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Enregistrement W2895229614 · doi:10.1002/mrd.23064

John D. Biggers (1923–2018)

2018· article· en· W2895229614 sur OpenAlexaff
Jay M. Baltz

Notice bibliographique

RevueMolecular Reproduction and Development · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueReproductive Biology and Fertility
Établissements canadiensOttawa HospitalUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésPassionBiologyLibrary scienceSociologyMedia studiesPsychology

Résumé

récupéré en direct d'OpenAlex

John D. Biggers, one of the true pioneers in the field of reproductive biology, passed away at his home in Lexington, Massachusetts on April 7, 2018. His scientific career spanned seven decades, with more than 175 peer-reviewed papers and many reviews and book chapters published beginning in 1951 and continuing through 2016. John was born in Reading, England, in 1923. He graduated from the Royal Veterinary College and obtained his Ph.D. from the University of London. He then moved to the University of Sydney in Australia to take up a post in Veterinary Physiology where he investigated estrogen signaling and developed estrogen assays in collaboration with Peter Claringbold in the department headed by Clifford Emmens. This period helped establish John’s lifelong passion for statistical and biometric analysis. In 1955, John D. Biggers returned to England, taking a faculty position at the Royal Veterinary College at the University of London, where he embarked on studies of tissue culture, initially focusing on organ culture of bones. The development of media for long-term growth of embryonic bones in vitro (Heyner & Biggers, 1958) established one of the research themes that drove his entire career—the development and optimization of chemically defined culture media. Anne McLaren was also in London by this time, and their complementary interests led to their historic collaboration. Their 1958 Nature paper, “Successful Development and Birth of Mice Cultivated In Vitro as Early Embryos,” provided the first demonstration that embryos that had developed in culture could produce normal offspring (McLaren & Biggers, 1958). This was one of the most important advances for experimental embryology and the eventual development of assisted reproduction technologies. In 1959, John moved to the US, where he held faculty positions at the University of Pennsylvania and The Johns Hopkins University before being appointed as the Professor of Physiology at Harvard Medical School, in 1972. From 1960s through early 1980s, he published extensively on the metabolism of preimplantation embryos and regulation of oocyte maturation, with trainees and collaborators who included Ralph Brinster, Wes Whitten, David Whittingham, Dale Benos, and many other well-known reproductive biologists. During this time, he also established methodologies for analysis of the preimplantation embryo and egg microenvironment in a long-lived collaboration with the biophysicist Claude Lechene and with Henry Leese. John was a founding member and second president of the Society for the Study of Reproduction (SSR), as well as the Editor of their journal Biology of Reproduction. He received the SSR’s highest award, the Carl G. Hartman Award, in 1987. The mid-1980s saw the establishment of the National Cooperative Program on Non-Human In Vitro Fertilization and Preimplantation Development under the leadership of Richard J (Dick) Tasca at the US National Institutes of Health. It was within this program, informally called the “Culture Club,” that the first media capable of supporting complete preimplantation embryo development from fertilized eggs to blastocysts were developed. Biggers’ KSOM embryo culture medium (Lawitts & Biggers, 1993) that was developed in an extensive series of investigations with his postdoctoral fellow Joel Lawitts, which used sophisticated statistical optimization techniques to drive medium formulation, is widely used today and is the basis for successful human clinical IVF culture media. The importance of the Culture Club, particularly the contributions of the Biggers laboratory, to the success of Human Assisted Reproductive Technologies (ART) cannot be overstated. John D. Biggers was also very much interested in the ethics of ART and wrote and lectured extensively on this subject. He was called to testify before the US Senate about IVF and embryo transfer and appointed by President Carter as Chief Scientific Advisor on the Ethics Board of the US Department of Health, Education and Welfare. John remained active in research until the end of his life. Most recently, he had an active collaboration with Mehmet Toner to develop methods of long-term storage of mouse sperm and had just completed a book chapter with his collaborator Catherine Racowsky. Only 2 years ago, he and his coauthor Carol Kountz authored a book on Walter Heape, an underappreciated pioneer in the field of reproduction who performed the first successful embryo transfer at the end of the 19th century (Biggers & Kountz, 2016). John traveled extensively including all seven continents, often with his wife, late Betsey Williams, a former faculty member in the Anatomy Department at Harvard. He was an excellent cook and a passionate bird watcher and photographer. He will be remembered as a valued collaborator, a superb mentor who trained many top researchers, and a talented scientist whose work includes some of the most important advances made in the field of reproduction (Figure 1). John D. Biggers and Anne McLaren with one of the mice from their landmark 1958 paper (McLaren & Biggers, 1958), which first reported that embryos that had been cultured in vitro before being transferred to a recipient female could give rise to a live offspring. Photo from John D. Biggers (Biggers, 2001)

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,405
Score d'incertitude au seuil0,414

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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 Opus0,025
Tête enseignante GPT0,277
Écart entre enseignants0,253 · 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'étudeExpérimental (laboratoire)
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
Publié2018
Routes d'admission1
Résumé présentoui

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