Notice bibliographique
Résumé
William Coley, a young surgeon at New York Memorial Hospital, was traumatized by the loss of his first patient to bone cancer in 1891. He was unable to save this young patient and she succumbed to her Sarcoma within 3 months of surgery. He searched the hospital archive to learn more about Sarcoma and discovered the case of a patient with a large sarcoma who had undergone five unsuccessful surgeries over a 3 year period. This case had been determined to be hopeless. After the last of these operations, the patient became very ill from an erysipelas infection.
 Coley was astonished to read that after the fever broke and the patient had recovered, the tumour had vanished. Seven years later, the patient was still alive and well. Coley concluded that whatever had caused the fever must also have destroyed the cancer. Coley searched for and found this patient still in excellent health. Coley reasoned that if a chance infection could make tumours vanish, then a purposefully induced infection could do the same.
 The hypothesis was tested by infecting his next 10 patients with Streptococcus pyogenes to cause Erysipelas. Some of the patients were difficult to infect, some died, and some had a strong reaction and their disease regressed. Coley switched to deactivated S. pyogenes to avoid the mortality observed with the live strain. Afterxperimentation with various formulations, a combination of S pyogenes and Serratia marcescens was decided upon and became known as Coley’s Toxin.
 The preferred method of delivery was injection of the toxin directly into the primary tumour or metastases in increasing doses to avoid immune tolerance. Fever response in the patient was essential to imitate a naturally occurring infection and the body’s natural response. Though Coley met with success, this therapy was abandoned as chemotherapy became more popular.
 Hoption Cann SA, Gunn HD, van Netten JP, van Netten C. Dr William Coley and tumour regression: a place in history or in the future. Post Graduate Medical Journal 2003; 79:672-680.
 Hobohm U. Fever and Cancer in Perspective. Cancer Immunology & Immunotherapy 2001; 50:391-396.
 Grange JM, Standord JL, Stanford CA. Campbell De Morgan’s ‘Observations on cancer’, and their relevance today. Journal of the Royal Society of Medicine 2002 (June); 95:296-299.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,003 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».