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AHMAD, A.

Publications and source records attributed to AHMAD, A..

2 recordsLinked to original sources

Restoration of Type 17 immune signaling is not sufficient for protection during influenza-associated pulmonary aspergillosis

Influenza-associated pulmonary aspergillosis (IAPA) is a severe complication of influenza infection that occurs in critically ill patients and results in higher mortality compared to influenza infection alone. Interleukin-17 (IL-17) and the Type 17 immune signaling pathway cytokine family are recognized for their pivotal role in fostering protective immunity against various pathogens. In this study, we investigate the role of IL-17 and Type 17 immune signaling components during IAPA. Wild-type mice were challenged with influenza A H1N1 (Flu) and then exposed to Aspergillus fumigatus ATCC42202 resting conidia on day 6 post-influenza infection, followed by the quantification of cytokines and chemokines at 48 hours post-fungal infection. Gene and protein expression levels revealed that IL-17 and Type 17 immune cytokines and antimicrobial peptides are downregulated during IAPA compared to mice singularly infected solely with A. fumigatus. Restoration of Type 17 immunity was not sufficient to provide protection against the increased fungal burden observed during IAPA. These findings contrast those observed during post-influenza bacterial super-infection, in which restoration of Type 17 immune signaling protects against exacerbation seen during super-infection. Our study highlights the need for future studies to understand the immune mechanisms that increase susceptibility to fungal infection. ImportanceIAPA significantly elevates the risk of mortality in patients with severe influenza. Type-17 immunity is critical to host defense during fungal infections and, therefore, vital to understand its role during IAPA. The observations in this study reveal that Type 17 immunity is impaired during IAPA, potentially increasing susceptibility to secondary infection with Aspergillus fumigatus. However, restoration of IL-17 signaling alone is not sufficient to reduce fungal burden in our murine IAPA model. These observations differ from those observed in post-influenza bacterial super-infections, suggesting that the mechanisms underlying viral-fungal super-infection are different than those that underly viral-bacterial super-infection. By elucidating the complex interactions between the host immune system, influenza, and A. fumigatus, these findings are vital for developing strategies to enhance immune responses and improve survival rates during IAPA.

immunology↗

Quantitative assessment of morphology and sub-cellular changes in macrophages and trophoblasts during inflammation

During inflammatory condition in pregnancy, the macrophages present at the feto-maternal junction release an increased amount of NO and pro-inflammatory cytokines such as TNF- and INF-{gamma}, which can disturb the trophoblast functions and thereby the pregnancy outcome. Measurement of the cellular and sub-cellular morphological modifications associated with inflammatory responses are important in order to quantify the extent of trophoblast dysfunction for clinical implication. With this motivation, we investigated morphological, cellular and sub-cellular changes in externally inflamed RAW264.7 (macrophage) and HTR-8/SVneo (trophoblast) using structured illumination microscopy (SIM) and quantitative phase microscopy (QPM). We monitored the production of nitric oxide (NO), changes in cell membrane and mitochondrial structure of macrophages and trophoblasts when exposed to different concentration of pro-inflammatory agents (LPS and TNF-). In vitro NO production by LPS-induced macrophages increased 22-folds as compared to controls, whereas no significant NO production was seen after TNF- challenge. Under similar conditions as with macrophages, trophoblasts did not produce NO following either LPS or TNF- challenge. Super-resolution SIM imaging showed changes in the morphology of mitochondria and plasma membrane in macrophages following LPS challenge and in trophoblasts following TNF- challenge. Label-free QPM showed a decrease in the optical thickness of the LPS-challenged macrophages while TNF- having no effect. The vice-versa is observed for the trophoblasts. We further exploited machine learning approaches on QPM dataset to detect and to classify the inflammation with an accuracy of 99.9% for LPS-challenged macrophages and 98.3% for TNF--challenged trophoblasts. We believe that the multi-modal advanced microscopy methodologies coupled with machine learning approach could be an alternative way for early detection of pregnancy related inflammation after clinical studies.

cell biology↗