Proximity adjusted centroid mapping for accurate detection of nuclei in dense 3D cell systems.

In the past decade, deep learning algorithms have surpassed the performance of many conventional image segmentation pipelines. Powerful models are now available for segmenting cells and nuclei in diverse 2D image types, but segmentation in 3D cell systems remains challenging due to the high cell density, the heterogenous resolution and contrast across the image volume, and the difficulty in generating reliable and sufficient ground truth data for model training. Reasoning that most image processing applications rely on nuclear segmentation but do not necessarily require an accurate delineation of their shapes, we implemented Proximity Adjusted Centroid MAPping (PAC-MAP), a 3D U-net based method that predicts the position of nuclear centroids and their proximity to other nuclei.

Simple generation of cleavable labels for multiplexed imaging.

The most common methods for multiplexed immunohistochemistry rely on cyclic procedures, whereby cells or tissues are repeatedly stained, imaged, and regenerated. Here, we present a simple and inexpensive approach for amine-targeted labeling of antibodies using a linker that can be easily cleaved by a mild reducing agent. This method requires only inexpensive and readily-available reagents, and can be carried out without synthetic experience in a simple one-pot reaction.

Trial watch: anticancer vaccination with dendritic cells.

Dendritic cells (DCs) are critical players at the intersection of innate and adaptive immunity, making them ideal candidates for anticancer vaccine development. DC-based immunotherapies typically involve isolating patient-derived DCs, pulsing them with tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs), and utilizing maturation cocktails to ensure their effective activation. These matured DCs are then reinfused to elicit tumor-specific T-cell responses.

Dissecting the immune infiltrate of primary luminal B-like breast carcinomas in relation to age.

The impact of aging on the immune landscape of luminal breast cancer (Lum-BC) is poorly characterized. Understanding the age-related dynamics of immune editing in Lum-BC is anticipated to improve the therapeutic benefit of immunotherapy in older patients. To this end, here we applied the 'multiple iterative labeling by antibody neo-deposition' (MILAN) technique, a spatially resolved single-cell multiplex immunohistochemistry method.