RESUMO
Background: The APP/PS1 mouse model recapitulates pathology of human Alzheimer's disease (AD). While amyloid-ß peptide deposition and neurodegeneration are features of AD, the pathology may involve inflammation and impaired vascular regeneration. Objective: This study evaluated inflammatory environments in the brain and bone marrow (BM), and the impact on brain microvascular density. Methods: BM and frontal cortex from male nine-month-old APP/PS1 or the control C57Bl6/j mice were studied. Vascular density and inflammatory cells were evaluated in the sections of frontal cortex by immunohistochemistry. Different subsets of hematopoietic stem/progenitor cells (BM) and monocyte-macrophages were characterized by flow cytometry and by clonogenic assays. Myelopoietic or inflammatory factors were evaluated by real-time RT-PCR or by western blotting. Results: CD34+ or CD31+ vascular structures were lower (pâ<â0.01, nâ=â6) in the frontal cortex that was associated with decreased number of Lin-Sca-1+cKit+ vasculogenic progenitor cells in the BM and circulation (pâ<â0.02, nâ=â6) compared to the control. Multipotent progenitor cells MPP4, common lymphoid, common myeloid and myeloid progenitor cells were higher in the APP/PS1-BM compared to the control, which agreed with increased numbers of monocytes and pro-inflammatory macrophages. The expression of pro-myelopoietic factors and alarmins was higher in the APP/PS1 BM-HSPCs or in the BM-supernatants compared to the control. Frontal cortices of APP/PS1 mice showed higher number of pro-inflammatory macrophages (CD11b+F4/80+ or CD80+) and microglia (OX42+Iba1+). Conclusions: These findings show that AD pathology in APP/PS1 mice is associated with upregulated myelopoiesis, which contributes to the brain inflammation and decreased vascularity.
RESUMO
Tumor-derived extracellular vesicles (EVs) show great potential as biomarkers for several diseases, including pancreatic cancer, due to their roles in cancer development and progression. However, the challenge of utilizing EVs as biomarkers lies in their inherent heterogeneity in terms of size and concentration, making accurate quantification difficult, which is highly dependent on the isolation and quantification methods used. In our study, we compared three EV isolation techniques and two EV quantification methods. We observed variations in EV concentration, with approximately 1.5-fold differences depending on the quantification method used. Interestingly, all EV isolation techniques consistently yielded similar EV quantities, overall size distribution, and modal sizes. In contrast, we found a notable increase in total EV amounts in samples from pancreatic cancer cell lines, mouse models, and patient plasma, compared to non-cancerous conditions. Moreover, individual tumor-derived EVs exhibited at least a 3-fold increase in several EV biomarkers. Our data, obtained from EVs isolated using various techniques and quantified through different methods, as well as originating from various pancreatic cancer models, suggests that EV profiling holds promise for the identification of unique and cancer-specific biomarkers in pancreatic cancer.