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UID:DSC-19668
DTSTART;TZID=Europe/Berlin:20230309T100000
SEQUENCE:1678343957
TRANSP:OPAQUE
DTEND;TZID=Europe/Berlin:20230309T110000
URL:https://www.dresden-science-calendar.de/calendar/de/detail/19668
LOCATION:IFW\, Helmholtzstraße 2001069 Dresden
SUMMARY:Jha: Microsensors for Gamete quality assessment and sorting
CLASS:PUBLIC
DESCRIPTION:Speaker: Pallavi Jha\nInstitute of Speaker: IFW Dresden\nTopics
 :\n\n Location:\n  Name: IFW (A1E.10\, Hörsaal\, IFW Dresden)\n  Street: 
 Helmholtzstraße 20\n  City: 01069 Dresden\n  Phone: \n  Fax: \nDescriptio
 n: Infertility is a global problem that affects millions of couples worldw
 ide. According to the World Health Organization (WHO)\, infertility affect
 s approximately 15% of couples in reproductive age [1]. Despite advancemen
 ts in assisted reproductive technologies\, such as in vitro fertilization 
 (IVF)\, the success rate is limited to 5-30% per IVF cycle for women in di
 fferent age groups [2]. The success rate of IVF increases with the number 
 of cycles but repeated failures can take a toll on couples financially and
  emotionally. A significant hurdle in this process is the selection of goo
 d-quality embryos which can lead to successful pregnancies.    Traditional
  embryo quality assessment is done by morphological analysis using optical
  microscopy. This method provides information about the physical character
 istics of the embryo such as the number of cells\, symmetry\, fragmentatio
 n\, and the presence of pronuclei. However\, this technique can be subject
 ive and the physical parameters may not always be sufficient to accurately
  predict embryo quality. In recent years\, the role of AI techniques has b
 een investigated to rank embryos for implantation or predicting the probab
 ility of pregnancies. Some of these studies have shown promising results b
 ut a general consensus on how to interpret or compare these AI evaluations
  is currently missing [3]. Therefore\, research into additional quantitati
 ve parameters such as genetic and metabolic profiling\, mechanical propert
 ies of embryos and the presence of specific biomarkers secreted by embryos
  is necessary to provide additional information on the developmental poten
 tial of the embryo.  Impedimetric detection enables non-invasive\, label-f
 ree and rapid analysis. The use of 3D tubular electrodes is motivated base
 d on studies that have shown them to have higher sensitivity in comparison
  to planar electrodes [4]. The tubular cross-section of the 3D tubular ele
 ctrodes also creates a better microenvironment by mimicking physiological 
 topographical constraints [5]. The optical transparency of these electrode
 s makes them suitable for dual optical and impedance tomography\, for morp
 hological and functional characterization of the embryos. The ability to s
 elect high-quality embryos is critical for improving pregnancy rates and r
 educing the incidence of multiple pregnancies. Additionally\, this method 
 could offer an alternative to preimplantation genetic testing which is use
 d in some IVF labs to identify genetic disorders\, before embryo transfer 
 [6]. Overall\, the goal of this work is to contribute in improving the imp
 lantation rates of embryos produced in vitro leading to high pregnancy out
 comes for couples struggling with infertility.  [1] World Health Organizat
 ion. (n.d.). Infertility. World Health Organization. Retrieved February 27
 \, 2023\, from https://www.who.int/health-topics/infertility  [2] NHS. (20
 21\, October 18). IVF Overview. NHS. Retrieved February 27\, 2023\, from h
 ttps://www.nhs.uk/conditions/ivf  [3] Kragh\, M. F.\, &amp\;amp\; Karstoft
 \, H. (2021). Embryo selection with Artificial Intelligence: How to evalua
 te and compare methods? Journal of Assisted Reproduction and Genetics\, 38
 (7)\, 1675–1689.  [4] Medina-Sánchez\, M.\, Ibarlucea\, B.\, Pérez\, N.
 \, Karnaushenko\, D. D.\, Weiz\, S. M.\, Baraban\, L.\, Cuniberti\, G.\, &
 amp\;amp\; Schmidt\, O. G. (2016). High-performance three-dimensional tubu
 lar nanomembrane sensor for DNA detection. Nano Letters\, 16(7)\, 4288–42
 96.  [5] Weiz\, S. M.\, Medina-Sánchez\, M.\, &amp\;amp\; Schmidt\, O. G.
  (2017). Microsystems for single-cell analysis. Advanced Biosystems\, 2(2)
 \, 1700193.  [6] De Rycke\, M.\, &amp\;amp\; Verdyck\, P. (2020). Preimpla
 ntation Genetic Testing for monogenic disorders. Preimplantation Genetic T
 esting\, 77–86.
DTSTAMP:20260701T003050Z
CREATED:20230301T063919Z
LAST-MODIFIED:20230309T063917Z
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