Adoption of artificial intelligence in precision matching of donor sperm during assisted reproduction process (Preprint)

UNSTRUCTURED An artificial intelligence (AI) based sperm donor humanized matching system was launched to meet infertile patients' requirements on personalized physical appearance of the expected sperm donor such as blood type, origin, ethnicity, height, weight, body build, skin color, hair, face shape, nose bridge, eyelids, iris color, lips, etc. Relying on high-speed 5G networks, the AI matching information in an encoded pattern is fed back to patients in real time and ranked according to similarity. To date, the highest similarity is up to 96%. This system can provide high efficiency and accuracy and avoid the drawbacks of previous manual operations which were tedious, slow and error-prone. In addition, the system helps patients carrying genetic mutations (including thalassemia, spinal muscular atrophy) avoid off-springs’ genetic diseases by matching donors who are qualified by further genetic testing. This system sets a good example of the smart medical market which can also play an important role in addressing patients' personalized medical requirements in addition to aiding in the diagnosis and treatment of diseases.

Co-designing genomics research with a large group of donor-conceived siblings

Background Human genomics research is growing rapidly. More effective methods are required for co-design and involving people, especially those sub-populations which are inherently high interest to medical research and thus at greater risk of being exploited. This case study documents how we worked with a large group of donor-conceived siblings who share the same sperm donor father, to explore how they might want to engage with and influence any future genomic research. Method A participatory action research process was used to explore the views of a group of 18 people who knew they are donor-conceived siblings. They are part of a larger group of up to 1000 people who share the same sperm donor father but the only ones in contact with each other; it is likely that many of the uncontacted siblings are unaware of their biological father, have been unable to trace others or have died. The discussion explored views about how the group would like to be involved in future research. Five members participated in co-design; 12 completed a pre-discussion online survey; and six participated in an online discussion forum and evaluation survey. The online discussion was led by one facilitator, supported by the study team. Results Of the 18 siblings approached in 2018, 14 participated in the co-design stages or the surveys and online discussion. Co-design informed the research process. Participants reported enjoying the overall experience of the surveys and discussion forum, which were perceived as inclusive and flexible. Most participants’ views regarding the value of involvement in research changed during the process, and ‘widened’ about who should be involved. Participants were supportive of future research being done with the siblings group. All who completed the final survey requested to remain part of the co-design process. Other themes in the online discussion included concerns about conflicting interests and a desire for research participation to improve the situation for people affected by assisted conception. The process informed later discussions in the sibling group about participating in a self-managed biobank and informed decision making about participating in genomics research. Conclusion Findings from this study help inform ways in which people from certain sub-populations can be involved in planning and defining their participation in genomic research, particularly those that are inherently high interest to medical research and thus at greater risk of exploitation. This process provides a replicable method of involving potential participants in co-designing genomics research using online discussions, with positive outcomes. Reporting this study using ‘Standardised data on initiatives (STARDIT)’ to report the process allows comparison with other studies.

A Slap in the Face of Socialist Taste: The Novel "Nikolai Nikolaevich" by Yuz Aleshkovsky As a Contestation of the Rules of Socialist Realism

Yuz Aleshkovsky wrote the novel „Nikolai Nikolaevich” in the 1970s. For a long time, the work was disseminated in samizdat and it appeared in print for the first time only in 1980. Composed under the censorship conditions of socialist realism dominant in the arts, this work violates strict taboos imposed on subjects related to sexuality and stylistic solutions which exclude sub-normative vocabulary. In many aspects, the composition of the novel resembles the pattern of the production novel. At the same time, the writer negate the values propagated in the art of socialist realism: the main character is a former pickpocket, who built a comfortable life for himself as a sperm donor in a laboratory and talks about his professional achievements in a language saturated with profanity and elements of criminal jargon. The plot of the work is based on an amalgamation of components characteristic of ideologized literary texts with elements that were unacceptable in such texts. The introduction into the novel of the theme of corporality, and human sexuality, which was a taboo topic in socialist realist literature, introduces a major dissonance and induces produces a comic effect.

Adoption of artificial intelligence in precision matching of donor sperm during assisted reproduction process (Preprint)

UNSTRUCTURED An artificial intelligence (AI) based sperm donor humanized matching system was launched to meet infertile patients' requirements on personalized physical appearance of the expected sperm donor such as blood type, origin, ethnicity, height, weight, body build, skin color, hair, face shape, nose bridge, eyelids, iris color, lips, etc. Relying on high-speed 5G networks, the AI matching information in an encoded pattern is fed back to patients in real time and ranked according to similarity. To date, the highest similarity is up to 96%. This system can provide high efficiency and accuracy and avoid the drawbacks of previous manual operations which were tedious, slow and error-prone. In addition, the system helps patients carrying genetic mutations (including thalassemia, spinal muscular atrophy) avoid off-springs’ genetic diseases by matching donors who are qualified by further genetic testing. This system sets a good example of the smart medical market which can also play an important role in addressing patients' personalized medical requirements in addition to aiding in the diagnosis and treatment of diseases.