11-month-olds' knowledge of how familiar words sounds

During the first year of life, infants' perception of speech becomes tuned to the phonology of the native language, as revealed in laboratory discrimination and categorization tasks using syllable stimuli. However, the implications of these results for the development of the early vocabulary remain controversial, with some results suggesting that infants retain only vague, sketchy phonological representations of words. Five experiments using a preferential listening procedure tested Dutch 11-month-olds' responses to word, nonword and mispronounced-word stimuli. Infants listened longer to words than nonwords, but did not exhibit this response when words were mispronounced at onset or at offset. In addition, infants preferred correct pronunciations to onset mispronunciations. The results suggest that infants' encoding of familiar words includes substantial phonological detail

Phonetic detail in the developing lexicon

Although infants show remarkable sensitivity to linguistically relevant phonetic variation in speech, young children sometimes appear not to make use of this sensitivity. Here, children's knowledge of the sound-forms of familiar words was assessed using a visual fixation task. Dutch 19-month-olds were shown pairs of pictures and heard correct pronunciations and mispronunciations of familiar words naming one of the pictures. Mispronunciations were word-initial in Experiment 1 and word-medial in Experiment 2, and in both experiments involved substituting one segment with [d] (a common sound in Dutch) or [g] (a rare sound). In both experiments, word recognition performance was better for correct pronunciations than for mispronunciations involving either substituted consonant. These effects did not depend upon children's knowledge of lexical or nonlexical phonological neighbors of the tested words. The results indicate the encoding of phonetic detail in words at 19 months

Lexical exposure and word-from encoding in 1.5-year-olds

In this study, 1.5-year-olds were taught a novel word. Some children were familiarized with the word's phonological form before learning the word's meaning. Fidelity of phonological encoding was tested in a picture-fixation task using correctly pronounced and mispronounced stimuli. Only children with additional exposure in familiarization showed reduced recognition performance given slight mispronunciations relative to correct pronunciations; children with fewer exposures did not. Mathematical modeling of vocabulary exposure indicated that children may hear thousands of words frequently enough for accurate encoding. The results provide evidence compatible with partial failure of phonological encoding at 19 months of age, demonstrate that this limitation in learning does not always hinder word recognition, and show the value of infants' word-form encoding in early lexical development

Lexical competition in young children's word learning

In two experiments, 1.5-year-olds were taught novel words whose sound patterns were phonologically similar to familiar words (novel neighbors) or were not (novel nonneighbors). Learning was tested using a picture-fixation task. In both experiments, children learned the novel nonneighbors but not the novel neighbors. In addition, exposure to the novel neighbors impaired recognition performance on familiar neighbors. Finally, children did not spontaneously use phonological differences to infer that a novel word referred to a novel object. Thus, lexical competition—inhibitory interaction among words in speech comprehension—can prevent children from using their full phonological sensitivity in judging words as novel. These results suggest that word learning in young children, as in adults, relies not only on the discrimination and identification of phonetic categories, but also on evaluating the likelihood that an utterance conveys a new word

tRNA signatures reveal polyphyletic origins of streamlined SAR11 genomes among the alphaproteobacteria

Phylogenomic analyses are subject to bias from compositional convergence and noise from horizontal gene transfer (HGT). Compositional convergence is a likely cause of controversy regarding phylogeny of the SAR11 group of Alphaproteobacteria that have extremely streamlined, A+T-biased genomes. While careful modeling can reduce artifacts caused by convergence, the most consistent and robust phylogenetic signal in genomes may lie distributed among encoded functional features that govern macromolecular interactions. Here we develop a novel phyloclassification method based on signatures derived from bioinformatically defined tRNA Class-Informative Features (CIFs). tRNA CIFs are enriched for features that underlie tRNA-protein interactions. Using a simple tRNA-CIF-based phyloclassifier, we obtained results consistent with those of bias-corrected whole proteome phylogenomic studies, rejecting monophyly of SAR11 and affiliating most strains with Rhizobiales with strong statistical support. Yet SAR11 and Rickettsiales tRNA genes share distinct patterns of A+T-richness, as expected from their elevated genomic A+T compositions. Using conventional supermatrix methods on total tRNA sequence data, we could recover the artifactual result of a monophyletic SAR11 grouping with Rickettsiales. Thus tRNA CIF-based phyloclassification is more robust to base content convergence than supermatrix phylogenomics on whole tRNA sequences. Also, given the notoriously promiscuous HGT of aminoacyl-tRNA synthetases, tRNA CIF-based phyloclassification may be relatively robust to HGT of network components. We describe how unique features of tRNA-protein interaction networks facilitate the mining of traits governing macromolecular interactions from genomic data, and discuss why interaction-governing traits may be especially useful to solve difficult problems in microbial classification and phylogeny

tRNA functional signatures classify plastids as late-branching cyanobacteria.

BackgroundEukaryotes acquired the trait of oxygenic photosynthesis through endosymbiosis of the cyanobacterial progenitor of plastid organelles. Despite recent advances in the phylogenomics of Cyanobacteria, the phylogenetic root of plastids remains controversial. Although a single origin of plastids by endosymbiosis is broadly supported, recent phylogenomic studies are contradictory on whether plastids branch early or late within Cyanobacteria. One underlying cause may be poor fit of evolutionary models to complex phylogenomic data.ResultsUsing Posterior Predictive Analysis, we show that recently applied evolutionary models poorly fit three phylogenomic datasets curated from cyanobacteria and plastid genomes because of heterogeneities in both substitution processes across sites and of compositions across lineages. To circumvent these sources of bias, we developed CYANO-MLP, a machine learning algorithm that consistently and accurately phylogenetically classifies ("phyloclassifies") cyanobacterial genomes to their clade of origin based on bioinformatically predicted function-informative features in tRNA gene complements. Classification of cyanobacterial genomes with CYANO-MLP is accurate and robust to deletion of clades, unbalanced sampling, and compositional heterogeneity in input tRNA data. CYANO-MLP consistently classifies plastid genomes into a late-branching cyanobacterial sub-clade containing single-cell, starch-producing, nitrogen-fixing ecotypes, consistent with metabolic and gene transfer data.ConclusionsPhylogenomic data of cyanobacteria and plastids exhibit both site-process heterogeneities and compositional heterogeneities across lineages. These aspects of the data require careful modeling to avoid bias in phylogenomic estimation. Furthermore, we show that amino acid recoding strategies may be insufficient to mitigate bias from compositional heterogeneities. However, the combination of our novel tRNA-specific strategy with machine learning in CYANO-MLP appears robust to these sources of bias with high accuracy in phyloclassification of cyanobacterial genomes. CYANO-MLP consistently classifies plastids as late-branching Cyanobacteria, consistent with independent evidence from signature-based approaches and some previous phylogenetic studies

When half a word is enough: infants can recognize spoken words using partial phonetic information

Adults process speech incrementally, rapidly identifying spoken words on the basis of initial phonetic information sufficient to distinguish them from alternatives. In this study, infants in the second year also made use of word-initial information to understand fluent speech. The time course of comprehension was examined by tracking infants' eye movements as they looked at pictures in response to familiar spoken words, presented both as whole words in intact form and as partial words in which only the first 300 ms of the word was heard. In Experiment 1, 21-month-old infants (N = 32) recognized partial words as quickly and reliably as they recognized whole words; in Experiment 2, these findings were replicated with 18-month-old infants (N = 32). Combining the data from both experiments, efficiency in spoken word recognition was examined in relation to level of lexical development. Infants with more than 100 words in their productive vocabulary were more accurate in identifying familiar words than were infants with less than 60 words. Grouped by response speed, infants with faster mean reaction times were more accurate in word recognition and also had larger productive vocabularies than infants with slower response latencies. These results show that infants in the second year are capable of incremental speech processing even before entering the vocabulary spurt, and that lexical growth is associated with increased speed and efficiency in understanding spoken language

Infants' developing competence in recognizing and understanding words in fluent speech

Again and again in research on early cognitive development, infants turn out to be smarter than we thought they were. The refinement of experimental tech-niques for reading infants ' minds has been extremely productive, enabling us to study developing capabilities which are not yet observable in spontaneous behavior. When the task demands are made simple enough, infants demonstrate implicit knowledge across diverse domains ranging from understanding of the physical world and numerical concepts to social cognition (see Wellman & Gelman 1998). In the domain of language understanding as well, such techniques have been used to reveal the early emergence of linguistic competence before it is evident in overt behavior, and many ingenious experiments have demonstrated the considerable speech processing savvy of infants in the first year. These studies show that certain perceptual skills essential for spoken language under-standing emerge gradually over the first year, often months before infants are able to display their linguistic knowledge through speech production (see Aslin, Jusczyk & Pisoni 1998). Our own recent research on word recognition by olde

Microbial Community in Hyperalkaline Steel Slag-Fill Emulates Serpentinizing Springs

© 2019 by the authors. To date, a majority of studies of microbial life in hyperalkaline settings focus on environments that are also highly saline (haloalkaline). Haloalkaline conditions offer microbes abundant workarounds to maintain pH homeostasis, as salt ions can be exchanged for protons by dedicated antiporter proteins. Yet hyperalkaline freshwater systems also occur both naturally and anthropogenically, such as the slag fill aquifers around former Lake Calumet (Chicago, IL, USA). In this study, 16S rRNA gene sequences and metagenomic sequence libraries were collected to assess the taxonomic composition and functional potential of microbes present in these slag-polluted waterways. Relative 16S rRNA gene abundances in Calumet sediment and water samples describe community compositions not significantly divergent from those in nearby circumneutral conditions. Major differences in composition are mainly driven by Proteobacteria, primarily one sequence cluster closely related to Hydrogenophaga, which comprises up to 85% of 16S rRNA gene abundance in hyperalkaline surface sediments. Sequence identity indicates this novel species belongs to the recently established genus Serpentinomonas, a bacterial lineage associated with natural freshwater hyperalkaline serpentinizing springs