Optimization of a Cytokine Cocktail for the Expansion of Cord Blood (CB) CD34+ Cells into Megakaryocytes (MK) Progenitors towards the Ex Vivo Production of Platelets.
Notice bibliographique
Résumé
Abstract Platelet transfusion remains to this date the only therapy to restore safe platelet levels in thrombocytopenic patients. There are currently no substitutes for blood-derived platelets but the development of culture processes for HSC has raised the possibility of producing MK-progenitors and platelets ex vivo. The objective of this study is to optimize a cytokine cocktail for the expansion of MK-progenitors from CB CD34+ cells to enhance ex vivo platelet production. The cytokine selection process would be based on the assessment of the individual and synergistic effects of the cytokines tested. In short, CB CD34+ cells were first expanded for 6 days with TPO, SCF and different combinations of other cytokines. The expansion of various hematopoietic populations (CD34, CD41, GPA, CD15) and MK-progenitors were determined by FACS and CFU-MK assay respectively at day 6. The capacity of the expanded cells to produce platelets was also measured at day-14. Statistical analysis of these responses revealed the individual and interactive effects of cytokines tested by two-level factorial designs in the first six days of culture. To ascertain the magnitude of these, the calculated effects (E) were compared to the mean response (MR), which is the average of all conditions tested. FL, IL-3, IL-6, IL-9 and IL-11, cytokines commonly used to expand progenitors and MK cells, were first tested with SCF and TPO present at 1 and 30 ng/ml. IL-9, FL and IL-6 were best for the expansion of day-6 CD41+ MK, with E of 1.3, 1.1 and 0.6 respectively (MR=25, P<0.003). FL, IL-9 and IL-3 showed a similar quantitative capacity to expand CFU-MK progenitors (MR=57, E = 2.2–2.9, P<0.006), though a strong negative synergy between these 3 was apparent (−1.7 E). The use of all 5 cytokines was clearly disadvantageous since it led to non-MK expansion. Analysis of day-14 results indicated that FL and IL-9 strongly stimulated platelet production (E of 68 and 53, MR=391, P<0.003), whereas IL-11 was highly detrimental due to its individual effect (−30 E) and negative interaction with IL-9 (−33 E, P<0.03). Numerous other interactions were also revealed, including a strong negative interaction between FL and IL-3 on platelet production (−53 E, P<0.003). Based on these, IL-3 and IL-11 were eliminated. Next, a series of factorial screens were done to test the effect of SCF concentration levels and to select the cytokine(s) for the final cocktail. As expected, increasing SCF concentration (50 ng/ml) strongly promoted cell expansion (P<0.0001), though this did not increase day-6 MK and CFU-MK (P=0.2), but rather led to the expansion of erythrocytes (27 E, MR=69, P<0.0001) resulting in a reduction of 25 and 10% in mature CD42+ MK (P<0.02) and platelets produced. In contrast to FL, IL-6 and IL-9 also favoured erythrocyte expansion under elevated SCF concentration (individual and synergistic effects with SCF, P<0.05). In summary, strong cytokine interactions with important impacts on the differentiation fate of CD34+ cells were identified. Notably, the concentration level of SCF had profound influences on the individual and interactive effects of other cytokines. Our results demonstrate redundant and distinctive properties for IL-9 and IL-6, both stimulating megakaryopoiesis but at distinct stages of maturation. A dose-response surface methodology is presently used to find the concentrations of FL, IL-9, TPO and SCF that will optimize the production of MK-progenitors and platelets.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».