Notice bibliographique
Résumé
INTRODUCTION The lung’s exceptionally large surface area, and minimal distance between the blood and external environment leave it vulnerable to infection. Most importantly is-that pulmonary infections can often lead to severe complications such as sepsis or septic shock. We are interested in pulmonary Plasmacytoid Dendritic Cells (pDC) which in other organs of the body have been shown to be critical in fighting severe infection through the initiation of inflammation and the modulation of T cell responses [1, 2]. We hypothesize that pDC, are prepositioned in the lung and are capable of rapidly responding to pathogenic insults. METHODS Lungs from the mouse were exsanguinated and excised from the mouse and prepared as a whole lung homogenate. The cells were then Fc blocked and then stained with the antibody cocktail. Following the staining, the cells were analysed using flow cytometry. RESULTS Using flow-cytometry, we have identified pDC using the cell surface markers PDCA-1+ and Siglec-H+ within exsanguinated unstimulated whole lung homogenates. Analysing the anatomical locations of lung pDC revealed at baseline, pDC are almost exclusively located in the pulmonary vasculature with a small population in the lung parenchyma and none within the alveolus. pDC make up 0.5 % of total CD45+ pulmonary leukocytes. Stimulating the lung with pathogen associated molecular patterns that either directly or indirectly activate pDC demonstrated that early on during inflammation the absolute number of pDC does not change, suggesting they are not recruitable. Following either stimulation, the population of PDCA-1+ cells increased; however, using our more rigorous definition of pDC by employing multiple cell surface markers we discovered that the true pDC population (PDCA-1+/Siglec-H+) did not change in number. Under unstimulated conditions, PDCA-1+ pDC were visualized within the vasculature. These cells crawled along the endothelium and were not part of the blood cellular blood flow. Following 24 hours after stimulation with a TLR 9 agonist, an increase in the total number of the PDCA-1+ was observed. The PDCA-1+ cells displayed a mix of a crawling and stationary phenotype. DISCUSSION AND CONCLUSIONS We have examined in detail our current definitions of pDC, the phenotypic markers used in the identification of them, their anatomical location within the lung, and finally the effects of two TLR agonists on pDC. We created an assay to identify the anatomical locations of pulmonary leukocytes, and developed methods to identify the roles that these cells play in pulmonary host defence. We now know that PDCA-1 is not an effective marker for pDC during inflammatory conditions and that a rigorous definition of pDC is needed to identify them during inflammatory conditions. We made the novel observation that pDC, upon stimulation will react differently depending on the stimuli, which means they display plasticity in their roles within the hierarchy of host defence. The findings in this paper provides the basis for further insight into the nature of pulmonary pDC and their roles in pulmonary inflammation. We will explore these exciting new avenues by asking questions regarding the roles and interactions which pDC have in the initiation of severe pneumonia, and its functions during. This work will allow us to continue to investigate the unknown roles and functions that pDC play during pulmonary inflammation, which will reveal exciting new pathways to treat severe pneumonia, or pulmonary inflammation.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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) | 0,003 | 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 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 ».