Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, well compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, well discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. Well also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata

Salicylic acid:old and new implications for the treatment of type 2 diabetes?

Efficacy of salicylic acid as a treatment for diabetes was first established well over a century ago. Antihyperglycaemic effects are thought to include improved peripheral insulin sensitivity and suppression of hepatic glucose production. For most of this period, the molecular mechanisms underlying these effects have been poorly understood and these are still a focus of considerable research, which is reviewed here. Antihyperglycaemic effects are observed only at much higher concentrations than analgesic, antipyretic and antithrombotic properties, suggesting that different targets underlie the antidiabetic aspects of salicylate pharmacology. In the 1950s, antihyperglycaemic responses were linked to mitochondrial uncoupling effects of the drug. Then at the beginning of this century, antihyperglycaemic effects were linked to anti-inflammatory effects of the drug on NF-κB signalling. More recently, new work suggests that direct activation of AMPK may contribute to antihyperglycaemic/antihyperlipidemic actions of salicylates. Better understanding of the mechanism of salicylate’s anthyperglycaemic effects may ultimately accelerate the development of new drugs for human use