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13. Religion in Anthropocene and Digital Culture : symposium2023, other monographs and other completed works Abstract: The primary goal of the symposium is to analyse and establish links between theological and ethical perspectives on the environment, on the one hand, and digital technologies, on the other.
The starting point is the increasing intertwinement of natural and digital environments for contemporary and future life on our planet. The development and increasing use of advanced digital technologies and artificial intelligence raise several challenging ethical questions. Understanding these challenges and formulating theologically reflective responses to them are important aspects of digital theology, as defined by Peter Phillips, Kyle Schiefelbein-Guerrero and John Kurlberg (2019).
Digital culture is the context within which we increasingly do theology, thus, digital theology impacts both theology as a discipline and digital culture within which we live.
This symposium draws upon, contributes to, and brings together the fields of theology, philosophy, sociology of religion, anthropology of religion, philosophy of technology, and digital humanities. More precisely it brings together methodologies and epistemologies from Creation theology, eco-theology, eco-feminism, theological anthropology, philosophical theology, post-metaphysical philosophy of religion, digital philosophy and cosmotheology, philosophy and ethics of AI, and human-machine relationships. It also addresses questions raised by digital theology through the lenses of the alternative theologies of pantheism, panentheism and panpsychism. Published in DiRROS: 11.07.2023; Views: 416; Downloads: 179 Full text (1000,27 KB) This document has many files! More... |
14. Robust saliva-based RNA extraction-free one-step nucleic acid amplification test for mass SARS-CoV-2 monitoringEva Rajh, Tina Šket, Arne Praznik, Petra Sušjan, Alenka Šmid, Dunja Urbančič, Irena Mlinarič-Raščan, Polona Kogovšek, Tina Demšar, Mojca Milavec, Katarina Prosenc, Žiga Jensterle, Mihaela Zidarn, Viktorija Tomič, Gabriele Turel, Tatjana Lejko-Zupanc, Roman Jerala, Mojca Benčina, 2021, original scientific article Abstract: Early diagnosis with rapid detection of the virus plays a key role in preventing the spread of infection and in treating patients effectively. In order to address the need for a straightforward detection of SARS-CoV-2 infection and assessment of viral spread, we developed rapid, sensitive, extraction-free one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and reverse transcription loop-mediated isothermal amplification (RT-LAMP) tests for detecting SARS-CoV-2 in saliva. We analyzed over 700 matched pairs of saliva and nasopharyngeal swab (NSB) specimens from asymptomatic and symptomatic individuals. Saliva, as either an oral cavity swab or passive drool, was collected in an RNA stabilization buffer. The stabilized saliva specimens were heat-treated and directly analyzed without RNA extraction. The diagnostic sensitivity of saliva-based RT-qPCR was at least 95% in individuals with subclinical infection and outperformed RT-LAMP, which had at least 70% sensitivity when compared to NSBs analyzed with a clinical RT-qPCR test. The diagnostic sensitivity for passive drool saliva was higher than that of oral cavity swab specimens (95% and 87%, respectively). A rapid, sensitive one-step extraction-free RT-qPCR test for detecting SARS-CoV-2 in passive drool saliva is operationally simple and can be easily implemented using existing testing sites, thus allowing high-throughput, rapid, and repeated testing of large populations. Furthermore, saliva testing is adequate to detect individuals in an asymptomatic screening program and can help improve voluntary screening compliance for those individuals averse to various forms of nasal collections. Keywords: SARS-CoV-2, COVID-19, COVID-19 serological testing, real-time polymerase chain reaction, saliva, oral cavity swab, passive drool, pooling Published in DiRROS: 09.11.2021; Views: 1090; Downloads: 546 Link to full text |
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