MétaCan
Menu
Retour à la cohorte
Enregistrement W4317775963 · doi:10.1097/rd9.0000000000000060

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

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

Notice bibliographique

RevueReproductive and Developmental Medicine · 2023
Typearticle
Langueen
DomaineMedicine
ThématiquePrenatal Screening and Diagnostics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésChinaVice presidentLibrary scienceChristian ministryPolitical scienceExecutive directorManagementMedicineMedical educationLaw

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,549
Score d'incertitude au seuil0,585

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,019
Tête enseignante GPT0,287
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueReproductive and Developmental MedicineMême sujetPrenatal Screening and DiagnosticsTravaux en français237 207