Flow cytometry: A biomedical platform offering diagnostic diversity
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Notice bibliographique
Résumé
In 2003 two medical historians, Peter Keating and Alberto Cambrosio, published a scholarly thesis that documents meticulously the story of clinical flow cytometry (1). They described this technology not just as a new tool for medical diagnosis and monitoring but as biomedical platform. The authors reasoned that from a historical perspective, medicine is a steady uphill struggle with some remarkable landmark plateaus achieved at strategic times, to help with the journey along the challenging and forbidding obstacles formed by a plethora of diseases. Keating and Cambrosio concluded that during the closing years of the twentieth century, flow cytometry indeed had achieved such a platform status (1). With the advent of the 21st century, a new area in diagnostics became apparent, that is realigning the normal and pathological manifestations. This perspective is based on immunophenotyping metrology that harnesses both intrinsic and extrinsic cellular attributes. Invariably, history illustrates that visionaries are frequently too far ahead of their time, as a result of which their contributions are often not recognized at all, or appreciation of their discoveries is delayed for years, decades or even centuries. An example of a European discovery that was delayed in terms of years is the commercial production of clinical flow cytometers. The first so-called “impulscytophotometer”, the precursor of a commercial flow cytometer was developed by a young German scientist, W. Göhde. It was installed in Leiden (The Netherlands) around 1970, the birth place of epi-illumination for microscopy. Here, a small local committee of experts concluded that the new device, termed “flow cytometer”, had no future in the field of immunology and haematology (2). From a European perspective, this was a serious setback for this discovery as it provided time for the development of competing efforts from overseas. In a short time, commercial flow cytometers developed in the US reached the market including the laboratory in Leiden (2). Within the same context, there is an episode involving a Canadian doctor who was also a victim of circumstances. The injustice in his case falls in the category of discoveries “not recognized at all”. Back in 1789, Peter deSales LaTerriere published his Bachelor of Medicine dissertation describing the cause of puerperal fever as part of a Harvard University MD requirement (3). This document was about how to reduce lethal complications involving young mothers at child-birth. It remained unnoticed, only to be rediscovered by Ignaz Semmelweis, a Hungarian MD working in Vienna in 1861 (4). Semmelweis' classic descriptive epidemiology study was published 72 years after the Harvard dissertation. In the medical literature, the credit for the discovery, to this day, is denied from the original observer. It had to do with timing, as Semmelweis' observation was at the time of Lister and Pasteur. Going back much further in history, there is a description of coeliac disease (CD) that takes us back to ancient Greek times. Aretaeus of Cappadocia practiced medicine in the 1st century during the reign of Nero (5). He wrote a general treatise on diseases and, in this way, set a platform for dissemination of medical information. In his opus that covers several volumes, he included most of the classical features and symptoms of a disease that later became known as CD. CD is a treatable infliction, which is still causing significant suffering worldwide–without a cure within sight. The “Extant Works of Aretaeus”, a classical description of the disease, is certainly one of the most valuable and astonishing relics left from antiquity. A limitation of this study is that the detection of the aberrant T cells in the peripheral blood has been hardly touched upon. The aberrant immunophenotype would have made a perfect target for “rare event detection” in blood. Better knowledge on this point might pave the way for the possibility of a blood test for T-cell subsets in RCD Type 2, either as a prognostic factor and/or monitoring tool for therapy. This conclusion may be a “take home message” of this work, which is yet another example to reinforce the phrase: timing is everything.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
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 découle