Short-term symptom improvement in infants with suspected cow’s milk protein allergy using amino acid formula: a prospective cohort analysis

BackgroundCow’s milk protein allergy (CMPA) occurs commonly in infants. While the long-term efficacy of amino acid formulas for managing CMPA is well-established, there is limited data on the short-term symptom improvement of using amino acid formula (AAF).ObjectiveThis study aimed to determine the short-term effects of managing suspected CMPA in infants aged 6 months and under using a commercial AAF.MethodsHealthcare providers who treated infants with suspected CMPA aged 6 months or younger (n = 104) provided de-identified survey data in this prospective study. Healthcare providers scored symptoms for severity from 0 to 3 (none, low, moderate, severe) before using a commercial AAF at Visit 1 and at Visit 2 (3–6 weeks later).ResultsGastrointestinal (94%), skin (87%), respiratory (86%), and uncategorized symptoms (89%) improved from AAF initiation, and these findings were consistent across different follow-up visit durations.ConclusionThis study is the most extensive prospective analysis conducted in the United States examining the short-term change in suspected CMPA symptoms using an AAF. These findings suggest that AAF may decrease the severity of suspected CMPA symptoms in infants 6 months or younger, often by the next follow-up visit. Further randomized controlled trials are required to confirm these initial findings

Fish Species of Greatest Conservation Need in Wadeable Iowa Streams: Current Status and Effectiveness of Aquatic Gap Program Distribution Models

Effective conservation of fish species of greatest conservation need (SGCN) requires an understanding of species– habitat relationships and distributional trends. Thus, modeling the distribution of fish species across large spatial scales may be a valuable tool for conservation planning. Our goals were to evaluate the status of 10 fish SGCN in wadeable Iowa streams and to test the effectiveness of IowaAquatic Gap Analysis Project (IAGAP) species distribution models. We sampled fish assemblages from 86 wadeable stream segments in the Mississippi River drainage of Iowa during 2009 and 2010 to provide contemporary, independent fish species presence–absence data. The frequencies of occurrence in stream segments where species were historically documented varied from 0.0% for redfin shiner Lythrurus umbratilis to 100.0% for American brook lamprey Lampetra appendix, with a mean of 53.0%, suggesting that the status of Iowa fish SGCN is highly variable. Cohen’s kappa values and other model performance measures were calculated by comparing field-collected presence–absence data with IAGAP model–predicted presences and absences for 12 fish SGCN. Kappa values varied from 0.00 to 0.50, with a mean of 0.15. The models only predicted the occurrences of banded darter Etheostoma zonale, southern redbelly dace Phoxinus erythrogaster, and longnose dace Rhinichthys cataractae more accurately than would be expected by chance. Overall, the accuracy of the twelve models was low, with a mean correct classification rate of 58.3%. Poor model performance probably reflects the difficulties associated with modeling the distribution of rare species and the inability of the large-scale habitat variables used in IAGAP models to explain the variation in fish species occurrences. Our results highlight the importance of quantifying the confidence in species distribution model predictions with an independent data set and the need for long-term monitoring to better understand the distributional trends and habitat associations of fish SGCN

Habitat Associations of Fish Species of Greatest Conservation Need at Multiple Spatial Scales in Wadeable Iowa Streams

Fish and habitat data were collected from 84 wadeable stream reaches in the Mississippi River drainage of Iowa to predict the occurrences of seven fish species of greatest conservation need and to identify the relative importance of habitat variables measured at small (e.g., depth, velocity, and substrate) and large (e.g., stream order, elevation, and gradient) scales in terms of their influence on species occurrences. Multiple logistic regression analysis was used to predict fish species occurrences, starting with all possible combinations of variables (5 large-scale variables, 13 small-scale variables, and all 18 variables) but limiting the final models to a maximum of five variables. Akaike’s information criterion was used to rank candidate models, weight model parameters, and calculate model-averaged predictions. On average, the correct classification rate (CCR = 80%) and Cohen’s kappa (κ = 0.59) were greatest for multiple-scale models (i.e., those including both large-scale and small-scale variables), intermediate for small-scale models (CCR = 75%; κ = 0.49), and lowest for large-scale models (CCR = 73%; κ = 0.44). The occurrence of each species was associated with a unique combination of large-scale and small-scale variables. Our results support the necessity of understanding factors that constrain the distribution of fishes across spatial scales to ensure that management decisions and actions occur at the appropriate scale

Multiple Facets of Biodiversity Drive the Diversity-Stability Relationship

A significant body of evidence has demonstrated that biodiversity stabilizes ecosystem functioning over time in grassland ecosystems. However, the relative importance of different facets of biodiversity underlying the diversity–stability relationship remains unclear. Here we used data from 39 biodiversity experiments and structural equation modeling to investigate the roles of species richness, phylogenetic diversity, and both the diversity and community-weighted mean of functional traits representing the ‘fast–slow’ leaf economics spectrum in driving the diversity–stability relationship. We found that high species richness and phylogenetic diversity stabilize biomass production via enhanced asynchrony. Contrary to our hypothesis, low phylogenetic diversity also enhances ecosystem stability directly, albeit weakly. While the diversity of fast–slow functional traits has a weak effect on ecosystem stability, communities dominated by slow species enhance ecosystem stability by increasing mean biomass production relative to the standard deviation of biomass over time. Our results demonstrate that biodiversity influences ecosystem stability via a variety of facets, thus highlighting a more multicausal relationship than has been previously acknowledged

Functional Structure of Biological Communities Predicts Ecosystem Multifunctionality

The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages