27 research outputs found
AI Model for Predicting Anti-PD1 Response in Melanoma Using Multi-Omics Biomarkers
No full textBackground: Immune checkpoint inhibitors (ICIs) have demonstrated significantly improved clinical efficacy in a minority of patients with advanced melanoma, whereas non-responders potentially suffer from severe side effects and delays in other treatment options. Predicting the response to anti-PD1 treatment in melanoma remains a challenge because the current FDA-approved gold standard, the nonsynonymous tumor mutation burden (nsTMB), offers limited accuracy. Methods: In this study, we developed a multi-omics-based machine learning model that integrates genomic and transcriptomic biomarkers to predict the response to anti-PD1 treatment in patients with advanced melanoma. We employed least absolute shrinkage and selection operator (LASSO) regression with 49 biomarkers extracted from tumor–normal whole-exome and RNA sequencing as input features. The performance of the multi-omics AI model was thoroughly compared to that of nsTMB alone and to models that use only genomic or transcriptomic biomarkers. Results: We used publicly available DNA and RNA-seq datasets of melanoma patients for the training and validation of our model, forming a meta-cohort of 449 patients for which the outcome was recorded as a RECIST score. The model substantially improved the prediction of anti-PD1 outcomes compared to nsTMB alone, with an ROC AUC of 0.7 in the training set and an ROC AUC of 0.64 in the test set. Using SHAP values, we demonstrated the explainability of the model’s predictions on a per-sample basis. Conclusions: We demonstrated that models using only RNA-seq or multi-omics biomarkers outperformed nsTMB in predicting the response of melanoma patients to ICI. Furthermore, our machine learning approach improves clinical usability by providing explanations of its predictions on a per-patient basis. Our findings underscore the utility of multi-omics data for selecting patients for treatment with anti-PD1 drugs. However, to train clinical-grade AI models for routine applications, prospective studies collecting larger melanoma cohorts with consistent application of exome and RNA sequencing are required
Accelerated photochemical reactions at oil-water interface exploiting melting point depression
No full textWater can accelerate a variety of organic reactions far beyond the rates observed in classical organic solvents. However, using pure water as a solvent introduces solubility constraints that have limited the applicability of efficient photochemistry in particular. We report here the formation of aggregates between pairs of arenes, heteroarenes, enamines, or esters with different electron affinities in an aqueous medium, leading to an oil-water phase boundary through substrate melting point depression. The active hydrogen atoms in the reactants engage in hydrogen bonds with water, thereby accelerating photochemical reactions. This methodology realizes appealingly simple conditions for aqueous coupling reactions of complex solid molecules, including complex drug molecules that are poorly soluble in water
Distinct ADAM metalloproteinases regulate G protein-coupled receptor-induced cell proliferation and survival
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Biallelic MAD2L1BP (p31comet) mutation is associated with mosaic aneuploidy and juvenile granulosa cell tumors
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Characterization for high dynamic range imaging
No full textIn this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device-dependent signals, such as digital camera RAW images, into a well-defined color space. This is a well-understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments
Regional Patterns of Late Medieval and Early Modern European Building Activity Revealed by Felling Dates
No full textFredrik Charpentier Ljungqvist, Andrea Seim, Willy Tegel, Paul J. Krusic, Claudia Baittinger, Christelle Belingard, Mauro Bernabei, Niels Bonde, Paul Borghaerts, Yann Couturier, Anne Crone, Sjoerd van Daalen, Aoife Daly, Petra Doeve, Marta Domínguez-Delmás, Jean-Louis Edouard, Thomas Frank, Christian Ginzler, Michael Grabner, Friederike M. Gschwind, Kristof Haneca, Anton Hansson, Franz Herzig, Karl-Uwe Heussner, Jutta Hofmann, David Houbrechts, Ryszard Jerzy Kaczka, Tomáš Kolář, Raymond Kontic, Tomáš Kyncl, Vincent Labbas, Per Lagerås, Yannick Le Digol, Melaine Le Roy, Hanns Hubert Leuschner, Hans Linderson, Francis Ludlow, Axel Marais, Coralie M. Mills, Mechthild Neyses-Eiden, Kurt Nicolussi, Christophe Perrault, Klaus Pfeifer, Michal Rybníček, Andreas Rzepecki, Martin Schmidhalter, Mathias Seifert, Lisa Shindo, Barbara Spyt, Josué Susperregi, Helene Løvstrand Svarva, Terje Thun, Felix Walder, Tomasz Ważny, Elise Werthe, Thorsten Westphal, Rob Wilson, Ulf BüntgenAlthough variations in building activity are a useful indicator of societal well-being and demographic development, historical datasets for larger regions and longer periods are still rare. Here, we present 54,045 annually precise dendrochronological felling dates from historical construction timber from across most of Europe between 1250 and 1699 CE to infer variations in building activity. We use geostatistical techniques to compare spatiotemporal dynamics in past European building activity against independent demographic, economic, social and climatic data. We show that the felling dates capture major geographical patterns of demographic trends, especially in regions with dense data coverage. A particularly strong negative association is found between grain prices and the number of felling dates. In addition, a significant positive association is found between the number of felling dates and mining activity. These strong associations, with well-known macro-economic indicators from pre-industrial Europe, corroborate the use of felling dates as an independent source for exploring large-scale fluctuations of societal well-being and demographic development. Three prominent examples are the building boom in the Hanseatic League region of northeastern Germany during the 13th century, the onset of the Late Medieval Crisis in much of Europe c. 1300, and the cessation of building activity in large parts of central Europe during armed conflicts such as the Thirty Years’ War (1618–1648 CE). Despite new insights gained from our European-wide felling date inventory, further studies are needed to investigate changes in construction activity of high versus low status buildings, and of urban versus rural buildings, and to compare those results with a variety of historical documentary sources and natural proxy archives
The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases
No full textThe SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article
