رسالة جامعية

C. elegans based strategy for high-throughput early cancer detection through urine analysis

التفاصيل البيبلوغرافية
العنوان: C. elegans based strategy for high-throughput early cancer detection through urine analysis
المؤلفون: LANZA, ENRICO
المساهمون: A. Ganesan, Silvia Campello, Lanza, Enrico, FOLLI, VIOLA, RUOCCO, Giancarlo, TRIPODI, Marco
بيانات النشر: Università degli Studi di Roma "La Sapienza"
سنة النشر: 2020
المجموعة: Sapienza Università di Roma: CINECA IRIS
مصطلحات موضوعية: C. elegan, breast cancer, chemosensation
الوصف: In this work, we built an optical setup and defined experimental protocols to assess responses of C. elegans neurons expressing calcium indicators while exposing them to timely controlled stimuli. We then applied this setup to assess the accuracy of C. elegans in discriminating between a group of women affected by breast cancer and a group of healthy donors. To do this we first ran a series of preliminary tests that defined the experimental parameters and protocols to run high-throughput experiments and then tested the response of the AWC neurons to the removal of urine samples collected from both groups. The results obtained prove the impressive accuracy of the AWC neuron to respond with activation upon removal of samples collected from patients affected by breast cancer of both lobular and ductal forms, at different stages. This ability can be quantified by a variable that measures the activation rate of the neuron in response to the stimulus, the neuronal activation index, or NAI. The accuracy associated with the NAI is of 97.22%, which stays the same also when considered in conjunction with the chemotaxis index, CI, through the linear combination defined by the first component of a PCA applied to the plane(NAI, CI).
نوع الوثيقة: doctoral or postdoctoral thesis
اللغة: English
العلاقة: alleditors:A. Ganesan; Silvia Campello; http://hdl.handle.net/11573/1341528Test
الإتاحة: http://hdl.handle.net/11573/1341528Test
حقوق: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.33025870
قاعدة البيانات: BASE