Development and clinical application of a preimplantation genetic testing for monogenic disease (PGT-M) for beta thalassemia in Vietnam.

PURPOSE: The purpose of this research is to study the clinical outcomes using a next-generation sequencing-based protocol allowing for simultaneous testing of mutations in the beta thalassemia (HBB) gene, including single nucleotide polymorphism (SNP) markers for PGT-M along with low-pass whole genome analysis of chromosome aneuploidies for PGT-A. METHODS: A combined PGT-M (thalassemia) plus PGT-A system was developed for patients undergoing IVF in Vietnam. Here we developed a system for testing numerous thalassemia mutations plus SNP-based testing for backup mutation analysis and contamination control using next-generation sequencing (NGS). Low -pass next-generation sequencing was used to assess aneuploidy in some of the clinical PGT cases. Patients underwent IVF followed by embryo biopsy at the blastocyst stage for combined PGT-A/M. RESULTS: Two cases have completed the entire process including transfer of embryos, while a further nine cases have completed the IVF and PGT-M/A analysis but have not completed embryo transfer. In the two cases with embryo transfer, both patients achieved pregnancy with an unaffected, euploid embryo confirmed through prenatal diagnosis. In the further nine cases, 39 embryos were biopsied and all passed QC for amplification. There were 8 unaffected embryos, 31 carrier embryos, and 11 affected embryos. A subset of 24 embryos also had PGT-A analysis with 22 euploid embryos and 2 aneuploid embryos. CONCLUSIONS: Here we report the development and clinical application of a combined PGT-M for HBB and PGT-A for gross chromosome aneuploidies from 11 patients with detailed laboratory findings along with 2 cases that have completed embryo transfer.

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing-Part II: Emerging Technologies and Open Issues.

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs.