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Time-restricted eating (TRE), a type of intermittent fasting in which all daily calories are consumed within a window of ≤12 hours, is hypothesized to promote long-term weight management because of its relative simplicity. This study reports correlates of adherence among community-dwelling adults currently or formerly following a TRE dietary strategy. A 25-minute cross-sectional online survey was developed, including questions about TRE perceptions, behaviors, motivators and drivers, and demographics. The survey was administered in February 2021 via Prolific, an online platform for sample recruitment and survey dissemination. Eligibility criteria included US adult ages 18+ who currently or formerly (past 3 months) followed TRE (ie, consumed all daily calories within a window of ≤12 hours) for a minimum of 1 week. χ2 tests and analysis of covariance (ANCOVA; adjusting for sex and age) compared responses between current and former followers. Current followers (n = 296, mean [SD]: 34.2 ± 12.2y) were older than former followers (n = 295, mean [SD]: 31.1 ± 10.9 y) and practiced TRE for longer (median: 395 vs 90 days, P < 0.001). Current followers reported more success with meeting TRE goals (P ≤ 0.015), were less likely to report TRE concerns (P < 0.001), and more likely to report TRE satisfaction (P < 0.001). Four TRE motivators were more important among current (vs former) followers: weight maintenance, health (not weight), improved sleep, and preventing disease (P ≤ 0.017); weight loss was more important among former (vs current) followers (P = 0.003). Among adherence drivers, ability to work from home and the impact of COVID-19 were reported as more helpful for TRE adherence among current compared with former followers (P ≤ 0.028). TRE motivators and drivers differed between current and former followers; interventions tailored to individuals' preferences and circumstances may benefit TRE adherence. [ABSTRACT FROM AUTHOR]

The digestive physiology of ruminants is sufficiently different (e.g., with respect to mean retention time of digesta, digestibility of the feed offered, digestion, and fermentation characteristics) that caution is needed before extrapolating results from one type of ruminant to another. The objectives of the present study were (1) to provide an overview of some essential differences in rumen physiology between dairy cattle, beef cattle, and sheep that are related to methane (CH 4) emission; and (2) to evaluate whether dietary strategies to mitigate CH 4 emission with various modes of action are equally effective in dairy cattle, beef cattle, and sheep. A literature search was performed using Web of Science and Scopus, and 94 studies were selected from the literature. Per study, the effect size of the dietary strategies was expressed as a proportion (%) of the control level of CH 4 emission, as this enabled a comparison across ruminant types. Evaluation of the literature indicated that the effectiveness of forage-related CH 4 mitigation strategies, including feeding more highly digestible grass (herbage or silage) or replacing different forage types with corn silage, differs across ruminant types. These strategies are most effective for dairy cattle, are effective for beef cattle to a certain extent, but seem to have minor or no effects in sheep. In general, the effectiveness of other dietary mitigation strategies, including increased concentrate feeding and feed additives (e.g., nitrate), appeared to be similar for dairy cattle, beef cattle, and sheep. We concluded that if the mode of action of a dietary CH 4 mitigation strategy is related to ruminant-specific factors, such as feed intake or rumen physiology, the effectiveness of the strategy differs across ruminant types, whereas if the mode of action is associated with methanogenesis-related fermentation pathways, the strategy is effective across ruminant types. Hence, caution is needed when translating effectiveness of dietary CH 4 mitigation strategies across different ruminant types or production systems. [ABSTRACT FROM AUTHOR]

Humans generally solve multi-destination routes with simple rules-of-thumb. Animals may do the same, but strong evidence is limited to a few species. We examined whether strepsirrhines, who diverged from haplorhines more than 58 mya, would demonstrate the use of three heuristics used by humans and supported in vervets, the nearest neighbor rule, the convex hull, and a cluster strategy, when solving a multi-destination route. We hypothesized that the evolution of these strategies may depend on a species' dietary specialization. Three nocturnal lemur species were tested on an experimental array at the Duke Lemur Center. Frugivorous fat-tailed dwarf lemurs (Cheirogaleus medius) were expected to follow paths most consistent with distance-saving navigational heuristics because fruit trees are stationary targets. Gray mouse lemurs (Microcebus murinus) and aye-ayes (Daubentonia madagascariensis), which rely on more mobile and ephemeral foods, were expected to use fewer paths consistent with these heuristics and be more exploratory. Our data supported all of these hypotheses. Dwarf lemurs used paths consistent with all three heuristics, took the shortest paths, and were the least exploratory. Mouse lemurs were quite exploratory but sometimes used paths consistent with heuristics. Aye-ayes showed no evidence of heuristic use and were the most exploratory. Distinguishable patterns of inter- and intra-individual variation in ability to solve the route, speed, and behavior occurred in each species. This research suggests that these simple navigational heuristics are not part of a readily available set of cognitive tools inherited by all primates but instead evolve due to need in each lineage. [ABSTRACT FROM AUTHOR]

• Proportion of concentrate, lipids, inhibitors and electron acceptors decrease methanogenesis. • Hydrogen production improve methane production models. • Hydrogen production slope depends on the mitigation strategy and its mechanism of action. • Hydrogen slope is negative with inhibitors or electron acceptors. • Hydrogen slope is positive with proportion of concentrate and lipids. Stoichiometric models that predict methane (CH 4) production of ruminants assume that the amount of hydrogen gas (H 2) produced during fermentation in the rumen equals the amount of H 2 consumed by electron sinks in the rumen and thus that H 2 should not be emitted into the environment. However, some studies have demonstrated that H 2 emissions occur under practical conditions. In addition, the H 2 emissions increase when nutritional mitigation strategies are used. Hence, this study hypothesized that considering H 2 emission would improve the prediction of enteric CH 4 emission, especially when using mitigation strategies that induce high variation in the H 2 emission. The objective of this study was to develop and evaluate the performance of CH 4 emission prediction models using H 2 emission as an explanatory variable. A database of CH 4 and H 2 emission (mean treatment data) from ruminants (dairy cattle, growing cattle and sheeps) was built to develop mixed-effects models at three levels of complexity: level 1 - H 2 production/yield, DMI, or both; level 2 - level 1 explanatory variables plus chemical composition of the diet (i.e. CP, EE, NDF, OM, or PCO); and level 3 - level 2 explanatory variables plus animal metabolic weight (BW0.75, kg). When all animal categories were grouped, including H 2 production improved the performance of CH 4 production prediction only in level 1 models for the electron-receptor mitigation strategy, reducing the root mean square of prediction error (RMSPE) by 18 %. For dairy cattle and sheep, dry matter intake was not a significant explanatory variable in level 1 or 2 models. For growing beef cattle, for all mitigation strategies together and the inhibitor-mitigation strategy alone, including H 2 production reduced RMSPE by 13 % and 27 %, respectively. Overall, H 2 production was included in 60 % of level 1 models and 100 % of level 2 and 3 models, which best predicted CH 4 production. Thus, including H 2 emission does improve prediction of enteric CH 4 emission, especially when mitigation strategies that induce variation in the H 2 are used. [ABSTRACT FROM AUTHOR]

Ungulates often adjust their diet when food availability varies over time. However, it is poorly understood when and to what extent individuals change their diet and, if they do so, if all individuals of a population occupy distinct or similar dietary niches. In the arid Namibian Kunene Region, we studied temporal variations of individual niches in grazing gemsbok ( Oryx gazella gazella) and predominantly browsing springbok ( Antidorcas marsupialis). We used variation in stable C and N isotope ratios of tail hair increments as proxies to estimate individual isotopic dietary niches and their temporal plasticity. Isotopic dietary niches of populations of the two species were mutually exclusive, but similar in breadth. Isotopic niche breadth of gemsbok was better explained by within-individual variation than by between-individual variation of stable isotope ratios, indicating that gemsbok individuals were facultative specialists in using isotopically distinct local food resources. In contrast, inter- and intra-individual variations contributed similarly to the isotopic niche breadth of the springbok population, suggesting a higher degree of individual isotopic segregation in a more generalist ungulate. In both species, between-individual variation was neither explained by changes in plant primary productivity, sex, geographical position nor by group size. Within species, individual dietary niches overlapped partially, suggesting that both populations included individuals with distinct isotopic dietary niches. Our study provides the first evidence for isotopic dietary niche segregation in individuals of two distinct desert ungulates. Similar, yet isotopically distinct dietary niches of individuals may facilitate partitioning of food resources and thus individual survival in desert ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: While larger containers have been found to increase food intake, it is unclear whether this effect is driven by container size, portion size, or their combination, as these variables are usually confounded. The study was advertised as examining the effects of snack food consumption on information processing and participants were served M&M’s for free consumption in individual cubicles while watching a TV show. Participants were served (1) a medium portion of M&M’s in a small (n =30) or (2) in a large container (n =29), or (3) a large portion in a large container (n =29). The larger container increased intake by 129% (199kcal) despite holding portion size constant, while controlling for different confounding variables. This research suggests that larger containers stimulate food intake over and above their impact on portion size. [Copyright &y& Elsevier]

Objective: Examine the influence of altering the size of snack food (ie, small vs large cookies) on short- term energy intake. Methods: First- and sixth-graders (n = 77) participated in a between-subjects experimental design. All participants were offered the same gram weight of cookies during an afternoon tea at their school. For half of the participants, food was cut in 2 to make the small item size. Food intake (number of cookies, gram weight, and energy intake) was examined using ANO VA. Results: Decreasing the item size of food led to a decrease of 25% in gram weight intake, corresponding to 68 kcal. Appetitive ratings and subject and food characteristics had no moderating effect. Conclusions and Implications: Reducing the item size of food could prove a useful dietary prevention strategy based on decreased consumption, aimed at countering obesity-promoting eating behaviors favored by the easy availability of large food portions. [ABSTRACT FROM AUTHOR]

• Published models were evaluated against more than 3000 individual records of methane emission (CH 4). • Specific model accurately predict CH 4 emissions from dairy cattle and under different dietary strategies. • Using diet intake, digestibility and composition in model reduce prediction error. • New models are needed to estimate CH 4 from beef cattle, sheep and goats. The objective of this study was to evaluate the performance of existing models predicting enteric methane (CH 4) emissions, using a large database (3183 individual data from 103 in vivo studies on dairy and beef cattle, sheep and goats fed diets from different countries). The impacts of dietary strategies to reduce CH 4 emissions, and of diet quality (described by organic matter digestibility (dOM) and neutral-detergent fiber digestibility (dNDF)) on model performance were assessed by animal category. The models were first assessed based on the root mean square prediction error (RMSPE) to standard deviation of observed values ratio (RSR) to account for differences in data between models and then on the RMSPE. For dairy cattle, the CH 4 (g/d) predicting model based on feeding level (dry matter intake (DMI)/body weight (BW)), energy digestibility (dGE) and ether extract (EE) had the smallest RSR (0.66) for all diets, as well as for the high-EE diets (RSR = 0.73). For mitigation strategies based on lowering NDF or improving dOM, the same model (RSR = 0.48 to 0.60) and the model using DMI and neutral- and acid-detergent fiber intakes (RSR = 0.53) had the smallest RSR, respectively. For diets with high starch (STA), the model based on nitrogen, ADF and STA intake presented the smallest RSR (0.84). For beef cattle, all evaluated models performed moderately compared with the models of dairy cattle. The smallest RSR (0.83) was obtained using variables of energy intake, BW, forage content and dietary fat, and also for the high-EE and the low-NDF diets (RSR = 0.84 to 0.86). The IPCC Tier 2 models performed better when dietary STA, dOM or dNDF were high. For sheep and goats, the smallest RSR was observed from a model for sheep based on dGE intake (RSR = 0.61). Both IPCC models had low predictive ability when dietary EE, NDF, dOM and dNDF varied (RSR = 0.57 to 1.31 in dairy, and 0.65 to 1.24 in beef cattle). The performance of models depends mostly on explanatory variables and not on the type of data (individual vs. treatment means) used in their development or evaluation. Some empirical models give satisfactory prediction error compared with the error associated with measurement methods. For better prediction, models should include feed intake, digestibility and additional information on dietary concentrations of EE and structural and nonstructural carbohydrates to account for different dietary mitigating strategies. [ABSTRACT FROM AUTHOR]