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Advances in molecular technologies and targeted therapeutics have accelerated the implementation of precision oncology, resulting in improved clinical outcomes in selected patients. The use of next-generation sequencing and assessments of immune and other biomarkers helps optimize patient treatment selection. In this review, selected precision oncology trials including the IMPACT, SHIVA, IMPACT2, NCI-MPACT, TAPUR, DRUP, and NCI-MATCH studies are summarized, and their challenges and opportunities are discussed. Brief summaries of the new ComboMATCH, MyeloMATCH, and iMATCH studies, which follow the example of NCI-MATCH, are also included. Despite the progress made, precision oncology is inaccessible to many patients with cancer. Some patients’ tumors may not respond to these treatments, owing to the complexity of carcinogenesis, the use of ineffective therapies, or unknown mechanisms of tumor resistance to treatment. The implementation of artificial intelligence, machine learning, and bioinformatic analyses of complex multi-omic data may improve the accuracy of tumor characterization, and if used strategically with caution, may accelerate the implementation of precision medicine. Clinical trials in precision oncology continue to evolve, improving outcomes and expediting the identification of curative strategies for patients with cancer. Despite the existing challenges, significant progress has been made in the past twenty years, demonstrating the benefit of precision oncology in many patients with advanced cancer.

PURPOSE Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing antitumor efficacy. A publicly accessible biomedical literature search engine dedicated to this domain will facilitate knowledge discovery and reduce manual search and review. METHODS We developed RetriLite, an information retrieval and extraction framework that leverages natural language processing and domain-specific knowledgebase to computationally identify highly relevant papers and extract key information. The modular architecture enables RetriLite to benefit from synergizing information retrieval and natural language processing techniques while remaining flexible to customization. We customized the application and created an informatics pipeline that strategically identifies papers that describe efficacy of using combination therapies in clinical or preclinical studies. RESULTS In a small pilot study, RetriLite achieved an F 1 score of 0.93. A more extensive validation experiment was conducted to determine agents that have enhanced antitumor efficacy in vitro or in vivo with poly (ADP-ribose) polymerase inhibitors: 95.9% of the papers determined to be relevant by our application were true positive and the application's feature of distinguishing a clinical paper from a preclinical paper achieved an accuracy of 97.6%. Interobserver assessment was conducted, which resulted in a 100% concordance. The data derived from the informatics pipeline have also been made accessible to the public via a dedicated online search engine with an intuitive user interface. CONCLUSION RetriLite is a framework that can be applied to establish domain-specific information retrieval and extraction systems. The extensive and high-quality metadata tags along with keyword highlighting facilitate information seekers to more effectively and efficiently discover knowledge in the combination therapy domain.

Extreme weather events and severe flash floods during July 2021 caused numerous deaths and massive ecological disasters across Europe. The regionally overstrained environmental and socio-cultural resilience triggered an intensive discussion about cause and effect, responsibilities and public denouncement, and the financial consequences of climate-induced extreme events. In this article we analyze the flood event by four methodological approaches: (1) hermeneutics, with an analog interpretation of printed newspapers and sources; (2) text mining and natural language processing of digital newspaper articles available online; (3) precipitation and discharge models based on instrumental data; and (4) how the findings can be linked to the historical extreme floods of 1804 and 1910, based on documentary source analysis. These four approaches are used to compare and evaluate their consistency by tracking the course, consequences, and aftermaths of the flood disaster. The study shows a high consistency between the analog, digital, and instrumental data analysis. A combination of multidisciplinary methods and their application to historical events enables the evaluation of modern events. It enables to answer the question of return periods and intensities, which are indispensable for today’s risk assessments and their social contextualization, a desideratum in historical and modern climatology.

The present article deals with the reconstruction of drought time series in Germany since 1500. The reconstructions are based on written records from the historical climate and environmental database tambora.org, early and official instrument data as well as precipitation and temperature indices. From the historical descriptions of the weather climatic processes and their effects and consequences for the environment and society, action paths and drought categories are derived. Furthermore, a historical precipitation index (HPI) is calculated and correlated with the SPI index. These are correlated and quantified in a rating scheme with modern rainfall indices and recent drought categories. Finally, a Historical Drought Index (HDI) and a Historical Wet Index (HWI) derived from the hygric indices are presented. On this basis, the long-term development of dryness and drought and significant accumulations and extremes in Germany since 1500 are discussed.

River flooding is among the most destructive of natural hazards globally, causing widespread loss of life, damage to infrastructure and economic deprivation. Societies are currently under increasing threat from such floods, predominantly from increasing exposure of people and assets in flood¿prone areas, but also as a result of changes in flood magnitude, frequency, and timing. Accurate flood hazard and risk assessment are therefore crucial for the sustainable development of societies worldwide. With a paucity of hydrological measurements, evidence from the field offers the only insight into truly extreme events and their variability in space and time. Historical, botanical, and geological archives have increasingly been recognized as valuable sources of extreme flood event information. These different archives are here reviewed with a particular focus on the recording mechanisms of flood information, the historical development of the methodological approaches and the type of information that those archives can provide. These studies provide a wealthy dataset of hundreds of historical and palaeoflood series, whose analysis reveals a noticeable dominance of records in Europe. After describing the diversity of flood information provided by this dataset, we identify how these records have improved and could further improve flood hazard assessments and, thereby, flood management and mitigation plans., This publication is a contribution to the Past Global Changes (PAGES) Floods Working Group. PAGES is supported by the US National Science Foundation and the Swiss Academy of Sciences.

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches. ©2019. American Geophysical Union. All Rights Reserved., Code and data to reproduce the figures of this article are available on GitHub and released on Zenodo (doi:10.5281/zenodo.3165019). Definition of properties and recommendations are summarized here: http://wiki.linked.earth/PaCTS_v1.0 . This work was supported by the National Science Foundation through the EarthCube Program with Grant ICER‐1541029. Feedback solicitation on the standard was facilitated by the Past Global Changes (PAGES) organization. The 2016 workshop on Paleoclimate Data Standards was hosted by the World Data Service for Paleoclimatology (WDS/NOAA‐Paleo), and the participation of international attendees was made possible by a PAGES travel grant. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Tambora.org is a new web-based Collaborative Research Environment (CRE) for Historical Climatology (HC) and Environmental research, already containing several huge data collections from different regions with different cultural background. The integration and sustainable storage of existing data collections, as well as the entry of new data are core features of the system. Additionally, tambora.org provides a growing toolbox for creating, analysing and presenting the data. With many active contributors and everyone being invited to add further datasets, it is continuously growing. Tambora.org enables researchers to collaboratively interpret climate information derived from historical sources. It includes tools to support the complete workflow of transforming the raw source material (typically text) to data useful for climatic analysis and finally the publication of data. It provides a database for original text quotations together with bibliographic references and derived searchable, dated and geo-referenced information on climate and environment. To acknowledge scientific work, tambora.org facilitates the process of assigning citable DOIs (digital object identifier) to data collections by providing the necessary infrastructure and institutional responsibility for quality control.

Stroke, a major cause of significant morbidity and death, has limited therapeutic options. To that end, our goal is to develop novel stroke therapies by exploiting the brain’s own neuroreparative potential. We have discovered that perlecan, a prominent brain extracellular matrix proteoglycan, is proteolyzed into the bioactive protein fragment domain V (DV) after experimental and human ischemic stroke. DV is both neuroprotective and pro-angiogenic. Furthermore, functional outcome can be significantly improved in rodents by administering DV 6-24 hours after experimental transient (distal MCA occlusion) or permanent (photothrombosis) stroke. Here we studied in mechanistic detail whether delayed DV administration (initiated 7 days post-stroke) could increase neurogenesis and improve functional outcome after mouse transient MCA occlusion. Delayed DV administration also served to minimize confounding neuroprotective and angiogenic effects which occur with acute DV therapy. After two doses of DV (post-stroke day 7 and 9), stroked 3-month old male C57BL6 mice had significant functional improvement (rotor rod) compared to vehicle treated stroke controls. Brain immunohistochemistry 21 days after stroke demonstrated that DV treated mice had significantly more cells that were positive for BrdU (a marker of cell division), doublecortin (DCX, a marker for immature neurons), and NeuN (another neuronal marker) in the infarct area. Furthermore, stereotactic brain injection (AP + 0.00, ML - 1.2, DV – 2.5) with alpha 2 integrin (a known neuronal DV receptor) function blocking antibody on post-stroke day 3 inhibited DV’s post-stroke neurogenic effects. These results suggest that delayed DV treatment after experimental stroke increases neurogenesis, increases the number of new neurons that reach stroked brain regions and survive there, and improves functional outcome through an alpha 2 integrin dependent mechanism. Importantly, as we are unaware of any other delayed treatment other than FLAME clinical trial (fluoxetine treatment initiated 5-10 days after stroke) that significantly improves functional outcome after stroke, our data further suggest the promise of DV as an effective stroke therapy.