'Pearls' of the nineteenth-century: from therapeutic actors to global commodities medicinal leeches in the Ottoman Empire.

Nineteenth-century physicians increasingly favoured leeching - the placing of a live leech onto a patient's skin to stimulate or limit blood flow - as a cure for numerous ailments. As conviction in their therapeutic properties spread, leech therapy dominated European medicine; France imported over fifty million leeches in one year. Demand soon outpaced supply, spawning a lucrative global trade. Over-collection and farming eventually destroyed leech habitats, wreaked environmental havoc and forced European merchants to seek new supply sources. Vast colonies of leeches were found to inhabit the immense wetlands of the Ottoman Empire, which soon became a major exporter of medicinal leeches. Following the Treaty of Balta Liman (1838), the Ottoman state moved to exert control over the lucrative trade, imposing a tax on leech gathering and contracting with tax-farmers (mültezim) to collect the taxes. British diplomats, merchants and other stakeholders protested the imposition of the tax, as had previously happened with the commodification of wildlife; their pursuit of profit led collectors and farmers to over-gather leeches, with catastrophic consequences. By the end of the century, so great had their worth climbed that the leech population faced extinction. This paper situates medicinal leeches as therapeutic actors of history and adopts an interscale approach in formulating the human-leech interaction. It offers a substantive contribution to the history of medicine, in revealing the centrality of leeches to the rise of modern medicine and global trade, but also by making visible their role in shaping imperial diplomacy and worldwide economic markets.

DeepKinZero: zero-shot learning for predicting kinase-phosphosite associations involving understudied kinases.

MOTIVATION: Protein phosphorylation is a key regulator of protein function in signal transduction pathways. Kinases are the enzymes that catalyze the phosphorylation of other proteins in a target-specific manner. The dysregulation of phosphorylation is associated with many diseases including cancer. Although the advances in phosphoproteomics enable the identification of phosphosites at the proteome level, most of the phosphoproteome is still in the dark: more than 95% of the reported human phosphosites have no known kinases. Determining which kinase is responsible for phosphorylating a site remains an experimental challenge. Existing computational methods require several examples of known targets of a kinase to make accurate kinase-specific predictions, yet for a large body of kinases, only a few or no target sites are reported. RESULTS: We present DeepKinZero, the first zero-shot learning approach to predict the kinase acting on a phosphosite for kinases with no known phosphosite information. DeepKinZero transfers knowledge from kinases with many known target phosphosites to those kinases with no known sites through a zero-shot learning model. The kinase-specific positional amino acid preferences are learned using a bidirectional recurrent neural network. We show that DeepKinZero achieves significant improvement in accuracy for kinases with no known phosphosites in comparison to the baseline model and other methods available. By expanding our knowledge on understudied kinases, DeepKinZero can help to chart the phosphoproteome atlas. AVAILABILITY AND IMPLEMENTATION: The source codes are available at https://github.com/Tastanlab/DeepKinZero. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.