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Iron deficiency has been linked to impaired humoral immunity to vaccines. In this issue of Med, Frost et al. demonstrate the importance of serum iron levels for lymphocyte function during vaccination and infection, pointing to iron supplementation as a strategy to boost vaccine efficacy, including against COVID19. 1

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Summary The discovery of the NLRP 3 ( NLR family, pyrin domain containing 3) inflammasome provided an important molecular mechanism in the induction of the central pro‐inflammatory cytokine interleukin‐1β ( IL ‐1β), via activation of caspase‐1, which processes pro‐ IL ‐1β into its mature active form. IL ‐1 has long been known to exert metabolic effects, most notably being implicated in insulin resistance and obesity. A key phenotype of the NLRP 3‐deficient mouse is insulin hypersensitivity. Over the past 5 years, a number of discoveries have been made suggesting a close interplay between NLRP 3 and metabolism. Metabolic products have been shown to activate NLPR 3, and disturbed mitochondria have been shown to be involved in NLRP 3 function. It is possible that under normal physiology NLRP 3 is homeostatic and maintains the metabolic balance. However, upon chronic activation (e.g. in obesity or hypercholesterolemia), NLRP 3 becomes pathologic and promotes disease. Here, we review these findings and place them in the context of exciting new insights that are improving our understanding of the link between inflammation and metabolism. These insights are giving rise to better understanding of disease pathogenesis and might point to new therapeutic approaches.

HIF1α is a common component of pathways involved in the control of cellular metabolism and has a role in regulating immune cell effector functions. Additionally, HIF1α is critical for the maturation of dendritic cells and for the activation of T cells. HIF1α is induced in LPS-activated macrophages, where it is critically involved in glycolysis and the induction of proinflammatory genes, notably Il1b. The mechanism of LPS-stimulated HIF1α induction involves succinate, which inhibits prolyl hydroxylases (PHDs). Pyruvate kinase M2 (PKM2) is also induced and interacts with and promotes the function of HIF1α. In another critical inflammatory cell type, Th17 cells, HIF1α acts via the retinoic acid-related orphan receptor-γt (RORγt) to drive Th17 differentiation. HIF1α is therefore a key reprogrammer of metabolism in inflammatory cells that promotes inflammatory gene expression.

Conference Article| February 01 1996 Effect of pertussis toxin and PGE2 on the functioning of the IL-2 promoter in Interleukin-1 treated EL4. NOB-1 thymoma cells L. M. McCarthy; L. M. McCarthy 1Biochemistry Dept, Trinity College, Dublin 2, Ireland. Search for other works by this author on: This Site PubMed Google Scholar L. A. J. O'neill L. A. J. O'neill 1Biochemistry Dept, Trinity College, Dublin 2, Ireland. Search for other works by this author on: This Site PubMed Google Scholar Author and article information Publisher: Portland Press Ltd Online ISSN: 1470-8752 Print ISSN: 0300-5127 © 1996 Biochemical Society1996 Biochem Soc Trans (1996) 24 (1): 82S. https://doi.org/10.1042/bst024082s Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Cite Icon Cite Get Permissions Citation L. M. McCarthy, L. A. J. O'neill; Effect of pertussis toxin and PGE2 on the functioning of the IL-2 promoter in Interleukin-1 treated EL4. NOB-1 thymoma cells. Biochem Soc Trans 1 February 1996; 24 (1): 82S. doi: https://doi.org/10.1042/bst024082s Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsBiochemical Society Transactions Search Advanced Search This content is only available as a PDF. © 1996 Biochemical Society1996 Article PDF first page preview Close Modal You do not currently have access to this content.

Toll‐like receptors (TLRs) signal the presence of pathogens and tissue injury, triggering the inflammatory process in macrophages. The goal of inflammation is to resolve the injury and return the body to homeostasis. MicroRNAs are an important group of regulators of TLR signaling and several are induced by TLRs in macrophages. These TLR‐induced microRNAs target signaling components in the TLR pathway, thereby producing a negative feedback loop, and they are therefore prime candidates for the initiation of repair. Importantly, their dysregualtion may be important for chronic inflammation, which in turn can lead to autoimmunity and cancer, as discussed in this Viewpoint .

Introduction La sélection embryonnaire est un enjeu majeur en Assistance Médicale à la Procréation (AMP), d’autant plus depuis la généralisation du transfert mono-embryonnaire, et son optimisation permettrait l’amélioration des résultats cliniques en Fécondation In Vitro (FIV). Récemment, plusieurs modèles d’Intelligence Artificielle (IA) basés sur le deep-learning tels que l’iDAScore, ont été développés. Ces modèles, entraînés sur des séquences d’images Time-Lapse (TL) d’embryons dont le potentiel implantatoire est connu, sont capables de générer un score prédictif de grossesse pour chaque blastocyste, de façon automatisée et standardisée. Matériels et méthodes Dans cette étude, nous avons comparé la hiérarchisation de 311 blastocystes J5 établie par l’iDAScore v1.0 et les biologistes de notre centre. Les 311 blastocystes ont été classés par les biologistes selon la classification de Gardner en top (Top : 70,1 %), bonne (Q+ : 10,6 %) et mauvaise qualité (Q– : 19,3 %). L’iDAScore médian était respectivement compris entre [9,9–8,4],]8,4–7,5] et]7,5–2,1] pour ces trois catégories de blastocystes. Résultats La catégorisation des embryons en qualité Top, Q+ et Q– était concordante entre le biologiste et l’iDAScore dans respectivement 89,5 %, 36,4 % et 48,3 % (p < 10−4). De plus, l’iDAScore hiérarchisait, lorsque comparé aux biologistes, les trois meilleurs blastocystes de la cohorte comme suit : Rang 1 : 71,9 % ; Rang 2 : 61,6 % ; Rang 3 : 56,8 % de similitude (p =0,07). Cent cinquante et un blastocystes dont les issues de grossesse étaient connues ont été analysés. L’iDAScore des blastocystes qui se sont implantés était significativement plus élevé que celui des blastocystes qui ne se sont pas implantés (implantation+ : 9,10±0,57 ; implantation– : 8,70±0,95, p =0,003). Conclusion Cette étude préliminaire montre que l’iDAScore permet de rendre une classification hiérarchique des blastocystes reproductible, fiable et instantanée. De plus, cet outil permet d’identifier les blastocystes avec le meilleur potentiel implantatoire. Si ces résultats sont confirmés sur de plus grandes cohortes d’embryons et de patients, l’IA pourrait révolutionner les laboratoires de FIV en standardisant la sélection hiérarchique embryonnaire. Introduction Embryo selection is a major challenge in ART, especially since the generalization of single embryo transfer, and its optimization could lead to the improvement of clinical results in IVF. Recently, several Artificial Intelligence (AI) models, based on deep-learning such as iDAScore, have been developed. These models, trained on time-lapse videos of embryos with known implantation data, can predict the probability of pregnancy for a given embryo, allowing automatization and standardization in embryo selection. Material and methods In this study, we have compared the hierarchical categorization of 311 D5 blastocysts of iDAScore v1.0 and the embryologists of our unit. These 311 D5 blastocysts have been classified as top (70.1%), good (Q+: 10.6%) and poor (Q–: 19.3%) quality by embryologists according to Gardner classification. Median iDAScores were [9.9–8.4],]8.4–7.5] and]7.5–2.1] for top, good and poor-quality blastocysts respectively. Results We observed a significantly concordant categorization between iDAScore and embryologists for top, good and poor-quality blastocysts (respectively, 89.5, 36.4 and 48.3%, P < 10−4). Moreover, the hierarchical categorization of the three best blastocysts between iDAScore and the embryologists was as follow: 1st rank: 71.9%; 2nd rank: 61.6%; 3rd rank: 56.8% (P =0.07). One hundred and fifty-one blastocysts with known implantation data were analyzed. The iDAScore of blastocysts that implanted was significantly higher than those that did not implant (implantation+: 9.10±0.57; implantation–: 8.70±0.95, P =0.003). Conclusion This preliminary study shows that iDAScore is able to perform a reproducible, reliable and immediate hierarchical classification of blastocysts. Moreover, this tool can identify the blastocysts with the highest implantation potential. If these results confirmed on a larger scale of embryos and patients, IA could revolutionize IVF laboratories by standardizing embryo hierarchical selection.

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Macrophage activation is a key event in the inflammatory process, since these cells produce a range of pro-inflammatory molecules, including ROS (reactive oxygen species), prostaglandins, cytokines and nitric oxide. These factors promote inflammation by causing vasodilation and recruitment of neutrophils, monocytes and lymphocytes, which ultimately clear infection and repair damaged tissue. One of the most potent macrophage activators is the Gram-negative-derived bacterial cell wall component LPS (lipopolysaccharide). LPS is sensed by TLR4 (Toll-like receptor 4) and triggers highly complex signalling pathways that culminate in activation of transcription factors such as NF-κB (nuclear factor κB), which in turn increases transcription of genes encoding proteins such as COX2 (cyclo-oxygenase 2, a key enzyme in prostaglandin biosynthesis), nitric oxide synthase and cytokines such as TNF (tumour necrosis factor). Recently, a role for metabolic pathways in the regulation of LPS signalling has become a focus of research in inflammation. A notable example is LPS promoting the so-called Warburg effect - aerobic glycolysis. This allows for an up-regulation in ATP production, and also for the production of biosynthetic intermediates to meet the demands of the activated macrophages. In this issue of the Biochemical Journal, Infantino et al. add a new finding to the role of metabolism in LPS action. They demonstrate a requirement for the mitochondrial citrate carrier in the induction of ROS, nitric oxide and prostaglandins by LPS. The knockdown of the carrier with siRNA (small interfering RNA), or the use of an inhibitor BTA (benzene-1,2,3-tricarboxylate), abolishes these responses. Although no mechanism is provided, the authors speculate that acetyl-CoA is synthesized from citrate in the cytosol. The acetyl-CoA generated could be required for phospholipid biosynthesis, the phospholipids being the source of arachidonic acid for prostaglandin production. Another product of citrate metabolism, oxaloacetate, will indirectly generate nitric oxide and ROS. This finding places citrate, transported from the mitochondria, as a key player in LPS signalling, at least for ROS, nitric oxide and prostaglandin production. This somewhat unexpected role for citrate in LPS action adds to a growing literature on the role for metabolism in the regulation of signalling in inflammation.

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