before and After Liver Transplantation

Objectives: Our objective was to test the hypothesis that children with end-stage chronic liver disease (ESCLD) are hypermetabolic when compared to healthy children, and that this hypermetabolism persists for at least 6 months after liver transplant. Methods: Seventeen patients with end-stage chronic liver disease and 14 healthy controls had their resting energy expenditure measured (mREE) by indirect calorimetry. Weight, height, and body mass index were converted to standard deviation (SD) scores. Children older than 5 years had air displacement plethysmography and patients older than 5 years also had whole body dual-energy X-ray absorptiometry with characterization of fat mass (FM), fat-free mass (FFM), and bone-free fat free (lean) mass. Results: When compared to the prediction equation 44% of the patients and 50% of the healthy controls were hypermetabolic. The younger patients (0–5 years) had a lower mREE than the healthy controls but were significantly lighter and shorter than their healthy counterparts. mREE correlated strongly for all children with age, weight, height, and FFM. There was a strong negative correlation between age and mREE/kg in both patients (rs = −0.94, P < 0.01) and controls (rs = −0.91, P < 0.01). Almost 84% of the variance in mREE was explained by age (P < 0.001). There were no significant differences between resting energy expenditure (REE)/FFM between the 2 groups. mREE/kg before liver transplant correlated with mREE/kg after transplant (Pearson r = 0.83, P < 0.01). Conclusions: REE mostly reflected the size of the child. The patients were not hypermetabolic when compared to the healthy children. The main determinant of REE/kg after transplant was REE/kg before transplant

Utility of Specific Bioelectrical Impedance Vector Analysis for the assessment of body composition in children

Summary Background & aims Bioelectrical impedance analysis (BIA) is widely considered a body composition technique suitable for routine application. However, its utility in sick or malnourished children is complicated by variability in hydration. A BIA variant termed vector analysis (BIVA) aims to resolve this, by differentiating hydration from cell mass. However, the model was only partially supported by children's data. To improve accuracy, further adjustment for body shape variability has been proposed, known as specific BIVA (BIVAspecific). Methods We re-analysed body composition data from 281 children and adolescents (46% male) aged 4–20 years of European ancestry. Measurements included anthropometry, conventional BIA, BIVA outcomes adjusted either for height (BIVAconventional), or for height and body cross-sectional area (BIVAspecific), and fat-free mass (FFM) and fat mass (FM) by the criterion 4-component model. Graphic analysis and regression analysis were used to evaluate different BIA models for predicting FFM and FM. Results Age was strongly correlated with BIVAconventional parameters, but weakly with BIVAspecific parameters. FFM correlated more strongly with BIVAconventional than with BIVAspecific parameters, whereas the opposite pattern was found for FM. In multiple regression analyses, the best prediction models combined conventional BIA with BIVAspecific parameters, explaining 97.0% and 89.8% of the variance in FFM and FM respectively. These models could be further improved by incorporating body weight. Conclusions The prediction of body composition can be improved by combining two different theoretical models, each of which appears to provide different information about the two components FFM and FM. Further work should test the utility of this approach in pediatric patients

Restoration of dystrophin expression using the Sleeping Beauty transposon.

The Sleeping beauty (SB) system is a non-viral DNA based vector that has been used to stably integrate therapeutic genes into disease models. Here we report the SB system is capable of stably integrating the ΔR4-R23/CTΔ micro-dystrophin gene into a conditionally immortal dystrophin deficient muscle cell-line, H2K SF1, a murine cell model for Duchenne muscular dystrophy. Genetically corrected H2K SF1 cells retained their myogenic properties in vitro. Moreover, upon transplantation ΔR4-R23/CTΔ micro-dystrophin expression was detected within mdx nu/nu mice. Our data suggests the SB system is an effective way of stably integrating therapeutic genes into myogenic cells

The “drive to eat” hypothesis: energy expenditure and fat-free mass but not adiposity are associated with milk intake and energy intake in 12 week infants

Background Recent work has challenged the long-held assumption that appetite functions to maintain stable body mass and fat mass (FM), suggesting instead that appetite matches food intake to energy expenditure and its correlate, fat-free mass (FFM). Whether this scenario applies to young infants, in chronic positive energy balance, remains unknown. Objectives To test associations of components of energy expenditure and body composition with milk intake (MI) and energy intake (EI) in 12-week infants, by reanalyzing published cross-sectional data. Methods Data were available for 48 infants. In addition to anthropometric measurements, we assessed MI and EI by test-weighing, sleeping metabolic rate (SMR) by indirect calorimetry, and FFM, FM, and total energy expenditure (TEE) by doubly labeled water. Mean parental height was calculated as a marker of infant growth drive. Correlation and multiple regression analyses were applied. Results MI and EI correlated with FFM (r = 0.47 and 0.57, respectively; P 0.6). MI and EI correlated with SMR (r = 0.42 and 0.53, respectively; P 0.2). In a multiple regression analysis, MI was independently associated with TEE (partial r = 0.39) and FFM (partial r = 0.35). EI showed similar associations. Mean parental height was correlated with weight gain, MI, and EI. Conclusions As in adults, MI and EI in young infants were strongly associated with FFM and with total and sleeping components of energy expenditure, but not with fatness. The infant's growth drive contributed to these associations. This suggests that appetite is regulated by the rate of energy expenditure, the size of energy-using tissues, and tissue deposition rate, and that the high levels of body fat characteristic of infants may not constrain weight gain

Bio-electrical impedance vector analysis: testing Piccoli's model against objective body composition data in children and adolescents

BACKGROUND/OBJECTIVES: Bio-electrical impedance (BI) analysis is a simple body composition method ideal for children. However, its utility in sick or malnourished children is complicated by variability in hydration. BI vector analysis (BIVA) potentially resolves this, using a theoretical model that differentiates hydration from cell mass. We tested this model against reference methods in healthy children varying widely in age and nutritional status. SUBJECTS/METHODS: We compiled body composition data from 291 children and adolescents (50% male) aged 4-20 years of European ancestry. Measurements included anthropometry, BIVA outcomes (height-adjusted resistance (R/H) and reactance (Xc/H); phase angle (PA)), and fat-free mass (FFM), fat mass (FM) and FFM-hydration (HFFM) by the criterion 4-component model. All outcomes were converted to age- and sex-standardised standard deviation scores (SDS). Graphic analysis and regression analysis were used to evaluate the BIVA model. RESULTS: R/H and Xc/H declined with age in curvilinear manner, whereas PA increased linearly with age. R/H-SDS and Xc-SDS were negatively correlated with FFM-SDS, HFFM-SDS. and FM-SDS. PA was positively correlated with FFM-SDS but unrelated to HFFM-SDS and FM-SDS. CONCLUSIONS: While previous studies of adults with major fluid perturbations support the BIVA model, it is less successful in predicting variability in FFM in healthy children and adolescents. BIVA outcomes varied as predicted by the model with HFFM, but not as predicted with FFM. Variability in adiposity also explains some of the variability in BIVA traits. Further work is needed to develop a theoretical BIVA model for application in paediatric patients without major fluid disturbances