Teixeira, G. | bioRxiv Science

bioRxiv2025

Deep Learning-Enhanced Light Sheet Microscopy Unveils Semaglutide Impact on Cardiac Fibrosis

BackgroundExtensive preclinical research aims to develop novel therapeutics for myocardial fibrosis (MF), a condition marked by collagen accumulation that impairs cardiac function. MF is particularly relevant in heart failure with preserved ejection fraction (HFpEF), a growing clinical challenge with limited treatment options. However, current methods for quantifying MF in mouse models struggle to accurately capture its heterogeneous regional distribution, creating a significant barrier to reliably assessing the efficacy of therapeutics. PurposeTo develop a whole-heart fibrosis imaging and deep learning (DL)-based quantification method and validate the workflow by assessing the efficacy of a glucagon-like peptide-1 receptor (GLP-1R) agonist in mouse HFpEF model. Experimental ApproachBy utilizing a fluorescent collagen-labelling dye, tissue clearing and 3D light sheet microscopy, we developed a high-throughput imaging platform for MF. We established DL framework to quantify perivascular and replacement fibrosis, as well as hypertrophy, in 17 left ventricular (LV) segments. The antifibrotic effects of the GLP-1R agonist semaglutide were evaluated in the db/db UNx-ReninAAV mouse model, which exhibits diabetes, kidney failure, obesity, and hypertension. Key ResultsWhole-heart 3D light sheet microscopy, combined with artificial intelligence, enables micrometer-resolution analysis of MF distribution in rodents. This approach allows for detailed characterization of distinct regional fibrosis patterns. Chronic semaglutide treatment significantly reduced LV hypertrophy and perivascular fibrosis but had no significant effect on replacement fibrosis. Conclusions and ImplicationsThe established 3D imaging and quantification approach provides a powerful tool for evaluating the therapeutic efficacy of antifibrotic compounds and studying the cellular and pathological mechanisms underlying cardiovascular diseases.

pathology↗

bioRxiv2023

EXPANSION OF ANTIGEN- SPECIFIC MEMORY CELLS AS A POTENTIAL BOOSTER FOR FOOD TOLERANCE INDUCTION

Approximately 3% of children in Western countries are diagnosed with peanut allergy, a likely lifelong disease. The preferred treatment for food allergy is allergen avoidance. However, oral immunotherapy is an FDA-approved treatment to re-induce tolerance, still, not all patients respond as expected. Thus, the aim of this work is to evaluate whether the association of an antigen-specific tolerogenic (oral tolerance) bystander effect can ameliorate the recovery of inflamed intestinal mucosa. Adult male C57BL/6 mice were divided into five groups, four of which were submitted to an intestinal inflammation induction protocol to peanuts. After sensitization, experimental groups were orally challenged with either peanuts or a hybrid diet (peanuts + mouse chow). In a second stage, groups were sensitized, challenged with peanuts, and then received either peanuts, hybrid diet, or ovalbumin chow during the recovery period of the inflamed mucosa. Results showed no changes in diet intake and body weight. Polyisotypic anti-peanut IgG and IgG1 were significantly increased in the serum from animals in allergic groups. The group that received the hybrid diet showed an increase in CD4+CD25+Foxp3+ regulatory T cells, as well as in B220+CD3-CD27+ memory B cells. Histology of the duodenum showed a decrease in intraepithelial leukocytes in animals who received hybrid diet. Together, our results show that when the tolerogen is added to a diet containing the allergen, it can ameliorate the induction of local inflammation. Simultaneously offering the allergen with a tolerated food increased the mucosal recovery due to the expansion of previously induced memory cells.

immunology↗