Pancreatic involvement in murine antibody‐mediated transfusion‐related acute lung injury?
Notice bibliographique
Résumé
Transfusion-related acute lung injury (TRALI) is a syndrome of acute respiratory distress caused by blood transfusions.1, 2 Currently, TRALI is a leading cause of blood transfusion–associated fatalities, and therapeutic strategies are not available.1, 3 The pathogenesis is multifactorial and complex, with involvement of both donor and recipient factors.1 Clinical recipient factors (the so-called first hit) are often characterized by a state of inflammation, and when combined with factors in the transfusion product (the so-called second hit) such as anti-WBC antibodies, the onset of TRALI is triggered. To obtain insights into the TRALI pathophysiology, a commonly used mouse model of antibody-mediated TRALI has been used where a potent TRALI-inducing anti–major histocompatibility complex (MHC) class I antibody called 34-1-2S is administered to a primed recipient.1 With great interest, we read the article by Tariket and colleagues4 where the authors use the 34-1-2S mouse model of TRALI based on priming with lipopolysaccharide (LPS; first hit) followed by infusion of 34-1-2S (second hit). With this model, the authors observed significant damage to the pancreas, which they described as acute lung injury–induced pancreatic degradation. Pancreatic damage was assessed via damage scores based on pancreatic tissue histology analysis (hematoxylin and eosin staining). In addition, immunoassays were conducted to measure plasma levels of the pancreatic enzymes amylase and lipase, which, when elevated, are generally considered to be reliable indicators of pancreatic injury. In our opinion, to firmly conclude that TRALI responses induce pancreas degradation, controls such as mice primed with only with LPS and mice infused with 34-1-2S alone (thus without a first hit) should be analyzed, as the antibody itself may directly target and damage the pancreas without inducing TRALI. To obtain further insights into the involvement of the pancreas in TRALI, we also performed experiments using our previously established antibody-mediated TRALI model in C57BL/6 mice.5, 6 As a first hit, we depleted CD4+T cells and primed the mice with a low dose of LPS. As a second hit, we infused 34-1-2S together with another anti–MHC class I, AF6-88.5.5.3. We observed that the lung wet-to-dry weight ratio (an established read-out for the degree of pulmonary edema) was increased when both hits were combined; however, untreated mice, mice subjected to only the first hit or mice subjected to only the second hit (Figure 1A) did not undergo TRALI-induced lung damage. Strikingly, however, we did not observe any increase in plasma amylase and lipase levels in these TRALI mice compared with untreated mice (Figure 1B, C, respectively). We also did not observe any elevation in plasma amylase and lipase levels in the mice subjected to the first or second hit only. In contrast to Tariket et al,4 based on the normal levels of plasma amylase and lipase, our findings do not support the occurrence of TRALI-induced pancreatic degradation. A possible reason for the different outcomes of both studies may perhaps be related to differences in the composition of the gut microbiota.5 As we performed CD4+ T-cell depletion before TRALI induction, in contrast to Tariket et al, it is possible that this may also have contributed to the discrepancy in the two studies. Due to the delicate nature of the pancreatic tissue, we did not consider pancreatic tissue histology analysis to be reliable in our hands. Further research is required to clarify the potential involvement of the pancreas and other organs besides the lungs in TRALI. The authors declare no conflicts of interest.
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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) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».