Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

Background:There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually.Methods:In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data.Results:We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap.Conclusions:Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the inter-active knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases

Matching anticancer compounds and tumor cell lines by neural networks with ranking loss

Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug’s inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model’s capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data

Newly Diagnosed IDH-Wildtype Glioblastoma and Temporal Muscle Thickness: A Multicenter Analysis

Background: Reduced temporal muscle thickness (TMT) has been discussed as a prognostic marker in IDH-wildtype glioblastoma. This retrospective multicenter study was designed to investigate whether TMT is an independent prognostic marker in newly diagnosed glioblastoma. Methods: TMT was retrospectively measured in 335 patients with newly diagnosed glioblastoma between 1 January 2014 and 31 December 2019 at the University Hospitals of Leipzig and Rostock. The cohort was dichotomized by TMT and tested for association with overall survival (OS) after 12 months by multivariate proportional hazard calculation. Results: TMT of 7.0 mm or more was associated with increased OS (46.3 ± 3.9% versus 36.6 ± 3.9%, p > 0.001). However, the sub-groups showed significant epidemiological differences. In multivariate proportional hazard calculation, patient age (HR 1.01; p = 0.004), MGMT promoter status (HR 0.76; p = 0.002), EOR (HR 0.61), adjuvant irradiation (HR 0.24) and adjuvant chemotherapy (HR 0.40; all p < 0.001) were independent prognostic markers for OS. However, KPS (HR 1.00, p = 0.31), BMI (HR 0.98, p = 0.11) and TMT (HR 1.06; p = 0.07) were not significantly associated with OS. Conclusion: TMT has not appeared as a statistically independent prognostic marker in this cohort of patients with newly diagnosed IDH-wildtype glioblastoma

Evaluating grazing response strategies in winter annuals : A multi-trait approach

Plants minimize fitness losses through grazing by three fundamental strategies: tolerance, avoidance and escape. Annual species have been traditionally assumed to escape grazing through their short life cycle and seed dormancy; however, their grazing response strategies remain almost unexplored. How traits and their coordination affect species' grazing responses, and whether the generalized grazing model, which posits convergent filtering by grazing and drought, is applicable to this ecologically and economically important species group thus remain unclear. We used a trait-based approach to evaluate grazing response strategies of winter annuals from the Middle East. Across 23 species, we examined the coordination of 16 traits hypothesized to be relevant for grazing responses, and linked them to species' fecundity responses, as proxy for fitness responses, to simulated grazing in controlled conditions, to species' abundance responses to grazing in the field and to species' distribution along a large-scale rainfall gradient. Winter annuals exhibited both grazing escape and to a lesser extent tolerance indicated by (a) independent coordination of escape and tolerance traits, and (b) maintenance of higher fecundity in species with more pronounced escape or tolerance traits under simulated grazing. In the natural habitat, species with a more pronounced escape but not tolerance strategy maintained higher abundance under grazing in dry habitats, indicating convergent favouring of escape by both grazing and drought. However, this finding at the local scale was not mirrored by a strategy shift along a large-scale rainfall gradient. Synthesis. The convergent favouring of escape traits by grazing and drought in annuals is consistent with the generalized grazing model. This model, which has been developed for perennials based on the avoidance strategy, can thus be extended to annuals based on escape, a finding that should facilitate projecting consequences of global change in drylands dominated by annuals. © 2021 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Societ

Putting learning back into learning analytics: actions for policy makers, researchers, and practitioners

This paper is based on (a) a literature review focussing on the impact of learning analytics on supporting learning and teaching, (b) a Delphi study involving international expert discussion on current opportunities and challenges of learning analytics as well as (c) outlining a research agenda for closing identified research gaps. Issues and challenges facing educators linked to learning analytics and current research gaps were organised into four themes, the further development of which by the expert panel, led to six strategy and action areas. The four themes are 1. development of data literacy in all stakeholders, 2. updating of guiding principles and policies of educational data, 3. standards needed for ethical practices with data quality assurance, and 4. flexible user-centred design for a variety of users of analytics, starting with learners and ensuring that learners and learning is not harmed. The strategies and actions are outcomes of the expert panel discussion and are offered as provocations to organise and focus the researcher, policymaker and practitioner dialogs needed to make progress in the field

Ecological restoration across the Mediterranean Basin as viewed by practitioners

Restoration efforts in the Mediterranean Basin have been changing from a silvicultural to an ecological restoration approach. Yet, to what extent the projects are guided by ecological restoration principles remains largely unknown. To analyse this issue, we built an on-line survey addressed to restoration practitioners. We analysed 36 restoration projects, mostly from drylands (86%). The projects used mainly soil from local sources. The need to comply with legislation was more important as a restoration motive for European Union (EU) than for non-EU countries, while public opinion and health had a greater importance in the latter. Non-EU countries relied more on non-native plant species than EU countries, thus deviating from ecological restoration guidelines. Nursery-grown plants used were mostly of local or regional provenance, whilst seeds were mostly of national provenance. Unexpected restoration results (e.g. inadequate biodiversity) were reported for 50% of the projects and restoration success was never evaluated in 22%. Long term evaluation (> 6 years) was only performed in 31% of cases, and based primarily on plant diversity and cover. The use of non-native species and species of exogenous provenances may: i) entail the loss of local genetic and functional trait diversity, critical to cope with drought, particularly under the predicted climate change scenarios, and ii) lead to unexpected competition with native species and/or negatively impact local biotic interactions. Absent or inappropriate monitoring may prevent the understanding of restoration trajectories, precluding adaptive management strategies, often crucial to create functional ecosystems able to provide ecosystem services. The overview of ecological restoration projects in the Mediterranean Basin revealed high variability among practices and highlighted the need for improved scientific assistance and information exchange, greater use of native species of local provenance, and more long-term monitoring and evaluation, including functional and ecosystem services' indicators, to improve and spread the practice of ecological restoration

Does the exotic equal pollution? Landscape methods for solving the dilemma of using native versus non‐native plant species in drylands

There is a need to resolve methods to determine the merits of native versus nonnative plant use in drylands and indeed in more temperate areas around the world. This is because whilst plant introductions may have positive objectives, they can have significant negative landscape and environmental impacts. A key discussion on this issue focuses on whether the use of non-native plant species can be considered to be pollution and pollutive based on the concept that pollution can be regarded as ‘matter out of place’. The consequences of putting the wrong plant species in the wrong place can be extremely detrimental to the landscape character, quality and value of the land, let alone the effects on ecosystem structure and functioning as well as on biodiversity. These effects can also affect human communities who may rely on the landscape, for example, for tourism. It is thus necessary that the discussion on how decisions are made in determining plant choice evolves so that the right decisions are made when planting is necessary, for the land, for nature and for the people. This discussion has been initiated through COST Action ES1104, which focused on the restoration of degraded dry and arid lands. This article discusses a number of landscape methods based on sustainability principles to determine when and where native and non-native plants could and should be used.info:eu-repo/semantics/publishedVersio

Thematic Working Group 5: Formative assessment supported by technology.

The future of assessment faces major challenges including the use of IT to facilitate formative assessment that is important for improving learners’ development, motivation and engagement in learning. In many countries, in recent years, a renewed focus on assessments to support learning has been pushing against the burgeoning of testing for accountability, which in some countries, renders effective formative assessment practices almost impossible. Moreover, a systematic review by Harlen and Deakin Crick (2002) revealed that a strong focus on summative assessment for accountability can reduce motivation and disengage many learners. At the same time use of IT‐enabled assessments has been increasing rapidly, as they offer promise of cheaper ways of delivering and marking assessments as well as access to vast amounts of assessment data from which a wide range of judgements might be made about students, teachers, schools and education systems (Gibson & Webb, 2015). These opportunities also extend to assessment of complex collaborative work (Webb & Gibson, 2015). Current opportunities for using IT, including for harnessing the data that is being collected automatically, for formative assessment are underexplored and less well understood than those for summative assessments. Opportunities for learning with IT and perhaps with less teacher input are increasing but this depends on students developing as autonomous or independent learners. Research in formative assessment including effective feedback has emphasised the value of peer assessment practices for developing self‐assessment capabilities and hence independent learners (Black, Harrison, Lee, Marshall, & William, 2003). At previous EDUsummITs the possibilities and challenges for IT‐enabled assessments to support simultaneously both formative and summative purposes were analysed (Webb, Gibson, & Forkosh‐Baruch, 2013). While these challenges remain, at EDUsummIT 2017 we focused on the opportunities and challenges of IT supporting formative assessment because effective formative assessment is known to be extremely important for learning.RETHINKING LEARNING IN A DIGITAL AGE, EDUsummIT 2017 Summary Reports 18-20 september, Bulgari

VIP Regulates the Development & Proliferation of Treg in vivo in spleen

<p>Abstract</p> <p>Background</p> <p>Mounting evidence supports a key role for VIP as an anti-inflammatory agent and promoter of immune tolerance. It suppresses TNF-α and other inflammatory cytokines and chemokines, upregulates anti-inflammatory IL-10, and promotes immune tolerant cells called T regulatory (Treg) cells. VIP KO mice have recently been demonstrated to have spontaneous airway and pulmonary perivascular inflammatory responses, as part of asthma-like and pulmonary hypertension phenotypes, respectively. Both inflammatory responses are correctable with VIP. Focusing on this model, we have now investigated the influence of VIP not only on inflammatory cells but also on Treg cells.</p> <p>Methods</p> <p>Using flow cytometric analysis, we examined the relative preponderance of CD25+CD4+ cells and anti-inflammatory Treg cells, in extracts of thymus and spleen from VIP KO mice (5 VIP KO; 5 VIP KO+ VIP; 10 wild-type). This method allowed antibody-based flow cytometric identification of Treg cells using surface markers CD25 and CD4, along with the: 1) intracellular activation marker FoxP3; and 2) Helios, which distinguishes cells of thymic versus splenic derivation.</p> <p>Conclusions</p> <p>Deletion of the VIP gene results in: 1) CD25+CD4- cell accumulation in the thymus, which is corrected by VIP treatment; 2) more Treg in thymus lacking Foxp3 expression, suggesting VIP is necessary for immune tolerance; and, 3) a tendency towards deficiency of Treg cells in the spleen, which is normalized by VIP treatment. Treg lacking Helios are induced by VIP intrasplenically rather than by migration from the thymus. These results confirm the dual role of VIP as an anti-inflammatory and immune tolerance-promoting agent.</p