Non-verbal information in spontaneous speech -- towards a new framework of analysis

Non-verbal signals in speech are encoded by prosody and carry information that ranges from conversation action to attitude and emotion. Despite its importance, the principles that govern prosodic structure are not yet adequately understood. This paper offers an analytical schema and a technological proof-of-concept for the categorization of prosodic signals and their association with meaning. The schema interprets surface-representations of multi-layered prosodic events. As a first step towards implementation, we present a classification process that disentangles prosodic phenomena of three orders. It relies on fine-tuning a pre-trained speech recognition model, enabling the simultaneous multi-class/multi-label detection. It generalizes over a large variety of spontaneous data, performing on a par with, or superior to, human annotation. In addition to a standardized formalization of prosody, disentangling prosodic patterns can direct a theory of communication and speech organization. A welcome by-product is an interpretation of prosody that will enhance speech- and language-related technologies

Connective tissue activation. IV. Regulatory effects of antirheumatic drugs

Cortisol, phenylbutazone, indomethacin, acetylsalicylic acid, meclofenamic acid, flufenamic acid and mefanamic acid were potent inhibitors of connective tissue activation, especially if introduced into synovial cultures within 2 hours of initiation of the activation process. Colchicine, chloroquine and gold thiomalate were ineffective, while hydroxychloroquine and sodium salicylate exhibited modest inhibitory capacity. Most of the active agents exhibited suppressive capacity at concentrations similar to those used clinically. The suppressive capacity of the various drugs was reduced 20 to 60% by the presence of serum. Antirheumatic drugs do not appear to alter the activity of the stimulatory connective tissue activating peptide molecule itself, but may act by interfering with the transcriptional and translational components of the connective tissue activation sequence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37722/1/1780150506_ftp.pd

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

PlexinA2 and Sema6A are required for retinal progenitor cell migration

International audienceIn the vertebrate retina six types of neurons and one glial cell type are generated from multipotent retinal progenitor cells (RPCs) whose proliferation and differentiation are regulated by intrinsic and extrinsic factors. RPCs proliferate undergoing interkinetic nuclear migration within the neuroblastic layer, with their nuclei moving up and down along the apico-basal axis. Moreover, they only differentiate and therefore exit the cell cycle at the apical side of the neuroblastic layer. Sema6A and its receptors PlexinA4 and PlexinA2 control lamina stratification of the inner plexiform layer in the mouse retina. Nevertheless, their function in earlier developmental stages is still unknown. Here, we analyzed the embryonic retina of PlexinA2 and Sema6A knockout mice. Using time-lapse videomicroscopy we provide evidence that Sema6A/PlexinA2 signaling participates to interkinetic nuclear migration of RPCs around birth. When disrupted, RPCs migration is blocked at the apical side of the neuroblastic layer. This is the first evidence supporting a role for transmembrane molecules in the regulation of interkinetic nuclear migration in the mouse retina