Evidence for protein leverage on total energy intake, but not body mass index, in a large cohort of older adults.

BACKGROUND: Protein leverage (PL) is the phenomenon of consuming food until absolute intake of protein approaches a 'target value', such that total energy intake (TEI) varies passively with the ratio of protein: non-protein energy (fat + carbohydrate) in the diet. The PL hypothesis (PLH) suggests that the dilution of protein in energy-dense foods, particularly those rich in carbohydrates and fats, combines with protein leverage to contribute to the global obesity epidemic. Evidence for PL has been reported in younger adults, children and adolescents. This study aimed to test for PL and the protein leverage hypothesis (PLH) in a cohort of older adults. METHODS: We conducted a retrospective analysis of dietary intake in a cohort of 1699 community-dwelling older adults aged 67-84 years from the NuAge cohort. We computed TEI and the energy contribution (EC) from each macronutrient. The strength of leverage of macronutrients was assessed through power functions ( TEI = µ * EC L ). Body mass index (BMI) was calculated, and mixture models were fitted to predict TEI and BMI from macronutrients' ECs. RESULTS: In this cohort of older adults, 53% of individuals had obesity and 1.5% had severe cases. The mean TEI was 7673 kJ and macronutrients' ECs were 50.4%, 33.2% and 16.4%, respectively for carbohydrates, fat, and protein. There was a strong negative association (L = -0.37; p < 0.001) between the protein EC and TEI. Each percent of energy intake from protein reduced TEI by 77 kJ on average, ceteris paribus. However, BMI was unassociated with TEI in this cohort. CONCLUSIONS: Findings indicate clear evidence for PL on TEI, but not on BMI, likely because of aging, body composition, sarcopenia, or protein wasting.

Low-Fat, High-Carbohydrate Diets Reduce Body Weight and Sperm Count but Increase Sperm Motility in Mice.

BACKGROUND: Male reproduction is impacted by both over- and under-nutrition, demonstrated by animal studies using high-fat and low-protein dietary interventions. Little is known about the impacts of low-fat, high-carb diets and types of dietary carbohydrates on sperm traits. OBJECTIVES: Using a nutritional geometry approach, we investigated the effects of partially or completely substituting glucose for fructose in isocaloric diets containing either 10%, 20%, or 30% fat (by energy) on sperm traits in mice. METHODS: Male C57BL/6J mice were fed 1 of 15 experimental diets for 18 wk starting from 8 wk of age. Reproductive organs were then harvested, and sperm concentration, motility, and velocity were measured using Computer-Assisted Sperm Analysis. RESULTS: Increasing dietary fat from 10% to 30% while maintaining energy density at 14.3 kJ/g and protein content at 20% resulted in increased body weight and sperm production but reduced the percentage of motile sperm. Body weight and seminal vesicle weight were maximized on diets containing a 50:50 mix of fructose and glucose, but carbohydrate type had few significant impacts on epididymal sperm traits. CONCLUSIONS: The opposing impacts of dietary fat on mouse sperm quantity and quality observed suggest that male fertility may not be optimized by a single diet; rather, context-specific dietary guidelines targeted to specific concerns in semen quality may prove useful in treating male infertility.

Mice Regulate Dietary Amino Acid Balance and Energy Intake by Selecting between Complementary Protein Sources.

BACKGROUND: A balanced intake of protein and constituent amino acids (AAs) requires adjustments to total food intake (protein leverage [PL]) and food selection to balance deficits and excesses (complementary feeding). We provided mice with choices of casein and whey, 2 protein sources that are complementary in AA balance, across a range of protein concentrations (P%) of digestible energy (DE). OBJECTIVES: We aimed to determine if: 1) PL operates similarly for casein and whey; 2) one protein source is preferred at control P%; 3) the preference changes as P% falls; and 4) AA intakes under control and low P% levels identify AAs that drive changes in protein selection. METHODS: Food intake and plasma fibroblast growth factor-21 (FGF21) concentrations were measured in mice at various P% (P7.5%-P33%). For direct comparisons, defined diets were used in which the protein source was either casein or whey. In food choice studies, mice had access to foods in which both casein and whey were provided at the same P% level at the same time. RESULTS: PL operated at different P% thresholds in casein (13%)- and whey (10%)-based diets, and the magnitude of PL was greater for casein. Although mice preferred casein under control conditions (P23%), a pronounced preference shift to whey occurred as P% fell to P13% and P10%. At low P%, increases in food intake were accompanied by increases in plasma FGF21, a protein hunger signal. Among AAs deficient in casein and enriched in whey, the intake of Cys was the most invariant as P% changed between P23% and P10%, appearing to drive the switch in protein preference. CONCLUSIONS: Mice selected between complementary protein sources, casein and whey, achieving stable total energy intake and regulated intake of AAs as P% varied. Supplementation of low P% casein diets with one whey-enriched AA, Cys, suppressed plasma FGF21 and total food intake.

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research.

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research.

Macronutrient composition of plant-based diets and breast cancer risk: the E3N prospective cohort study.

PURPOSE: Recent evidence suggests that plant-based diets may reduce the risk of breast cancer (BC). However, the macronutrient composition of plant-based diets and its potential impact on BC risk has not been well explored. This analysis investigated the association of macronutrient composition with BC risk across a spectrum of plant-based diet indexes using a multidimensional approach. DESIGN: This study followed 64,655 participants from the Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale (E3N) cohort from 1993 to 2014. Diets were evaluated using validated 208-item diet history questionnaires at baseline (1993) and follow-up (2005), to calculate adherence to the overall plant-based diet (PDI), healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI). The association of macronutrient composition with BC risk was assessed via generalized additive time-dependent Cox models across different levels of these indexes. Response surfaces were generated to visualize compositional associations at the 25th, 50th, and 75th percentile of each index (low, moderate, and high). RESULTS: A total of 3,932 incident BC cases were identified during the 21-year follow-up. There was a significant association between macronutrient composition and BC risk for hPDI, uPDI, and PDI (all P < 0.001). Akaike information criterion favored the hPDI model for characterizing the association between macronutrients and BC. BC risk was highest for individuals with a lower hPDI score who also consumed a diet containing lower protein (10%), lower carbohydrate (35%), and higher fat (55%). The lowest risk of BC was observed in those with higher hPDI scores with the lowest intake of protein (10%). At higher PDI and uPDI, diets containing higher protein (30%) and fat (45%) had the highest BC risk. CONCLUSION: These results demonstrate a complex relationship between macronutrient composition, plant-based diet quality, and BC risk. Further research is needed to examine specific foods that may be driving these associations. REGISTRY: The protocol is registered at clinicaltrials.gov as NCT03285230.

A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations.

The log response ratio, lnRR, is the most frequently used effect size statistic for meta-analysis in ecology. However, often missing standard deviations (SDs) prevent estimation of the sampling variance of lnRR. We propose new methods to deal with missing SDs via a weighted average coefficient of variation (CV) estimated from studies in the dataset that do report SDs. Across a suite of simulated conditions, we find that using the average CV to estimate sampling variances for all observations, regardless of missingness, performs with minimal bias. Surprisingly, even with missing SDs, this simple method outperforms the conventional approach (basing each effect size on its individual study-specific CV) with complete data. This is because the conventional method ultimately yields less precise estimates of the sampling variances than using the pooled CV from multiple studies. Our approach is broadly applicable and can be implemented in all meta-analyses of lnRR, regardless of 'missingness'.

Global associations between macronutrient supply and age-specific mortality.

Animal experiments have demonstrated that energy intake and the balance of macronutrients determine life span and patterns of age-specific mortality (ASM). Similar effects have also been detected in epidemiological studies in humans. Using global supply data and 1,879 life tables from 103 countries, we test for these effects at a macrolevel: between the nutrient supplies of nations and their patterns of ASM. We find that macronutrient supplies are strong predictors of ASM even after correction for time and economic factors. Globally, signatures of undernutrition are evident in the effects of low supply on life expectancy at birth and high mortality across ages, even as recently as 2016. However, in wealthy countries, the effects of overnutrition are prominent, where high supplies particularly from fats and carbohydrates are predicted to lead to high levels of mortality. Energy supplied at around 3,500 kcal/cap/d minimized mortality across ages. However, we show that the macronutrient composition of energy supply that minimizes mortality varies with age. In early life, 40 to 45% energy from each of fat and carbohydrate and 16% from protein minimizes mortality. In later life, replacing fat with carbohydrates to around 65% of total energy and reducing protein to 11% is associated with the lowest level of mortality. These results, particularly those regarding fats, accord both with experimental data from animals and within-country epidemiological studies on the association between macronutrient intake and risk of age-related chronic diseases.

Meta-analysis links dietary branched-chain amino acids to metabolic health in rodents.

BACKGROUND: The role of dietary branched chain amino acids (BCAAs) and their effect on metabolic health is complex. How dietary BCAA levels and their interaction with background nutrition affect health is unclear. Here, we used meta-analysis and meta-regression, together with the nutritional modelling, to analyse the results of rodent studies that increased the level of dietary BCAAs and measured circulating levels, outcomes related to metabolic health, body mass and food intake. RESULTS: Across all studies, increasing dietary BCAAs resulted in increased levels of circulating BCAAs. These effects, however, were heavily moderated by background dietary levels whereby on high BCAA diets, further increases were not reflected in the blood. Impaired glucose tolerance was associated with elevated dietary BCAAs, with the greatest effect occurring with a simultaneous increase in total protein intake. Effects of dietary BCAAs on plasma glucose, insulin, or HOMA emerged only when dietary macronutrient background was considered. We found that elevated dietary BCAAs increases % body fat, with largest increases in adiposity occurring when BCAAs are increased on a high protein, low carbohydrate dietary background. Finally, we found that increased dietary BCAAs were associated with increased food intake when the background diet was low in BCAAs. CONCLUSION: Our data highlights the interaction between BCAAs and background nutrition. We show that the effects of BCAAs on metabolic health cannot be studied in isolation but must be considered as part of complex mixture of dietary components.

Multidimensional associations between nutrient intake and healthy ageing in humans.

BACKGROUND: Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process. RESULTS: Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don't deviate too much from norms ('homeostatic plateaus'). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space. CONCLUSION: Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

Impact of fluctuating developmental temperatures on phenotypic traits in reptiles: a meta-analysis.

During the vulnerable stages of early life, most ectothermic animals experience hourly and diel fluctuations in temperature as air temperatures change. While we know a great deal about how different constant temperatures impact the phenotypes of developing ectotherms, we know remarkably little about the impacts of temperature fluctuations on the development of ectotherms. In this study, we used a meta-analytic approach to compare the mean and variance of phenotypic outcomes from constant and fluctuating incubation temperatures across reptile species. We found that fluctuating temperatures provided a small benefit (higher hatching success and shorter incubation durations) at cool mean temperatures compared with constant temperatures, but had a negative effect at warm mean temperatures. In addition, more extreme temperature fluctuations led to greater reductions in embryonic survival compared with moderate temperature fluctuations. Within the limited data available from species with temperature-dependent sex determination, embryos had a higher chance of developing as female when developing in fluctuating temperatures compared with those developing in constant temperatures. With our meta-analytic approach, we identified average mean nest temperatures across all taxa where reptiles switch from receiving benefits to incurring costs when incubation temperatures fluctuate. More broadly, our study indicates that the impact of fluctuating developmental temperature on some phenotypes in ectothermic taxa are likely to be predictable via integration of developmental temperature profiles with thermal performance curves.

Heightened among-individual variation in life history but not morphology is related to developmental temperature in reptiles.

Increases in phenotypic variation under extreme (e.g. novel or stressful) environmental conditions are emerging as a crucial process through which evolutionary adaptation can occur. Lack of prior stabilizing selection, as well as potential instability of developmental processes in these environments, may lead to a release of phenotypic variation that can have important evolutionary consequences. Although such patterns have been shown in model study organisms, we know little about the generality of trait variance across environments for non-model organisms. Here, we test whether extreme developmental temperatures increase the phenotypic variation across diverse reptile taxa. We find that the among-individual variation in a key life-history trait (post-hatching growth) increases at extreme cold and hot temperatures. However, variations in two measures of hatchling morphology and in hatchling performance were not related to developmental temperature. Although extreme developmental temperatures may increase the variation in growth, our results suggest that plastic responses to stressful incubation conditions do not generally make more extreme phenotypes available to selection. We discuss the reasons for the general lack of increased variability at extreme incubation temperatures and the implications this has for local adaptation in hatchling morphology and physiology.

LC-N2G: a local consistency approach for nutrigenomics data analysis.

BACKGROUND: Nutrigenomics aims at understanding the interaction between nutrition and gene information. Due to the complex interactions of nutrients and genes, their relationship exhibits non-linearity. One of the most effective and efficient methods to explore their relationship is the nutritional geometry framework which fits a response surface for the gene expression over two prespecified nutrition variables. However, when the number of nutrients involved is large, it is challenging to find combinations of informative nutrients with respect to a certain gene and to test whether the relationship is stronger than chance. Methods for identifying informative combinations are essential to understanding the relationship between nutrients and genes. RESULTS: We introduce Local Consistency Nutrition to Graphics (LC-N2G), a novel approach for ranking and identifying combinations of nutrients with gene expression. In LC-N2G, we first propose a model-free quantity called Local Consistency statistic to measure whether there is non-random relationship between combinations of nutrients and gene expression measurements based on (1) the similarity between samples in the nutrient space and (2) their difference in gene expression. Then combinations with small LC are selected and a permutation test is performed to evaluate their significance. Finally, the response surfaces are generated for the subset of significant relationships. Evaluation on simulated data and real data shows the LC-N2G can accurately find combinations that are correlated with gene expression. CONCLUSION: The LC-N2G is practically powerful for identifying the informative nutrition variables correlated with gene expression. Therefore, LC-N2G is important in the area of nutrigenomics for understanding the relationship between nutrition and gene expression information.

Sex-specific metabolic responses to 6 hours of fasting during the active phase in young mice.

KEY POINTS: Night time/active phase food restriction for 6 h impaired glucose intolerance in young male and female mice. Females displayed increased capacity for lipogenesis and triglyceride storage in response to a short daily fast. Females had lower fasting insulin levels and an increased potential for utilizing fat for energy through ß-oxidation compared to males. The need for the inclusion of both sexes, and the treatment of sex as an independent variable, is emphasized within the context of this fasting regime. ABSTRACT: There is growing interest in understanding the mechanistic significance and benefits of fasting physiology in combating obesity. Increasing the fasting phase of a normal day can promote restoration and repair mechanisms that occur during the post-absorptive period. Most studies exploring the effect of restricting food access on mitigating obesity have done so with a large bias towards the use of male mice. Here, we disentangle the roles of sex, food intake and food withdrawal in the response to a short-term daily fasting intervention, in which food was removed for 6 h in the dark/active phase of young, 8-week-old mice. We showed that the removal of food during the dark phase impaired glucose tolerance in males and females, possibly due to the circadian disruption induced by this feeding protocol. Although both sexes demonstrated similar patterns of food intake, body composition and various metabolic markers, there were clear sex differences in the magnitude and extent of these responses. While females displayed enhanced capacity for lipogenesis and triglyceride storage, they also had low fasting insulin levels and an increased potential for utilizing available energy sources such as fat for energy through ß-oxidation. Our results highlight the intrinsic biological and metabolic disparities between male and female mice, emphasizing the growing need for the inclusion of both sexes in scientific research. Furthermore, our results illustrate sex-specific metabolic pathways that regulate lipogenesis, obesity and overall metabolic health.

Meta-Analysis of Copper and Iron in Parkinson's Disease Brain and Biofluids.

BACKGROUND: Variations in study quality and design complicate interpretation of the clinical significance of consistently reported changes in copper and iron levels in human Parkinson's disease brain and biofluids. METHODS: We systematically searched literature databases for quantitative reports of biometal levels in the degenerating substantia nigra (SN), CSF, serum, and plasma in Parkinson's disease compared with healthy age-matched controls and assessed the quality of these publications. The primary outcomes of our analysis confirmed SN copper and iron levels are decreased and increased, respectively, in the Parkinson's disease brain. We applied a novel Quality Assessment Scale for Human Tissue to categorize the quality of individual studies and investigated the effects of study quality on our outcomes. We undertook a random-effects meta-analysis and meta-regression subgroup analysis. RESULTS: In the 18 eligible studies identified (211 Parkinson's disease, 215 control cases), SN copper levels were significantly lower (d, -2.00; 95% CI, -2.81 to -1.19; P < 0.001), and iron levels were significantly higher (d, 1.31; 95% CI, 0.38-2.24; P < 0.01) in Parkinson's disease. No changes were detected in CSF, serum, or plasma for any metals (29 studies; 2443 Parkinson's disease and 2183 control cases) except serum iron, which was lower in Parkinson's disease (14 studies; 1177 Parkinson's disease and 1447 control cases). CONCLUSIONS: Reductions in copper levels and elevations in iron were confirmed as characteristic of the degenerating SN of Parkinson's disease. Iron in serum was also changed, but in the opposite direction to that in the SN and to a lesser extent. © 2019 International Parkinson and Movement Disorder Society.

Dietary macronutrient content, age-specific mortality and lifespan.

Protein and calorie restrictions extend median lifespan in many organisms. However, studies suggest that among-individual variation in the age at death is also affected. Ultimately, both of these outcomes must be caused by effects of nutrition on underlying patterns of age-specific mortality (ASM). Using model life tables, we tested for effects of dietary macronutrients on ASM in mice ( Mus musculus). High concentrations of protein and fat relative to carbohydrates were associated with low life expectancy and high variation in the age at death, a result caused predominantly by high mortality prior to middle age. A lifelong diet comprising the ratio of macronutrients self-selected by mouse (in early adulthood) was associated with low mortality up until middle age, but higher late-life mortality. This pattern results in reasonably high life expectancy, but very low variation in the age at death. Our analyses also indicate that it may be possible to minimize ASM across life by altering the ratio of dietary protein to carbohydrate in the approach to old age. Mortality in early and middle life was minimized at around one-part protein to two-parts carbohydrate, whereas in later life slightly greater than equal parts protein to carbohydrate reduced mortality.

Virological factors that increase the transmissibility of emerging human viruses.

The early detection of pathogens with epidemic potential is of major importance to public health. Most emerging infections result in dead-end "spillover" events in which a pathogen is transmitted from an animal reservoir to a human but is unable to achieve the sustained human-to-human transmission necessary for a full-blown epidemic. It is therefore critical to determine why only some virus infections are efficiently transmitted among humans whereas others are not. We sought to determine which biological features best characterized those viruses that have achieved sustained human transmission. Accordingly, we compiled a database of 203 RNA and DNA human viruses and used an information theoretic approach to assess which of a set of key biological variables were the best predictors of human-to-human transmission. The variables analyzed were as follows: taxonomic classification; genome length, type, and segmentation; the presence or absence of an outer envelope; recombination frequency; duration of infection; host mortality; and whether or not a virus exhibits vector-borne transmission. This comparative analysis revealed multiple strong associations. In particular, we determined that viruses with low host mortality, that establish long-term chronic infections, and that are nonsegmented, nonenveloped, and, most importantly, not transmitted by vectors were more likely to be transmissible among humans. In contrast, variables including genome length, genome type, and recombination frequency had little predictive power. In sum, we have identified multiple biological features that seemingly determine the likelihood of interhuman viral transmissibility, in turn enabling general predictions of whether viruses of a particular type will successfully emerge in human populations.

The nutritional nexus: Linking niche, habitat variability and prey composition in a generalist marine predator.

Our understanding of the niche concept will remain limited while the quantity and range of different food types eaten remain a dominant proxy for niche breadth, as this does not account for the broad ecological context that governs diet. Linking nutrition, physiology and behaviour is critical to predict the extent to which a species adjusts its nutritional niche breadth at the levels of prey ("prey composition niche," defined as the range of prey compositions eaten) and diet ("realized nutritional niche" is the range of diets composed through feeding on the prey). Here, we studied adult chick-rearing Australasian gannets Morus serrator to propose an integrative approach using sea surface temperature anomalies (SSTa), geographic location and bathymetry over different years, to explore their relationship with the nutritional composition of prey and diets (i.e. prey composition and nutritional niche breadth), habitat use and foraging behaviour. We found that gannets feed on prey that varied widely in their nutritional composition (have a broad prey composition niche), and composed diets from these prey that likewise varied in composition (have a broad realized nutritional niche), suggesting generalism at two levels of macronutrient selection. Across seasons, we established "nutritional landscapes" (hereafter nutriscapes), linking the nutritional content of prey (wet mass protein-to-lipid ratio-P:L) to the most likely geographic area of capture and bathymetry. Nutriscapes varied in their P:L from 6.06 to 15.28, over time, space and bathymetry (0-150 m). During warm water events (strong positive SSTa), gannets expanded their foraging habitat, increased their foraging trip duration and consumed prey and diets with low macronutrient content (wet mass proportions of P and L). They were also constrained to the smallest prey composition and realized nutritional niche breadths. Our findings are consistent with previous suggestions that dietary generalism evolves in heterogeneous environments, and provide a framework for understanding the nutritional goals in wild marine predators and how these goals drive ecological interactions and are, in turn, ultimately shaped by environmental fluctuations.

Quantitative analysis of the dose-response of white spot syndrome virus in shrimp.

White spot syndrome virus (WSSV) is an important cause of mortality and economic losses in shrimp farming. Although WSSV-induced mortality is virus dose dependent and WSSV infection does not necessarily lead to mortality, the relationships between virus-particle dose, infection and mortality have not been analysed quantitatively. Here, we explored WSSV dose-response by a combination of experiments, modelling and meta-analysis. We performed dose-response experiments in Penaeus vannamei postlarvae, recorded host mortality and detected WSSV infection. When we fitted infection models to these data, two models-differing in whether they incorporated heterogeneous host susceptibility to the virus or not-were supported for two independent experiments. To determine the generality of these results, we reanalysed published data sets and then performed a meta-analysis. We found that WSSV dose-response kinetics is indeed variable over experiments. We could not clearly identify which specific infection model has the most support by meta-analysis, but we argue that these results also are most concordant with a model incorporating varying levels of heterogeneous host susceptibility to WSSV. We have identified suitable models for analysing WSSV dose-response, which can elucidate the most basic virus-host interactions and help to avoid underestimating WSSV infection at low virus doses.

Meta-evaluation of meta-analysis: ten appraisal questions for biologists.

Meta-analysis is a statistical procedure for analyzing the combined data from different studies, and can be a major source of concise up-to-date information. The overall conclusions of a meta-analysis, however, depend heavily on the quality of the meta-analytic process, and an appropriate evaluation of the quality of meta-analysis (meta-evaluation) can be challenging. We outline ten questions biologists can ask to critically appraise a meta-analysis. These questions could also act as simple and accessible guidelines for the authors of meta-analyses. We focus on meta-analyses using non-human species, which we term 'biological' meta-analysis. Our ten questions are aimed at enabling a biologist to evaluate whether a biological meta-analysis embodies 'mega-enlightenment', a 'mega-mistake', or something in between.