What is universal and what differs in language development?

Goldin-Meadow (2015) presents an exceptional synthesis of work from studies of children acquiring language under variable circumstances of input or processing abilities. Deaf children who acquire homesign without any well- formed model from which to learn language represent a powerful example. Goldin-Meadow argues that the resilient properties of language that nevertheless emerge include simple syntactic structures, hierarchical organisa- tion, markers modulating the meaning of sentences, and social-communicative functions. Among the fragile or input-dependent properties are the orders that the language follows, the parts into which words are decomposed, and the features that distinguish nominals from predicates. Separation of these two types of properties poses questions concerning the innate constraints on language acquisition (perhaps these equate to the resilient properties) and con‐ cerning the specificity of processes to language (e.g., whether properties such as hierarchical organisation are specific to language or originate in the structure of thought). The study of the resilient properties of human language in the face of adversity and the relation of these properties to the information that is encoded in the human genome represent a research strategy that draws inferences about species universals (properties that all humans share) from data about individual differences (IDs; factors that make humans different from one another). In the following, we suggest three reasons to be cautious about this approach.

Quantifying diet-induced metabolic changes of the human gut microbiome

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.