Machine Learning in Drug Discovery and Development Part 1: A Primer

Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.Laboratorio de Investigación y Desarrollo de Bioactivo

The United States of America and Scientific Research

To gauge the current commitment to scientific research in the United States of America (US), we compared federal research funding (FRF) with the US gross domestic product (GDP) and industry research spending during the past six decades. In order to address the recent globalization of scientific research, we also focused on four key indicators of research activities: research and development (R&D) funding, total science and engineering doctoral degrees, patents, and scientific publications. We compared these indicators across three major population and economic regions: the US, the European Union (EU) and the People's Republic of China (China) over the past decade. We discovered a number of interesting trends with direct relevance for science policy. The level of US FRF has varied between 0.2% and 0.6% of the GDP during the last six decades. Since the 1960s, the US FRF contribution has fallen from twice that of industrial research funding to roughly equal. Also, in the last two decades, the portion of the US government R&D spending devoted to research has increased. Although well below the US and the EU in overall funding, the current growth rate for R&D funding in China greatly exceeds that of both. Finally, the EU currently produces more science and engineering doctoral graduates and scientific publications than the US in absolute terms, but not per capita. This study's aim is to facilitate a serious discussion of key questions by the research community and federal policy makers. In particular, our results raise two questions with respect to: a) the increasing globalization of science: “What role is the US playing now, and what role will it play in the future of international science?”; and b) the ability to produce beneficial innovations for society: “How will the US continue to foster its strengths?

Pancreatic (pro)enzymes treatment suppresses BXPC-3 pancreatic Cancer Stem Cell subpopulation and impairs tumour engrafting

Cancer stem cells (CSCs) subpopulation within the tumour is responsible for metastasis and cancer relapse. Here we investigate in vitro and in vivo the effects of a pancreatic (pro)enzyme mixture composed of Chymotrypsinogen and Trypsinogen (PRP) on CSCs derived from a human pancreatic cell line, BxPC3. Exposure of pancreatic CSCs spheres to PRP resulted in a significant decrease of ALDEFLUOR and specific pancreatic CSC markers (CD 326, CD 44 and CxCR4) signal tested by flow cytometry, further CSCs markers expression was also analyzed by western and immunofluorescence assays. PRP also inhibits primary and secondary sphere formation. Three RT2 Profiler PCR Arrays were used to study gene expression regulation after PRP treatment and resulted in, (i) epithelialmesenchymal transition (EMT) inhibition; (ii) CSCs related genes suppression; (iii) enhanced expression of tumour suppressor genes; (iv) downregulation of migration and metastasis genes and (v) regulation of MAP Kinase Signalling Pathway. Finally, in vivo anti-tumor xenograft studies demonstrated high anti-tumour efficacy of PRP against tumours induced by BxPC3 human pancreatic CSCs. PRP impaired engrafting of pancreatic CSC’s tumours in nude mice and displayed an antigrowth effect toward initiated xenografts. We concluded that (pro)enzymes treatment is a valuable strategy to suppress the CSC population in solid pancreatic tumours

Survey and Excavation at the Henges of the Wharfe Valley, North Yorkshire, 2013-15

YesGeophysical survey at the three major henge monuments in the Wharfe Valley has provided details of survival and internal features. Excavation at Yarnbury has confirmed its Bronze Age date and has recovered material matching that from previous unrecorded excavations. The excavation has provided environmental data for the construction of the henge. The sites are placed in their regional context.British Academ

Neanderthal Use of Fish, Mammals, Birds, Starchy Plants and Wood 125-250,000 Years Ago

Neanderthals are most often portrayed as big game hunters who derived the vast majority of their diet from large terrestrial herbivores while birds, fish and plants are seen as relatively unimportant or beyond the capabilities of Neanderthals. Although evidence for exploitation of other resources (small mammals, birds, fish, shellfish, and plants) has been found at certain Neanderthal sites, these are typically dismissed as unusual exceptions. The general view suggests that Neanderthal diet may broaden with time, but that this only occurs sometime after 50,000 years ago. We present evidence, in the form of lithic residue and use-wear analyses, for an example of a broad-based subsistence for Neanderthals at the site of Payre, Ardèche, France (beginning of MIS 5/end of MIS 6 to beginning of MIS 7/end of MIS 8; approximately 125–250,000 years ago). In addition to large terrestrial herbivores, Neanderthals at Payre also exploited starchy plants, birds, and fish. These results demonstrate a varied subsistence already in place with early Neanderthals and suggest that our ideas of Neanderthal subsistence are biased by our dependence on the zooarchaeological record and a deep-seated intellectual emphasis on big game hunting