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Record W4317775963 · doi:10.1097/rd9.0000000000000060

Executive Editor-in-Chief’s introduction for This Special Issue

2023· article· en· W4317775963 on OpenAlexaboutno aff
Hefeng Huang

Bibliographic record

VenueReproductive and Developmental Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsChinaVice presidentLibrary scienceChristian ministryPolitical scienceExecutive directorManagementMedicineMedical educationLaw

Abstract

fetched live from OpenAlex

Prof. He-Feng Huang is an Academician of the Chinese Academy of Sciences; Fellow Honoris Causa of Royal College of Obstetricians and Gynecologists; Academician of the Third World Academy of Sciences; member of the Chinese Academy of Medical Sciences, and Director of the Institute of Reproduction and Development of Fudan University. Chair Professor, Doctoral supervisor, Chief physician at Fudan University, Shanghai Jiao Tong University and Zhejiang University, Visiting Professor at Hong Kong University and University of Adelaide, Australia. The chief scientist of the National 973 Program, National “Twelfth Five-Year” Plan for Science & Technology Support Project, National 863 Program, International Cooperation Project of China and Canada NSFC and CIHR, National Key Research and Development Program of China. Director of the Key Laboratory of Reproductive Genetics, Ministry of Education and Shanghai Key Laboratory of Embryo Original Diseases. Vice president of Chinese Maternal and Child Health Association, Vice president of Chinese Association for Improving Birth Outcome and Child Development; Founding Board Director of International Society of Reproductive Genetics. Editor for RBMO, JOVR, etc. By now she has published over 300 peer-reviewed papers, including Nature, Nature Medicine and PNAS.He-Feng HuangAs an Executive Editor-in-Chief, I have edited this Special Issue (SI), entitled “Preimplantation genetic testing (PGT)” published in the journal of Reproductive and Developmental Medicine (RDM; ISSN:2096-2924, CN:10-1442/R), the first-ever English journal in the field of reproductive medicine and developmental biology in mainland China. Since its launch in 2017, the RDM has been dedicated to providing a good platform for academic exchanges among scientists, both domestically and abroad. Having healthy birth could be challenging for some people in several critical conditions. Aneuploidy is well known to be one of the driving causes of miscarriage. Additionally, the risk of spontaneous abortion significantly increases in women with advanced age and cytogenetic abnormality, such as translocations. Last but not least, although monogenic diseases, caused by single nucleotide variants and indels and genomic diseases caused by duplications and deletions, may not cause miscarriage, they considerably impact offspring’s health. Improving the success rate of the reproductive process and blocking transmission of monogenic diseases are essential. Therefore, PGT, which comprises a group of state-of-the-art detection methods, was introduced in the human reproductive field to help people have healthy babies, and plays important role in assisted reproductive technologies (ART). PGT has first been practiced more than 30 years ago and conventionally called preimplantation genetic diagnosis (PGD) and screening (PGS). It is used to examine the deoxyribonucleic acid from polar bodies or embryos for detecting aneuploidy (PGT-A), monogenic/single-gene defects (PGT-M), or chromosomal structural rearrangements (PGT-SR). PGT-A is the definitive tool for embryo selection based on assessment of euploidy and genomic alterations; PGT-SR can effectively rule out abnormal chromosomal structures to reduce miscarriage risk. PGT-A and PGT-SR are able to improve pregnancy, implantation, and live birth rates in patients facing fertility challenges. PGT-M is generally used to prevent transmission of monogenic diseases from couples to their newborns and purposefully decrease the rate of birth defects and other diseases that may markedly impact quality of life. The articles published in this SI should provide readers with an immediate recognition of how physicians practice PGT in clinics, quality controls (QC)/guidelines at the bedside and benchside, and the dramatic development of PGT with the advent of new detection and evaluation techniques. Good practice of PGT is essential for regulation and standardization of screening methods and diagnosis. The European Society of Human Reproduction and Embryology issued recommendations in 2020 on this good practice. Since the PGT field is rapidly evolving, updated guidelines are necessary. The International Society of Reproductive Genetics (ISRG) is an organization dedicated to advancing knowledge of reproductive genetics, founded by internationally renowned clinicians and scientists in the ART field. The first article includes a number of guidelines provided by a workgroup assembled by the ISRG for embryologists, medical geneticists, clinical laboratory technicians, and other healthcare providers to improve the well-being of patients seeking ART treatment for having healthy newborns. Prof. Huang from the Obstetrics and Gynecology Hospital of Fudan University, China; Prof. Qiao from the Peking University Third Hospital, China; and Prof. Handyside from the University of Kent, UK led the workgroup. These guidelines were developed based on published literature and the latest findings of PGT research. This included primarily three parts from benchside to bedside: clinical procedures and QC of PGT, micromanipulation and QC in embryo lab, and genetic testing and QC in genetic lab, and an additional part of prospects of PGT. In addition to QC content in every section, the first part mainly elaborated on indications and contraindications for PGTs. The second part described biopsy details. Moreover, the third part elucidated testing strategies and methods for PGTs. Finally, the working group briefly mentioned progress in the PGT field, such as noninvasive PGT (niPGT), polygenic PGT (PGT-P), and comprehensive PGT. These guidelines are sourced from the most updated data and currently available clinical options, providing suggestions for future studies, and reliable recommendations for PGT practices. Although not the first introduced as a type of PGT, PGT-A is currently the most studied among other PGTs. Many aspects of PGT-A have been assessed. However, Prof. Sun and his colleagues found that no well-powered retrospective study has compared the obstetric and perinatal outcomes of patients with repeated implantation failure (RIF) with and without PGT-A. The research recruited 466 patients with RIF, of which 209 were in the RIF-PGT-A group, and the others were allocated to the RIF-non-PGT-A group. The samples in this study underwent trophectoderm biopsy, single nucleotide polymorphism microarray testing, and next-generation sequencing. Significantly higher rates of positive serum human chorionic gonadotropin (56.9% vs 33.9%), clinical pregnancy (49.5% vs 31.2%), live birth (43.1% vs 25.7%), and fetal heart rates (50.0% vs 29.8%) were observed in the RIF-PGT-A group compared with the RIF-non-PGT-A group. These results remained unchanged after propensity score matching, which eliminated differences in age, number of transferred embryos, and transfer cycles and downsized the cycles from 627 to 218. The study demonstrated that PGT-A could significantly improve critical parameters, such as clinical pregnancy and live birth rates. Although the exact causes of RIF remain unclear, these data illustrate that PGT-A applied to elective single-embryo transfer could minimize the risk of clinical outcomes, particularly fetal body weight, in patients with RIF. PGT has been universally performed worldwide, as markedly advanced techniques have been taking place over the years. Therefore, presenting the cutting-edge PGT techniques is essential. In the third article, Du et al., from Basecare, summarized the three conventional PGTs (PGT-A, PGT-M, and PGT-SR) from several perspectives, including history, application scope, detection methods, and limitations. Notably, the mosaicism issue is discussed in the PGT-A section. Additionally, three recently developed PGT technologies (comprehensive PGT [PGT-Plus], niPGT, and PGT-P) are comprehensively described in this review. PGT-Plus is a combination of three PGTs based on the HaploPGT technique, a universal platform, with numerous economic and efficient benefits for both patients and clinicians. PGT-P and niPGT can potentially result in healthier offspring via evaluation of polygenic risk scores of available embryos and interrogation of culture medium instead of performing an invasive biopsy. Of note, the meta-analyses of the PGT section in this review collected large numbers of PGT applications globally, providing a comprehensive vision for clinical outcomes. Furthermore, with the rapid advancement of high-throughput sequencing technologies, such as long-read sequencing, there is no doubt that PGT will continue to evolve. Thus, although these emerging new PGTs appeared as expected, some are still debatable, both ethically and technically. Nevertheless, combining these novel technologies may greatly expand the indications for PGT applications, potentially leading to healthier offspring. Various PGT technologies have considerably improved the success rate of live births and reduced congenital birth defects, and a large number of patients have benefited from treatment. PGT applications have had profound effects on the reproductive field. However, further technical advances and scientific discoveries are needed to address unresolved issues mentioned in these articles. We recognized that there is an ongoing dispute on PGT technologies, including not only emerging PGTs but also conventional PGT-A, I hope that this SI contributes to the increased availability of PGTs and offers valuable information to colleagues in the field. If any new readers are enlightened and excited by this SI and could, one day, also contribute to the shared goal of making people have healthy babies, the pleasure is all ours.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.287
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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