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10.1242/bio.059111 http://scihub22266oqcxt.onion/10.1242/bio.059111 35502829!9096705!35502829     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biol+Open 2022 ; 11 (4): ä Nephropedia Template TP {{tp|p=35502829|t=2022. Bees can be trained to identify SARS-CoV-2 infected samples |pdf=|usr=}}{{35502829}} gab.com Text Bees can be trained to identify SARS-CoV-2 infected samples JO: Biol Open http://www.kidney.de/pget.php?&tw=1&pmid=35502829 #FOAvip The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the volatile organic compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected minks (Neovison vison) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink's odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject's health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods. Twit Text FOAVip Bees can be trained to identify SARS-CoV-2 infected samples ????Biol Open http://www.kidney.de/pget.php?&tw=1&pmid=35502829 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35502829 #FOAvip English Wikipedia <ref>{{Cite pmid|35502829}}</ref> Bees can be trained to identify SARS-CoV-2 infected samples #MMPMID35502829 Kontos E; Samimi A; Hakze-van der Honing RW; Priem J; Avargues-Weber A; Haverkamp A; Dicke M; Gonzales JL; van der Poel WHM Biol Open 2022[Apr]; 11 (4): ä PMID35502829show ga The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the volatile organic compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected minks (Neovison vison) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink's odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject's health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods. |*COVID-19/diagnosis[MESH] |*SARS-CoV-2[MESH] |Animals[MESH] |Bees[MESH] |Humans[MESH] |Learning[MESH] |Odorants[MESH]Bees can be trained to identify SARS-CoV-2 infected samples (epmc).pdf DeepDyve Pubget Overpricing