Scienze della vita

Scienze della vita

Scienze della vita

Questo è il posto giusto per ampliare le vostre conoscenze, le capacità di ricerca e le applicazioni pratiche della microscopia in vari campi scientifici. Imparate come ottenere una visualizzazione precisa, l'interpretazione delle immagini e i progressi della ricerca. Troverete informazioni approfondite sulla microscopia avanzata, sulle tecniche di imaging, sulla preparazione dei campioni e sull'analisi delle immagini. Gli argomenti trattati comprendono la biologia cellulare, le neuroscienze e la ricerca sul cancro, con particolare attenzione alle applicazioni e alle innovazioni più avanzate.
Cell DIVE multiplexed image of FFPE tissue section from syngeneic murine cancer model, 4T1.

Mapping Tumor Immune Landscape with AI-Powered Spatial Proteomics

Spatial mapping of untreated tumors provides an overview of the tumor immune architecture, useful for understanding therapeutic responses. Immunocompetent murine models are essential for identifying…
Automated Laser Microdissection for Proteome Analysis

Deep Visual Proteomics Provides Precise Spatial Proteomic Information

Despite the availability of imaging methods and mass spectroscopy for spatial proteomics, a key challenge that remains is correlating images with single-cell resolution to protein-abundance…
Multiplexed Cell DIVE imaging of Adult Human Alzheimer’s brain tissue section demonstrating expression of markers specific to astrocytes (GFAP, S100B), microglia (TMEM119, IBA1), AD-associated markers (p-Tau217, β-amyloid) and immune cells such as CD11b+, CD163+, CD4+, and HLA-DRA+, clustered around the β-amyloid plaques.

Spatial Analysis of Neuroimmune Interactions in Alzheimer’s Disease

Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neurofibrillary tangles, β-amyloid plaques, and neuroinflammation. These dysfunctions trigger or are exacerbated by…

AI-Powered Multiplexed Image Analysis to Explore Colon Adenocarcinoma

In this application note, we demonstrate a spatial biology workflow via an AI-powered multiplexed image analysis-based exploration of the tumor immune microenvironment in colon adenocarcinoma.
Intestinal organoids label with FUCCI reporter to follow cell cycle dynamics. Courtesy of Franziska Moos. Liberali lab. FMI Basel (Switzerland).

Dual-View LightSheet Microscope for Large Multicellular Systems

Visualizing the dynamics of complex multicellular systems is a fundamental goal in biology. To address the challenges of live imaging over large spatiotemporal scales, Franziska Moos et. al. present…

A Meta-cancer Analysis of the Tumor Spatial Microenvironment

Learn how clustering analysis of Cell DIVE datasets in Aivia can be used to understand tissue-specific and pan-cancer mechanisms of cancer progression
Multiplexed Cell DIVE imaging of Colon Adenocarcinoma (CAC) tissue. A panel of approximately 30 biomarkers targeted towards various leukocyte lineages, epithelial, stromal, and endothelial cell types was utilized to characterize the tumor immune microenvironment in human colon adenocarcinoma (CAC) tissue.

Mapping the Landscape of Colorectal Adenocarcinoma with Imaging and AI

Discover deep insights in colon adenocarcinoma and other immuno-oncology realms through the potent combination of multiplexed imaging of Cell DIVE and Aivia AI-based image analysis
Clustering based analysis reveals various immune cell populations enriched in tumor cells within CT26.WT syngeneic mouse tumor models.

Spatial Architecture of Tumor and Immune Cells in Tumor Tissues

Dig deep into the spatial biology of cancer progression and mouse immune-oncology in this poster, and learn how tumor metabolism can effect immune cell function.
Pancreatic Ductal Adenocarcinoma with 11 Aerobic Glycolysis/Warburg Effect biomarkers shown – BCAT, Glut1, HK2, HTR2B, LDHA, NaKATPase, PCAD, PCK26, PKM2, SMA1, and Vimentin.

IBEX, Cell DIVE, and RNA-Seq: A Multi-omics Approach to Follicular Lymphoma

In a recent study by Radtke et al., a multi-omics spatial biology approach helps shed light on early relapsing lymphoma patients
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